Currency Crises and Optimal

International Liquidity

Mateusz Szczurek

Doctor of Philosophy Thesis

University of Sussex

March 2005

I hereby declare that this thesis has not been and will not be, submitted in whole or in

part to another University for the award of any other degree.

Mateusz Szczurek

University of Sussex

Mateusz Szczurek

Doctor of Philosophy thesis

Currency Crises and Optimal International Liquidity

Summary

The thesis investigates the importance of international liquidity for currency crisis gen-eration, prevention and costs. It includes a case study of the main 1990s currency crises, a model of policymaker optimising foreign exchange reserve stock with respect to its alternative costs, its impact on currency crisis probability and expected damage related to the currency collapse. An attempt is also made at matching revealed policymakers’ crisis aversion with real-life output losses related to currency crises. International liquid-ity played significant, albeit very rarely dominant role in the crises of the 1990s. The exceptions included Korea, Thailand and, possibly, Mexico. Calibration and application of the reserve stock optimisation model showed that most of the emerging markets poli-cymakers are prepared to suffer considerable annual costs of maintaining their official reserves. On average, the central banks in the sample spent 0.3% of GDP annually on their reserve holdings. The implied aversion to crises (expected crisis cost) was about 9% of GDP. In case of some of the countries, prospective currency crisis would have to cost (in terms of both forgone output and reputation) over 20% of GDP in order for their 0.9% of GDP annual investment in reserves stock to pay back. This is far more than the estimated average output loss of 2.3% of GDP in the past currency crises. The article underscores that the quasi-fiscal costs of keeping war-chests of international liquidity are considerable enough to justify cooperation between governments and central banks on a more active foreign debt and liquidity management policy.

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Table of Contents

TABLE OF CONTENTS 4

LIST OF FIGURES AND TABLES 8

CHAPTER 1 INTRODUCTION 10

CHAPTER 2 RESERVES IN CRISIS MODELS: A SURVEY OF LITERATURE 17

Section 2.1 First generation models 17

Section 2.2 Second generation models 27

Section 2.3 Asymmetric information as a cause of crises 34

Section 2.4 Liquidity and balance sheet models 38

Section 2.5 Inventory model of foreign exchange reserves 47

Section 2.6 Summary: liquidity in crisis models 51

CHAPTER 3 LEADING INDICATORS LITERATURE 53

Section 3.1 When and where 54

Section 3.2 Methods used 56 Section 3.2.1 Quantal response techniques 56 Section 3.2.2 Standard regression 57 Section 3.2.3 Signals approach 58 Section 3.2.4 Other methods 61

Section 3.3 What is a currency crisis? 62 Section 3.3.1 Exchange rate definitions 62 Section 3.3.2 Capital flows definitions 63 Section 3.3.3 Exchange Market Pressure (EMP) 64 Section 3.3.4 Discretionary definitions 67 Section 3.3.5 Other definitions 68

Section 3.4 What works? 69 Section 3.4.1 International liquidity 69 Section 3.4.2 Money supply 76 Section 3.4.3 Budget deficit, public debt 76 Section 3.4.4 Other balance of payments variables, real exchange rate 79 Section 3.4.5 The real sector 80 Section 3.4.6 Contagion variables 81

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Section 3.4.7 Institutional and structural factors 83 Section 3.4.8 Political variables 85

CHAPTER 4 RECENT CURRENCY CRISES: LIQUIDITY PERSPECTIVE 92

Section 4.1 Introduction 92

Section 4.2 1992 EMS crisis 98 Section 4.2.1 Crisis identification 98 Section 4.2.2 The role of reserves 100

Section 4.3 The Tequila crisis 1994 105 Section 4.3.1 Crisis identification 105 Section 4.3.2 The role of liquidity 108 Section 4.3.3 The cost of liquidity 111

Section 4.4 Bulgarian crisis of 1996-1997 112 Section 4.4.1 Crisis identification 112 Section 4.4.2 Role of liquidity and the cost of reserves 117

Section 4.5 East Asian crisis of 1997 118 Section 4.5.1 Crisis identification 118 Section 4.5.2 The role of liquidity 126 Section 4.5.3 The cost of liquidity 127

Section 4.6 1998 Russian crisis 131 Section 4.6.1 Crisis identification 131 Section 4.6.2 Role of liquidity 136 Section 4.6.3 Cost of reserves 137

Section 4.7 1998 crises in other FSU counties: Ukraine and Moldova 138 Section 4.7.1 Crises identification 138 Section 4.7.2 Role of liquidity 142

Section 4.8 2000-2001 Turkey default and lira collapse 143 Section 4.8.1 Crisis identification 143 Section 4.8.2 The role and cost of liquidity 146

Section 4.9 The end of Argentine currency board 147 Section 4.9.1 Crisis identification 147 Section 4.9.2 The role of liquidity 154

Section 4.10 Case study conclusions 155

CHAPTER 5 INTERNATIONAL LIQUIDITY TARGETING: A MODEL 158

Section 5.1 Crisis and its costs 158

Section 5.2 International liquidity and its cost 164

Section 5.3 Optimisation problem 170

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Section 5.4 Empirical application: Introduction 172

Section 5.5 Model calibration 173 Section 5.5.1 Data 174 Section 5.5.2 The results 176

Section 5.6 Model application: best value for money liquidity 185

Section 5.7 Model application: How much policymakers fear the crisis? 189

Section 5.8 Conclusions 194

CHAPTER 6 THE OUTPUT COST OF CURRENCY CRISES 196

Section 6.1 Introduction 196

Section 6.2 Crises and output: the theory 197

Section 6.3 Empirical treatments 199

Section 6.4 Research concept and data used 204

Section 6.5 The results 206

Section 6.6 Crisis costs conclusions 211

CHAPTER 7 FINAL CONCLUSIONS 213

REFERENCES 215

APPENDIX 1. CHRONOLOGY OF RECENT CURRENCY CRISES 227

Chronology of the Mexican crisis 227

Chronology of the Bulgarian Crisis 227

Chronology of Thai crisis 229

Chronology of the Malay crisis 231

Chronology of the Indonesian crisis 232

Chronology of the Korean crisis 234

Chronology of the Russian Crisis 235

Chronology of the Ukrainian crisis 236

Chronology of the Moldovan Crisis 237

The chronology of the Turkish crisis 237

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Chronology of the Argentine crisis of 2001 238

APPENDIX 2: ALTERNATIVE SET OF MODEL EQUATIONS 248

APPENDIX 3: MODEL OPTIMISATION MATHEMATICA© 5 CODE 250

APPENDIX 4: THE LIST OF COUNTRIES USED FOR ESTIMATIONS IN CHAPTER 5 255

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List of figures and tables

Figure 1 Target exchange rate with limited reserves 24 Figure 2 Target exchange rate with large reserves 25 Figure 3 Reserves determine the range of possible equilibria 28 Figure 4 Devaluation and fixing loss functions under devaluation and fixing expectations 32 Figure 5 Expected profit of domestic economy/investor as a function of short-term debt 44 Figure 6 Modified Mundell-Fleming model 46 Figure 7 Binary recursive tree estimation result 61 Figure 8 Leading indicator literature summary: methods, datasets, results (sorted by publication date) 86 Figure 9 GBP/ECU rate and UK’s reserves 103 Figure 10 ECU/SEK rate and Sweden’s reserves 103 Figure 11 ECU/ESP rate and Spanish reserves 103 Figure 12 ECU/LIT rate and Italian reserves 103 Figure 13 IRP/ECU rate and Irish reserves 104 Figure 14 ECU/FIM rate and Finnish reserves 104 Figure 15 UK’s reserves/M4 104 Figure 16 Swedish reserves/M3 104 Figure 17 Spanish reserves/M3 104 Figure 18 Italian reserves/M2 104 Figure 19 General budget deficit (% of GDP) 105 Figure 20 Real GDP growth (YoY%) in ERM 105 Figure 21 Real GDP growth in Mexico (YoY) 107 Fig 22 Mexican CA and budget balance (% GDP) 107 Fig 23 Nominal exchange rate and reserves 108 Fig 24 Mexican international liquidity measures 108 Figure 25 Mexico Par Brady bond zerocoupon spread (bps) 112 Figure 26 Bulgarian money demand function 114 Figure 27 Purchasing power parity test 115 Figure 28 Bulgarian exchange rate and reserves 116 Fig 29 Bulgarian international liquidity measures 116 Fig 30 Bulgarian monetary indicators (in logs) 116 Fig 31 Deficit monetisation and exchange rate 116 Fig 32 GDP, CA and unemployment in Bulgaria 116 Figure 33 Bulgarian Discount Brady bond zerocoupon spread (bps) 118 Fig 34 Budget balances in ASEAN-5 (% of GDP) 121 Figure 35 ASEAN-5 Current account (%) of GDP 121 Fig 36 Indonesian exchange rate and reserves 121 Figure 37 Korean exchange rate and reserves 121 Figure 38 Malaysian exchange rate and reserves 122 Figure 39 Philippine exchange rate and reserves 122 Figure 40 Thai exchange rate and reserves 122 Figure 41 Reserves/Money+quasi-money 124 Figure 42 Reserves/Money+quasi-money 124 Figure 43 Philippines Brady spread (bps) 130

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Figure 44 Indonesia Yankee 06 spread (bps) 130 Figure 45 Korea Dev Bank 06 130 Figure 46 Thailand 02 zerocoupon spread (bps) 130 Figure 47 Malaysia 00 zerocoupon spread (bps) 131 Figure 48 Russian exchange rate and reserves 132 Figure 49 Rus Reserves to short term debt (BIS) 132 Figure 50 Russian budget and reserves/M2 133 Figure 51 Russian GKO yield 133 Figure 52 Hryvna rate and reserves (US$m) 140 Figure 53 Ukraine’s reserves/M2 140 Figure 54 Moldovan exchange rate and reserves 141 Figure 55 Reserves/M2 and deficit monetisation 141 Figure 56 Ukrainian growth and CA 142 Figure 57 Moldovan growth and CA 142 Figure 58 US$/TKL and Turkish reserves 145 Figure 59 Reserve/M2 and TCMB gov. financing 145 Figure 60 YoY GDP growth and CA balance 145 Fig 61 Turkey Republic 30, zerocoupon spread 145 Fig 62 Argentina Discount Brady bond zerocoupon spread (bps) 155 Figure 63 Summary of the case studies 157 Figure 64 Probability of a crisis vs. international liquidity and a budget deficit 159 Figure 65 Marginal return to international liquidity vs. liquidity and REER 163 Figure 66 Optimal international liquidity – marginal cost and benefit 171 Figure 67 Probability of a crisis as a function of key variables only 177 Figure 68 Crisis probability as a function of all main variables 177 Figure 69 Final benchmark model of crisis probability 178 Figure 70 OLS results of the impact of liquidity, lagged fundamental variables and crisis dummy on the current account (full sample) 181 Figure 71 OLS results of the impact of liquidity, lagged fundamental variables on the current account (crisis sample) 182 Figure 72 OLS results of the impact of liquidity, lagged fundamental variables on the real exchange rate (crisis sample) 183 Figure 73 OLS results of the impact of liquidity, lagged fundamental variables on budget deficit (crisis sample) 183 Figure 74 OLS results of the impact of liquidity, lagged fundamental variables on GDP growth (crisis sample) 183 Figure 75 International bond spreads as a function of liquidity, currency crises and foreign debt 184 Figure 76 Annual costs of keeping foreign exchange reserves 186 Figure 77 Optimal liquidity holding versus cost of the crisis, sample average. 188 Figure 78 Expected crisis cost to the policy maker, as of 2001 189 Figure 79 Marginal liquidity cost and benefit curves in emerging markets 190 Figure 80 Marginal benefit from international liquidity for sample countries 192 Figure 81 Implied crisis costs and sovereign spreads 192 Figure 82 Output loss in first and two first years of a crisis 207 Figure 83 Output crisis cost in 2 years of the crisis; all variables 207 Figure 84 Output crisis cost in 2 years of the crisis; parsimonious version 208 Figure 85 Output crisis cost in the year of a crisis; all variables 209 Figure 86 Crisis year output loss; final model 209 Figure 87 Expected output loss, and total implied crisis cost (% of GDP) 212

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Chapter 1 Introduction1 Because the IMF and other international organisations do not have the resources to act as lenders of last resort, the emerging market countries that want to prevent sharp currency declines must provide for their own protection through increased liquidity.

Martin Feldstein, 1999

The point seems to make perfect sense: even with less-than perfect macro policy, the

government could survive any speculative attack, provided it has enough “foreign ex-

change ammunition”. What is more, if the reserves are high enough, the attack (bound

to fail) will never happen. The simple argument for higher reserves is not obvious, how-

ever.

First, in monetary terms sterilised intervention (and foreign exchange interventions are

very often sterilised) should not influence the exchange rate significantly. The main

problem here is that sterilisation increases the potential for hot money outflow – “multi-

plies the enemy with the same amount of ammunition” to stick with the military par-

able. If the foreign exchange intervention is not sterilised, the economy (and the bank-

ing sector in particular) must be able to survive a serious liquidity squeeze (which could

have worse effects than devaluation itself).

Second, in fixed exchange regime “sufficient liquidity” may mean foreign exchange re-

serves close to money supply. Any level of reserves smaller than this may not fully

eliminate the “attack” equilibrium, as not only foreign investors, but also residents could

choose to exchange domestic for foreign currency. It may well be that relationship be-

tween foreign exchange reserves and probability of a crisis is not linear at all – it would

1 I would like to thank Robert Eastwood for skilful supervision, Jerzy Pruski and other participants of CASE seminars for useful comments, David Spegel from ING Financial Markets for his extensive bond price database, ING Bank for financial support and, above all, my family for endless support and patience.

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be plausible that a country with very high reserves would enjoy almost zero probability

of a speculative attack. Would a marginal decline in liquidity have the same effect on

the crisis risk regardless of the state of other fundamentals?

Finally, liquidity is costly. Even if the government issues international debt solely for

the purpose of building up the war chest of international reserves (with the annual cost

of the spread over the US Treasuries) the gain in terms of liquidity will be limited be-

cause of the additional build-up of obligations. If the proper measure of liquidity in-

cludes the level of short-term debt, borrowing short to build up reserves will make little

sense. Still, provided the international reserves are built up with the long-term bonds, an

increase of international liquidity is feasible.

This work aims at answering several questions related to the role of foreign exchange

reserves, international liquidity in crisis prediction, crisis prevention and crisis costs.

First, where does international liquidity fit in the existing theoretical and empirical work

on currency crises? Second, what was the role of international liquidity in the currency

crises of the 1990s? Third, if the liquidity can reduce crisis probability, what is the de-

sired stock of foreign exchange reserves to be held by countries facing risk of a cur-

rency crash? Fourth, how does the behaviour of the emerging market borrowers fit with

the model, the existing literature and estimates of currency crisis-related output loss?

The first question concerns the theoretical reasons why international liquidity should

influence the timing or probability of the crisis. If theory speaks for the importance of

international liquidity for crisis timing or probability, can the knowledge of the mecha-

nisms bring any benefit to the policymakers? The answer to these issues require a thor-

ough review of the theoretical crisis literature, from early, ”first-generation” models in

which crisis erupts as a result of a macroeconomic policy incompatible with fixed ex-

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change rates, through the latest balance sheet crises in which capital outflow expecta-

tions becomes self-fulfilling though its negative effect on real output, or ability to bor-

row and invest.

The answer to the first part is “usually yes”, as foreign exchange reserves do appear in

most of the models describing the currency crises. The answer to the second part is

much less encouraging. In some models (e.g. in Krugman’s classic, or in Dooley’s in-

surance model) the amount of reserves influence timing of the crisis, but governments

cannot postpone the crisis by managing reserve level, as it either boosts fiscal costs, the

ultimate cause of the crisis, or increases the moral hazard for local corporations. Other

models leave some more room for deliberate liquidity targeting as a tool for crisis pre-

vention. In particular, many balance sheet models allow for a trade off between costly

liquidity and higher crisis risk.

Vast empirical literature confirms that foreign exchange reserves and other measures of

international liquidity are one of the most reliable leading indicators of currency crises.

Just as predicted in the theoretical models, however, the significance of such variables

in crisis probability equations does not mean that targeting high liquidity can avert the

currency crises or even that low liquidity is among their main causes of crises (as op-

posed to warning signals).

This is confirmed in the answer to the second of the main questions of the work. The

currency crises of the nineties and early 21st century, including EMS, Mexican, Bulgar-

ian, Asian, Russian, Turkish and Argentine collapses are rarely caused solely by poor

liquidity. But some countries, in particular Thailand, Korea and Mexico could have

avoided at least some of the costs of crises (if not crises altogether) without the reliance

on the short term foreign financing.

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The answer to the third of the main questions required construction of an optimising

policymaker model. In the model, international liquidity is the only variable under the

direct control. The policymaker tries to minimise the loss function including the cost of

the currency crisis (the probability of which depends partially on the liquidity held) and

the annual cost of international liquidity. Using the structure presented it is possible to

estimate the implicit reputation cost of a prospective currency crash to the policy-maker.

This line of modelling joins the strain of the buffer stock modelling of desired foreign

exchange reserves stock (Frenkel and Jovanovic, 1981) and the more recent research on

currency crises.

Empirical testing of the model required calibration of the main parameters. Pooled logit

regression study was performed to check if and how different measures of international

liquidity and other control variables help in averting emerging market crises. Reserves

to short-term foreign debt, money supply growth, budget and current account deficits

were found to influence crisis risk significantly. Other estimations included checks of

responsiveness of the main model variables to the crisis occurrence (to allow for esti-

mating the costs of postponing the crisis), and the influence of liquidity targeting policy

on sovereign spreads and costs of liquidity itself. It turned out that the negative effect of

higher overall debt outweighs the benefits of lower perceived crisis risk on spreads.

Thus, the countries borrowing in long maturities cannot count on cheaper financing

thanks to lower liquidity, on the contrary, trying to offset the burden of short-term li-

abilities by borrowing liquid assets increases debt and costs of external financing.

The theoretical model was employed to estimate the curve of optimal international li-

quidity holdings with respect to changing expected crisis costs for a group of countries.

The “Guidotti rule” dictating 100% coverage of short term debt by (usable) foreign ex-

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change reserves implies about 8% of GDP average crisis cost for a median country. This

is a reasonable result, as some of the crisis cost studies (e.g. Bordo et al., 2001, Hutchin-

son and Neuberger, 2001) point to the output losses of a similar magnitude. However,

the variations in both costs of borrowing and in fundamentals faced by different coun-

tries makes the quick 100% rule very unreliable. Countries like Croatia could profitably

increase their official reserve stock (by means of long-term borrowing) – the benefits of

thus bought protection against excessive foreign exchange volatility outweigh the cost

of keeping reserves. On the other extreme is Singapore, which is prepared to pay con-

siderable annual amounts to keep the duration of debt its reserves high, without signifi-

cant crisis protection gains.

The intersection of the optimum liquidity curve with actual liquidity held by various

countries sheds light on the fourth and final of the main questions of the thesis. Re-

vealed expected crisis cost to the policymakers is at about 9% of GDP, but with the in-

dividual results varying from 1.5% in Croatia to over 15% for the pegged exchange rate

countries, and as much as 78% for Singapore.

The latter result confirms the limitations of the model: for many countries reserves are

more than just a tool for crisis protection. Own calculations suggest that the average

output cost of a currency crisis in the group of emerging market economies sums up to

slightly above 2% of GDP. The cost grows with debt, but falls with the importance of

the export sector for the economy. This result is close to the lower-end of the findings of

the existing literature on output costs of the crises, but no paper estimates the output loss

anywhere close to the 15% of GDP, the figure significantly exceeded by estimated ex-

pected crisis cost to policy makers of Argentina, Bulgaria, or Singapore. In fact, no cri-

sis in the past 20 years proved that expensive (yet the impact of the Argentine currency

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board collapse was not included in the calculations). The model suggests the policy-

makers’ fear for crisis output costs is dwarfed by dislike to the potential reputation or

political power loss.

The second chapter provides a survey of all major strains of currency crisis theory with

the emphasis given to the links between international liquidity and timing, probability or

costs of the currency crises.

The third chapter reviews the vast empirical literature on leading indicators of the cur-

rency crises, including the analysis of techniques and variables as well as a comprehen-

sive summary table with the results and estimation methods of 75 papers on leading cri-

sis indicators.

Chapter four consists of case studies of the currency crises in the EU in 1992, Mexico in

1994, Bulgaria in 1996, East Asia in 1997, Russia, Ukraine and Modova in 1998, Tur-

key in 2000, and Argentina in 2001. The main issues confronted are the role of various

measures of international liquidity as a crisis prediction and the feasibility of the re-

serves as crisis prevention tool.

The fifth chapter presents the international liquidity policy optimisation model, its em-

pirical calibration and the estimates of optimal liquidity curves for various levels of cur-

rency crisis costs and resulting implied crisis aversion by policymakers in a group of

emerging market economies.

Finally, chapter six reviews the theoretical and empirical literature on actual output

costs of currency crises, and estimates the determinants and size of output loss related to

currency crises in the 1990s in emerging markets. This allows for comparison of prefer-

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ences revealed by policymakers in their international liquidity holdings, and expected

output loss in the prospective currency crisis. The final section concludes.

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Chapter 2 Reserves in crisis models: a survey of literature

Section 2.1 First generation models

Beginning of the currency crisis literature is attributed to Krugman (1979) classic, later

simplified and extended by Flood and Garber (1984) and surveyed in Agenor et al.

(1992)2. So called first generation crisis models base on exhaustible resource literature

originating in Hotelling (1931). The first generation crisis occurs as a result of an unre-

formable macroeconomic policy incompatible with fixed exchange rate. In Krugman’s

example the policy is the one of excessive fiscal deficits, monetised away.

The international reserves are quite central to the analysis: they take the role of ex-

haustible resource in the equivalent model of Salant and Henderson (1978). Incompati-

ble macroeconomic policy causes gradual depletion of reserves. Fixed exchange regime

can last only until foreign exchange reserves reach certain critical level. The model pre-

dicts, however, that the end comes earlier than that. Rationally thinking speculators at-

tack and buy all remaining stock of reserves as soon as the shadow price – the price

which would prevail without central bank fixing the exchange rate reaches the official

rate. The regime turns smoothly to a float (exchange rate does not jump, only the level

of reserves).

The model presented below (following Flood and Marion, 1998) is the simple linear

version of the original, but it captures well enough all the main features of the class.

2 Balance of payments models are older than that: Mundell (1960) shows an example of a general equilibrium model in which abandonment of a peg depends on the level of in-ternational reserves.

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The model can be described with four equations, showing, respectively, money demand,

money supply, price level (following the PPP), and exchange determination model (fol-

lowing uncovered interest parity):

m - p=-α i, α>0,

m = ln(D + R),

p = p*+ s,

i = i* + s`

m is the (nominal) money supply, p and p* domestic and foreign price level, i and i*

domestic and foreign interest rate, D is the domestic credit level, R is the stock of for-

eign reserves, s is the exchange rate, and s’ is the expected (and actual, perfect foresight

is assumed) rate of change of the exchange rate. All variables except D, R, i and i* are

in logs.

Log of domestic credit d is assumed to grow at a constant rate µ, envisaging a

monetised budget deficit financing. When the exchange rate is fixed at ŝ, expected de-

preciation s’ is equal to 0, and domestic interest rate equal to foreign interest rate i*.

With foreign interest rates and price level constant, the money market equilibrium re-

quires that the log of reserves r must be falling at the rate -µ, because money supply m

is constant. Thus, the country must run out of reserves at some stage, which will trigger

growth in m (along with growing domestic credit) and the collapse of the fixed ex-

change rate.

When this will actually happen depends on the expectations of future exchange rate pol-

icy, and on the threshold level of reserves, at which the central bank lets the currency

go. In what follows, I assume that the threshold (log) level of reserves is zero, and that

the post-crisis regime is a float.

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To determine the timing of the collapse, let’s define shadow exchange rate as the ex-

change rate consistent with the money market equilibrium, provided the reserves are at

the threshold level (completely exhausted in our case). For simplicity, let’s also normal-

ise foreign price and interest rate level at zero. Combining four initial equations, we get:

d – š =-α š’,

where d is log of domestic credit D.

Because with the reserves depleted, money supply, price level and the exchange rate all

grow together with d at the rate µ, so the shadow exchange rate š is equal to:

š = d + αµ.

The peg collapses with the speculative attack when the shadow exchange rate exceeds

the fixed rate ŝ. As long as the shadow rate is smaller, the attack would leave the attack-

ers with capital losses. But competition between the speculators makes the profitable

run on the currency impossible, thus shadow rate š cannot be bigger than the fixed rate.

Thus the speculative attack is not associated with a discrete jump in exchange rate.

What will jump is the domestic interest rate i, which from the moment of the attack

must reflect the devaluation rate equal to the credit growth µ. This allows the drop in

money supply (caused by discrete fall in reserves at the moment of the attack) to be

matched with a drop in money demand (due to a hike in interest rate). During the attack,

reserves will fall so that ∆m is equal to -αµ.

What is the timing of the speculative run? We know that the domestic money follows

dt = d0 + µ T.

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At the moment of the attack, shadow exchange rate š is equal to the fixed rate (which, in

turn is equal to the log of the initial money supply, assuming zero foreign interest rates

and inflation):

m0 = d0 + µ T + αµ.

Thus

µ

αµ

µ

αµ

µ

αµ−

+

=

−

=−−

= 0

0

0

0

0

1lnlnD

R

D

M

dmT o , where T is the timing of the at-

tack, and R0 is the initial stock of reserves.

The result shows that the attack comes later when the initial stock of reserves (relative

to domestic money) is higher or domestic credit expands more slowly. Foreign ex-

change reserves are crucial as a leading indicator of the currency crisis. The importance

of the reserves in crisis prevention, however is limited, as, in the basic form of the

model, the government influences (decreases) the level reserves only by expanding do-

mestic credit (at a constant rate).

In reality, policymakers often fail to behave as assumed in the Krugman’s model. Tan-

ner (1997) shows that the outflow of reserves in Latin America and Asian countries in

the 1990s was usually associated with offsetting growth of domestic money3. Countries

undergoing crises in late 1990s resisted the temptation to offset money supply fall by

domestic money growth only until a point (early, in case of Ukraine, or Russia, late in

3 There are examples though of central bankers taking the exchange rate policy seriously – Moldova in 1998 experience severe tightening of the money supply and temporary falls in inflation because of the speculative attack. Also, Tanner’s results could indicate central banks reacting to banking panics and rising money demand and currency ratio. Injecting liquidity in such a case would still leave model’s findings relevant.

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case of Moldova or Turkey), when other factors, like banking system stability started to

weigh more than the durability of the peg. Government’s refusal to defend the peg in

such a way would make reserves irrelevant, because in case of a speculative attack, the

rate of change of domestic credit would increase above the normal rate µ, as the policy-

maker would start printing money to offset falling money supply. Rational investors

would attack the currency immediately, regardless of the reserves (see Flood and

Jeanne, 2000).

Another problem, which concerns also later extensions of the basic versions, is the use

of the standard monetary model of exchange rate determination. This model simply

does not work well in explaining exchange rates in developed economies, as was

pointed out in the classic paper by Meese and Rogoff (1983). The problem is not even

with the fact that the budget deficits may be financed by other means than monetisation

in open developed economies. The core of the model is the unsustainable monetary pol-

icy leading to the collapse. But due to the money demand function instability, econo-

metric attempts to link monetary policy with G7 exchange rates tend to fail. This ren-

ders Krugman’s model rather ineffective in predicting the developed countries’ currency

crises. Also, in many developed countries, the government has little control over mone-

tary policy – for example, EMU member governments cannot simply order the ECB to

finance their deficits. Somewhat relieving is the stylised fact of better performance of

monetary models in developing countries’ currencies forecasting, possibly due to faster

changing money stocks in such countries (or less problems with “near” money defini-

tions, and money demand estimations).

The basic model can be extended to incorporate a possibility of an interest rate defence,

leading to a (short-term) build-up of reserves. Such a model can be found in Flood and

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Jeanne (2000). By adding the uncertainty in the portfolio balance framework, they relax

the simple uncovered interest parity condition, allowing for an interest rate defence.

While it leads to a replenishment of the reserves, it also increases the fiscal costs, the

ultimate reason behind the vulnerability of the peg. As a result, the collapse is usually

hastened because domestic credit starts to expand faster due to the increased fiscal costs.

This important result serves a reminder that the reserves do not come for free.

An interesting model from the point of view of the importance of international liquidity

is one by Krugman and Rotemberg (1992). It joins two strands of the exchange rate lit-

erature – target zones models and currency crisis models4. The model goes as follows

(the variables’ designations are as before, unless otherwise indicated):

∂

∂++=

t

sEγvms , where a change in v is a shock to the money demand following

random walk with a drift:

ztv ∂+∂=∂ σµ

Log money supply m = ln(D + R)

Under the free floating regime, expected depreciation is equal to the drift in the money

demand. The exchange rate equation is then: s m v γµ= + +

Holding money supply constant, the general solution of the model, is5:

4 Other models of this kind are shown in Flood and Garber (1989), models in Krugman and Miller (1992) and Bertola and Svensson (1993).

5 See e.g. Garber and Svensson (1994) for the derivation of the solution, which uses Ito’s lemma

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vv BeAevms 21 ++++= ααγµ , where A and B are free parameters, and

02

02

2 <+−−

=

>++−

=

2

222

2

222

1

γσ

γσµγγµα

γσ

γσµγγµα

With the exchange rate fully floating, money supply is truly constant and cannot be ex-

pected to change, thus the expectations component is simply equal to the expected

change in v – the drift. In such case both A and B are equal to zero. If, however, the cen-

tral bank is expected to spend the reserves, defending some target exchange rate, then

rational speculators expect money supply to fall as soon as exchange rate reaches the

edge of the band. The size of A and B depends on the amount that the government is

willing to spend defending the edges, the size of the reserves in the case of A, and the

amount of reserves the central bank will buy in case of an “attack” on the stronger side

of the band (which determines B). We assume that the band is single-sided, which

means that v may fall as much as it wants, without triggering the response of the central

bank. This means that B is equal to zero (investors do not expect an increase in money

supply as a result of the strengthening pressure on the local currency). A can be deter-

mined, knowing the level of the foreign exchange reserves, and that no predictable dis-

crete jumps in exchange rate can happen.

After the speculative attack, when reserves r are exhausted, log money supply m falls to

log domestic money d, and the regime is floating, thus the shadow exchange rate is:

š = d + v +γµ

- 24 -

For small level of reserves (reserve/domestic credit ratio 11

−< 1αeD

R), The attack oc-

curs, as before, when shadow exchange rate is equal to the regime exchange rate. This is

the only rate that eliminates the possibility of capital gains for the speculators. The at-

tack happens when v reaches the critical level v’ (for which š is equal to the targeted

level of the exchange rate smax):

vAevmvd 1+++=++ αγµγµ ''

A, which ensures the no-exchange rate jump attack is equal to: ( ) re ds 2−−− αγµmax .

Figure 1 Target exchange rate with limited reserves

2 4 6 8 10 v

2

4

6

8

10 s

smax

v’

š

X

Y

Z

Source: Author, based on Krugman and Rotemberg (1992) model

Figure 1 shows exchange-rate-money demand shock loci for the free-float (dashed line)

and zero-reserves (post attack) float (solid straight line, parallel to the free float). The

latter can be considered a shadow exchange rate. It becomes the actual exchange rate at

a point where it crosses the curved line (target regime).

While it is obvious that the zero-reserves curve shows stronger exchange rate than the

(no-attack) free-float (total money supply is lower by the amount of reserves spent, so

the exchange rate must be stronger for a given shock to money demand after the attack),

the fact that the target regime curve is below the free float is more exciting. It shows

- 25 -

that despite inability of the government to defend the target rate (as soon as v reaches v’

the regime collapses and the exchange rate starts to follow the zero-reserves curve), the

exchange rate is supported by the sheer willingness of the authorities to spend reserves

defending the target (Krugman’s honeymoon effect). The kinked thick curve (X-Y-Z) is

the actual exchange rate-money demand schedule.

The situation looks different when reserves to domestic credit ratio is bigger. For large

reserves, the regime curve reaches its maximum to the left of the post-attack locus. The

speculative attack does not then take place at all, and the target can be kept with very

small interventions. Situation like that is shown in Figure 2. A is set to make the regime

locus tangent to the exchange rate target (s cannot be expected to grow above the smax

without the attack). Each intervention, however shifts the regime locus to the right, as

the reserves get smaller and smaller. When the reserves reach “small” limit

( 11

−= 1αeD

R), i.e. when the maximum of the regime locus is at the (smax,v’) point,

speculative attack occurs consuming all remaining reserves, and the regime turns into

free float.

Figure 2 Target exchange rate with large reserves

2 4 6 8 10 v

2

4

6

8

10 s

Source: Author, based on Krugman and Rotemberg (1992) model

- 26 -

The important point from this analysis is that the attack cannot occur for sufficiently

large reserves. If the initial reserves are much larger then domestic credit, reserve loss is

zero when fundamentals are good enough (v is low). As v gets worse, the reserves start

to dribble out (along the horizontal part of the bold curve in Figure 2). As they keep

worsening, the attack occurs at some stage (the drift in the money demand shock term

ensures that), which eliminates all the remaining reserves.

When the reserves are initially small, they do not contribute radically to the defence of

the exchange rate target. All the reserves are suddenly wiped out when the fundamentals

v worsen beyond some threshold. The only benefit from the reserves is the some support

to the currency for moderate levels of fundamentals, before the attack.

Other extensions of the 1st generation crisis model include adding price stickiness,

which leads to real appreciation ahead of the crisis as agents increase prices expecting

the exchange rate depreciation (Goldberg, 1991), including forward-looking wage con-

tracts, which boost wages ahead of currency depreciation (Willman, 1988); uncertainty

about the rate of deficit monetisation, which increases interest rate spread and makes it

possible temporarily for the shadow exchange rate to be weaker than the peg rate (Flood

and Garber, 1984), introducing the capital controls, which could lengthen the peg and

make the step-devaluation possible.

- 27 -

Section 2.2 Second generation models

Second generation models (a good example is shown in Obstfeld 1994) addressed seri-

ous drawbacks of the first generation models6. First, the governments and central banks

of the models building on Krugman (1979) were like lemmings: once engaged in a pol-

icy incompatible with fixed exchange rates, they were heading for the disaster of reserve

depletion. In reality, the governments have more options. For example, they can change

their policy when balance of payments gets worse, or devalue without depleting the re-

serves first. The second-generation models allow the governments to optimise. The loss

function usually includes the exchange rate and some variable dependent on both actual

depreciation and the prior public expectations of depreciation. In two models presented

in Obstfeld (1996), the variable is a level of taxation (dependent on nominal interest

rates, and thus on public expectations of nominal depreciation), or unemployment (de-

pendent on agents’ wage setting decisions, and thus nominal depreciation).

The circular causality indicated above gives rise to fascinating properties of second-

generation models. Exchange rate regimes that at first glance may seem to be perfectly

viable may suddenly collapse simply because they are expected to. The possibility of

multiple equilibria and self-fulfilling attacks fits well with crises like 1992 EMS col-

lapse. Important feature of most of the second-generation models is that self-fulfilling

attacks cannot occur for any value of fundamentals. Usually, there is a range of funda-

mentals for which an attack is impossible, a range for which the attack is certain, and a

range in which both “attack” and “calm” equilibria are possible.

6 For other models of this kind see e.g. Obstfeld (1996), Velasco (1996), Ozkan and Sutherland (1998), Drazen (1999). A survey is provided in Eichengreen, Rose and Wy-plosz (1996)

- 28 -

What is the role of international reserves, so central to first generation models, in the

second-generation alternatives? Many models of the second kind, and the ERM crisis

itself seem to suggest that reserves influence neither probability nor the timing, nor the

scale of the currency collapse. In principle, the British problem of 1992 was not about

being able to defend the currency, but about Britain not wanting to do it. Britain had

plenty of reserves, could borrow more from other European central banks7, or could de-

crease the money supply and defend the pound for a long time (as it had been doing be-

fore the 1st World War). ERM crisis erupted because the speculators believed Britain

would have found defending the pound unprofitable if attacked.

A simple explanation of the possible role of the international reserves is shown in

Obstfeld (1996), and reproduced in Figure 3.

Figure 3 Reserves determine the range of possible equilibria

Trader 2 Trader 2 Trader 2 Hold Sell Hold Sell Hold Sell Hold 0,0 0,-1 Hold 0,0 0,2 Hold 0,0 0,-1

Tra

der

1

Sell -1,0 -1,-1

Tra

der

1

Sell 2,0 ½,½

Tra

der

1

Sell -1,0 3/2,3/2

(a) High Reserve game (b) Low Reserve game (c) Intermediate Res. game Source: Obstfeld (1996)

In a simplified model, Obstfeld envisages three agents: the government (selling foreign

reserves to fix the currency’s exchange rate), and two investors who either hold to their

7 According to some market commentators the Bank of England was actually unable to arrange enough foreign currency in time to defend the pound on Black Wednesday. A very stylised model trying to explain why a currency can collapse despite arrangements such as VSTFF (Very Short Term Financing Facility) of the EMS which provide virtu-ally unlimited intervention financing is provided by Lall (1997). The model assumes that the amount of foreign currency that a central bank can access in any given day is limited, and that an unexpected shock to the money demand could trigger a collapse of the currency peg.

- 29 -

local currency assets, or sell them, draining reserves. When the reserves (which serve as

a measure of the government’s commitment to the peg) are high enough to absorb both

investors’ selling-out of the domestic assets, the only Nash equilibrium in the one-shot

non-cooperative game is the “no crisis” equilibrium. When the reserves are insufficient

to satisfy even one of the traders, than it is optimal for each one of the investors to force

devalue the currency and get some profits. The most exciting situation is when the cur-

rency is devalued only when both traders sell. Then two equilibria exist – it is optimal

for trader 2 to attack the currency only when trader 1 does so. Without the attack, the

peg may last forever, when attack occurs, the peg fails8.

The simple model above served only as an example of multiple equilibria in foreign ex-

change markets. But other, full-fledged, second-generation models exist, which stress

the importance of international liquidity. Sachs et al. (1996a) provide one example, in

which the fundamental, which governs the possibility of a successful attack, is the net

level of debt the government owes. Sufficiently high level of reserves (net of govern-

ment debt) makes an attack impossible to succeed. Such a model could explain the styl-

ised fact of relative crisis immunity of highly liquid developing countries.

In the simplified version of Sachs et al. model, the government faces the following

budget constraint and loss function:

( ) 0 , >=−+ θππθ tte

tt xRb

8 But this outcome relies on the assumption of the discretionality of the speculative deci-sions – one can argue that the speculator knows that his fellow speculator would attack as soon as he starts the attack. In such case the attack equilibrium would be the only one viable in this case – the payoff is the highest for the attack in the intermediate reserve level case. This looks like a trivial error in Obstfeld’s example.

- 30 -

0 ,2

22

>+

= ααπ tt x

L

The budget constraint forces the policymaker to equalise tax revenues x with debt ser-

vice costs (international real interest rate R, taken as given by the small open economy

times the inherited stock of debt net of reserves b). Debt service costs can be lowered by

surprise devaluation/inflation tax gains being a function of the difference between ex-

pected (πe) and actual (π) depreciation.

The loss function L says that the government dislikes taxes and depreciation. Additional

reputation cost c is borne by the policymaker in case of devaluation (provided he did not

devalue in the first period).

The basic framework provides the scene for a typical feature in this kind of model: inde-

terminacy of the outcome – multiple equilibria. The policymaker must choose the level

of taxation x and devaluation π subject to the state of the economy (in this case the level

of inherited debt over reserves) and expectations of devaluation. The expectations, how-

ever, are set rationally by investors/economic agents, who understand the government’s

optimisation problem and its incentives to devalue. Thus for some levels of fundamen-

tals, the government devalues if and only if when the public expects it to (there are vari-

ous channels by which this could be happening: higher depreciation expectations boost

interest rate burden, drives up wages increasing unemployment, and hampers growth

and taxes).

First order conditions require the policymaker to set taxes and devaluation minimising

the loss function at:

( ) ( )ett

ett RbRbx θπ

θα

θπθπ

θα

α+

+=+

+=

22 ;

- 31 -

Assuming perfect foresight equates expected and actual devaluation πe=π. The tax lev-

els and devaluation now become:

α

θππ

RbRbx te

ttt === ;

Corresponding “devaluation” government’s loss is equal to:

( )( ) cRb

Le

ttd ++

+=

2

2

2 θα

θπα, where c is the one-off reputation cost to the government.

If the policymaker commits to the fixed exchange rate, then πt = 0. The “fixing” loss

function is then:

( )2

2etf Rb

Lθπ+

=

Although the policymaker commits to the fixed exchange rate, that does not mean that

expected devaluation πe=0 as there may be little credibility to the official claims.

The policymaker devalues when the loss from fixing is higher than the loss from de-

valuing. That requires that:

( )( )

( )22

2

2

2 et

ett Rb

cRb θπ

θα

θπα +<+

+

+, or

( )0

2 2

>≡+

>+ kc

Rb et θ

θαθπ

The result is intuitive – the policymaker devalues when expectations of devaluation or

fundamentals (inherited debt) are bad enough. But that is not the full story. Because

speculators are rational, we can distinguish three ranges of international liquidity. One,

which ensures devaluation (it would happen even if πe=0). This requires that Rbt > k. In

such case, of course, fixing pledge has no credibility at all – the exchange rate fixing is

bound to fail, and everyone expects the government to devalue.

- 32 -

We also know that rational speculators cannot expect any devaluation. Knowing the

government’s optimisation problem they expect that if the government devalues, it does

so by α

θπ

Rbte = . Plugging such formed expectations back into the inequality, we find

out that the policymaker may devalue only if θα

α

+>

kRbt . If net debt is smaller than

that, no rational speculator can expect the government to devalue – the regime enjoys

full credibility.

Finally, if the debt satisfies the condition θα

α

+>>

kRbk t , the regime fails only if it is

expected to fail, but will stay unchanged otherwise. The problem is illustrated in Figure

4.

Figure 4 Devaluation and fixing loss functions under devaluation and fixing expec-

tations

20 40 60 80netdebt b

0.5

1

1.5

2

2.5

lossL

Lf, devaluationexpected

Ld, devaluationexpected

Ld, devaluationnot expected

Lf, devaluationnot expected

BA

Source: Author, based on Sachs et al. (1996a) model

For level of net debt smaller than A, devaluation can be neither desired nor expected, as

the loss from devaluing is higher than from fixing, even under unfavourable expecta-

tions. Conversely, for the level of debt higher than B, devaluation is the only viable (and

- 33 -

therefore expected) option, as it pays to devalue, even if it is not expected by the public

(loss from fixing is higher, regardless of expectations). Multiple equilibria occur for

A<b<B, as the optimal choice of devaluation depends on the expectations.

The typical problem with this part of the model is that it does not explain how the public

sets expectations between zero and α

θπ

Rbte = . So, the holy grail of leading crisis indi-

cators literature – crisis probability as the function of fundamentals get only limited

support in second generation crisis models. The models say that the crisis cannot occur

when fundamentals are very good; they say that it must occur when fundamentals are

really bad, but in the immediate range we only learn that probability is greater than

zero9.

In the two-period version of the model, Sachs et al. show that although devaluation may

destroy all the credibility of the future pegs, it can also reduce the size of expected sec-

ond-period devaluation. Devaluation allows running down on net debt, which can relax

the budget constraint in t+1, even with depreciation expectations always higher than

zero as a result of lower credibility.

9 The problem will persist as long as the investors have the complete knowledge of the state of the economy. Morris and Shin (1998, 2004) show how unique equilibrium could be achieved when speculators have incomplete knowledge of the component of the gov-ernment’s loss function. Chui et al. (2000) show a model merging this modification of the second generation crisis models with Diamond and Dybvig’s (1983) type of creditor run. It yields an unique attack equilibrium for a threshold level of foreign exchange re-serves.

- 34 -

Section 2.3 Asymmetric information as a cause of crises

Asymmetric information was quite early identified as an important factor behind finan-

cial crises. Asian crisis provided an example of how moral hazard (resulting from im-

plicit government guarantees) can cause over-investment, excessive risk taking and con-

tribute to a currency crisis. One of the advocates of the asymmetric information roots of

many financial crises was Mishkin (1998, 1999).

Mishkin argues that asymmetric information, a situation when only one party to a con-

tract have necessary information, was at the roots of most of the currency crises in the

1990s. He pointed to two main channels thorough which asymmetric information can

contribute to a crisis. First, the banking intermediaries and foreign lenders did not have

enough expertise, or motivation to manage the lending risk. Domestic institutions were

not prepared for the lending explosion which followed financial market liberalisation.

Foreign lenders, on the other hand did not have enough incentives to do so, which leads

to the second asymmetric information problem: moral hazard. Explicit or assumed gov-

ernments’ safety nets are an invitation for a reckless lending and borrowing.

Right after the eruption of the Asian crisis, Paul Krugman (1998) suggested a moral

hazard explanation to the crisis. His idea was that implicit public guarantees for the pri-

vate enterprises generated excess demand for risky investments. The firms (and their

foreign creditors) were confident that if their project failed, the government would bail

them out. Such logic can rarely work in the economy-wide scale. When things went

badly for East Asia (depreciation of the yen against the dollar, fall in semiconductor

prices, etc.) too many projects started to fail. The government was not able to bail out

everyone, short term foreign financing dried out and the currency plunged.

- 35 -

Corsetti et al. (1999) present a formalised version of this model. In their formulation,

the country’s economic population consist of élite agents (with access to capital mar-

kets), the government, and the rest of the country (who live out of labour and do not

have access to capital). Rest of the country provides labour, élite borrows money abroad

to finance risky production (production function is a standard Cobb-Douglas formula-

tion, with the random production technology parameter). The utility of the elite depends

on consumption, which in turn depends on the amount produced, debt costs, taxes, and

possible government transfers. Several assumptions are made:

• The government is always able to service its liabilities: either through taxes or

through seignorage, and subsequent inflation and devaluation.

• The government’s initial policy is of a fixed exchange rate, balanced budget, and

negative net liabilities (foreign exchange reserves higher than liabilities). This as-

sumption can be relaxed to show the importance of early fiscal reforms and reserve

build up

• Entire capital stock of the country is financed externally.

• The government’s utility falls to its lowest level if it pursues a laissez-faire policy,

and lets its élite go bankrupt. In other words, regardless of the government’s prom-

ises of no bailout, the companies can rationally expect positive transfers from the

government.

The latter assumption is crucial for the dynamics of the crisis. The élite agents, knowing

about the full bailout as soon as the foreign creditor stop evergreening their losses, pen-

cil in the government transfer contingent on the negative productivity shock, equal to

the difference between the bad pay-off from capital and the cost of borrowing. With this

- 36 -

assumption, marginal return from capital is not equal to the international interest rate r

(as it would be in the distortion-free world), but is higher by the marginal amount of

bail-out.

As a result, equilibrium investment level is higher than optimal (from the point of view

of the economy). This results in sub-optimal return on capital.

When the state of the nature turns negative the elite accumulate losses (on balance lar-

ger than without bail-out presumption, due to excessive investments). But these can be

covered by further borrowing, as long as the rest of the world provides credit. The rest

of the world does provide credit at a riskless rate, because up to a point it is fully in-

sured by the government. The additional borrowing shows as trade deficit, positive even

with the balanced budget.

The financial crisis comes as soon as the foreign investors see that their liquid collateral

(official reserves) reach some critical fraction of the total level of corporate losses fi-

nanced by “evergreening” loans. This critical level is not endogenous in the model. It

would be possible to extend the model to allow for uncertainty regarding the critical

level of reserves, which would allow for financial crisis probability being a function of

the foreign exchange reserves.

Corsetti et al. distinguish between financial crisis and a currency crisis. Financial crisis

means that the implicit government’s obligations become explicit: creditors of the élite

firms refuse to roll their debt, which requires the government bailout. This may, but

does not have to lead to a currency crisis. The latter happens if the government is unable

to raise enough funds through taxes, and must resort to the money-printing, which leads

to the collapsing peg, in a first-generation spirit model.

- 37 -

Two important outcomes of the model concern the benefits of financial market repres-

sion and tight fiscal policy ahead of the crash. The former increases costs of capital to

the élite, lowering the excess rate of investments10. Tax on foreign borrowing counter-

balances biased upwards (perceived) return on capital for the firms, and is justifiable.

This way firms internalise the contingent liability of the government towards the foreign

creditors.

Higher taxes overall (on labour) are worse, as they do little to prevent financial crises

(bailouts), but they still do help in stemming currency crises – government debt gets

lower with higher tax intake, allowing to bailout elite firms without resorting to money

printing. If reserves grow at a sufficient rate (higher than the rate of growth of exter-

nally-financed corporate losses), the crisis may never turn into a currency crash. High

budget surplus alone is not enough to guarantee immunity from a currency crisis. It de-

pends on the relative rates of public debt reduction and loss accumulation by elite firms.

Presumably, the latter depends on the quality of corporate governance and the overall

stage of development: in the early stages the risk of failed investments could be quite

high, due to political disturbances, border conflicts, quality of education, etc. East Asian

economies were on the other side of the spectrum: the return on capital already de-

creased towards developed countries’ levels, while the inflow of money continued.

Dooley (1997) shows a similar, yet less encouraging story in his “insurance model.” It is

especially interesting as it suggests that high international liquidity can actually cause a

10 Aizenman and Turnovsky (1999) show that introduction of reserve requirement in ei-ther lender or borrower country could increase both countries’ welfare, thanks to lower default risk.

- 38 -

deterministic cycle resulting in a violent crisis. The mechanism suggested by Dooley

works as follows.

Once (1) the government of a country has incentives to bail out domestic borrowers, (2)

the government has a positive net worth, and (3) capital account is sufficiently liberal-

ised, the crisis cycle starts. Domestic residents compete to borrow foreign money

(knowing that the government will provide free insurance, and will bail them out any-

way if they fail to pay – see (1) above), driving the domestic yield upwards. Foreign

creditors seeing that the government is (1) willing and (2) able to pay the insurance

premium if their borrowers fail to pay use (3) the liberalised capital account to pump in

the funds. As soon as the overall liabilities (including the implicit liabilities) of the gov-

ernment match available assets (these are not growing in line with liabilities because of

moral-hazard induced excessive yield11), the foreign creditors rush to claim their insur-

ance premium. Regardless of the exchange rate regime, resulting sudden outflow of

capital causes severe fiscal costs.

Section 2.4 Liquidity and balance sheet models

In the models described above the international liquidity played a prominent role, but it

was not the key, driving factor behind crisis-creation. Recent years brought to the light

several models dealing explicitly with (lack of) international liquidity as an ultimate fac-

tor behind foreign exchange crises. Typical model of this kind is presented in Chang

and Velasco (2000). The model is based on the work on bank runs of Diamond and

11 One could ask why competition for foreign funds drives yields up, while foreign com-petition to lend to counterparties with government guarantees does not drive yields down. The answer to that could be a difference in the government’s ability to service private debt risk assessment by foreign creditors and domestic corporations.

- 39 -

Dybvig (1983). In the models, the banking sector works as a term-structure transformer,

and as such has a structural asset-liability term mismatch. Banks are needed, because

private agents have incomplete knowledge of other agents’ inter-temporal consumption

preference and because the production technology is illiquid. With individual consump-

tion preference unobservable, the risk of the investment needing to be liquidated before

its normal yield is uninsurable. In the absence of banks, the agents must settle for less

profitable, but liquid technology.

Because banks deal with many clients, they can use law of large numbers to optimise

their term structure, amount of reserves held, and long-term investments undertaken.

The optimised (in terms of expected profit) amount of reserves, however, usually gives

rise to a multiple equilibrium solution. Either an outcome superior to the private com-

petitive (without bank inter-mediation) equilibrium prevails, or run on banks happens.

Because the small liquidation value of the non-liquid assets, this outcome of a run is

usually worse than that without bank intermediation.

The translation of such a model of a bank run to the world of foreign exchange crises is

then quite straightforward. If foreign depositors decide to run on the (insufficiently liq-

uid) local banking sector, either banks fail (if the central bank does nothing), or fixed

exchange system collapses (if the central bank provides liquidity to the sector by print-

ing money after using up insufficient foreign exchange reserves). The level of interna-

tional liquidity is crucial, the more international reserves the central bank has, the less

severe banking/currency crisis is.

The class of models does not only explain how runs on insufficiently liquid banking

sectors can translate into currency crises. It also shows that the overall liquidity level

held by the sector may be optimal from expected return point of view, but it may still

- 40 -

give rise to a switch to crisis equilibrium. While it is quite easy to remain liquid, it is

rational (certainly for individual banks, but also often for the economy as a whole after

taken into account the social cost of the systemic crisis) to have some maturity mis-

match. Similar argument applies to the term structure – high short-term indebtedness

may be individually rational (although it can be socially inferior to long-term debt). A

very simple model of this kind is provided by Rodrik and Velasco (1999).

The domestic investor (or a bank which represents several homogeneous investors, the

profit or loss of which depends on the performance and fate of the “real economy”) in a

three period world has access to an illiquid technology which yields kR > k for k units

invested after two periods, but in case of earlier liquidation of the part of the investment

l ≤ k gives only lρ < l. Consumption (linear function of which is the investors’ utility)

occurs in period 2, in which the investors pay back all the remaining debt and consume

the rest. Foreign financing of the project can take two forms – long term (LT, equal to k-

d) and short term (ST, equal to d), up to the total limit of k. Debt principal cannot ex-

ceed the investment in any period. Holders of the short term debt may choose not to

roll-over their loans in period 1 (before the illiquid investment matures), which will be

called “a run”.

Runs occur with a positive probability p. Rodrik and Velasco’s model share the problem

typical to most of the multiple equilibrium models – p is exogenous. The reasons why

the lenders suddenly panic are outside the realm of the model.

While the world risk-less rate is zero, the ST and LT interest rates rs and rl faced by the

domestic investor are endogenous as shown below.

- 41 -

Two scenarios can be considered: no-run and run. In the optimistic case of no run, the

domestic investors’ revenues are:

(R k)– d rs – (k-d) rl

When d, or ST debt is positive, a run may occur in period 1, resulting in the need to liq-

uidate a part of the investment (equal to ρ

)1( srd +)12. Three things may happen, depend-

ing on the amount of short-term debt and the degree of illiquidity ρ. If d is small and/or

ρ is close to 1, ST debt holders are repaid, and so are LT debt holders in period 2. Inves-

tors’ revenue is smaller (proportionally to the size of the run). If d is larger, (the critical

size requires, that ( )

( ) ( )k

rrR

rRd

ls

l ρρ 11

1

+−+

+−> ) after the liquidation satisfying the ST

debt holders, there is not enough money to repay the LT creditors and the investor bank-

rupts. With sufficiently illiquid technology, or sufficiently large ST debt, the investor

goes bust as early as in period 1, which requires the total investment ρ

)1( srdk

+< .

The run equilibrium is welfare inferior to both domestic investors and foreign creditors.

The costs of winding down of the illiquid project are the reason for it. The short-term

debt, unleashes the potential for the crisis.

12 There seems to be a trivial mistake in the Rodrik and Velasco’s model: the total amount the foreign currency short-term lender gets in period 1 (if it runs) and in period 2 (if it does not) is exactly the same! If p were greater than zero, it would be suboptimal to ever roll-over short-term debt. A simple correction could be adjusting the term in

brackets to 1

2xrd

ρ

+

, where 2

1 12x

s

rr

= + −

- 42 -

The term structure of the interest rates is derived on two assumptions. First is the risk

neutrality of the foreign creditors. Second is the assumption that if funds of the bankrupt

domestic investor do not suffice to serve all the creditors, the remaining sum is evenly

divided among them. It is an equivalent (for risk neutral creditors) to the situation when

the probability of getting the full amount is directly proportional to the ratio of available

funds to the total debt. LT creditors want to have expected return from lending to the

domestic investor equal to the foreign interest rate of zero. That requires:

( )( )( )( )

( ) 111,0,1

11 =+

−+

−

++− ll

l rdkr

dkR

MinpMaxrpρ

, which means that:

( )

( )

kdR

Rk

kdp

dk

dkpR

p

R

Rkd

rl ρρ

ρ

ρ

ρ

ρρ

<<−

−

>−

−

−

−

−

−

−<

=+

−

1for ,

for ,1

11

1

1for ,1

1

1

ST debt holders face risk-less return of their money if d < kρ, so in such case rs is zero

(which is world interest rate). Otherwise, the short term rate follows:

( )( ) 111 =++−d

kprp s

ρ, so

( )

−

−=+

d

p

prs

ρ1

1

11

The bottom line is that the short-term interest rate is always lower than long term inter-

est rate (unless ST debt is very small, then both are at the world level). This is a danger-

ous situation. Although in the world of the model, it is optimal for the domestic investor

- 43 -

(or the economy – there is only one borrower) not to have short-term debt whatsoever

(the risk of the run is internalised, as shown in Figure 5), it would be easy to extend the

model to allow for borrowers wanting to take advantage of ST credit. There may be

several issues preventing the individual investor from choosing LT debt. One is that

normally, there are many investors (as opposed to just one in the basic model), who do

not internalise the impact of ST debt size on the price of credit. Then, if both interest

rates, and the overall maturity structure of the foreign debt are taken as given, it be-

comes optimal to borrow as much as possible in the short bonds (rs<rl unless, the as-

sumed overall share of ST debt is zero). Rodrik and Velasco argue the problem is

strengthened by the lending policy of sovereign ceilings, where the overall risk of the

sovereign lending in a country takes precedence over the individual creditor’s risk. This

meant that no corporation can enjoy better credit rating than the sovereign bonds of the

country it is based in. The policy started to be relaxed recently, especially for middle-

income countries, by differentiating sovereign rating from a country ceiling, see

FitchRatings (2004).

Other reasons why ST debt may prevail could be regulatory framework favouring ST

debt, implicit bail-out guarantees, which alter the consumption function of the investor

and make it much less worried about the risk of the run, and subsequent bankruptcy.

- 44 -

Figure 5 Expected profit of domestic economy/investor as a function of short-term

debt

0.2 0.4 0.6 0.8 1 d

0.1

0.2

0.3

0.4

0.5 Profit

Source: Author, based on Rodrik and Velasco (1999) model

While the model is very simple and does not take into account such issues as exchange

rate, the reason behind the crash, etc., it yields several interesting results about the im-

portance of short term debt (or low international liquidity):

• Large short term debt increases the severity of the prospective crisis, as in case

of a run more real assets have to be liquidated

• Amount of short term debt influences the price a country must pay for long-term

capital. When liquidity is really low, the ST interest rate is also affected by

growing of ST debt.

• An economy, which internalises the above-mentioned impact of ST debt on the

yield curve should choose to have as high liquidity as possible. Individual bor-

rowers’ optimal decisions, however, could easily prove to be sub-optimal from

the social point of view.

Other models explicitly dealing with liquidity include: Goldfajn and Valdez (1997),

Chang and Velasco (1999 and 2000), and Krugman (1999).

- 45 -

Krugman (1999) present a simple crisis model dealing not so much with how, and when

depreciation happens, but with the costs to the real economy, and how the multiple ex-

change rate equilibria can occur. His modified (and simplified) Mundell-Fleming model

consists of three equations.

+

=

−+−+−

ysNXsyiDy ,,, ,

where y is output, D is domestic demand, and NX is net exports. Signs over domestic

interest rate i and real exchange rate s indicate first derivatives. Output equation differs

from the standard Mundell-Fleming setup, with the dependence of domestic demand D

on the exchange rate. In Krugman’s model exchange rate has dual effect on domestic

firms. On one hand, weaker currency allows the firms to compete and export. On the

other, large depreciation cripples the firms’ ability to invest through adverse impact on

their balance sheets. Plunging currency enlarges dollar denominated debt, shrinking the

net value of the domestic companies, and severely restricting their ability to invest, thus

the adverse impact of depreciation (rising real exchange rate s) on domestic demand D.

Krugman does not specify the exact functional form of the equation, the idea is, how-

ever, that s

D

∂

∂ is only significantly negative for intermediate values of the real exchange

rate change. For extremely weak currency, big (indebted abroad) firms would all be al-

most all dead anyway, so further depreciation would not depress investments further;

for extremely strong currency, some depreciation could hardly harm the firms. In other

words, liquidity (at least domestic corporations’ liquidity) is the key, if not for currency

crash prevention, certainly for ensuring the crisis does not cost too much. Highly lever-

aged economy will suffer a lot more as a result of a plunge.

- 46 -

Two remaining equations of the simple model, representing money market equilibrium

and interest rate parity are as follows:

=

+−

yiLP

M, , where M is the nominal money supply, P is the price level, L is the de-

mand for the real money balances, which in a standard way depends on the interest rate

i and the real income y.

i = i*, is the final, interest parity equation, which assumes static expectations about the

exchange rate. This implies that domestic interest rate is equal to its foreign counterpart

i*.

The three equation setup is enough to determine the balance between the (real) ex-

change rate and real income, as shown in Figure 6:

Figure 6 Modified Mundell-Fleming model

s

y

A

A

G

G

Source: Krugman (1999)

Because of the adverse impact of real depreciation on investments and domestic de-

mand, the GG curve, representing goods market equilibrium has a back bending seg-

ment. As a result the GG curve crosses the AA curve (representing interest parity) sev-

eral times. There are multiple real income-real exchange rate equilibria. An equilibrium

with strong local currency with poor exports and large investments can, via an exchange

- 47 -

rate collapse (as a result of market speculation, or a bout of financial market contagion)

switch into equilibrium of bankrupt indebted corporate sector but thriving small-time

exporters.

The important caveat coming out of this model is that net foreign debt, and low interna-

tional liquidity of the real sector makes multiple equilibria and large depreciations pos-

sible. Lowering the level of foreign-currency denominated debt would straighten the

backward bending section of the GG curve. The role of the official reserves, however, is

somewhat problematic. Do they influence the risk of the equilibrium switch? If the poli-

cymaker is willing to tighten monetary policy (leave foreign exchange interventions un-

sterilised), it should. The speculative attack will result in AA curve moving to the left,

which will hurt the real economy, but the exchange rate should remain close to the

original levels. Sterilised interventions leave us in the indeterminate region – if they

help to restore confidence the economy may remain in the strong peso equilibrium, if

not, the currency plunges.

The model differs from the earlier Krugman (1998), which stressed the importance of

moral hazard, and excess investments in Asian crisis economies. In the newer model,

excess investments and resulting inefficiencies are not necessary to create a crisis. They

aggravate the backward bending feature of the GG curve, but basic shape of the goods

market equilibrium curve may remain even without moral hazard – high corporate for-

eign currency gearing for whatever reasons suffices.

Section 2.5 Inventory model of foreign exchange reserves

There are few models addressing the issue of foreign exchange reserve holding deci-

sions. Frenkel and Jovanovic’s (1981) inventory model of foreign exchange reserves is

- 48 -

one. Although it is not directly connected with foreign exchange crises, it does not even

assume fixed exchange rate (some need for foreign exchange reserves suffice), its modi-

fied version may be used to predict the holdings of reserves for a country under a threat

of a speculative attack.

The model rests on three reasonable assumptions: 1) some reserves are necessary; 2) the

restocking of the foreign exchange reserves is costly; 3) holding reserves bears some

opportunity costs. The model assumes that the reserves follow a random process, and if

they fall below a certain threshold, they must be restocked (via domestic demand

squeeze, monetary tightening, etc). Holding more reserves reduces the risk of bearing

the costs of restocking, but is usually costly on its own account (difference between lo-

cal and foreign bond yield, according to Frenkel and Jovanovic). In the original model,

the stochastic process governing the reserve fluctuations is a drift-less Wiener process,

which ensures an easy solution and no discrete jumps in the stock of the foreign ex-

change reserves. In such case, the solution of the model is

r

CR

σ=0 ,

where R is the optimal reserve level, following a restocking, σ is volatility of reserve

changes, C is a country-specific constant representing costs of restocking (e.g. persis-

tence of the current account deficit, reliance on imports, etc), and r is the opportunity

cost of holding foreign exchange reserves. Log transformation of the result yields an

easy to estimate form:

ln R0 = c + 0.5 ln σ – 0.25 ln r,

where c is the country-specific constant, representing costs of restocking.

- 49 -

The empirical application proved surprisingly successful. Flood and Marion (2002) re-

port the Frenkel and Jovanovic’s model parameters as “nothing short of miraculous:”

the sample of 22 developed countries in 1971-1975 yields ln σ and ln r parameters at

0.505 and –0.279 respectively. As Flood and Marion note, though, there are several

problems in both the empirical application of the original model, and the theoretical as-

sumptions.

The assumption of the smoothly changing (Wiener process) foreign exchange reserves

are at odds with both the theory of the currency crises and the recent experience of both

developed and developing and emerging countries. Most of the currency crises models

point to a rapid depletion of remaining reserves when a crisis hits (Krugman’s classic,

Dooley’s insurance model, liquidity crisis models).

Second problem was the positive bias of the reserve volatility created by restocking ac-

tions by the policymakers. Restocking increases volatility, but that increase should not

be taken into account by the policy makers pondering the risk of reserves hitting the

lower limit.

The two effects described above are not negligible. Flood and Marion report skewness

tests showing 41% of countries exhibiting non-normal positive shocks to reserve hold-

ings, and 21% of countries suffering from negative skewness (crises). Therefore, using

the original functional form of the optimal reserve equation is invalid. Flood and Marion

propose using a shadow exchange rate concept known from the 1st generation crisis lit-

erature instead: if the shadow exchange rate crosses the market rate (somehow regu-

lated, or influenced by the policymaker), the reserves flow out, forcing the authorities to

pay for the restocking of the reserves. This is the equivalent of the reserves hitting the

lower-threshold value, but allows to substitute modelling of irregularly changing foreign

- 50 -

exchange reserves by smoother-looking shadow exchange rate model. This has one ma-

jor drawback. In order to properly model shadow exchange rate, the underlying floating

exchange rate must be modelled as well, a difficult (and restricting) task to say the least.

Thirdly, neither the original model, nor the subsequent extensions addressed the possi-

bility of the level of reserves influencing the risk of their sudden depletion. In a Sachs et

al. (1996a) type of model, the level of reserves enter the equation as driving variable: if

reserves are large, they never have to be restocked, because there is never a speculative

attack. Having very little of them is useless, because they do not last a single period. In

an intermediate range, the original model may (almost) applicable – we know little why

the switch in investors’ sentiment happens, so it may well be modelled as a purely ran-

dom process. But even then, the reserve volatility σ must be replaced with some other

measure of crisis risk. The actual reserve volatility explain only a risk of reserves reach-

ing the threshold of the “sure crisis zone”, but does not have to be directly related to the

crisis risk in “the self-fulfilling crisis range.”

Finally, some of the empirical applications of the model (Frenkel and Jovanovic, Flood

and Marion) used local currency bond yields, or local currency bond yield minus US

interest rates as a proxy for opportunity cost of holding international reserves r. The

costs of obtaining foreign exchange reserves is not the local currency interest rate, it

should be the foreign currency bond yields (less equivalent yield of the instrument in

which the reserves are held). Therefore, it is more appropriate to follow Edward’s

(1985) path, using eurocurrency markets, or Eurobonds and Brady bonds for the emerg-

ing markets in the 1990s.

- 51 -

Although the inventory model of foreign exchange reserves is only loosely related to the

crisis literature, it does provide a very useful and flexible tool for analysing foreign ex-

change reserve adequacy.

Section 2.6 Summary: liquidity in crisis models

Foreign exchange reserves or international liquidity appears in every class of the ex-

change rate crisis models. In the basic first generation model foreign exchange reserves

are like sand in the hourglass, which dribbles out as the crisis comes nearer. Foreign ex-

change reserves are a useful crisis prediction tool, but usually they cannot serve as a

prevention mechanism – excessive fiscal deficits are at the root of the problem.

Setting net debt as a fundamental variable, a model within the second-generation

framework can be constructed, which allows for multiple equilibria for some ranges of

international reserves (net of debt), and single equilibrium with very high and very low

liquidity. The level of reserves is therefore relevant for the country’s susceptibility to a

bout of financial market panic.

International liquidity has a dual role in moral hazard models of financial crises. On one

hand, higher official reserves may prevent the currency crisis from happening, in a

sense offsetting the artificially high corporate sector debt. On the other hand, liquid

government welcomes the abuse of the implicit insurance it offers to the country’s

firms. High reserves net of government debt mean that there is plenty of space for risk-

free lending. It may lead to a problem similar to the first generation crisis, with high re-

serves only postponing the crisis, but not eliminating the ultimate cause of it – the build

up of contingent liabilities. The ultimate importance of prudent fiscal policy and foreign

exchange reserves depends on the quality of local investments.

- 52 -

Models explicitly dealing with insufficient international liquidity as a source of crises

point to the inherent risk for developing countries, which rely on external financing ef-

fectively being liquidity transformers. The risk is similar to the one faced by a bank, al-

ways threatened by a run on deposits. Banks are protected by the institution of the

lender of the last resort, reserves (not necessarily mandatory) and capital adequacy ra-

tios. Countries can benefit from only a limited support from international rescue lenders

(like IMF), they should, therefore ensure that their liquidity does not fall too low. Li-

quidity crisis literature is just one strain of the new balance sheet approach to the cur-

rency crises. Another model of this broad class is represented by Krugman (1999), who

points to the exchange rate-corporate balance sheets-investments channel of exoge-

nously determined depreciation. Foreign currency borrowing by firms makes their bal-

ance sheets (and subsequently, the ability to borrow and invest) vulnerable to deprecia-

tion. High foreign exchange reserves and an unsterilised intervention, while hurting

output, could prevent the jump-depreciation from happening.

Finally, buffer-stock models of foreign exchange reserves can, in principle, break away

from exchange rate modelling and the exact mechanism of reserve depletion. In its

original form, the policymaker simply attempts to minimise the risk of reserves hitting

the lower threshold, simply by observing its volatility, and costs of potential restocking

(necessary when reserves do hit the threshold). The problem is that probability distribu-

tion of the reserve changes itself requires powerful and restrictive assumptions regard-

ing the process driving the whole process.

- 53 -

Chapter 3 Leading indicators literature

The currency crisis models described above tried to explain the crises which had hap-

pened. Assuming the underlying forces behind crises do not change too much (not every

crisis is different), they should also help in predicting crises, or in setting up policies

preventing them. This chapter reviews the leading indicators empirical literature, which

attempts to find how reliable the models are for predicting crises (and to find out which

other variables should the theoretical research be focused on). There is a long way from

being able to predict crises to being able to prevent them. There are two problems caus-

ing this divergence. One is the difference between a leading indicator, and the actual

cause of crises (Flood and Jeanne, 2000 show how countries addressing low liquidity

problem by higher borrowing can hasten the crisis increasing their fiscal burden). Sec-

ond issue is political problems relating to addressing the causes of crises, even if they

can be correctly identified.

There are several ways to categorise the leading indicators of currency crises literature

(also called as early warning systems). One is by time and country range of the sample.

Second is by the methods used. Third is by the crisis definitions – the leading indicator

of what is being searched for. Fourth and final categorisation is the results – what vari-

ables were used, and which are statistically significant in predicting crises. Figure 8 on

page 86, which in part bases on surveys in Kaminsky et al. (1998) and Abiad (2003)

summarises the recent efforts. The four sections below describe the different approaches

and results of the leading crisis indicator literature.

- 54 -

Section 3.1 When and where

While most research is essentially cross-country, pooled studies, the scope of the analy-

sis differs.

The timeframe of the analysis varies, with the longest studies spanning from the 1950s

(Bilson, 1979; Edwards and Santaella, 1993; Kamin, 1988), most of the recent studies

concentrate on the last 15-25 years. The empirical application of the model in Chapter 5

and the model in Chapter 6 both fall in the latter category.

Several studies (including Sachs et al., 1996b) concentrate on just one bout of market

volatility, across several countries: e.g. Mexican crisis of 1994, Asian crisis of 1997 etc.

The idea behind such an approach is that currency crises differ over time – theoretical

literature also follows this pattern: first generation crisis model was inspired by the de-

faults of the 70s, EMS and Mexican crises heralded the advent of second-generation

models, and the Asian crisis shifted attention to the “balance sheet” models. If each cri-

sis bout is different, it makes sense to evaluate them in clusters.

Important consequence of such estimation method is that the results speak about the

probability of the crisis (or depth of the crisis) conditional on it happening somewhere

else (Mexico, the EU, Russia, East Asia). Thus, the resulting model is unable to provide

answers to the question of crisis risk in any given year. It can, however, tell about the

impact of a set of variables in preventing infection by a contagious crisis elsewhere.

Such restriction helps to improve the fit of the probit models. In long time series pooled

regressions, ones on the left-hand-side of the equation happen extremely rarely, but the

meaning of the parameters is different. If a policymaker is concerned of the costs related

to the crises, it should take into account the global probability, not just conditional risk

estimates.

- 55 -

Frequency of the data depends on the country sample and timeframe used – most of the

recent studies use monthly data. On one hand it does not allow to use some of the more

exotic variables (like Ghosh and Ghosh’s, 2003 structural factors), on the other it pro-

vides an opportunity to find dynamic dependencies in the data, precisely pinpoint the

time of the crisis and provide a functional early warning signal for financial markets.

Four classes of country range can be found in the literature. The narrowest include just

one country. In order for the numerical analysis to be meaningful in such case, the coun-

try must have quite a turbulent currency history. Ötker and Pazarbaşioğlu, 1995 analyse

Mexico between 1982 and 1994. In that period the authors find 4 devaluations and 7

exchange rate regime shifts.

Many studies concentrate on a region. Latin America (Sachs et al., 1996b; Goldstein,

1996; Herrera and Garcia, 1999), East Asia (e.g. Moreno, 1995; Nag and Mitra, 1999;

Kwack, 2000; Zhang, 2001), transition economies (Krkoska, 2001; Bruggeman and

Linne, 2000), FSU countries, ERM-2 members (Ötker and Pazarbaşioğlu, 1997; Marti-

nez-Pena, 2002) are the main subjects of such studies. As regional clustering tends to

imply trade linkages, and sharing the same investment sources, the studies of this kind

make it impossible to assess the influence of (potentially powerful) effects of trade-

related or bandwagon effect contagion (all countries in the sample share similar charac-

teristic).

Third class of research sample scope is the broad country class. Emerging markets

(Vlaar, 2000; Weller, 2001), developed countries (Eichengreen et al. 1995), or develop-

ing countries (Frankel and Rose, 1996) are the main classes of this kind. There may be

two reasons for keeping the groups separate. One is the data reliability and availability.

For example, data on market interest rates (necessary for some crisis definition calcula-

- 56 -

tions) may not be available for non-industrialised countries. Second reason is the suppo-

sition that there are other drivers causing currency crises in developed and emerging

markets.

The final sample size is all countries in the world (subject to data availability). Exam-

ples of such studies include Edison (2000), Collins (2001), Caramazza et al. (2000).

Section 3.2 Methods used

Most of the studies use one of the three approaches of evaluating crisis risk –

logit/probit analysis of the crisis probability, OLS regression of the continuous crisis (or

devaluation) variable, and signals method, popularised by Kaminsky et al. (1998).

Section 3.2.1 Quantal response techniques

Logit/probit technique analysis requires a binary (or otherwise discrete) definition of

the crisis – probability of its occurrence is the dependent variable. Explanatory variables

are a set of the leading indicators, usually chosen using the general-to-specific tech-

nique.

Because most of the studies are panel regressions, fixed effects are a potential problem.

If individual, unobservable country characteristics are correlated with explanatory vari-

ables (or there-is a time-varying element, correlated with explanatory variables), the es-

timators are biased13. The studies, which address it, however, are quite rare (Esquivel

and Larrain, 1998; Hawkins and Klau, 2000 do deal with it) – the degrees of freedom

costs are large if sample spans across many countries.

13 The problem concerns also OLS-type regressions

- 57 -

Autoregressive Conditonal Hazard model (based on Hamilton and Jorda, 2002) ex-

tends the probit-type model by incorporating the time, which passed since the previous

crisis as an explanatory variable.

Fisher discriminant analysis (McLachlan, 1992) is another form of quantal response

model, which translates a set of explanatory variables into several discrete states of the

explanatory variable. Burkart and Coudert (2000) claim that this method is less prone to

the multicollinearity problem than the logit.

Section 3.2.2 Standard regression

Equivalent analysis explaining continuous crisis variables requires simple OLS regres-

sion. Bussière and Mulder (1999ab), Kwack (2000) are the recent examples of such

studies.

A variant of this approach is a non-linear regression technique (Bussière and Mulder

1999b) addressing the interactions between explanatory variables. A non-linearities in

parameters specification allows some variables to act as triggers – e.g. fundamental

weaknesses only matter if coupled with low international liquidity. Similar way to ad-

dress the interaction between explanatory variables is the slope dummies regression

used by Sachs, Tornell and Velasco (1996b), and Nitithanprapas and Willett (2000).

The method is to add a new variable being a product of an indicator already included in

the regression and a dummy of e.g. “sufficient reserves”. If high international liquidity

makes country invincible to the excessive current account problem then sum of the two

coefficients should be zero. Nitithanprapas and Willett (2000) also specify a composite

indicator to test the “Lawson doctrine” (current account is irrelevant as long as govern-

- 58 -

ment balances its books) – their current account deficit variable is greater than zero only

if budget deficit is greater than 3% of GDP.

Section 3.2.3 Signals approach

The third technique requires a little more elaboration. The signals approach of Kamin-

sky et al. (1998), and later utilised in many more studies is essentially univariate and

non-parametric. The authors using this method first identify the binary crisis occur-

rences using one of the techniques described in the Section 3.3 below. This allows dif-

ferentiating between “tranquil” and “crisis” periods in a country. Then they set an arbi-

trary signalling window. This is the time frame within which the switch from tranquil to

crisis state should occur, once an indicator issues a warning signal. Kaminsky et al.

(1998), and Goldstein et al. (2000) use 24 month as a signalling window.

The idea behind the technique is that the macroeconomic indicators issue signals before

the crisis occurs. For example, if lending-deposit interest ratio increases above a certain

threshold, a currency crisis within the following 24 months becomes likely. The signal

threshold (in the example, “to what percentile lending-deposit spread would have to

grow relative to its country-specific distribution”) is estimated to minimise noise (N) to

signal (S) ratio for each variable. The authors wanted to find such a level of variables

which will constitute a signal issuing as little “false alarms” as possible. Specifically,

Kaminsky et al. minimise:

BN B D

ASA C

+=

+

(3.1)

- 59 -

where A is the number of cases where crisis occurred after the indicator issued a signal,

B is the number of cases with no crisis after signal, C shows unsignalled crises and D

are no-signal no-crisis occurrences. Noise is thus only type I errors. Another indicator,

used by Goldstein et al. (2000) is “proportion of crises actually called” PC=C/(A+C).

This indicator concentrates on type II errors14.

Thresholds minimising these indicators are set in percentiles, not absolute values of the

early warning variables, so the signals are different for different countries.

There are several options from then on. One is simply counting the number of the vari-

ables that issue crisis signals at any given time. The higher the number, the higher the

crisis risk in the next 24 months. A more sophisticated approach is creating a composite

index, and weighing the crisis signals by their reliability: noise/signal ratio (see e.g.

Goldstein et al. 2000, p. 58).

The procedure has since been applied in numerous papers including Edison (2000),

Berg and Patillo (1999), Bruggemann and Linne (2000) and Hawkins and Klau (2000).

A variant of such study is informal graphical presentation of the behaviour of various

indicators around the crisis period. Aziz et al. (2000), Osband and Van Rijkeghem

(2000) pursue this strategy. One advantage of such non-parametric descriptive exercise

is that it allows to look beyond the crisis. Błaszkiewicz and Paczyński (2003) attempt to

evaluate the social and economic consequences of currency crises in several transition

and emerging market economies.

14 Another version of the measuring the fit would be sum of type I and type II errors relative to properly predicted crises and calm periods: (B+C)/(A+D).

- 60 -

Another variant of the signals approach is Binary recursive tree (Ghosh and Ghosh,

2003 apply it to in the crisis risk research) method which leads the ranking procedure

several steps forward. After setting the thresholds to minimise the noise to signal ratio

(Ghosh and Ghosh use a sum of type I – B in the formulation of Kaminsky et al. and

type II errors – C), the most reliable indicator (e.g. high current account deficit) is cho-

sen. It splits the sample into subsamples of high and low deficit countries. Then the

same procedure is repeated for the two subsamples (branches of the tree). The procedure

is continued as long as it brings significant improvement to the fit (otherwise it could be

continued until all observations are placed). Figure 7 shows a result from Ghosh and

Ghosh (2003). The most reliable indicator (Public Sector Governance) is the first node.

Countries with poor public sector governance stand 4.8% chance of suffering a currency

crisis. The indicator which best signals crises among counties with poor public sector

governance is current account deficit (second node on the left-side branch). Countries

with poor public governance and current account deficit above 2.6% of GDP stand 9%

chance of suffering the currency crisis. The procedure then continues for all branches

and sub-branches until the addition of another node brings little new information (at the

limit, all nodes in the bottom of the tree give conditional probability of 0 and 100; all

observations are then included in the tree).

The benefit of this procedure is the fact that it captures the interactions between the

variables well. It allows to differentiate between the influence of e.g. high budget deficit

under high and low international liquidity. This could help choosing non-linear interac-

tion terms in probit models. On the negative side the statistical properties of such an in-

dicator are not very well known.

- 61 -

Figure 7 Binary recursive tree estimation result

(1)

Good Public Sector

Governance? 2

(6)

Corp

Debt/Equity

< 380 pct?

(2)

CA/GDP < -2.6

pct?

(3)

Corp.

Debt/Equity

< 96 pct?

(5)

�REER < 2.5

pct?

(4)

Ext. Debt/

Reserves

< 20

Yes

0

No

14.7

Yes

0

No

7.0

Yes

0

No

28.6

No

100

No

4.8

Yes

0.7

Yes

9.0

No

2.2

Yes

3.0

Source: Ghosh and Ghosh (2003), page 497.

Section 3.2.4 Other methods

Apart from the three main methods of constructing early warning systems, other ap-

proaches have also been attempted.

Artificial Neural Networks (ANN) – Nag and Mitra (1999) try to apply this technique

(Kuan and White, 1994 provide a survey of ANN’s applications in economics). The

ANN approach is similar to binary recursive tree technique: input signals are weighted

and trigger a binary output if certain input threshold is exceeded. The signals can then

- 62 -

be used as input for further evaluation producing final output. The approach is flexible,

but if there are too many nodes overfitting could be a problem (the model is then cali-

brated to react to noise in the data).

VAR – restricted vector autoregressive estimation was applied by Krkoska (2001). The

technique requires the use of a continuous crisis variable, and under normal data avail-

ability circumstances, arbitrary choices regarding exogenous variables and restrictions.

In Krkoska’s work it was especially important, as the transition economies’ sample

leaves very little degrees of freedom.

Section 3.3 What is a currency crisis?

The sample and the methodology used to construct an early warning system touched an

important problem in measuring the crisis vulnerability – definitions of the crucial vari-

ables. The problem starts very early: how do we define a currency crisis? A few ways to

define a currency crisis are used in the literature. The problem is real, as the choice of

the dependent variable can influence the results. Eichengreen at al. (1995) get opposite

results on the importance of fundamentals depending if the crisis is defined using the

exchange market pressure indicator or by a regime switch. The following section de-

scribes the most important ones.

Section 3.3.1 Exchange rate definitions

Currency crisis must concern the value of a currency. This is why many authors define a

crisis as extreme movements in exchange rate. Frankel and Rose (1996) is a good ex-

ample of such a definition: a crisis is said to occur when local currency depreciates rela-

tive to the US$ by 25% in one year. In order to filter out hyperinflationary currencies,

additional condition of 10% higher depreciation than in the preceding year is added.

- 63 -

Other measures involve taking into account real, instead of nominal depreciation (see

e.g. Goldfajn and Valdés, 1997 – this is also a convenient way of dealing with hyperin-

flationary countries), or the exchange rate regime change. The latter definition, while

close to what is generally considered a currency crisis in much of the crisis literature

(most of the first, and second generation models), cannot deal with floating exchange

rate cases.

Section 3.3.2 Capital flows definitions

Less often, authors resort to capital flow definitions, defining crisis as a severe outflow

of capital from the concerned country. An example of such a definition is Rodrik and

Velasco (1999) and Radelet and Sachs (1998b). One of their crisis indicators is equal to

1 if net private annual capital flow changes from positive to negative by at least 5 per-

centage points. This kind of definition can (among others) easily detect speculative at-

tacks of the first generation type, which are characterised not by a major jump in ex-

change rate, but instead a fall in foreign exchange reserves (pure exchange rate defini-

tion would not necessarily capture such a crisis). Such a definition would not, however,

detect a crisis preceded by a year of slow leak of capital.

Another type of capital flow which could be associated with currency crises is domestic

capital movement. Banking crises are often analysed in conjunction with currency crises

for two reasons. First, systemic bank runs put a severe strain on monetary policy and

may lead to the collapse of pegs if foreign exchange reserves are not sufficient. In such

case, the only way to provide liquidity to the banking system is to increase money sup-

ply. Theoretically, a purely domestic bank run, in which deposits are converted to local

currency and held in that form by households should not put any pressure on the ex-

change rate. Increase in money supply is the right (and safe) response to thus increased

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money demand. In practice, however (Turkey 2001, Russia 1998), bank runs in devel-

oping countries result in conversion of savings into foreign currency. Opportunity cost

of holding local-currency is often high due to inflation (Turkey), and rational domestic

agents can expect lower confidence and capital outflow as a result of banking system

distress. Still, banking crises, while often associated with currency crashes, are separate

events, and most of the research dealing with both, differentiate between them (Gold-

stein et al., 2000; Kaminsky and Reinhard, 1999; Aziz et al., 2000)

Section 3.3.3 Exchange Market Pressure (EMP)

A measure joining the two previously mentioned definitions is the exchange market

pressure indicator. It was developed by Girton and Roper (1977), and since then used by

numerous authors in empirical studies.

EMP indicator is defined as.

1 2t

t tt

REMP w e w

M

−∆= ∆ +

(3.2)

where e is the log exchange rate, Rt is the stock of foreign exchange reserves, and Mt is

the money supply. Weights w1, and w2, are usually set to equalise the variance of the

two components.

The idea behind the indicator is that the simple rate of change of exchange rate is not

the best gauge of speculative pressure, especially when analysing countries with a

mixed exchange rate regime. In particular, a furious speculative attack could be parried

by e.g. unsterilised intervention. As Krugman’s (1979) model shows, even successful

attack may not lead to a rapid depreciation – there is no jump in exchange rate, only a

hike of the interest rate and the fall in reserves. The latter point is especially important,

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as it shows that exchange rate depreciation alone cannot serve as a reliable crisis scale

(there is no question that first generation currency crisis is a crisis, while it is not associ-

ated with a jump in exchange rate).

In its simplest form, EMP indicator is the measure of the domestic money supply and

real money demand. Tanner (1999) shows a monetary model:

( , )t t tmd i Y m π∆ = ∆ − (3.3)

*t t te π π∆ = − (3.4)

1

t tt

t

R Dm

M −

∆ + ∆∆ = (3.5)

(3.3) describes money market equilibrium with real money demand (md) growth equal

to nominal base money supply percentage change (∆m) corrected for inflation π. All the

abovementioned variables are in logs. (3.4) is the purchasing power parity; in what fol-

lows, foreign inflation (π∗) is normalised at zero. Finally percentage change in base

money supply can be split to nominal change in domestic assets (D) and reserves (R)

change relative to nominal money supply level. Putting (3.5) and (3.4) in (3.3) yields:

1 1

( , )t tt t

t t

D Rmd i Y e EMP

M M− −

∆ ∆− ∆ = ∆ − ≅ (3.6)

The right hand side of Equation (3.6) is EMP (Equation (3.2) with weights equal to 1) -

the reduced form of EMP, which shows the difference between growth of the domestic

part of the monetary base, and money demand growth. Depending on the exchange rate

regime, excessive domestic money supply growth (not counterbalanced by higher

money demand) should translate into reserve outflow or exchange rate depreciation.

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As Flood and Marion (1999) show, the problem with the EMP as a crisis indicator used

for early warning system, is that it is biased towards showing unpredictable crises. The

argument applies also to the reduced-form EMP measures – the ones taking into account

solely exchange rate or capital outflow. If the collapse of the exchange rate regime is

anticipated, the reserves start to flow out fast early on, in a sense smoothing the actual

impact. The problem disappears with lower data resolution, but so does the usefulness

of the predictive power of the tests based on such models.

In the empirical literature, crisis is usually defined as an extreme value of EMP. Abiad

(2003) points that authors use the different thresholds varying from 1.5 (Eichengreen et

al. 1996, Aziz et al., 2000), through 1.645 (Caramazza et al., 2000), 1.75 (Kamin et al.

2001), 2.5 (Edison, 2000), and 3 times standard deviations (Karmen et al. 1998) of the

pooled EMP. Odd crisis definition thresholds appear, as some authors maximise good-

ness of fit of their models by varying the threshold parameters (Kamin et al. 2001). Oth-

ers (Caramazza et al., 2000) set it to qualify 5% of observations as crises (Abiad, 2003).

When developed countries are included in the sample, a third component of EMP – in-

terest rate spread is sometimes added.

Abiad (2003) points to two more “technical problems” related to the use of the EMP

thresholds as crisis definitions, advocating Markov-switching approach (see Hamilton,

1994). First, past crises may disappear as volatility of the EMP goes up (together with

the cut-off level of EMP). Second, common procedure of registering only one adjacent

instance of a crisis leads to a serial correlation problem – crisis in t cannot be followed

by a crisis in t+1. Researchers set windows of exclusion between one quarter and 3

years (Frankel and Rose, 1996).

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Another problem of this approach lies in the weighing of the reserve outflow and depre-

ciation. Typical practice of equalising the variance of two components hardly has any

theoretical underpinning. Basic monetary model of exchange rate determination and

Equation (3.6) suggest equal weighs (for a more general approach, see Weymark, 1998).

Exchange market pressure itself and the policymakers’ response to it was a subject of

numerous studies including Connolly and Da Silveira (1979), Wohar and Lee (1992)

and Burkett and Richards (1993) and Tanner (1999).

Section 3.3.4 Discretionary definitions

Another common way of defining currency crisis is the “you will know what a crisis is

when you see it” method. In other words, financial press and academic papers and sub-

jective judgement are used to compile a list of crisis-inflicted countries. Examples of

empirical papers, which use such a definition, include Glick and Rose (1999) and Van

Rijckeghem and Weder (1999). Although in cross-country studies such definition is less

frequent than the ones relying on a precise description, it is prevalent in single-country

studies. In particular most of the post-mortem analyses do not include a detailed, nu-

merical explanation why the episode analysed is considered a crisis. The authors simply

assume that it was (by considering it worth taking about), and rarely anyone is willing to

argue with it (even if exchange market pressure was closer to the mean than 1.5 stan-

dard deviations).

The argument for such a method is that you directly get the results, which other methods

aim at indirectly. One can argue that the crisis thresholds of the numerical methods are

set in such a way to include all the commonly recognised crisis episodes (“your crisis

indicator is not worth much if it does not count X in 1997 as a crisis!”). Goldstein at al.

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(2000) boast that their EMP-based crisis criterion “map well into the dates that would be

obtained if one were to define crises by relying exclusively on events” (p. 20). Instead

of doing it, and facing numerous data collection problems, why not just identify the epi-

sodes manually?

There are two main drawbacks of the method. First, because it is discretionary, some

episodes may be questionable. An example of such a “crisis” is the Czech depreciation

of 1997, seen by some15 as a currency crisis, and considered by others as insignificant

market volatility. Second drawback is the judgement on the more exotic countries’ ex-

perience. It is not easy to find out information in neither financial press nor academic

papers on countries like Kyrgyzstan or Moldova. It is sometimes easier to use numerical

indicators in such cases, as data (although still possibly questionable) is more readily

available than popular investors’ opinion on these countries.

Section 3.3.5 Other definitions

Other crisis definitions include measuring GDP losses. This method, while usually fol-

lowing strict numerical thresholds, is similar to the discretionary one, as it involves

judging the outcome of the foreign exchange market disturbances. Especially in case of

floating exchange rate regimes, GDP loss can be the determinant factor in judging if a

depreciation represented a crisis or not. The problem with this approach, however, is

that a currency crisis can, in principle, be beneficial for both short term and long term

growth prospects (while still constituting significant distress to many economic agents).

The UK and Sweden are classic examples of such a case. Depreciation of the British

15 Mostly politicians and analysts from neighbouring Central and Eastern European countries, boasting that their currency was never subject to a crash

- 69 -

pound in 1992 was generally seen as a currency crash (a change in regime, 15% reserve

outflow and 15% depreciation), but it ended the period of slow, -1.4 to 0.8% growth,

which lasted for the previous 3 years. Sometimes, short-term GDP losses are accompa-

nied by major structural reforms, which provide for a stable long-term growth for the

years to come. Bulgarian crisis of 1996 could be an example, where severe crisis was

followed by establishment of a currency board, fiscal reform, an average 4.1% growth

in 1999-2003, and likely EU accession mere 11 years later. Also, in transition econo-

mies the effect of transition dynamics may be difficult to disentangle from the crisis im-

pact (Błaszkiewicz and Paczyński, 2003). Chapter 6 deals with the output costs of cur-

rency crises.

Finally, default criterion is often used in empirical crisis literature. This, strictly speak-

ing, is not necessarily a symptom of a currency crisis, but a debt crisis. The two are of-

ten connected, just as banking crisis may be a result or precedent of a currency crash.

Section 3.4 What works?

This section provides a survey of the explanatory variables found to be statistically sig-

nificant in predicting currency crises. The crisis definition problem applies also to the

explanatory variables. In a sense, the problem is deeper here, as it involves not only sub-

jective view of what we call a crisis (as in the previous case), but also the economic the-

ory.

Section 3.4.1 International liquidity

We can broadly define adequate international liquidity as the ability of a central bank or

the economy to survive a temporary capital flow reversal without serious macroeco-

nomic (e.g. exchange rate or GDP growth) consequences. Translating such a definition

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into the world of available indicators is difficult. One side of the equation (international

assets available on short notice) is quite easy to determine – in a vast majority of cases it

is defined as the stock of international reserves. Even there, however the simple statistic

does not tell the whole truth. Sometimes an international support may effectively in-

crease the international liquidity. Regression results in Bussière and Mulder (1999b)

show that IMF support programmes reduce the currency crisis vulnerability of the

emerging market economies. On the other hand, the official foreign exchange reserves

are sometimes more then the actual available assets. For example, central banks do not

report their off-balance sheet obligations. Simple forward transactions (an obligation to

e.g. sell foreign exchange in the future) are often not represented in official reserves sta-

tistics – this artificially boosted Thai reserve assets in 1997. Central banks may also in-

vest their foreign exchange in illiquid, or excessively risky assets. Blejer and

Schumacher (1998) advocate the use of Value-at-Risk approach to assess the central

bank vulnerability. The strategy comes down to risk-weighing the central bank’s assets

– e.g. fellow-emerging market government bonds would be worth less than US Treasur-

ies, even though both technically qualify as foreign reserve assets. Aizenman and

Marion (1999) present some statistics on discrepancy between official reserves and ac-

tually available assets in the East Asian countries.

The real problem starts with the definition of “hot” liabilities. How many obligations the

central bank may be forced to honour depend on many factors. For example, in the ex-

treme case, under a fixed exchange rate regime the central bank should be able to buy

all the money stock (M2/M3/M4) for dollars (or other reserve currency) from the public

to preserve the peg. How much the central bank should actually be ready to buy out de-

pends on e.g. the level of dollarisation of the economy. In countries like Bosnia and

Herzegovina, or Montenegro, euro can easily be used for transactional purposes, thus in

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times of foreign exchange distress, the transactional demand for local currency will be

close to zero. Therefore in such country, the central bank committed to defending the

exchange rate must be ready to buy out the entire money stock, not only from the for-

eigners, but also from the residents. That is one of the reasons why Montenegro decided

to officially accept the euro as a legal tender – the country was effectively euroised

anyway! On the other hand, the costs (ignoring reputation damage) of the fixed ex-

change rate collapse in such a country is likely to be small – private savings are likely to

be in foreign currency, local-currency prices (and wages) tend to adjust very quickly in

such an environment.

Floating exchange rate regime (and currency bands to a lesser degree) reduces the im-

portance of local currency liabilities of the central bank. The stylised fact is that floating

exchange rate regimes tend to be more self-regulating, allowing for smoother exchange

rate adjustments. Arguably, the only recent occurrence of a floating currency crisis was

Bulgaria (1996). Without the peg, speculators face not only the interest rate spread play-

ing against them, but also the currency risk (lack of free FX option as Krugman, 1979

points out).

Weak banking sector enlarges the potential liability of the central bank. Bank sector

panic and the subsequent rescue operation by the lender of the last resort requires a

boost in money supply, which may lead to depreciation if it is accompanied by conver-

sion of local savings into foreign currency. Turkish experience of 2000-2001 serves as a

warning. Sweeping disinflationary reforms are prone to confidence crises if resources to

defend both the nominal exchange rate anchor and the banking system are not large

enough.

- 72 -

Banking system rescue operations are generally accepted as one of the functions of the

central bank. But they are just one example of implicit or explicit guarantees of the

(widely defined) government to the private or public sector. All guarantees, implicit or

explicit, that the corporate sector would be spared by the government in the face of in-

solvency increases requirements for the overall liquidity of the government/central

bank. Asian difficulties, modelled in Krugman (1998), Dooley (1997) and Corsetti et al.

(1999) are good examples of this.

Thus, concentrating on sovereign short-term foreign debt alone is not enough. Private

sector foreign liabilities, are just as important, as they drain the reserves in case of a

confidence loss. The importance of the local currency debt depends on the exchange

rate regime (pegs make such debt more important), and on other factors, like inflation,

foreign short-term investments or the extent of dollarisation of the economy.

Probably, the most often used measure of hot liabilities is Bank for International Settle-

ments’ (BIS) statistic of short-term debt in the foreign banking sector. This measure is

available for most of the emerging market counties in semi-annual frequency, which

makes it the statistic of choice for most of the cross-country estimations of international

liquidity (Bussière and Mulder, 1999b; Tornell, 1999; Radelet and Sachs, 1998b;

Rodrik and Velasco, 199916). Even disregarding the domestic liabilities of the central

bank, this short-term debt measure is biased downwards. For example, a five year treas-

ury bond held by a foreign fund is not included (the liability is more than one year, and

moreover it is not versus the foreign banking sector). Similarly, portfolio equity invest-

16 The latter also use IIF statistics on external indebtedness, which includes also non-banking debt

- 73 -

ments can flow out of the country in minutes, but they are not included in the BIS statis-

tic as a short-term liability17.

If the policymakers are fully determined to defend the peg (as is assumed in the Krug-

man 1979 model), the total money stock is the absolute upper limit for the short-term

liabilities of the central bank. This limit, however, has little informational power. Ar-

guably, on one hand the only central banks which could have to be forced to provide

foreign currency in exchange of all the domestic money are the ones from countries

where local currency is little more than a symbol of past sovereignty (Iraq is a recent

example). But in the countries where transaction demand for local currency would re-

main positive even in view of a major credibility decline (so some of the M2 could re-

main in local currency), interventions become sterilised at some stage (see Tanner, 1999

and case studies in Chapter 4), which makes the initial M2 limit move outward making

seemingly adequate reserves insufficient.

The variables used in the leading indicator literature to take into account the liquidity

issues include reserves/GDP, reserve change, reserves/M2, reserves/base money, re-

serves/M1, reserves to ST debt, reserves/imports. At least one of the indicators of such

kind is present, and significant in the vast majority of the studies described in Figure 8.

The following paragraphs we name just a few of the studies.

In an extensive research of 117 currency crashes Frankel and Rose (1996) concluded

that variables important for predicting currency crises (defined as 25% depreciation of

the local currency) include FDI/debt ratio, level of international reserves, high domestic

17 Sarno and Taylor (1999b) try to measure the degree of capital flows persistence, or “hotness” of different types of capital flows. Not surprisingly they find portfolio flows

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credit growth, increase in world interest rates, real exchange rate overvaluation, and re-

cessions. Current account and fiscal deficit were found to be insignificant.

A study in a similar, univariate spirit was conducted recently by Aziz, Caramazza and

Salgado (2000). In the study based on 50 countries in a sample spanning from 1975 to

1997 they found that out of the most of the 157 crises recorded were preceded by a fall

in international liquidity (international reserves/M2).

Sachs, Tornell, and Velasco (1996b) also show that M2/international reserves coupled

with weak fundamentals rendered the countries vulnerable to contagion effects follow-

ing the Mexican crisis.

In another study, Tornell (1999) presents three determinants of the vulnerability of

economies to the currency crises: weakness of the banking sector, real appreciation of

the local currency and international liquidity. Tornell found that some non-linear de-

pendencies between the variables. For example, if international liquidity is high enough,

than even significant real appreciation or banking sector fragility do not matter.

Bussière and Mulder (1999) point to the importance of international liquidity (defined

as short term foreign debt to reserves ratio) in predicting the depth of a currency crisis.

This variable, together with real appreciation of the local currency over the preceding

four years, current account deficit and lack of an IMF support programme was able to

explain much of the depreciation of the emerging markets’ currencies during the recent

contagious crises. What is more, multiplicative specification of the model (where inter-

(bond and equity) the least persistent, and FDI flows the most long-term.

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national liquidity dominates the overall vulnerability index when it is very low or very

high) seemed to perform even better.

Rodrik and Velasco (1999) present yet another proof that low international liquidity ac-

tually welcomes a currency crisis (defined as a sharp reversal of capital flow)18. Their

probit analysis shows that short-term debt/reserves ratio (especially short term debt to

foreign banks) significantly increases the probability of a crisis. Interestingly, the level

of long-term and medium-term debt is significantly negatively correlated with the prob-

ability of a crisis. The explanation for this could be that long-term debt is associated

with other, positive, country attributes (omitted from the analysis). Rodrik and Velasco

also find out that short-term debt to international reserves ratio helps in explaining the

severity of the foreign exchange crises (measured as a GDP cost or depreciation).

Limiting the scope of the research to just international liquidity would lead to an omit-

ted variable problem. Few currency crisis models exist (Bilson, 1979 is one), in which

international liquidity is the sole variable determining the likelihood, or the scale of the

collapse. The following section describes the main variables other than international li-

quidity, which could influence the probability of a currency crisis occurring in the speci-

fied timeframe.

18 Radelet and Sachs (1998b) reach similar conclusions in their study, which employs

similar methodology.

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Section 3.4.2 Money supply

In Krugman's 1979 model, crisis occurs when the fundamental value of the currency

falls below the official fixing. The country heads for the crisis, because of monetised

fiscal deficits. Thus, given the uncertainties around the crucial variables, money demand

functions, etc, one can argue that risk is higher for countries with higher budget deficits,

or, more directly, with faster growing domestic money supply. Apart from liquidity in-

dicators listed above, monetary policy sustainability is proxied by various indicators:

money demand-supply gap, change in bank deposits, central bank credit to banks,

money stock, “shadow” exchange rate, parallel market exchange rate premium, the posi-

tion of the exchange rate within the official band. These variables are included in a large

array of empirical studies, with mixed success. Money supply growth variables usually

enter as significant, provided the reserve variables are not in the equation.

Section 3.4.3 Budget deficit, public debt

Budget deficit can feed as a crisis factor through various channels also. 1st generation

interpretation of budget deficit is that it is equivalent to the drift in reserves.

Second channel through which fiscal deficit can increase vulnerability is less direct, and

related to current account. High budget deficit reduces the amount of domestic savings

available to the economy, and stimulates current account deficit. This is fine, provided

the fiscal spending is justifiable from the intertemporal consumption / investment

smoothing point of view. The prevailing view in the eighties19 was that it is fiscally-

19 Known as the Lawson Doctrine from British Chancellor Nigel Lawson who claimed that current account are not problematic if they result from private investment decisions. See IMF (1988).

- 77 -

promoted current account deficits, which are dangerous. While the Mexican, and Ko-

rean crisis showed that private investments could be just as perilous, fiscal deficits still

do increase dependence from external financing, and create debt.

Budget deficit can serve as a proxy for future worsening of the international liquidity -

higher budget deficit means higher rate of growth of public debt, which at some stage

provide liquidity problems. It could be argued that, as in the case of current account

deficit, sustainability is all what for the survival of a currency peg. Even large budget

deficit, likely to be replaced by surpluses in the future are acceptable from solvency

point of view. But, as in the current account case, the notion of sustainability is tricky at

best, and impossible to calculate at worst. Also, lack of sustainability and ultimate in-

solvency are not necessary for the currency crisis to happen. Insufficient liquidity is just

as problematic. Large financing requirements, large amounts of debt maturing, even if

perfectly viable from the longer perspective, could prove fatal if the “wind shifts”.

Krugman’s (1999) model underscoring the balance-sheet impact of sudden depreciation,

Sachs et al. (1996a) second generation model in which indebtedness increases incen-

tives to devalue(understood by the currency speculators), finally the literature based on

bank-run models, where costly liquidation of investments could validate a run all con-

firm that even sustainable debt creation could contribute to a currency crisis. In reality,

however, the hypothesis that a perfectly viable budget deficit or current account could

be prone to collapse due to liquidity problems is very difficult to verify empirically pre-

cisely because it is impossible to judge decisively on fiscal sustainability.

Large debt-taxation substitution may also have influence on longevity of a fixed ex-

change regimes, provided the taxes can be raised in a timely manner. Policymakers in

developed countries, which could yield large tax revenues to replace debt financing,

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may still be constrained politically, but their chances of success are much higher than it

is the case in countries with thriving black economy, in which major tax hikes translate

into higher tax evasion.

Even if the central bank does not provide direct financing for the government on a regu-

lar basis, it often ends up doing so in the debt financing crisis-which is thus turning into

a currency crisis. Ukraine, Russia, Moldova provided examples of such behaviour in

1998. Such a risk is especially important for countries without credibly independent

central banks. High local currency debt increases profits from devaluation, which in-

flates away public debt.

Public debt structure variables are a link between liquidity and fiscal indicators. They

indicate at what stage the potential problems may become the actual liquidity problems.

Finally, budget deficit is often a symptom of structural problems of a country. Dąb-

rowski (1999) in his account on Ukrainian transformation process writes:

Experience of transition process gives a lot of evidence that fiscal policy perform-ance reflects a quality of economic policy and systemic reforms in the specific coun-try. Any inconsequence of the conducted policy, delay in transition on the microeco-nomic level, weakness of government institutions and favourable political climate for intensive rent seeking negatively influence fiscal balances. Thus fiscal equilibrium depends not only on the fiscal policy itself but also on the speed, quality and conse-quence of overall reform process.

The variables of this class, which enter the leading-indicators’ literature equations in-

clude budget deficit/GDP, government consumption, credit to public sector, public debt,

shares of concessional debt, foreign aid, share of commercial bank loans, share of vari-

able-rate debt, share of short-term debt, share of multilateral development bank debt.

Budget deficit was found significant in some, but not all of the research. Kaminsky et al.

(1998) report two (out of five tried) cases when the budget deficit was found to be in-

significant in the pre-1997 research. Budget deficit was found to be a significant leading

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predictor of currency crises in seven of the 34 studies surveyed by Hawkins and Klau

(2000).

Section 3.4.4 Other balance of payments variables, real exchange rate

High current account deficit, regardless of its causes, becomes a problem when foreign

financing dries out. If the exchange rate is floating, high external imbalance forces de-

preciation as soon as capital inflow slows down. If the exchange rate is fixed, the poli-

cymaker must spend reserves, tightening monetary conditions enough to reduce domes-

tic savings-investments imbalance. Recessionary costs of such actions often prove to be

too much, and the exchange rate is allowed to depreciate nominally.

Apart from international reserve changes other balance of payments indicators have

been used in the literature. While the size of the capital flows can just as well be ap-

proximated by the sum of current account deficits and reserve changes, capital account

variables can provide valuable information on the structure of current account financing,

and its volatility. Large foreign direct investments, low short-term capital flows are in-

dicators of higher international liquidity.

Variables such as current account deficit and real exchange rate (overvaluation) serve a

similar role. High current account deficit indicates that the economy as a whole gets in-

debted quickly (or runs out of reserves), while overvalued exchange rate shows in-

creased risk of such a process. By definition, real exchange overvaluation must be cor-

rected somehow (the exchange rate could not be called overvalued if it could stay that

way indefinitely). It can either happen through slower price growth relative to rest of the

trading partners, or through nominal depreciation. Goldfajn and Valdez (1999) find that

the nominal depreciation (usually dramatic) is by far more likely way to correct the

overvaluation if the real exchange rate misalignment is large.

- 80 -

Also, it is much easier to reach the decision to float if the exchange rate is considered to

be fundamentally too strong. This is a standard “second generation” government optimi-

sation problem: the gains from floating / devaluation are likely to be larger with the

strong currency. The related costs could be smaller too, as the example of Brazil of

1999 showed – depreciation of the Real was followed by stock market boom, not the

devastating financial markets panic.

The variables of this class used in the empirical research include real exchange rate, the

current account balance, the trade balance, exports, imports, the terms of trade, the price

of exports, savings and investment, short-term capital flows, foreign direct investment

(sometimes relative to CA), or the differential between domestic and foreign interest

rates.

Section 3.4.5 The real sector

In many second-generation crisis models, e.g. Obstfeld (1994, 1996), real sector influ-

ences the crisis likelihood, as it determines the balance of costs and benefits of defend-

ing the peg. Second generation models stress the fact that it may be sub-optimal not to

devalue. This makes countries with high unemployment, ailing economy, and incoming

elections more vulnerable. Weak economy may make hiking interest rates or cutting

money supply impossible politically. UK in 1992, Moldova in 1998, and Argentina in

2001 experienced all this.

Apart from this crisis creation channel, which could work for wide range of fundamen-

tals (they do not have to be very bad if the policy makers would not be willing to touch

domestic interest rates, afraid of political costs), real economy can serve as a proxy for

external imbalances troubling the economy. Unemployment, GDP growth data can

- 81 -

greatly supplement information inferred from the balance of payments. High current

account deficit itself needs not to be a dangerous sign. A fast growing country could

well exhibit high current account deficits, without negative effects on stability ever,

provided it imports foreign savings investing it in future growth and exports (see e.g.

Rybiński and Szczurek, 2003). If a country grows slowly, has low investment growth

and high current account deficit, the odds are that sustainability of the current account

deficit is low, and that an external balance correction is due.

Real sector variables have been added to the leading-indicators’ models since the begin-

ning of such research. Real GDP growth, estimates of the output gap, employ-

ment/unemployment, wages, and changes in stock prices are the variables of choice in

this class.

Section 3.4.6 Contagion variables

Currency crises tend to be contagious. In particular, 1992, 1994, 1997 crises inflicted

quite a broad damage to the financial systems not only on a regional scale, but some-

times globally (1998 Russian crisis did require quite a substantial rescue operation in

the US banking system as well, due to the near-collapse of the LTCM hedge fund).

There are numerous channels of contagion. Masson (1999) distinguishes between sev-

eral related effects.

Monsoonal effects, or common shock influencing many countries, eventually leading to

currency crises in each. Such events could include terms of trade shocks (e.g. fall in mi-

croprocessor prices or oil price shocks), or world growth slowdown. Similar impact on

the country's vulnerability may have an increase in world interest rates. Higher world

interest rates tend to increase the overall debt service costs (for the new debt and floater

- 82 -

bonds), and aggravate the current account, budget deficit and public debt-financing

problems for almost all countries in the world.

Spillovers, worsening of economic conditions in one country as a result of a crisis in

another. Trade contagion, or competitive devaluation20, is the prime example of such

events. Trade competition can be measured as in Glick and Rose (1999)21. But other

types of spillovers are documented in the literature. Political contagion, when devalua-

tion in one country reduces the political cost of such move in another (“everyone deval-

ued already, don’t expect us to keep the peg”) was described by Drazen (1999). Another

way of propagation is through common creditor. Currency crash in one country could

prompt margin calls – investment fund clients withdrawing their money. Heavily lever-

aged fund, may thus be forced to liquidate positions in other countries, prompting in-

creased market pressure in all or a group of emerging markets.

The last type of crisis propagation through financial markets was termed pure conta-

gion, or crisis propagation with no relation to macro fundamentals. Apart from invest-

ment funds, or banks’ liquidity considerations, shifts in market “sentiment” (being a

code word for market risk aversion) can also promote crisis propagation. Almost by

definition such type of contagion must be modelled by a dummy of a crisis happening

20 Central and Eastern Europe witnessed a completely different type of competitive pol-icy changes – competitive interest rate reductions. Aggressive interest rate reductions in Hungary, Poland and Slovakia were perceived by some commentators (see e.g. ING, 2003) as competition to deter speculative inflows and nominal exchange rate apprecia-tion. It resulted in a backlash for Hungary, which just few months later had to hike rates by several percentage points to stem forint depreciation.

21 00

0 0

1 ik kk iki k

i ik k

x xx xTrade

x x x x

− +≡ −

+ + ∑ i , where xik is exports from country i to coun-

try k (different than i and ground zero country 0), and xi is total exports from country i.

- 83 -

elsewhere. Common creditor linkages may be approximated using BIS data on external

indebtedness (see e.g. Van Rijckeghem and Weder, 1999) – countries dependent on bor-

rowing from the same country as the crisis-hit economy should be more vulnerable.

Other researchers define contagion as an increase in cross-country correlation between

key financial markets’ variables, such as stock market returns or exchange rate move-

ments, conditional on crisis happening somewhere (see e.g. Forbes and Rigobon, 1999,

and Baig and Goldfajn, 1998).

In practice it is hard to disentangle the contagion concepts empirically. In particular, the

financial market spillovers (being a rationally justifiable result of liquidity shifts) are

likely to show up in the same circumstances as “pure contagion”, resulting from irra-

tional investors’ fear that a country of similar broad macroeconomic characteristics

could also fall a victim of a currency crisis. Eichengreen et al. (1996) and Glick and

Rose (1999) try to judge relative importance of trade links and macroeconomic similari-

ties, and conclude trade links are important in crises propagation. Rijckenhem and

Weder (1999), Kaminsky and Reinhard (1998) and Frankel and Schmukler (1996) find

that spillovers through common financing centre can be just as significant as spillovers

through a common trade partner.

Section 3.4.7 Institutional and structural factors

Institutional and structural indicators can describe various aspect of the currency crisis

vulnerability. One set of variables concern the strength of the banking sector. High

credit growth, apart from its relation to the monetary sustainability is often associated

with relaxation of the prudential procedures within the banking sector. A country may

lack skills and resources to properly monitor credits in the middle of a lending boom.

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Change in the money multiplier variable can also serve as a proxy for the speed of evo-

lution of the banking sector. Financial liberalisation often means competition. More

competition translates into lower value of the banking license. This could increase the

banks’ risk taking incentives – the shareholders have less to lose in case of a failure.

Low deposit-lending spread is another variable of this kind.

The variables just mentioned are of early-warning type. They do not represent foreign

exchange problems, they help to predict problems. High real interest rates, or a banking

crisis itself are directly related to the foreign exchange crises. Weak banking sector re-

quires tough choices for the policy maker, which must choose between saving the peg

and saving the banking sector.

Other structural variables relate to the financial openness of the economy. Existence of

multiple exchange rates, exchange controls, or foreign exchange restrictions on one

hand can insulate the economy from external imbalances, allowing to pursue independ-

ent monetary policy, on the other indicate propensity to irresponsible (e.g. hyperinfla-

tionary) policies.

Finally, duration of the fixed exchange rate period, past foreign exchange market crises,

and past foreign exchange market events show how attached the policymakers are to the

peg. In the second-generation world such variables are a proxy for the costs of floating

(both political and real – Argentine crash of 2001 showed how long spells of fixed ex-

change rates can make a country very vulnerable, at least in a short-run, to any nominal

depreciation).

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Section 3.4.8 Political variables

Politics can influence sustainability of the exchange rates either because of the policy

some government are thought to pursue (leftist governments are usually associated with

high budget deficit and slacker monetary policy), or because of the economic/social

chaos related to the illegal government transfers (coups, wars, etc).

Entirely legal power transfers may also be dangerous for three reasons. First, new gov-

ernment brings some policy uncertainty, thus prompting the investors to require higher

premium. This increases debt service costs, or could lead to an outright speculative at-

tack. Outgoing governments have little to lose, and often go for very expansionary fiscal

policy (correlation of the Hungarian budget deficit with the election cycle in the past 13

years is striking). Finally, new government face a temptation to blame everything on its

predecessors. Thus, even if the fiscal policy is not very bad in the run-up to elections,

the new government, complaining on all the skeletons in the cupboard they inherited

could spend as much as it can before the budget they are responsible for comes22.

Variables of this class used in the empirical studies include dummies for elections, in-

cumbent electoral victory or loss, change of the government, legal executive transfer,

illegal executive transfer (coups etc), left-wing government, and new finance minister;

degree of political instability (qualitative variable based on judgement). An example of

the latter variable is ING’s Political Stability Index. More points are scored for countries

with long time remaining ahead of the elections, which have majority, non-coalition

22 Poland in late 2001 is one example – the new cabinet announced another budget revi-sion would be necessary, after which it functioned effectively without any budget for three months, before the official 2001 budget revision took place in December 2001.

- 86 -

governments and in which the ruling party leads comfortably in the polls (see eg. ING,

2004).

Figure 8 Leading indicator literature summary: methods, datasets, results (sorted

by publication date)

Article Countries, time, fre-

quency

Method Crisis definition Results

Bilson (1979) 32 countries, focus on LATAM. Annual data 1955-1977

Bivariate analysis 5% devaluation 1-yr ahead Crisis probability with grows from 5 to 40% when Reserves/base money falls from 30 to 10%.

Kamin (1988) 107 crisis cases. Annual data 1953-1983

Graphical analysis of indicators 3-yrs before and 4-yrs after crisis against control group

15% devaluation against US$

Trade balance/GDP, export and import growth, real exchange rate, real GDP growth and inflation found to behave statistically different in crisis countries prior to the event.

Edwards (1989)

39 devaluations, 24 long-lasting pegs in develop-ing countries (control group). Annual and quar-terly data, 1962-1982

Analysis describing stylised facts.

15% devaluation against US$

Central banks foreign assets/base money, net

foreign assets/M1, domestic credit to public sec-tor/total credit, bilateral RER, parallel market pre-mium influence probability of devaluation. Growth of total and public sector credit, CA deficit/GDP, budget deficit/GDP all behave differently in the crisis countries.

Edwards and Montiel (l989)

20 devaluations, Annual data, 1962-1982

Analysis describing stylised facts in the 3-yr window ahead of the crisis.

15% devaluation against US$

Budget deficit growing, large domestic credit to public sector, large terms of trade shocks, falling

net foreign assets/money, worsening current ac-count/GDP, black market premium herald devalua-tion For some countries real wages follow inverted U

Cumby and Van Wijen-bergen (1989)

Argentina 1979-1980, monthly data

Probability of peg collapse calculated on the base of crisis model, in which risk of collapse depends on probability of credit exceeding a threshold throwing reserves below un-known critical level in t+1

Regime shift – single event

Model parametrised to take into account money demand function and credit growth trends yields plausible monthly estimate for the probability of the peg collapse.

Humberto, Julio and Herrera (1991)

Colombia. Monthly data One-step ahead probability of de-valuation

Regime change Credit growth, parallel market premium

Edwards and Santaella (1993)

48 developing countries devaluations including 26 under IMF programme. Annual data 1948-1971

Descriptive statistics analysis. Probit of IMF assistance like-lihood

14%+ devaluation after at least 2-years of fixing. 14-page ap-pendix describing the crisis episodes.

More focus on the consequences of devaluation, whether it leads to improvement in economic condi-tions. Politically unstable countries, with worse current accounts and net foreign assets are more likely to approach IMF for endorsement of their plan. Political instability makes real devaluation, and subsequent stabilization reforms less likely to suc-ceed. IMF assistance results in tighter post-devaluation policies, but does not markedly help to keep RER adjustment.

Edin and Vredin (1993)

Nordic countires, 16 devaluations. 1978-1989, monthly data.

Shift in the target zone. Crisis size measured as a % change in the central parity

Money, output growth and import coverage of

international reserves help predicting realign-ments. Size of the shift depends on money supply and output growth, as well as on the real exchange rate.

Klein and Marion (1994)

17 Latin American coun-tries. 1957-1991, monthly data.

Logit Month in which ex-change rate depreci-ates after at least 3 months of fixing.

Real exchange rate appreciation vs US$ (simple and squared), net foreign assets/M1 fall, higher trade openness increase probability of the peg collapse. In specifications with year dummies (some significant for post-1982 period) and individual country dum-mies, political variables (regular government changes and coup dummies) became significant. Devaluations are more likely in early years in power.

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Article Countries, time, fre-

quency

Method Crisis definition Results

Ötker and Pazarbaşioğlu (1994)

Denmark, Ireland, Nor-way, Spain, and Sweden. 15 devaluations and 10 realignments. 1979-1993, monthly data

Probit Regime change – shift in the band, or switch to the float

REER, foreign-domestic interest rate spread, unem-ployment rate, German inflation and exchange rate position within the band were significant in the pooled regression. Significant variables varied for individual countries.

Eichengreen, Rose and Wyplosz (1995)

22 industrialised counties 1967-1992, monthly data, sample split into ERM and non-ERM

Non-parametric distribution equality test (Kolomogorov-Smirnov, Kruskal-Wallis)

EMP and events (offi-cial devaluations and realignments) – results for one were the oppo-site for the other.

Fundamentals (credit, fiscal deficits) mattered in pre-ERM period for market pressure predictions, but did not for ERM comparing crisis and non-crisis countries. The opposite was true when analysing countries experiencing realignments.

Ötker and Pazarbaşioğlu (1995)

Mexico. 1982-1994, monthly data

Probit Regime change – discrete devaluation or switch to float

Widening of Mexican-US CPI differential, real exchange rate appreciation, sharp reserve losses, central bank credit to banking system, fiscal deficit, financial sector reform dummy significant in ex-plaining probability of a crash. Credit to banking system more gaining importance, budget loosing significance prior to 1994.

Collins (1995) 18 countries, annual data 1979-1991.

Model of distance from critical thresh-old at which country devalues and speed of approaching it. Probabilities of ex-change rate adjust-ments 6-60 months ahead.

Regime change, col-lapse of the peg.

International reserves/GDP and GDP growth are key determinants of the distance from devaluation threshold. Inflation a good proxy for mean rate of approaching the threshold. Countries adjusting their peg showed on average 46% probability of adjustment, the rest implied 28% probability of peg collapse within 12 months.

Moreno (1995)

East Asian countries, including Japan. 1980-1994, monthly and quar-terly

Statistical compari-son of macro indica-tors in calm and pre-crisis periods

Three-variable EMP. M2 growth relative to the US, fiscal deficit, output, inflation are statistically different one month before the crisis.

Dornbusch, Goldfajn, and Valdés (1995)

Argentina, Brazil, Chile, Finland, Mexico. 1975-1995, annual and quar-terly

Descriptive statistics Expert opinion Patterns in real exchange and interest rates, GDP growth, inflation, fiscal deficit/GDP, credit growth, trade balance and CA/GDP, international reserves,

and debt/GDP prior to the crisis. Milesi-Ferretti and Razin (1996)

Chile, Mexico, Ireland, Israel, South Korea, Australia. 1970- 1994, annual

No formal testing Debt service/GDP adjusted for GDP growth and changes in the real exchange rate, exports/GDP, real exchange rate deviation from historical average, savings/GDP, budget deficit, banking sector fragil-ity indicators, political instability, composition of capital flows compared for crisis and no-crisis coun-tries.

Frankel and Rose (1996)

105 developing coun-tries, 117 crashes. 1971-1992 annual data

Multinomial probit 25% depreciation vs. US$ + 10% higher depreciation rate than a year before

FDI/debt ratio, low reserves, high domestic credit growth, increase in world interest rates, RER over-valuation, recessions matter. CA and budget deficit do not.

Eichengreen, Rose and Wyplosz (1996)

20 industrialised econo-mies. 78 crises (45 de-fended). 1959-1993, quarterly data.

Probit, contagion dummy (1 if crisis somewhere else). Descriptive statistics, graphs.

Crisis when an index of weighted average of exchange rate, interest rate differen-tial and reserve/M1 differential change (weights to equalise variance of the three components), reaches mean+1.5 std. Devia-tion

Inflation, employment growth, current ac-count/GDP, capital controls, government loss, past foreign exchange market crisis influence probability of crises.

Calvo and Mendoza (1996)

Mexico. 1984-1994, monthly and quarterly.

M2/reserves, money demand-supply gap

Sachs, Tor-nell, Velasco (1996b)

20 emerging markets in 1995.

OLS with slope dummies

Continuous EMP index of reserve loss and depreciation (country-specific weights)

RER appreciation between 1986-89 and 1990-94, growth of bank credit to the private sector between 1990 and 1994, M2/reserves in 1994, and dummies for weak and strong fundamentals to capture non-linearities.

Goldstein (1996)

Latin American coun-tries. 1994 crisis case. Annual and monthly data

Descriptive statistics Expert judgment International interest rates, M3/reserves, CA/GDP, boom in bank lending, RER, short-term debt, bank-ing sector strength trends are used to discover why some countries did, and some did not fall victim of the Mexican crisis.

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Article Countries, time, fre-

quency

Method Crisis definition Results

Kaminsky and Reinhart (1999), Kaminsky Lizondo and Reinhart (1998), Gold-stein, Kamin-sky and Reinhart (2000)

15 industrial, 5 develop-ing countries. 1970-1995, monthly data.

Signals approach EMP with reserve loss and depreciation. Threshold of 3 times full sample standard deviation. Separate calculation done for hyperinflationary countries.

Export growth, bilateral real exchange, rate--deviation from trend, terms of trade changes, changes in reserves, money demand/supply gap, real interest rates, M2 money multiplier, M2/international reserves, growth in domestic credit/GDP, changes in stock prices, output growth, banking crises help predicting crises. M2/reserves, export growth and real interest rate have the highest share of correctly predicted crises. Real exchange rate leads in noise/signal ratio

Krugman (1996)

France, Italy, Sweden, UK. 1988-1995, annual, quarterly, daily.

Descriptive statistics Subjective judgment Trends in unemployment, inflation, public debt/GDP, and output gap do not support self-fulfilling nature of the EMS crisis

Flood and Marion (1997)

17 Latin American coun-tries. 1957-1991, monthly data.

OLS, non-linear specifications reflect-ing the model.

Month in which ex-change rate depreci-ates after at least 3 months of fixing. Explanatory variables are continuous and include size of real depreciation (also nominal depreciation), and time on peg (months)

Speed of real appreciation, high volatility of real exchange rate increase the size of exchange rate adjustment following the peg collapse. Strong real appreciation drift reduces and high real rate volatil-ity increases the life expectancy of the peg.

Goldfajn and Valdés (1997)

26 countries. 1984-1997 monthly survey data,

Logit Three measures: 25% depreciation (as in Frankel and Rose, 1996), 2 std.dev from the mean jump in real effective exchange rate, exchange rate market pressure index, as in Kaminsky and Reinhart (1996)

Crises not well predicted in survey data. Either predictions wrong, or crises due to rapid changes in fundamentals, or not fundamentals-related at all. Overvaluation does increase probability of crisis.

Ötker and Pazarbaşioğlu, (1997)

Probit Crisis if there is a regime change (de-valuation, widening of the band, a switch to flexible rates).

interest rate differential, deviation from the parity, log(reserves) and %ch in reserves. Exchange market pressure index predicts regime change well

Milesi-Ferretti and Razin (1998)

105 middle and low income countries. 1970-1996

Probit, graphical analysis of variables in the crisis window

As in Frankel and Rose (1996)

Crisis probability increases when reserves/M2 are low, REER high compared to the historical average, US interest rates are high, OECD growth is slow, terms of trade are not favourable

Osband and Van Ril-ckeghem (1998)

31 emerging markets. 1985-1998 monthly.

Identification o “safe” indicator ranges

10%+ depreciation which is more than prev. year mean plus two std. deviations from previous two years

External debt and reserve adequacy are the main filters, which allow to classify period as safe.

Radelet and Sachs (1998b)

19 emerging markets. 1994-1997

Probit Sharp switch from positive to negative capital flow

BIS-reported ST debt/reserves, private credit/GDP important. CA deficit marginally, real exchange appreciation rate not important.

Esquivel and Larrain (1998)

15 developed and 15 emerging markets. 1975-1996 annual data.

Panel probit, random effects

15% depreciation in real exchange rate, or 2.54x std deviation jump greater than 4%.

Change in reserve money/GDP, RER deviation from previous 5-yr average, CA deficit/GDP, M2/reserves, %change in terms of trade, per capita income fall dummy, regional contagion dummy all increase probability of crises

Kaufmann, Mehrez and Schmukler (1999)

58 countries. 1996-1998, annual data.

Unique data on local managers’ private information, ex-tracted using ordered probit. OLS

Continuous variable of fx volatility (standard deviation of monthly exchange rate changes).

Private information of local managers help predict-ing exchange rate volatility after controlling for CA, reserves’ import coverage, change in reserves/credit, inflation, growth in domestic credit, change in terms of trade, budget deficit, GDP growth, re-serves/deposits, ST debt/reserves, M2/reserves and lagged volatility.

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Article Countries, time, fre-

quency

Method Crisis definition Results

Rodrik and Velasco (1999)

32 emerging markets. 1988-1998

Probit Crisis if net private capital flow/GDP changes from positive to negative by at least 5 percentage points. Also, fall in GDP in the year of the crisis, and depreciation (both conditional on the crisis).

IIF ST debt/reserves, debt/GDP, CA/GDP, RER appreciation over three years increase probability of crises. Budget deficits, M2/reserves, credit growth/GDP are insignificant. ST debt/reserves also increases the severity of the crises as measured by GDP loss.

Bussière and Mulder (1999)

23 emerging economies (incl. Hong-Kong). 1994 and 1997 crises episodes only (2x23 observations).

OLS, non-linear specification

Weighted average of nominal depreciation and reserve outflow

Current account deficit, BIS-reported short term

debt/reserves, real exchange rate appreciation over preceding two years, IMF support dummy. ST debt/reserves parameter in a non-linear specification suggests that high (or low) liquidity makes “funda-mentals” almost irrelevant.

Tanner (1999) 23 emerging markets. Mexican and Asian crisis episodes.

OLS, non-linearities in explanatory vari-ables.

Depreciation + reserve loss/money supply weighted by relative country-specific vari-ances.

Weakness of the banking sector (lending boom), real appreciation, low M2/reserves . if international liquidity is high enough or banks are OK, then REER and banking sector fragility doesn’t matter.

Glick and Rose (1999)

142 countries. 1971, 1973, 1992, 1994, and 1997 crises episodes.

Probit, OLS Financial Times, journalistic and aca-demic histories sug-gesting if the country was, or was not a victim of a particular crisis episode. EMP, end depreciation vs. the ground zero cur-rency for OLS regres-sion.

Trade linkages with the first hit country very impor-tant, even after controlling for fundamentals (growth of credit, budget deficit, CA, real growth, M2/reserves, inflation).

Van Ri-jckeghem and Weder (1999)

BIS-reporting emerging economies. Subset of 48 emerging markets. Mexi-can, Asian and Russian episodes.

Probit, OLS, as in Glick and Rose (1999)

Binary variable (as in Glick and Rose, 1999), or market pressure (weighted average of deprecia-tion, % decline in reserves, and normal-ised change in interest rates)

Common bank lender channel (similar country of credit origin to the ground zero country) more im-portant than trade links, macro control variables less significant.

Gelos and Sahay (1999)

12 transition economies. 1990s, monthly, daily data.

Study concerns co-movements in mar-ket pressure. Macro similarities, trade linkages. VAR on daily fx data

Arbitrary identifica-tion of crisis episodes. Continuous dependent variables: EMP (incl. interest rates), ex-change rate, stock market returns

Correlations in market pressure relatively weak in 1990-1998. Hard to explain by fundamentals other than trade (mostly indirect) linkages.

Berg and Pattillo (1999)

20 developing and indus-trial countries. 1970-1995, monthly data

Replication of sig-nals approach of Kaminsky, Lizondo and Reinhart (1998), probit of Frankel and Rose (1996), and Sachs, Tornell and Velasco (1996).

Weighted average of exchange rate and reserve changes: threshold is 3 country- specific standard deviations above the mean. Hyperinflation-ary countries treated separately

Kaminsky et al. (1998) variables in probit specifica-tion with M2/reserves, CA level included perform relatively well. Frankel and Rose (1996) and Sachs, Tornell and Velasco’s (1996) models performed very poorly in predicting the 1997 Asian crisis.

Nag and Mitra (1999)

Three Asian countries. 1980-1998 monthly

Artificial neural network approach.

Weighted depreciation and reserve loss higher than 2 times country-specific std. Deviation over mean

12 indicators, plus lags enter the ANN system, which is able to predict 80% of crisis occurrences in the sample.

Herrera and Garcia (1999)

8 LATAM countries. 1980-1998, monthly.

Composite indicator EMP, reserve, interest rate and exchange rate not weighted. Crisis threshold at 1.5 stan-dard errors. Hyperin-flation countries treated separately.

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Article Countries, time, fre-

quency

Method Crisis definition Results

Aziz, Caramazza and Salgado (2000)

20 industrial and 30 developing countries. 1975-1997, monthly and annual.

Graphical analysis, comparison of tran-quil and crisis peri-ods.

Crisis when an index of weighted average of detrended fx and reserve change (weights to equalise variance of two com-ponents), reaches mean+1.5 std. Devia-tion

Overvaluation, terms of trade, inflation, domestic credit growth, M2/reserves, world real interest rates, current account all behave significantly differ-ent in the crisis periods.

Bruggemann and Linne (2000)

7 EU accession candi-dates (including Turkey) and Russia. 1993-2000, monthly

Composite indicator approach of Kamin-sky et al. (1998)

20% depreciation against US dollar within ten trading days.

Real exchange overvaluation, reserve losses, bank-ing sector weakness indicators help predicting cri-ses.

Burkart and Coudert (2000)

15 emerging markets. 1980-1998, quarterly.

Fisher discriminant analysis

Combination of EMP threshold, Milesi-Ferretti and Razin (1998) threshold, and amendments "in light of expert judgment."

Reserves/M2, reserves/debt, short-term/total

debt, overvaluation, contagion indicator, and infla-tion help predicting crises.

Caramazza, Ricci, and Salgado (2000)

41 emerging and 20 industrial countries. 1990-1998, monthly.

Probit for EMS, Mexican, Asian and Russian crisis

Crisis if weighted (to equalize variances) average of reserve losses and detrended currency depreciation drifts 1.645 pooled standard deviations from the pooled mean. High-inflation (150%) cases are excluded.

Real exchange rate appreciation, the current account deficit, real output growth, the maturity of bank lending, the common creditor, and ST

debt/reserves significantly increase the probability of falling victim of contagious crisis. Trade spill-overs only relevant when CA is weak.

Cerra and Saxena (2000)

Indonesia, 1985-1997, monthly

Markov-switching Determined as part of the Markov switching model

Evidence of contagion not related to the 8 funda-mental variables analysed

Edison (2000) 20 developing and indus-trial countries. 1970-1998, monthly.

Signals approach of Kaminsky et al. (1998)

As in Kaminsky et al. (1998)

Same as Kaminsky et al. (1998). Robust results, false alarms remain a problem.

Hawkins and Klau (2000)

24 emerging markets. 1993-1998, quarterly

Arbitrary scoring system, verified by panel probit with fixed effects

Score system from –2 to +2 based on quar-terly and annual ex-change rate, real inter-est rate and reserve changes.

Real exchange rate appreciation from 1990-98 average, CA deficit/GDP, export growth accelera-tion from 1990-98 average, international bond and bank debt/GDP level and % change over two years, BIS-reported short term debt/reserves, domestic bank credit to private sector/GDP growth, growth of liabilities to BIS banks, real interest rate enter the scoring system

Kwack (2000) 7 Asian countries. Total of 14 annual observations from 1995-1997.

OLS Continuous variable of weighted average of exchange rate and reserve changes.

LIBOR and the NPL ratio (and the debt- equity ratio of firms the key factors. ST debt/total, CA/GDP, credit to private sector not significant

Nitithanprapas and Witlett (2000)

26 emerging markets. Asian and Mexican crisis (52 observations)

OLS, slope dummies regression

Continuous index of 1:4-weighted ex-change rate and re-serve changes. Dis-cussion of weighing

Real exchange rate, enters the equation differently, depending on FDI and CA. High reserves reduce

crisis risk.

Vlaar (2000) 31 emerging markets. 1987-1996, monthly data

Separate models for crisis index, index volatility and weights of tranquil and crisis distribu-tions of the crisis index.

Continuous variable of weighted average of exchange rate and reserve changes. For evaluation purposes some thresholds are used

Contagion, past exchange rate, reserve behaviour are the key indicators.

Eliasson and Kreuter (2001)

10 emerging markets. 1990-200, monthly.

Multinomial logit Continuous crisis variable, based on exchange rate depre-ciation and interest rate changes estimated using a 5-step proce-dure. of fitting an extreme value distri-bution function to the difference of vari-ables’ actual and Gaussian distributions.

Falling equity markets, high domestic credit/GDP, high monthly growth of private credit, high M2/FX

reserves, high short-term debt to FX reserves and M2/banking reserves are the key leading indicators in Asia. Falling equity markets, high monthly growth of private credit high short-term debt to FX reserves

work in Latin America.

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Article Countries, time, fre-

quency

Method Crisis definition Results

Apoteker and Barthelemy (2001)

40 developing countries. 1970-2001, monthly and quarterly.

Graphical analysis of variable pairs, identi-fying dangerous interactions

20% change in real exchange rate in one quarter, 30% in two quarters or 40% in 3-6 quarters.

Grier and Grier (2001)

25 developing countries in 1997.

OLS of fx regime and control variables on depreciation and stock market

Continuous indicators of exchange rate de-preciation and stock market returns

After controlling for 1996 depreciation, current account deficit, M2/reserves, external debt/GDP, lending boom and real exchange rate appreciation, fixed exchange rate regimes resulted in deeper exchange rate adjustments and lower stock market returns

Kamin, Schindler and Samuel (2001)

26 emerging markets. 1981-1999 annual data

Probit Weighted two month real exchange rate and reserve fall exceeds 1.75 times standard deviations over coun-try specific mean.

Deficit/GDP, M2/reserves change (but not ST debt/reserves change), RER appreciation over 1980-97 average, CA/GDP, terms of trade shock, and world GDP growth change

Krkoska (2001)

Czech Republic, Hun-gary, Poland and Slova-kia. 1994-1999, quar-terly.

VAR with crisis variable as one of the endogenous vari-ables. Many restric-tions

Unweighted average of exchange and inter-est rate, and reserve changes. Crisis de-fined (but not used in numerical exercises) 2 times standard devia-tion of the pooled sample in the past 3 years (to take transi-tion into account)

CA-FDI gap is the most significant variable influ-encing speculative pressure index. Poor EU growth, and RER appreciation are also significant.

Weller (2001) 26 emerging economies. 1973-1998, monthly data.

Logit for pre, and post financial liber-alisation samples.

Standard 2-variable EMP, 3 times country specific std dev threshold

Risk pattern for post-liberalisation countries differ-ent. Overvaluation and short-term debt increase vulnerability more after liberalisation

Zhang (2001) Four ASEAN countries. 1993-1997, monthly data

Autoregressive Con-ditional Hazard (probit with past dependent variables entering the right-hand side)

Crisis if reserve loss or depreciation ex-ceeds 3 times standard deviation over mean (std deviation calcu-lated over 3 previous years

Duration of calm/crisis spell and contagion vari-ables dominate all the macro indicators. Fit is re-portedly better than the probit.

Detragiache and Spilim-bergo (2001)

69 countries, 1971-1998 Probit Debt crisis if arrears or rescheduling of more than 5% of debt to commercial credi-tors

Short term debt, debt repayment due and re-serves, large external debt, share of debt to multilat-eral lenders, exchange rate overvaluation, smaller trade openness are all significant

Kumar, Moor-thy, and Per-raudin (2002)

32 emerging markets. 1985-1999, monthly, quarterly.

Panel logit. The model is successfully tested through trad-ing strategies based on probability read-ings

Depreciation of 5 or 10% over the uncov-ered interest parity. Second definition is 5 or 10% depreciation doubling the previous period depreciation (“total crash”).

Twelve-month percentage changes in foreign

exchange reserves, real GDP expressed as a devia-tion from trend, and the regional contagion dummy are the key variables. Import coverage, portfolio investments, official debt as a proportion of total debt, and the lagged exchange rate are significant in at least one of the regressions.

Martinez Peria (2002)

7 EMS members. 1979-1993, monthly data.

Markov-switching Endogenously deter-mined through Markov-switching

Budget deficit and expectations (proxied by in-

terest rate differential) are significant in increas-

ing probability of a switch to the crisis state

Ghosh and Ghosh (2002)

42 countries. 1987-1999 annual data

Binary recursive tree (see text above)

Deep crisis: EMP more than 2 times country specific std. deviations and GDP growth rate falls at least 3 percentage points following the crisis.

See Figure 7 on page 61

Mulder, Per-relli. and Rocha (2002)

19 emerging markets. 1991-1999 monthly.

Extension of Berg and Pattillo (1999) probit and Bussière and Mulder (1999) OLS approaches

As in Berg and Pattillo (1999) (binary) and Bussière and Mulder (1999) – continuous. Both based on reserve changes and deprecia-tion.

ST debt/reserves ratio, CA deficit, RER apprecia-tion, high leverage and short maturity structures, shareholder rights indicators influence both prob-ability and depth (OLS estimate) of the crises.

Sources: Papers in the first column, Kaminsky et al. (1998), Abiad (2003).

- 92 -

Chapter 4 Recent currency crises: liquidity perspective

Section 4.1 Introduction

This chapter gives a description of the recent currency crises from the perspective of

international liquidity. It aims at clarifying several issues related to the liquidity and cri-

ses. This introductory section sets up the main questions to be answered and describes

the general approach of the chapter. The individual case studies of the recent currency

crises which follow are then structured to give answers to the points described here.

• The first question to be addressed in each of the crisis case studies concerns the

link between international liquidity and the recent foreign exchange crises. How

a particular instance of a crisis be categorised? How the crisis fits into the exist-

ing currency crises models literature?

Many authors attempted answering such questions. In fact, most of the currency crisis

models were devised as a response to a particular crisis bout (Obstfeld’s 2nd generation

to the EMS crisis, newer ones following the East Asian crises). In this piece, the answer

will be the drawn from the evolution of macro and structural variables around the crisis

period compared with the expected evolution of the variables as suggested by the mod-

els.

First-generation crises should be characterised by high budget deficits, high domestic

money supply growth, steady leak of foreign exchange reserves ahead of the crisis, pos-

sibly current account deficits and real appreciation, and local interest rate climbing

ahead of the attack. The models do not imply a change in monetary policy (leaving ex-

change rate policy aside) following the attack.

- 93 -

Second-generation crises, being self-fulfilling should provide less obvious hints of crisis

brewing. Policy (both fiscal and monetary) does not have to be expansionary in the

lead-up to the crisis. It becomes expansionary conditional on the crisis happening. The

basis for the crisis happening could be weak growth, high unemployment, high private

or sovereign leverage (which makes it politically impossible, or fiscally unprofitable to

tighten monetary conditions in case of an attack).

Asymmetric information models indicate problems with corporate governance, corrup-

tion, implicit government guarantees, high growth of debt, worsening banks’ portfolios,

amid falling productivity growth.

Finally liquidity crises put stress on short-term debt/reserves and total foreign debt. This

makes liquidity crises impossible to distinguish from a class of 2nd generation crisis

models (in fact, one could argue that in its macro form, liquidity currency crisis is a 2nd

generation model: foreign creditors refusing to roll-over their debt create incentive to

alter the monetary policy in order to bail out the banks). Similarly, balance sheet-type

crisis in which decisive interest rate defence of the peg impossible because of the dam-

age to the general (also non-bank) private sector can be, in fact seen as a variant of self-

fulfilling 2nd generation model: optimising government lets the peg fail not because it

has no other options, but because it is (politically) cheaper to do so.

Because most of the crisis models of 2nd generation require only a certain range of a

fundamental to enable the self-fulfilling mechanism to work, the actual trigger may be

completely separate from the underlying fundamental. So, the changes in the indicator

within a country may give false impression reduced vulnerability, whereas in fact, there

may be strong nonlinearity in the impact of the fundamentals change on crisis probabil-

- 94 -

ity. One way to get around this problem is to resort to cross-country studies, thus com-

paring the levels, not trends of crucial variables.

Another problem with identifying liquidity-related crises and the 1st generation type

ones is that money supply to reserves ratio is a crucial indicator for both deterministic

peg collapse occurring as a result of unsustainable monetary policy and of a potential

vulnerability in case of a liquidity run. It may be hard to judge if foreign investors re-

fuse to roll over their credit, decide to liquidate their equity investments (and require to

change their proceeds into foreign currency), even accepting losses because they are

afraid others would do the same, or because they see foreign exchange reserves become

small relative to domestic currency, and that the monetary policy is unsustainable. To

make matters worse, growth of domestic money could be a result of other issues, only

remotely related to currency crises. Money demand function shifts resulting from eco-

nomic transition, development and competition in the financial sector, or even increas-

ing confidence in local currency following a stabilisation programme could all increase

domestic-to-foreign money ratio. Such effect, in turn, could prove to be indistinguish-

able from a sign of unsustainable monetary and exchange rate policy.

The problem is serious enough to ensure that the same indicator (M2/reserves) in the

same crisis is being interpreted either as a sign of illiquidity (Chang and Velasco 1998),

or as a sure example of a policy collision course (Chinn et al. 1999). A crisis following

a period of falling M2/reserves is a sign of a self-fulfilling run. A crisis after a period of

growing M2/reserves could mean domestic money growth related to financial system

development and relaxed regulations, and a path towards new equilibrium (possibly fi-

nancially unstable). It could also be a result of monetised fiscal expansion (quite easy to

- 95 -

identify) or otherwise monetary policy too slack to be compatible with fixed exchange

rates.

• The second problem is the exact role of international liquidity. Is it just a help-

less leading indicator, or a variable, the management of which could prevent the

crisis altogether?

One way of answering that question is checking how international liquidity was chang-

ing ahead and during the crisis. Slow leak of foreign exchange reserves could indicate

the first-generation-type problems in which the issue to be addressed is not liquidity it-

self, but the process which causes its reduction over time – deficit monetisation, or gen-

erally too loose monetary policy. If the fall in liquidity is rapid, there are two possibili-

ties: either the reserves do not matter at all for the crisis prediction (the government

finds it too costly to avert the crisis, even though it could have the means to do so) or

they were not sufficient to start with, they created the vulnerability to financing stops,

and targeting them would have reduced the risk of a crisis.

• The third question concerns the choice of liquidity measure in evaluating vul-

nerability. In particular, on what type of short-term obligation should research

concentrate? Is it domestic money supply, or just short-term foreign obligations?

The choice of denominator of the liquidity measure best reflecting currency crisis vul-

nerability depends on the exact crisis mechanism. Broad money coverage by official

reserves should be the indicator to watch in highly developed, open countries with solid

banking sector and deep inter-bank market (allowing for large short positions against

local currency). Same indicator is likely to be viable in high-inflation, dollarised coun-

tries with weak banking sector. In such countries potentially very low demand for

- 96 -

money in a crisis requires policymakers to consider all domestic money a callable liabil-

ity in case of a currency crisis.

Short-term foreign debt and portfolio investments (in countries with open capital ac-

count) are both measures of vulnerability to financing stops and liquidity runs in all

economies.

In choosing the liquidity measure, tracking the in-country evolution of various liquidity

measures, or cross-county comparisons must be supplemented by qualitative judgement

of the behaviour of local firms and individuals, as well as foreign investors during the

crisis. Mass conversion of local savings into foreign currency would suggest concentrat-

ing on short-term foreign debt would have given a downwardly biased picture of crisis

vulnerability. On the other hand, a sudden depreciation resulting from foreign financing

stop, with limited consequences to the domestic deposit base, would mean short-term

debt/reserves ratio was a sufficiently broad measure of international liquidity in that par-

ticular crisis instance.

• The final of the four questions is “when does increasing liquidity become too

expensive to be useful?”

The cost of liquid assets can approximated by high-frequency foreign-currency bond

yield data. “Too expensive” is hardly a precise statement, as foreign currency long-

duration bond spreads faced by some countries on a regular basis would be considered

extraordinary market development related to a crisis by others. Malaysia’s sovereign

spreads reached 250bp in the middle of the East Asian currency crisis, while such cost

of credit would be unusually low for Mexico in the relatively calm 1992-early 1994 pe-

riod (see Figure 47 on page 131 and Figure 25 on page 112 in the East Asian and Mexi-

- 97 -

can sections below, respectively). A major upward shift in foreign currency long-bond

yields could indicate cut-off for explicit reserve acquisition possibility financed by long-

maturity foreign currency bond sale.

But liquidity can also be understood as liquid assets net of, or relative to liquid liabili-

ties. Thus liquidity could also be influenced by the choice of budget deficit financing

instruments, capital controls, or anything that influences the stock of short term debt.

To avoid issuing short-term debt, the government can either cut budget deficit (at cer-

tain political costs), issue long maturity bonds (at the alternative cost related to the slope

of the sovereign foreign currency yield curve) or resort to non-debt creating financing

altogether. The latter method is usually23 means selling non-liquid assets (via privatisa-

tion, radio frequency auctions, mobile telephony licences).

The policymakers could also try to influence the composition of capital inflows, to re-

duce the dependence on short-term capital. The evolution of the costs of such policies,

however, is next to impossible to estimate.

The answer to the fourth question will be based mostly on the evolution of high-

frequency long-bond spreads, which approximate the cost of acquiring foreign exchange

reserves. Whenever possible, reference to capital controls influencing maturity structure

of the capital account will be made.

23 But not exclusively: a common way of non-debt budget financing is usage of liquid assets held at the turn of the fiscal year. Such non-debt creating financing reduces gov-ernment’s, and potentially also overall international liquidity, and can only last as long as governments’ cash holdings do. But the same can be said of using up the less liquid, privatised assets.

- 98 -

While answering all the questions above, in case study analysis of this kind, there is a

trade-off between econometric rigour of the analysis and breadth of the data sample.

Following Mussa (2002), Radelet and Sachs (1998a), Chang and Velasco (1998), and

Chinn et al. (1999) (all of which still concentrate on a much smaller sample of 1990s

currency crises), in this chapter, the former was sacrificed in exchange for the latter.

Risking accusation of chart-pointing I decided to cover as many currency crises of the

last 15 years as possible, with heavy weight given to the transition economies’ crises,

which have been subject to much less extensive studies in the literature. The chronolo-

gies of the crises are provided in the Appendix 1.

Section 4.2 1992 EMS crisis

Section 4.2.1 Crisis identification

The EMS crisis spanned throughout the second half of 1992 and caused severe depre-

ciations, reserve losses, and short-term interest rate spikes in Italy, Ireland, the UK,

Spain, Finland and Sweden. The actual dynamic of the crisis variables was quite differ-

ent for the six countries, as shown in Figures 9-20. Reserves in the UK, and Spain were

rising between 1990 and the attack; they were stable in Ireland, and unstable, but trend-

less in Sweden; all speaking against the 1st generation crisis interpretation. Finnish, and

especially Italian pattern of reserve loss starting over two years ahead of the collapse

much better reminded the Krugman’s original model (see Figures 12 and 14). Re-

serves/broad money developments reflected changes in official reserves in most of the

countries (growth in Spain, roughly stable in Ireland and Sweden and falling in Finland

and Italy), with the exception of the UK, where domestic money expansion was over-

shadowing foreign exchange reserves growth in the final year ahead of the crisis. Re-

serves/broad money in the UK, at around 4.5%, was the lowest in the group, with the

- 99 -

exception of Italy, where this ratio declined from 12 to 4% between 1990 and 1992 (see

Figures 15-18).

Similar pattern can be seen in the local currency bond spreads over benchmark German

bund yields (not reported), which should reflect exchange rate expectations of the cur-

rency depreciation in the “deterministic” crisis framework. The spreads had been falling

in the UK, Ireland, Spain, Sweden, but jumping 300bp in early 1991 in Italy, and

slightly later and less in Finland, again confirming the first-generation-type mechanism

at work in the latter two countries.

Cross section look at the budget deficits in crisis-hit counties (Figure 19) reveals simi-

larly mixed picture: Italian deficit was consistently the highest in the group, averaging

10.3% of GDP in 1990-1992, Ireland run the smallest average deficit of 2.3% of GDP,

which coupled with 4.4% GDP growth in the period, was consistent with public debt

reduction, not expansion. GDP growth was slowing down across the board (Figure 20),

with the UK, Finland and Sweden in outright recession, and Italy and Spain with less

than 1% growth, the smallest in years. Ireland enjoyed the fastest growth in the run-up

to the crisis (and afterwards), but it was plagued by over 20% unemployment24.

In general, the data findings are consistent with crises of a self-fulfilling type in the UK,

Ireland (especially so), Spain and Sweden, but the case of Italy and Finland look coher-

ent with 1st generation speculative attack model. The channels through which specula-

tors could bring the governments of the first group into submission could be a combina-

tion of weak growth or outright recession everywhere, extremely high unemployment in

24 Buiter et al. (1998) provide a comprehensive survey of the crisis. Another survey of EMS countries’ fundamentals can be found in Eichengreen and Wyplosz (1993).

- 100 -

Ireland, Swedish banking sector weakening by September 1992 attack episode leading

to short-term interest rates exceeding 80%, and finally, relatively low (albeit rising)

level reserves compared to money supply in the UK.

Falling political costs of devaluing, thanks to other governments doing the same, made

the decision of the British, Swedish, or Irish governments and central banks even easier.

Section 4.2.2 The role of reserves

1992 crisis gave a boost to the 2nd generation crisis models, as they seemed to provide a

perfect example of authorities being forced to devalue, but not because they had no

other choice, but because speculators rightly predicted it would be not worthwhile for

the governments to defend the peg. This puts the importance of international liquidity in

question. The countries suffering the peg collapses in 1992 had relatively good access to

foreign currency. Obstfeld (1994) argues that the November 1992 collapse of the Swed-

ish corona peg was the result of a major fall in political costs of devaluation (English

and Italian exit from the EMS, Spanish and Finnish devaluation, low French support for

Maastricht treaty) and mounting real economy costs of the peg defence: a bout of high

interest rates during the speculative attack in May 1992 strained the domestic banking

system, budget deficit was at 7% of GDP, and recession was in full swing. All this made

a real non-sterilised monetary defence of the peg very costly for the Swedish govern-

ment. All the sterilised intervention in November 1992 achieved was a massive drop in

foreign exchange reserves.

The picture sketched could suggest that the swings in foreign exchange reserves were

not the most important feature of the crisis. They were merely a symptom of the real

(literally, real economic) crisis, which made the defence too costly politically. This

- 101 -

would imply that no reserves would have been sufficient to save the fixed exchange rate

regime. But why the foreign exchange reserves had to fall below zero in Sweden in or-

der for the peg to collapse (Obstfeld 1994, page 199)? Why the unofficial comments of

people linked with the Bank of England hint at the physical impossibility of the sterling

defence, despite the credit lines with numerous European central banks (see e.g. Lall,

1997)? Several issues arise.

Can sterilised intervention influence exchange rates in crisis? If it cannot, then the level

of foreign exchange reserves is indeed irrelevant for the countries like Britain, Italy, or

Sweden of 1992. In such case, if a country believes monetary tightening is unaccept-

able, the reserves are useless. However, if the sterilised intervention can influence ex-

change rate (e.g. due to the portfolio balance arguments), then the level of reserves

(relative to domestic-denominated bonds, money supply) can influence the crisis prob-

ability and severity.

If the latter is true, the policymakers of the 1992 crisis-inflicted countries could have

hoped the massive sterilised intervention would shift the portfolio balance in favour of

the domestic currency denominated bonds. Apparently the amount of reserves available

was not enough to achieve this. What level would be sufficient then?

Finally, in case of the EMS members, the actual amount of reserves at disposal of the

central banks was arguably larger than what was officially reported as a stock of foreign

exchange reserves: credit swap agreements with European peers allowed them to spend

more than they had. Still, apparently, it was not enough. Lall (1997) argues that the

amount of reserves that can be borrowed at any given day was limited, and therefore the

peg could have collapsed even with virtually unlimited credit lines. Similar argument

can be applied to the IMF support programmes: the money is available but not at a short

- 102 -

enough notice (in that case, it is a matter of months rather than a day), so the peg can

collapse anyway.

This shifts attention to the very core of the liquidity problems: the difference between

the liabilities and assets that can be withdrawn at a one-day (spot value date, strictly

speaking) notice. The focus on the liabilities side is then not on the standard “credit due

within a year” line, but instead the depth, liquidity, and openness of the swap and bond

markets. Poor credit quality of the domestic counterparties, capital flow restrictions, low

domestic currency bonds outstanding reduce the need for high foreign exchange re-

serves. If the foreign investor is unable to find a price for the local currency bond it

holds, and short selling is not allowed, the crisis mitigates itself – the panic may actually

slow down the outflow of capital25. Similarly, it is difficult to open a short currency po-

sition, if the trading counterparty limits the investor has for local banks is low. The de-

veloped countries have usually the opposite characteristics (excellent credit quality of

domestic banks, resulting in huge counterparty limits, no capital restrictions, and enor-

mous bond and swap markets).

This is a paradox – developed countries have cheaper and easier access to reserves, but

each unit is worth less as a crisis protection, precisely because of the depth of their fi-

nancial markets. The central banks must worry about the whole money supply, not just

foreign debt in such countries. Less developed markets, regardless of their policy, have

a form of capital controls built in by default. They work in two ways: by limiting in-

flows due to country exposure limits, and by locking out outflows during panic (limited

25 Several investment fund managers suggested the market impact of the December 2004 Ukraine election chaos was limited precisely because of the low liquidity and lack of the secondary market for Ukraine government bonds.

- 103 -

liquidity). The protection does not work well for floating exchange rate regimes (liquid-

ity difficulties result in “choppier” trade, and higher volatility). This sort of “protection”

does not come for free: the cost is dearer financing for the government and the private

sector of a country, and higher dependence on foreign currency debt.

Figure 9 GBP/ECU rate and UK’s reserves

Figure 10 ECU/SEK rate and Sweden’s reserves

1.2

1.25

1.3

1.35

1.4

1.45

1.5

1.55

1.6

Jan-

89

Jul-8

9

Jan-

90

Jul-9

0

Jan-

91

Jul-9

1

Jan-

92

Jul-9

2

Jan-

93

Jul-9

3

Jan-

94

Jul-9

4

Jan-

95

Jul-9

5

30000

32000

34000

36000

38000

40000

42000

44000

46000

EUROS PER POUND STERLING: PD.AVG.

TOTAL RESERVES MINUS GOLD

7

7.5

8

8.5

9

9.5

10

Jan-9

2

Apr-

92

Jul-92

Oct-

92

Jan-9

3

Apr-

93

Jul-93

Oct-

93

Jan-9

4

Apr-

94

Jul-94

Oct-

94

Jan-9

5

Apr-

95

Jul-95

Oct-

95

10000

12000

14000

16000

18000

20000

22000

24000

26000

28000

30000

SWEDISH KRONA PER EURO:PD.AVG.

TOTAL RESERVES MINUS GOLD

Source: ING Source: ING

_

Figure 11 ECU/ESP rate and Spanish reserves

Figure 12 ECU/LIT rate and Italian reserves

120

125

130

135

140

145

150

155

160

165

170

Jan-

89

Jul-8

9

Jan-

90

Jul-9

0

Jan-

91

Jul-9

1

Jan-

92

Jul-9

2

Jan-

93

Jul-9

3

Jan-

94

Jul-9

4

Jan-

95

Jul-9

5

30000

35000

40000

45000

50000

55000

60000

65000

70000

75000

SPANISH PESETAS PER ECU PD. AVG.

TOTAL RESERVES MINUS GOLD

1400

1500

1600

1700

1800

1900

2000

2100

2200

2300

Jan-

89

Jul-8

9

Jan-

90

Jul-9

0

Jan-

91

Jul-9

1

Jan-

92

Jul-9

2

Jan-

93

Jul-9

3

Jan-

94

Jul-9

4

Jan-

95

Jul-9

5

20000

25000

30000

35000

40000

45000

50000

55000

60000

65000

70000

ITAL.LIRA PER ECU; PD.AVERAGE

TOTAL RESERVES MINUS GOLD

Source: ING Source: ING

_

- 104 -

Figure 13 IRP/ECU rate and Irish reserves

Figure 14 ECU/FIM rate and Finnish reserves

1.2

1.22

1.24

1.26

1.28

1.3

1.32

1.34

1.36

Jan-

89

Jul-8

9

Jan-

90

Jul-9

0

Jan-

91

Jul-9

1

Jan-

92

Jul-9

2

Jan-

93

Jul-9

3

Jan-

94

Jul-9

4

Jan-

95

Jul-9

5

0

1000

2000

3000

4000

5000

6000

7000

8000

9000

10000

ECU PER IRISH POUND:END PD.

TOTAL RESERVES MINUS GOLD

4

4.5

5

5.5

6

6.5

7

Jan-

89

Jul-8

9

Jan-

90

Jul-9

0

Jan-

91

Jul-9

1

Jan-

92

Jul-9

2

Jan-

93

Jul-9

3

Jan-

94

Jul-9

4

Jan-

95

Jul-9

5

2000

3000

4000

5000

6000

7000

8000

9000

10000

11000

12000

MARKKAA PER ECU, END PD.

TOTAL RESERVES MINUS GOLD

Source: ING Source: ING

_

Figure 15 UK’s reserves/M4

Figure 16 Swedish reserves/M3

3.0%

3.5%

4.0%

4.5%

5.0%

5.5%

6.0%

6.5%

7.0%

Jan-

89

Jul-8

9

Jan-

90

Jul-9

0

Jan-

91

Jul-9

1

Jan-

92

Jul-9

2

Jan-

93

Jul-9

3

Jan-

94

Jul-9

4

Jan-

95

Jul-9

5

Reserves/M4

5%

10%

15%

20%

25%

30%

Jan-

89

Jul-8

9

Jan-

90

Jul-9

0

Jan-

91

Jul-9

1

Jan-

92

Jul-9

2

Jan-

93

Jul-9

3

Jan-

94

Jul-9

4

Jan-

95

Jul-9

5

Reserves/M3

Source: ING Source: ING

_

Figure 17 Spanish reserves/M3

Figure 18 Italian reserves/M2

6.0%

7.0%

8.0%

9.0%

10.0%

11.0%

12.0%

13.0%

14.0%

Jan-

89

Jul-8

9

Jan-

90

Jul-9

0

Jan-

91

Jul-9

1

Jan-

92

Jul-9

2

Jan-

93

Jul-9

3

Jan-

94

Jul-9

4

Jan-

95

Jul-9

5

Reserves/M3

2.0%

3.0%

4.0%

5.0%

6.0%

7.0%

8.0%

9.0%

10.0%

11.0%

12.0%

Jan-

89

Jul-8

9

Jan-

90

Jul-9

0

Jan-

91

Jul-9

1

Jan-

92

Jul-9

2

Jan-

93

Jul-9

3

Jan-

94

Jul-9

4

Jan-

95

Jul-9

5

Reserves/M2

Source: ING Source: ING

_

- 105 -

Figure 19 General budget deficit (% of GDP)

Figure 20 Real GDP growth (YoY%) in ERM

-11

-9

-7

-5

-3

-1

1

3

5

1990 1991 1992 1993 1994 1995

Finland Ireland Italy Spain

-6%

-4%

-2%

0%

2%

4%

6%

8%

1986 1987 1988 1989 1990 1991 1992 1993 1994 1995

Finland Ireland

Sweden Germany

Italy Spain

United Kingdom

Source: ING Source: ING

_

Section 4.3 The Tequila crisis 1994

Section 4.3.1 Crisis identification

Mexican crisis looks totally incompatible with 1st generation crisis models. The evolu-

tion of both foreign exchange reserves (Figure 23) and of other liquidity indicators

ahead of the crisis looked like the exact opposite of the one suggested by Krugman’s

formulation. Reserves to M4 and M1 were generally stable, while reserves to foreign

debt, or short-term foreign debt were rising (Figure 24). Budget was in surplus or bal-

ance in 1991-1994 (Figure 22). All liquidity indicators simply collapsed in March and

April 1994 (first bout of the attack, defended), and then again in December, after 6

months of stability.

The original variables unlocking the conditionality of the central bank’s and govern-

ment’s policies in response to the attack: low growth or high unemployment, were not

indicating the crisis either. Growth averaged 3.6% in 1991-1994 (Figure 21), while un-

employment stayed at 2.4% in 1993. Some other transmission factor must have been

responsible. One candidate had been the current account deficit, growing from 3 to 7%

- 106 -

of GDP in the 1990s (Figure 22). The Mexican experience alone could be seen like a

failed test of the Lawson Doctrine – despite the budget surplus, large current account

deficit can be cause external stability problems.

The two important questions are why this could happen, what made the current account

unsustainable, and what is the transmission mechanism between current account rever-

sals and the exchange rate. Obstfeld and Rogoff (2000) addressed the second question in

their article on US current account. In a simple model they show, how sudden current

account reductions (for whatever reason) lead to relative price adjustments, which, un-

der sticky prices can only be accommodated through major nominal depreciation or un-

employment. As for the reasons behind the current account reversal, the possible causes

include political instability, growing US interest rates (which upped the lower limit for

foreign investments profitability in Mexico), and the overall level of debt reaching ex-

posure limit of the creditor countries’ institutions, as advocated by Atkeson and Ríos-

Rull (1995). According to the Obstfeld and Rogoff’s model, actual current account re-

versal is not necessary to generate the central bank’s policy dilemma (between deprecia-

tion and unemployment) and nominal devaluation pressure, so these factors leading to a

sudden stop could, in theory, be enough. However, if they are combined with low li-

quidity, the problem becomes even more acute, leading to forced depreciation and po-

tentially higher output costs26. In such case, not only the foreign debt must stop growing,

but also it needs to be repaid.

26 Both occurred in 1994-1995, but small current account surplus was only recorded in 2Q1995.

- 107 -

Having said this, the current account explanation of the origin, or necessary condition of

the crisis does not find confirmation in cross-section data. Sachs et al (1996b) found that

while real exchange appreciation, lending boom and M2/reserves were significant in

explaining the propagation of the Tequila crisis, current account (and budget deficit, for

that matter) were not. The findings could be matched with the following 2nd generation

explanation: real exchange rate appreciation ahead of the crisis reduces the real eco-

nomic cost of nominal depreciation, while the lending boom makes the banks more vul-

nerable, which, in the absence of ample liquidity, makes the interest rate defence of a

liquidity run too costly.

Figure 21 Real GDP growth in Mexico (YoY)

Fig 22 Mexican CA and budget balance (% GDP)

-8%

-6%

-4%

-2%

0%

2%

4%

6%

8%

1991 1992 1993 1994 1995 1996 1997

GDP growth

-8.0

-6.0

-4.0

-2.0

0.0

2.0

4.0

1990 1991 1992 1993 1994 1995 1996 1997

CA/GDP Budget deficit (% of GDP)

Source: IFS Source: IFS

_

- 108 -

Fig 23 Nominal exchange rate and reserves

Fig 24 Mexican international liquidity measures

2

3

4

5

6

7

8

9

10

Jan-

89

Jan-

90

Jan-

91

Jan-

92

Jan-

93

Jan-

94

Jan-

95

Jan-

96

Jan-

97

Jan-

98

0

5000

10000

15000

20000

25000

30000

35000

US$/Peso, monthly average Reserves minus gold (US$m)

0%

20%

40%

60%

80%

100%

Feb-8

9

Feb-9

0

Feb-9

1

Feb-9

2

Feb-9

3

Feb-9

4

Feb-9

5

Feb-9

6

Feb-9

7

Feb-9

8

Reserves/M4 Reserves/M1

Reserves/BIS ST foreign debt Reserves/Foreign sovgn debt

Source: IFS Source: IFS

_

Section 4.3.2 The role of liquidity

International liquidity got into the centre of the policy debate after the Mexican crisis of

November 1994. As early as in June 1995 Sachs, Tornell and Velasco (1996c), were

arguing that Mexico became vulnerable not only because of fundamental imbalances

(large current account deficit, overvalued currency), or domestic and foreign shocks in

1994 (US rates rise, domestic political trouble), but also because it allowed for a large

build-up of short-term debt. This created the situation when the survival of the fixed ex-

change rate was dependent on right mood of the investors:

In the aftermath of the March assassination the exchange rate experienced a nominal devaluation of around 10 percent and interest rates increased by around 7 percentage points. However, the capital outflow continued. The policy response to this was to maintain the exchange rate rule, and to prevent further increases in interest rates by expanding domestic credit and by converting short-term peso-denominated govern-ment liabilities (Cetes) falling due into dollar-denominated bonds (Tesobonos). A fall in international reserves and an increase in short-term dollar-denominated debt re-sulted. The government simply ended-up illiquid, and therefore financially vulner-able. Illiquidity exposed Mexico to a self-fulfilling panic.

- 109 -

Other authors also point to the low liquidity problem of the Mexican economy. Calvo

and Mendoza (1996) note not only huge M2 to reserves and short-term public debt to

reserves ratios, but also to the historical volatility of both27.

The dynamics of the reserve changes show that the usefulness of the standard liquidity

indicators as crisis early warning signal (in a time-series context) is very limited. Crisis

probability dictated by such a model would have to be declining, together with growing

liquidity, up until March 1994. The situation was different in April-November, period,

when most of the liquidity indicators were declining. The key finding in this context is

Sachs et al. (1996b) paper, which in a cross-section study shows Mexico-originated

panic spread only to those Latin American countries where generally international li-

quidity was lower, real appreciation was higher and bank lending experienced major

expansion. It was the level then, not the trend that was the indication of vulnerability,

suggesting self-fulfilling mechanism at work, unlocked by vulnerability to liquidity

runs.

Apart from the importance in crisis generation suggested by empirical research,

Obstfeld, Rogoff (2000) work implies that the reserves, if used wisely along with other

instruments of monetary policy, might make a difference in crisis management and

costs of speculative attacks in countries exhibiting high current account deficits. Due to

limited, in short-run, tradables-non tradables consumption and production substitution,

sudden fall in current account deficit requires much sharper relative price adjustments

than in the case of smoother current account shrinkage. This is where reserves, properly

27 For other sources on Mexican crisis see Leiderman and Thorne (1995), Edwards (1997), Edwards and Naim (1997). More references, including view of the IMF, the World Bank, Mexican authorities, can be found in Edwards (1999).

- 110 -

used, could come into play. With the speculative pressure starting, the appropriate re-

sponse is to smooth the financing mismatch with foreign exchange reserves, while

tightening the monetary conditions with higher interest rates, or (better yet) with tight

fiscal policy. The higher the reserves, the smoother can be the current account adjust-

ment and smaller the resulting relative price/unemployment/nominal depreciation

shock. In Mexican case, however, only the first part of this prescription was adopted.

Starting from March 1994, the central bank was financing the current account deficit (as

it normally does under the pegged exchange rate) by running down on its reserves in the

absence of foreign inflows. Monetary tightening, the second, crucial step, however, was

not fulfilled. Current account deficit continued its expansion throughout 1994, and the

step adjustment very drastic (from US$7.5bn deficit in 4Q94 to 1.3bn in 1Q95 and

350m surplus in the 2Q of that year).

Compared with the EMS’ fate, the Mexican crisis is an example of a much more con-

vincing case for keeping international liquidity high. Even if in between of the two cri-

sis bouts in 1994, the acquisition of the reserves were too expensive to make sense for

the government (it is not really confirmed in the spreads data, see Figure 25 and Section

4.3.3), lower short-term debt relative to reserves before the initial attack, could have at

least delayed the crisis (helping to survive the political violence), soften its real eco-

nomic impact if the current account adjustment would have been made less dramatic, or

could help to avoid it altogether if time bought were used to fix the banking sector and

cool down domestic demand.

Such interpretation points to two scaling variables. One is the short-term foreign debt.

The second is the current account deficit. The higher the current account, the higher re-

serves are needed to smooth out its adjustment.

- 111 -

Section 4.3.3 The cost of liquidity

A question must be addressed while analysing the importance of international liquidity.

Is the international liquidity problem the same during and before the crisis? Mexico

(similarly to Sweden, and, more recently, Argentina) was faced more than one specula-

tive attack. One occurred in April 1994, second happened in November of the same

year. While the first attack was quite unexpected, the second one was not necessarily so.

Sachs, Tornell and Velasco (1996a) argue that after the initial adjustment in following

Colosio’s assassination, the interest rates stayed unchanged up until the final collapse by

the end of the year. Indeed, foreign exchange reserves did stay flat between April and

November 1994. International liquidity fell due to high credit growth, making the crisis

look more like a 1st generation kind.

Between the two, the Mexican authorities tried to avoid the negative impact of capital

outflow on real economy by sterilising reserve losses. This led to further build-up of

short-term debt and a major fall in international liquidity. If indeed Mexico was guilty

of maintaining insufficient foreign exchange reserves, can it be blamed equally for the

poor liquidity standing in early 1994 and for the policy mismanagement in late 1994?

Sachs et al. (1996a) try to address the problem in their earlier mentioned model, so does

Flood and Jeanne (2000) in a first generation spirit structure. The conclusions of both of

the models may be read as follows: once the level of debt relative to reserves rise

enough to allow for a self-fulfilling attack (or if the underlying budget deficit trend sets

in place), the defence of the peg is futile. Credibility gained by not devaluing is lost due

to the worsened fiscal position. In Mexican case it would mean that the peso should

have been allowed to float or devalued substantially more than the original 10% in

- 112 -

1H94, while the risk of a sovereign debt default was relatively remote (before engaging

in the 6-month sale of short-term dollar-linked tesobonos).

Figure 25 Mexico Par Brady bond zerocoupon spread (bps)

0

100

200

300

400

500

600

700

800

900

Ja

n-9

3

Ma

r-9

3

Ma

y-9

3

Ju

l-9

3

Se

p-9

3

No

v-9

3

Ja

n-9

4

Ma

r-9

4

Ma

y-9

4

Ju

l-9

4

Se

p-9

4

No

v-9

4

Ja

n-9

5

Ma

r-9

5

Ma

y-9

5

Ju

l-9

5

Se

p-9

5

No

v-9

5

Ja

n-9

6

Ma

r-9

6

Ma

y-9

6

Source: ING Financial Markets

_

But the evolution of sovereign spreads show that the costs of long-term borrowing was

not any more prohibitive than it was in early 1993 (Figure 25). This suggests that the

Mexican policymakers could have avoided, or at least alleviated the problems of low

liquidity by simply borrowing in longer maturities, instead of pursuing the self-

defeating strategy of stimulating sterilised short-term capital inflows.

Section 4.4 Bulgarian crisis of 1996-1997

Section 4.4.1 Crisis identification

Bulgaria’s lev collapse was an example a country with floating exchange rate experienc-

ing a currency crisis. Alternatively, the crisis was a typical case of hyperinflation bout,

caused by excessive budget financing needs fulfilled by the Bulgarian National Bank

(BNB). In his account of the crisis Ganev (2003) mentions a host of monetary and struc-

tural reasons for the 3500% depreciation in 12 months, including the pace of budget

- 113 -

deficit monetisation, bad loan problems, and real economy unable to provide the gov-

ernment enough taxes.

Instead of a typical first generation monetised budget deficits-slow outflow of reserves-

crash of the peg scenario, Bulgaria experienced long-lasting nominal depreciation,

which accelerated to crisis levels as the budget and social situation proved more diffi-

cult than usual. Budget deficits have been monetised for years in Bulgaria; it is just the

rate of change of money printing drastically increased as the fiscal situation deteriorated

in 1996. In that sense, the crisis was a natural consequence of simple flexible price

monetary model at work.

Data shortcomings prevent proper testing of the fully specified multivariate monetary

model. Still, attempts to find relationship between prices, domestic money demand and

local interest rate over 1993-1997, yield stable cointegrating vector representing money

demand function (see Figure 26. The hypothesis that price level coefficient is equal to 1

cannot be rejected with χ2(1)=0.0968). The results show that increase in deposit rates by

1% (higher opportunity cost of holding money) reduces real money demand by 0.4%.

At the same time, with interest rate constant, money supply growth translate one to one

to increased prices28.

28 The variables used are log of domestic money, log of consumer credit, and deposit rate level, all from IFS. Attempts to find link money demand with real growth (as a proxy for transaction demand for money) failed, the impact of quarterly consumption, or GDP deflated by consumer prices is very sensitive to the sample size, and generally in-significant. Quarterly inflation rate was also tried as an alternative measure of opportu-nity cost, cash in circulation and total money supply was tried instead of domestic money, all with similar results. The sample size does matter for the estimation results, which is not surprising given the fact time series is so short and that Bulgaria went from centrally planned economy to hyperinflation and to currency board, all potentially influ-encing money demand functions, in just five years.

- 114 -

Figure 26 Bulgarian money demand function

ML estimates subject to over identifying restriction(s)

Estimates of Restricted Cointegrating Relations (SE's in Brackets)

Converged after 18 iterations

Cointegration with unrestricted intercepts and unrestricted trends in the VAR

*******************************************************************************

20 observations from 1993Q1 to 1997Q4. Order of VAR = 1, chosen r =1.

List of variables included in the cointegrating vector:

D P I

*******************************************************************************

List of imposed restriction(s) on cointegrating vectors:

a2=1 ; a1=-1

*******************************************************************************

Vector 1

D -1.0000

( *NONE*)

P 1.0000

( *NONE*)

I -.037886

( .035820)

*******************************************************************************

LR Test of Restrictions CHSQ( 1)= .096832[.756]

DF=Total no of restrictions(2) - no of just-identifying restrictions(1)

LL subject to exactly identifying restrictions= -79.3716

LL subject to over-identifying restrictions= -79.4200

*******************************************************************************

Source: Author

Purchasing power parity testing shows cointegrating relation between the exchange rate

and the price level (Figure 27). 70% of the exchange rate movement passes through to

prices29.

29 P, P* and S are logs of Bulgarian and German price levels, and log of DM/Lev ex-change rate respectively. C is constant. 10% depreciation translates one-to-one into 10% jump of the price level after just two quarters. As above, sample size does matter, and the relationship is much weaker if estimated over extended period of time (spanning into the currency board period).

- 115 -

Figure 27 Purchasing power parity test

Autoregressive Distributed Lag Estimates

ARDL(0,1,0) selected based on Schwarz Bayesian Criterion

*******************************************************************************

Dependent variable is P

21 observations used for estimation from 1992Q4 to 1997Q4

*******************************************************************************

Regressor Coefficient Standard Error T-Ratio[Prob]

S .48524 .10513 4.6156[.000]

S(-1) .59914 .10517 5.6971[.000]

P* 2.1884 2.1007 1.0418[.312]

C -2.1992 9.7645 -.22523[.824]

*******************************************************************************

R-Squared .99317 R-Bar-Squared .99197

S.E. of Regression .14309 F-stat. F( 3, 17) 824.1438[.000]

Mean of Dependent Variable 4.9604 S.D. of Dependent Variable 1.5964

Residual Sum of Squares .34807 Equation Log-likelihood 13.2510

Akaike Info. Criterion 9.2510 Schwarz Bayesian Criterion 7.1619

DW-statistic 1.9130

*******************************************************************************

Diagnostic Tests

*******************************************************************************

* Test Statistics * LM Version * F Version *

*******************************************************************************

* * * *

* A:Serial Correlation*CHSQ( 4)= 5.3844[.250]*F( 4, 13)= 1.1206[.389]*

* * * *

* B:Functional Form *CHSQ( 1)= 6.7734[.009]*F( 1, 16)= 7.6177[.014]*

* * * *

* C:Normality *CHSQ( 2)= .19073[.909]* Not applicable *

* * * *

* D:Heteroscedasticity*CHSQ( 1)= .82409[.364]*F( 1, 19)= .77606[.389]*

*******************************************************************************

A:Lagrange multiplier test of residual serial correlation

B:Ramsey's RESET test using the square of the fitted values

C:Based on a test of skewness and kurtosis of residuals

D:Based on the regression of squared residuals on squared fitted values

Estimated Long Run Coefficients using the ARDL Approach

ARDL(0,1,0) selected based on Schwarz Bayesian Criterion

*******************************************************************************

Dependent variable is P

21 observations used for estimation from 1992Q4 to 1997Q4

*******************************************************************************

Regressor Coefficient Standard Error T-Ratio[Prob]

S 1.0844 .046441 23.3498[.000]

CSTAR 2.1884 2.1007 1.0418[.312]

C -2.1992 9.7645 -.22523[.824]

*******************************************************************************

Source: Author

- 116 -

Figure 28 Bulgarian exchange rate and reserves

Fig 29 Bulgarian international liquidity measures

0.0

0.2

0.4

0.6

0.8

1.0

1.2

1.4

1.6

1.8

2.0

Jan-

92

Jan-

93

Jan-

94

Jan-

95

Jan-

96

Jan-

97

Jan-

98

Jan-

99

0

500

1000

1500

2000

2500

3000

MARKET RATE TOTAL RESERVES MINUS GOLD

0%

10%

20%

30%

40%

50%

60%

70%

80%

Jan-

92

Jul-9

2

Jan-

93

Jul-9

3

Jan-

94

Jul-9

4

Jan-

95

Jul-9

5

Jan-

96

Jul-9

6

Jan-

97

Jul-9

7

Jan-

98

Jul-9

8

0%

100%

200%

300%

400%

500%

600%

700%

Reserves/Money+Quasi-money Reserves/BIS ST debt (rhs)

Source: IFS Source: IFS

_

Fig 30 Bulgarian monetary indicators (in logs)

0

1

2

3

4

5

6

7

8

9

Dec

-91

Jun-

92

Dec

-92

Jun-

93

Dec

-93

Jun-

94

Dec

-94

Jun-

95

Dec

-95

Jun-

96

Dec

-96

Jun-

97

Dec

-97

Jun-

98

-4.5

-4

-3.5

-3

-2.5

-2

-1.5

-1

-0.5

0

0.5

Price level Domestic credit DM/BGL

Source: IFS

_

Fig 31 Deficit monetisation and exchange rate

Fig 32 GDP, CA and unemployment in Bulgaria

-20%

-15%

-10%

-5%

0%

5%

10%

15%

1992 1993 1994 1995 1996 1997 1998 1999

-6%

94%

194%

294%

394%

494%

594%

Net central bank gov. financing

Budget balance

Average annual depreciation

-12%

-10%

-8%

-6%

-4%

-2%

0%

2%

4%

1991 1992 1993 1994 1995 1996 1997 1998 1999

0

2

4

6

8

10

12

14

16

18

CA/GDP GDP growth Unemployment (%)

Source: IFS Source: IFS

_

- 117 -

The crisis was extremely costly – real GDP fell by 17% in 1996-1997 following two

years of positive growth after the post-transformation recession (see Fig 32). But it

would be unfair to attribute the GDP loss to exchange rate depreciation itself. Lev

plunge, along with inflation and public finance chaos, was just a symptom of unfinished

stabilisation effort. On a positive note, the crisis did create a powerful stimulus for the

economic policy reform. Currency board paved way to stable exchange rate and prices,

low interest rates, faster growth, as well as EU accession negotiations. So far, the sys-

tem remains stable for 8 years, and Bulgaria looks set to enter both the EU, and the

EMU in a foreseeable future.

Section 4.4.2 Role of liquidity and the cost of reserves

Figure 28 above show that reserves fall did precede the lev collapse of 1996. The float-

ing exchange rate regime complicates interpretation of the data though. Domestic credit

expansion led to lev depreciation, and thus the local currency value of foreign exchange

reserves also went up. This, in turn, ensured reserves / money supply ratio varied but

generally stayed at around 15% level until the reforms in 2Q97 (Figure 29). Reserves

slowly flow out in the Krugman’s model, here, reserves exhibited less volatility, thanks

to the floating exchange rate. The rate of depreciation was correlated with the rate of

money printing, which, in turn, was correlated with the rate of fiscal disintegration (Fig-

ure 31). Reserves to short term foreign debt first fell below 100% only in 4Q97, follow-

ing a rise to healthy 200% a year before.

With the underlying cause of the currency depreciation so clearly defined as caused by

rapid acceleration of money printing, it is hard to find a serious role for international

liquidity. The model above finds some evidence of price stickiness, which caused ex-

change rate overshooting. In such environment there could be some use of foreign ex-

- 118 -

change reserves to counteract exchange rate overshooting. Still, as a tool for crisis pre-

vention, or even a leading indicator, the reserves were useless. Even if that were not the

case, at 800-1000bps, the costs of borrowing externally were prohibitive for Bulgaria

before the collapse (see Figure 33).

Figure 33 Bulgarian Discount Brady bond zerocoupon spread (bps)

0

200

400

600

800

1000

1200

1400

1600

Ma

y-9

4

No

v-9

4

Ma

y-9

5

No

v-9

5

Ma

y-9

6

No

v-9

6

Ma

y-9

7

No

v-9

7

Ma

y-9

8

No

v-9

8

Ma

y-9

9

No

v-9

9

Ma

y-0

0

No

v-0

0

Ma

y-0

1

No

v-0

1

Ma

y-0

2

No

v-0

2

Ma

y-0

3

No

v-0

3

Ma

y-0

4

No

v-0

4

Source: ING Financial Markets

_

Section 4.5 East Asian crisis of 1997

Section 4.5.1 Crisis identification

Economists were not universally in accord on the key role of inadequate liquidity in the

Tequila crisis (see e.g. Calvo and Mendoza, 1996 or Flood and Marion, 1996 for alter-

native views), and the East Asian crisis was no different30. But large debt relative to in-

ternational reserves was cited from the beginning of the East Asian crisis. Perhaps the

most explicit accounts of such an interpretation are papers by Chang and Velasco

(1999), Radelet and Sachs (1998a) and Feldstein (1999).

- 119 -

In a sense it is quite disturbing that less than three years after the Latin American crises,

the same sources of the financial collapse were referred to. The crises are different but

some of their causes seem to return. Martin Feldstein (1999) concluded his “Self-

protection for emerging market economies”:

There is no substitute for sound economic policies […] But even those countries that pursue such policies are at risk to the powerful forces of market contagion, shifts in risk aversion, and irrational speculation

Because the IMF and other international organisations do not have the resources to act as lenders of last resort, the emerging market countries that want to pre-vent sharp currency declines must provide for their own protection through in-creased liquidity. Reductions in the extent of short term capital inflows would reduce the risk of balance sheet illiquidity. Much larger amounts of foreign ex-change reserves than countries have traditionally held could be an important source of protection, flexibility and confidence. Collateralized credit facilities with private institutions might provide the rapid access to additional liquidity in place of the missing (and infeasible) official lender of last resort. Each of these options is expensive but prove far less costly than the damage of currency crises. [pp. 22-23]

Similarly, Radelet and Sachs (1998) point to the importance of the liquidity ratios:

A particularly telling indicator of these risks is the ratio of short-term debt to foreign exchange reserves. […] In mid-1997 in Indonesia, Thailand, and Korea – the three countries most severely afflicted by the crisis – short-term debt also exceeded available foreign exchange reserves. It is also instructive to note that the ratio exceeded 1.0 in several other countries that were no affected by the cri-sis (including the Asian countries in 1994). This suggests that short-term debt in excess of reserves does not necessarily cause a crisis, but that it renders a coun-try vulnerable to a financial panic.

As in the case of Mexico, a look at the typical vulnerability indicators revealed little of

the “classic” 1st generation crisis problems. Budgets in all five crisis-hit countries (In-

donesia, Korea, Malaysia, Philippines and Thailand) were in surplus in 1996. All but

Philippines and Malaysia moved into deficit a year later, but even the highest, Korean

deficit stood at a mere 1.3% of GDP (Fig 34).

30 Krugman (1998), Corsetti et al (1999) and Chinn et al. (1999) models are examples of an alternative thinking, stressing the importance of moral hazard and contingent gov-ernment liabilities build-up.

- 120 -

Widening of the budget deficits in the subsequent few years, is consistent either with

self-fulfilling nature of the currency crises (policy became expansionary as a result of

the speculative attack), or with a restrictive class of first-generation class models, in

which the shift in policy is not contingent on the crisis happening. In the latter models

speculators know the shift in policy invalidating the peg must occur, and so must the

speculative attack. This line of thinking is represented by Corsetti et al. (1998), Krug-

man (1998) (but not in Krugman, 1999), and Chinn et al. (1999). Observational equiva-

lence (where policy shift could be either contingent or deterministic) makes this di-

lemma impossible to resolve with certainty.

The most often called for arguments speaking for the deterministic explanation of the

crisis are the corruption, nepotism, implicit government guarantees for the corporate

sector and the banks, and otherwise falling profitability of investments31. Transparency

International’s Corruption Perception Index32 (1997) put the highest ranking Malaysia in

32 place and lowest ranking Indonesia in 46th place out of 52 countries reported in the

main poll, below Taiwan, Singapore and Hong-Kong, Chile, Poland, Hungary, emerg-

ing markets that did not suffer a crisis in late 1990s.

The mechanism of the crisis would then be as described in Dooley (1997) or Corsetti et

al. (1998) – mounting corporate debts would ultimately be honoured by the government,

resulting in fiscal (and ultimately monetary) policy not compatible with the peg. But the

low liquidity of most of the East Asian crisis economies was too significant to ignore.

31 See Chinn et al. 1999, or Sasin 2001a

32 See Transparency International (2003) for details on methodology, and Transparency International (1997) for the actual ranking

- 121 -

As the higher-resolution charts show (see Figures 36-40), reserves were increasing

Thailand, Philippines and Indonesia up until the moment of the crisis, a picture not con-

sistent with 1st generation crisis models. They started falling the earliest in Korea (June

1996), and were significantly below the 1994 peak in Malaysia, but rising.

Fig 34 Budget balances in ASEAN-5 (% of GDP)

Figure 35 ASEAN-5 Current account (%) of GDP

-4%

-3%

-2%

-1%

0%

1%

2%

3%

4%

5%

1990 1991 1992 1993 1994 1995 1996 1997 1998 1999

Indonesia Korea Malaysia

Philippines Thailand

-10%

-5%

0%

5%

10%

15%

1992 1993 1994 1995 1996 1997 1998 1999

Indonesia Korea Malaysia

Philippines Thailand

Source: IFS Source: IFS

_

Fig 36 Indonesian exchange rate and reserves

Figure 37 Korean exchange rate and reserves

2000

4000

6000

8000

10000

12000

14000

16000

Jan-

93

Jan-

94

Jan-

95

Jan-

96

Jan-

97

Jan-

98

Jan-

99

Jan-

00

10000

12000

14000

16000

18000

20000

22000

24000

26000

28000

30000

MARKET RATE TOTAL RESERVES MINUS GOLD

700

800

900

1000

1100

1200

1300

1400

1500

1600

1700

Jan-

93

Jan-

94

Jan-

95

Jan-

96

Jan-

97

Jan-

98

Jan-

99

Jan-

00

20000

30000

40000

50000

60000

70000

80000

90000

100000

MARKET RATE TOTAL RESERVES MINUS GOLD

Source: IFS Source: IFS

_

- 122 -

Figure 38 Malaysian exchange rate and reserves

Figure 39 Philippine exchange rate and reserves

2

2.5

3

3.5

4

4.5

5

Jan-

93

Jan-

94

Jan-

95

Jan-

96

Jan-

97

Jan-

98

Jan-

99

Jan-

00

15000

20000

25000

30000

35000

40000

MARKET RATE TOTAL RESERVES MINUS GOLD

20

25

30

35

40

45

50

55

Jan-

93

Jan-

94

Jan-

95

Jan-

96

Jan-

97

Jan-

98

Jan-

99

Jan-

00

4000

5000

6000

7000

8000

9000

10000

11000

12000

13000

14000

MARKET RATE TOTAL RESERVES MINUS GOLD

Source: IFS Source: IFS

__

Figure 40 Thai exchange rate and reserves

20

25

30

35

40

45

50

55

Jan-

93

Jan-

94

Jan-

95

Jan-

96

Jan-

97

Jan-

98

Jan-

99

Jan-

00

20000

22000

24000

26000

28000

30000

32000

34000

36000

38000

40000

MARKET RATE TOTAL RESERVES MINUS GOLD

Source: IFS

_

The evaluation of the reserves scaled by money supply reveals a picture (Figure 41-42)

more difficult to interpret (and interpreted differently by various authors: see Chang and

Velasco, 1998, and Chinn et al. 1999) but is not totally different from the outright re-

serve changes. The decline in liquidity in Malaysia is much more visible when reserves

are scaled by M2. The indicator had been falling since mid 1996 Korea and since late

1996 in Thailand, but in the 3 years leading to the crisis, a deterioration trend can only

- 123 -

be seen in Malaysia33. Chang and Velasco (1998) compare the level of the indicator with

that of other, mostly Latin American emerging markets, which survived the Asian crisis

untouched. However, a quick look at developed countries shows that the reserves/M2

below 10% (Indonesia, the lowest in the group) is quite common, also in the fixed ex-

change rate countries that did not have a crisis in the past 15 years. The ratio was 7.5%

the Netherlands, 8.5% in Belgium, and 2.8% in Germany in 1991.

There were two differences between East Asian economies and European ones exhibit-

ing even lower liquidity influencing the impact of low reserves/M2 ratio. First hypothe-

sis is that demand for money as a store of value in Western Europe is higher than in de-

veloping countries. Thus, the risk of a flight from local to foreign currency assets is

higher in emerging markets, calling for higher liquidity. When this is combined with

weaker banking system (which was the case in Thailand with its notorious finance com-

panies, and e.g. Indonesia, Sasin 2001b), the risk of domestic deposit withdrawal cou-

pled with higher perceived opportunity cost of keeping local currency cash makes the

fixed exchange system more vulnerable to sentiment shifts.

__

33 Philippine indicator is much higher than that reported by Chang and Velasco (1998), who’s source is also IMF. IFS money+quasi money, domestic credit + foreign assets and seasonally adjusted indicators all yield liquidity higher by the order of 2, compared with the paper. The differences for other four countries are negligible.

- 124 -

Figure 41 Reserves/Money+quasi-money

Figure 42 Reserves/Money+quasi-money

10%

15%

20%

25%

30%

35%

40%

Jan-

94

May

-94

Sep-9

4

Jan-

95

May

-95

Sep-9

5

Jan-

96

May

-96

Sep-9

6

Jan-

97

May

-97

Sep-9

7

Jan-

98

May

-98

Sep-9

8

Indonesia Korea Thailand

20%

30%

40%

50%

60%

70%

80%

90%

100%

Jan-

94

May

-94

Sep-9

4

Jan-

95

May

-95

Sep-9

5

Jan-

96

May

-96

Sep-9

6

Jan-

97

May

-97

Sep-9

7

Jan-

98

May

-98

Sep-9

8

Malaysia Philippines

Source: IFS Source: IFS

_

Another, more specific, liquidity-related vulnerability was the countries’ dependence on

short-term foreign debt. BIS data on external indebtedness reveals that reserve/short

term foreign debt ratio in Korea, Indonesia and Thailand and Philippines were among

the lowest in the sample of 60 developing countries. Out of 10 crises identified using the

25% depreciation in 3 months rule in 1997, 6 concerned countries with reserves/short

term debt below, or very close to 1 (Korea, Indonesia, Zimbabwe, Thailand, Philippines,

Bulgaria). The other four included hyperinflationary Belarus, and Albania, effectively

cut off from external financing, which makes the indicator not meaningful. Malaysia’s

liquidity, with reserves at 2.4x the short-term debt, should be considered relatively high

in the group.

Another common factor, confirming the non-deterministic view and underscoring the

role of liquidity, is the geographical proximity of the countries involved. When more

than one country in the region is affected by a crisis, investors become very vigilant to

potential risks related to other similarly structured economies. Dedicated investment

funds’ clients then demand their money back, forcing funds to liquidate otherwise

healthy positions. It then pays for a country to be safe from temporary financing stops.

- 125 -

Short-term debt argument, cited by Radelet and Sachs (1998) and Chang and Velasco

(1999), could point to low liquidity as an important factor, but still not necessary, or,

even less, sufficient to generate the crisis. The top 20 countries includes Russia, which

suffered a crisis a year later, Mexico, still recovering from one in 1996, and Panama

which had the lowest liquidity (just 7% of short term debt covered by reserves), but was

dollarised. That still leaves 8 countries including Singapore and Hong-Kong that man-

aged to escape unhurt between 1997 and 2002.

Judging on current account sustainability is probably the ultimate answer to the di-

lemma of the origins of the crisis. If the current account deficits can be judged as repre-

sentations of intertemporal consumption smoothing, perfectly viable from the long-term

point of view, then the Asian crises should be considered self-fulfilling. But that is im-

possible to do, as the notion of sustainability requires knowledge of the stream future

investment returns. As always, there is a problem with evaluating the sustainability of

the current account in fast growing countries, as the crisis-hit East Asian economies

were. Current account deficit was between 3.4% in Indonesia (seen as sustainable by

Milesi-Ferretti and Rasin, 1996) and 8.2% in Thailand in 1996 (see Figure 35).

The fact that current account was in surplus in Singapore and Hong-Kong, which sur-

vived the 1997, could lead to an impression of the crisis being a direct consequence of

unsustainable external deficits. But, as argued in the previous chapter, the importance of

the current account deficit in crisis prediction is still far from judging on the sustainabil-

- 126 -

ity34. Indiscriminate and self-fulfilling investors’ reaction to any country with a current

account deficit and having low liquidity could also be at play.

The difference between the countries involved may be significant (reliance on short

term debt in Thailand and Korea, and on portfolio equity investments in Malaysia; Thai

finance companies’ solvency problems leading to the crisis, and Korean banks’ difficul-

ties resulting from the speculative pressure), but neither of the cases can convincingly

prove the final distinction if the crisis was self-fulfilling (pointing to asymmetric infor-

mation 1st generation type explanation) or not. What the indicators do show is that in-

ternational illiquidity was a potential source of trouble, which turned into real crisis.

Section 4.5.2 The role of liquidity

The crisis identification section above shows that liquidity could have been at least a

crisis catalyst, even if not the main guilty party in the Asian crisis. At the same time it

was not a helpless predictor of a crisis: neither excessive base money creation by the

central banks, nor excessive budget deficits, nor even M2 growth relative to reserves

(with the exception of Malaysia) can be seen in the ASEAN-5 data.

This means that a policy targeting liquidity might have prevented the crisis altogether,

or, at least, influenced the scale of the crisis. Philippines and Malaysia, the countries

with the highest reserves/short term debt ratio suffered the smallest exchange rate col-

34 Real exchange rate measures are elusive for the same reason – appreciation experi-enced by Philippines (16.3% in 1996 relative to 1990 average), Malaysia (12.1%), Thai-land (7.6%) and Indonesia (5.4%), reported by Chang and Velasco after JP Morgan, are natural result of fast growth, productivity differential and current account deficits (see Obstfeld and Rogoff, 2000). Chinn (2000) estimates much smaller appreciation, when corrected by Balassa-Samuelson effect. Also, Korea showed 12.9% depreciation since 1990.

- 127 -

lapses (46 and 48% in 2H97, respectively, compared with 70-90% by the other three).

The speed of the recovery was better on average with 1999 GDP at over 106.7% of the

1996 in Philippines and Malaysia, but less than 100.1% in the other three35. This is con-

sistent with self-fulfilling crisis model by Chang and Velasco (1999), who argue, that

the impact of fundamental shocks (no doubt important in the case of the countries in-

volved), can be magnified by low liquidity, and that the detrimental effects of “crazy

policies” on liquidity is far more dangerous than the resulting loss of efficiency of the

investments.

Section 4.5.3 The cost of liquidity

It appears that the policymakers of the ASEAN countries had a choice in influencing the

maturity structure of their foreign debt. The problems influencing the liquidity of the

ASEAN-5 counties were twofold.

Because majority of the Asian countries’ borrowing was done by the private sector

(budget deficits were small), the policies could not come down to simply “borrow less

and in longer maturities”. But the governments and central banks themselves pursued

policies stimulating, or not preventing short-term debt accumulation. This exhibited it-

self in various forms.

Tax regulations in Philippines promoted foreign credit in general, while Thai and Ko-

rean policies introduced incentives promoting short-term debt. For example, as a result

of 1993 round of capital account and financial liberalisation, Korean banks were al-

35 Yet to be fair, Korea recovered the fastest in the group with 12% growth between 1996 and 1999.

- 128 -

lowed to lend long-term in foreign currency, but could only borrow short-term without

restrictions. Hesitance in allowing foreign direct investments into Korea, Malaysia,

Thailand and Indonesia (with slow opening of additional sectors for foreign invest-

ments, and frequent official interventions) was another factor stimulating short term

debt (Błaszkiewicz, 2001; Poret, 1998).

Thai and Malaysian bank regulators failed to take into account bank stability risks re-

lated stock-exchange and real estate bubbles36. Malaysian banks’ growth of equity pur-

chase financing grew from 4 to 20%, while growth of manufacturing sector credits fell

from 30 to 14% in mid 1990s (Sasin, 2001a). Thai finance companies were strongly en-

gaged in real estate speculation, which was the direct cause of their troubles in 1H1997

(Antczak, 2001). While in principle there is no strong reason why equity-financed in-

vestments should be inferior to debt-financed corporate expansion, one could argue that

equity speculation is more likely to stimulate short-term debt. Investment projects are

inherently illiquid, and thus call for as long-term financing as possible. Equity invest-

ments, in turn, can be liquidated instantaneously and with negligible transaction costs.

Liquidity, or solvency problems and forced equity investment liquidations by one insti-

tution can create a violent snowball effect of collapsing stock exchange, worsening bal-

ance sheets of other borrowers, and further equity liquidations together with maturing

short-term debt. The speed of the effect depends on the average duration of debt. Thus

regulations limiting banks exposure to equity investment financing would reduce the

accumulation of short-term debt, and ultimately the speed of the collapse.

36 For formal testing of the bubble hypothesis see Sarno and Taylor (1999b)

- 129 -

Sterilising capital inflows, which kept short-term interest rate consistently above world

levels was the third policy-related problem. Such activity deprives the fixed exchange

rate system from self-regulating powers. Falling return on capital reduces local interest

rates, which, in turn, reduces capital inflows. From the local perspective, lower interest

rate differential reduces the incentives to borrow in foreign currency, while the “carry

trade” – investing in short-term, local currency high yielding instruments with minimum

liquidity risk becomes less profitable for foreign investors. Lack of sterilisation also re-

duces quasi-fiscal costs for the central bank. The inflationary impact of lower local in-

terest rates in the environment of free capital flows would not be large (if at all visible).

Apart from regulation and policy issues, the worldwide trend towards short term financ-

ing (Chang and Velasco, 1998) was increasing the supply-related incentives to borrow

short. This resulted in nothing less than yield-curve speculation, where potentially long-

term problems Thai and Malaysian and Indonesian economies (yen appreciation, semi-

conductor price falls, falling return capital on capital) were attempted to be overcome by

refinancing.

Aside from correcting policy flaws described above, there was little, bar outright capital

controls (which Malaysia did resort to, following the crisis) that the policymakers could

do to influence private capital import structure. But they could try to counterbalance low

private sector liquidity by increasing the “war chest” available in times of a temporary

external financing halt. Such a war chest could not only be used to smooth-out the real

impact of current account reversals, but also to stabilise drops in asset prices37.

37 An example of such an action is Hong-Kong’s government’s intervention in the stock market, on 14 August 1998 (see e.g. Far Eastern Economic Review 1998)

- 130 -

The fiscal cost of “war chest” building was not high, compared with the situation of

Mexico, Bulgaria, or later Russia or Argentina. International bond markets have been

extremely favourable for the Asian government (and affiliated agencies), as shown in

the bond spread charts in Figures 43-47. As late as in June 1997, Thailand, Indonesia,

Philippines, Malaysia and Korea had all access to borrowing only 100bp above the US

market swap curve. On top of this, budget surpluses made room for additional borrow-

ing costs. Up until the crisis month, the path to higher liquidity stayed open for all the

East Asian countries involved.

_

Figure 43 Philippines Brady spread (bps)

Figure 44 Indonesia Yankee 06 spread (bps)

0

100

200

300

400

500

600

Jan

-93

Ju

l-9

3

Jan

-94

Ju

l-9

4

Jan

-95

Ju

l-9

5

Jan

-96

Ju

l-9

6

Jan

-97

Ju

l-9

7

Jan

-98

Ju

l-9

8

0

200

400

600

800

1000

1200

1400

1600

1800

20001

2/3

1/1

99

6

2/2

8/1

99

7

4/3

0/1

99

7

6/3

0/1

99

7

8/3

1/1

99

7

10/3

1/1

99

7

12/3

1/1

99

7

2/2

8/1

99

8

4/3

0/1

99

8

6/3

0/1

99

8

8/3

1/1

99

8

10/3

1/1

99

8Source: ING Financial Markets Source: ING Financial Markets

_

Figure 45 Korea Dev Bank 06

Figure 46 Thailand 02 zerocoupon spread (bps)

0

200

400

600

800

1000

1200

5/2

2/1

996

7/2

2/1

996

9/2

2/1

996

11

/22/1

996

1/2

2/1

997

3/2

2/1

997

5/2

2/1

997

7/2

2/1

997

9/2

2/1

997

11

/22/1

997

1/2

2/1

998

3/2

2/1

998

5/2

2/1

998

7/2

2/1

998

9/2

2/1

998

11

/22/1

998

0

100

200

300

400

500

600

700

27-F

eb

27

-Ap

r

27-J

un

27

-Au

g

27-O

ct

27

-Dec

27-F

eb

27

-Ap

r

27-J

un

Source: ING Financial Markets Source: ING Financial Markets

_

- 131 -

Figure 47 Malaysia 00 zerocoupon spread (bps)

0

50

100

150

200

250

300

2/2

7/1

997

4/2

7/1

997

6/2

7/1

997

8/2

7/1

997

10

/27/1

997

12

/27/1

997

2/2

7/1

998

4/2

7/1

998

6/2

7/1

998

Source: ING Financial Markets

_

Section 4.6 1998 Russian crisis

Section 4.6.1 Crisis identification

The rouble collapse can be seen as a classic example of a 1st generation crisis, with ex-

cessive private and unsustainable public spending, which led to an imminent collapse of

the exchange rate.

In fact, Russia experienced two currency crises in the 90s. The first one, in 1994, was

quite similar to the Bulgarian experience of 1996. In 1993-1994 IMF assistance was met

with only partial stabilisation effort. The rate of monetisation of budget deficits, reduced

in the first half of the years, tended to accelerate in the second half. With budget deficits

reaching 20% of GDP, large depreciation pressure was certain to occur. The Russian

central bank (CBR) was not only financing its own government, but also provided credit

facilities to the other Former Soviet Union (FSU) countries (until July 1993, when Rus-

sia started to issue new roubles and the old rouble area ceased to exist). With inflation

reaching 20% on a monthly basis, (in 4Q92, later falling to 4.5-6% per month in the

- 132 -

summer of 1994), an incidence of 20% depreciation of the rouble on 11 October 1994

should not be considered a big surprise. Antczak (2003) concludes:

The macroeconomic stabilization during 1992–1994 was characterized by the lack of authorities' ability or will to sustain adjustment efforts. Fiscal policy remained ex-pansionary and monetary policy monetized fiscal and quasi-fiscal deficits. None of the IMF (and authorities') stabilization programs were successfully carried through. Stabilization was not reached, as there was a systematic tendency to relax economic policies in the second half of each year in face of political pressure, leading to accel-eration of inflation. Inconsistencies in policy-mix resulted in "Black Tuesday" on Oc-tober 11, 1994 when the rouble collapsed on the Moscow interbank market by over 20 percent against the U.S. dollar. The first currency crisis in Russia was a warning indicator.

Figure 48 Russian exchange rate and reserves

Figure 49 Rus Reserves to short term debt (BIS)

0

5

10

15

20

25

30

Jan-

94

Jul-9

4

Jan-

95

Jul-9

5

Jan-

96

Jul-9

6

Jan-

97

Jul-9

7

Jan-

98

Jul-9

8

Jan-

99

Jul-9

9

0

5000

10000

15000

20000

25000

OFFICIAL RATE TOTAL RESERVES MINUS GOLD

0.00

0.50

1.00

1.50

2.00

2.50

3.00

1993 1994 1995 1996 1997 1998 1999 2000 2001 2002

Source: IFS Source: IFS, BIS

The second crisis of 1998 was slightly different. First, the exchange regime was more

rigid, evolving from a currency band (with a crawling central parity) in 1995 to effec-

tive peg at 6.2 new roubles/US$ in 1998. Secondly, central bank’s monetisation of

budget deficits in the run-up to the crisis, did not play such a huge role as in 1994.

Budget deficits remained large (between 6.1 and 7.7% of GDP in 1995-1997), but they

were mostly financed via short-term, local currency treasury bills (GKOs).

The outright budget deficit monetisation is not a necessary condition for the 1st genera-

tion-type crisis build-up. Another possibility is that growth of government’s credit in-

creases broad money (instead of high-powered money). Only after the government faces

- 133 -

payment difficulties, the central bank either rescues the government (via deficit moneti-

sation), or the private sector (facing government’s default). In both cases, the monetary

policy could become incompatible with prior exchange rate regime.

The first part of the mechanism was present in Russia. The monthly data on budget bal-

ance and reserves/M2 changes (Figure 50) show that the reserve to M2 ratio was corre-

lated with budget surplus. Several other indicators behaved in line with 1st generation

crisis theories. These include the stock of foreign exchange reserves, in downward trend

since mid-1997 (Figure 48), local currency yields (Figure 51), reflecting perceived

probability of the collapse was growing since mid 1997, as reflected in growing GKO

yield38.

__

Figure 50 Russian budget and reserves/M2

Figure 51 Russian GKO yield

-20000

-15000

-10000

-5000

0

5000

10000

15000

20000

Jan-

95

Jul-9

5

Jan-

96

Jul-9

6

Jan-

97

Jul-9

7

Jan-

98

Jul-9

8

Jan-

99

Jul-9

9

Jan-

00

Jul-0

0

10%

15%

20%

25%

30%

35%

40%

45%

50%

Budget deficit (RBLm) Reserves/M2 (rhs)

0%

10%

20%

30%

40%

50%

60%

70%

80%

Jan-

96

May

-96

Sep-9

6

Jan-

97

May

-97

Sep-9

7

Jan-

98

May

-98

Sep-9

8

Jan-

99

May

-99

Sep-9

9

Jan-

00

May

-00

Sep-0

0

GKO rate

Source: IFS Source: IFS, Russia defaulted on GKOs, thus the gap in yield data

38 The scale or timing of the collapse was clearly not reflected in the local currency yields of 60% in mid-1998, as Russia did not honour its local currency bills! In 4Q98, brokers reported, that the market price of the securities fell at one stage to 0 (represent-ing infinite yield). The explanation of this could be the reputation cost of having Rus-sian GKOs in the portfolio that were exceeding expected pay-off for some fund manag-ers.

- 134 -

Typically, the second part of the deterministic crisis explanation requires the central

bank ending up financing the government. But as the Russian local currency GKO bond

default proved, the government financing provided by the central bank was not suffi-

cient to avert debt crisis. The reason for this was the local banking system foreign cur-

rency exposure.

Both domestic banks and foreign investors had positions in GKOs, but local banks were

exposed the most to the foreign exchange risk and maturity mismatch. Local banks were

either borrowing abroad or using local foreign-denominated deposits to buy treasury

securities. Less than 4 years after the previous bout of hyperinflation and rouble col-

lapse, foreign currency deposits were still an important part of local savings. Foreign

currency deposits to broad money stood at 53% in 1997 and 43% in 1998 (Antczak,

2003).

Initially, the CBRs policy response to the foreign portfolio inflow came down to obliga-

tory forward contracts with the central bank, forcing foreign investors to swap the

GKOs (which they had to hold till maturity) local currency nominal interest rate into

foreign currency interest of 25% (in 1Q1996), reduced to 19% in April 1996. While un-

der the fixed exchange rate this does not increase vulnerability of the peg provided the

government is solvent (in case of a speculative run, the central bank would have to pro-

vide the dollars in exchange of the rouble GKO proceeds anyway), such policy provides

explicit guarantee of the central bank for the central budget – government’s insolvency

requires immediate money printing, undermining the exchange rate.

With capital account restrictions lifted in 1998, foreign investors, while actively partici-

pating in the local treasury market (50% of GKOs were owned by foreign funds), tried

to limit their local currency exposure, borrowing rouble funds from the domestic banks.

- 135 -

As a result, local banks’ short-term foreign currency liabilities to the non-residents were

twice as high as their short-term assets of US$5.8bn. 30% of all of the US$40bn foreign

currency liabilities had maturity lower than 1 month. On top of this, off-balance forward

contracts pointed to another US$10bn currency exposure.

Thus, by mid 1998, the Russian policymakers faced a dual problem. On one hand, half

of the sovereign papers were held by foreigners (Antczak, 2003 estimates it at

US$39bn), and maturity of the most of the debt was very short-term. US$1.2bn matured

every week in 2H98. This exposed the Russian government to the swings of global

market risk aversion (already lowered by the Asian crisis ten months before). Oil price

fall by 30%, leading to current account deficit (current account had been in surplus

since 1993) undermined investors’ faith in the ability of the Russian government to ser-

vice its debt.

But as described above, the foreign investors were not the only ones having rouble debt

exposure. Sovereign default would bear significant reputation loss, and would lead to

banking system problems, but averting the default by debt monetisation would have

similar consequences for the domestic banking system: the value of their liabilities (for-

eign currency debt and obligations) would grow relative to that of their assets (local cur-

rency GKOs).

By limiting monetary support for the government (and thus depreciation), the central

bank shared the negative consequences of the government insolvency between foreign

investors and local banks.

The Russian crisis was hence a result of a combination of two vulnerabilities. Unsus-

tainable budget deficit was, in a 1st generation crisis spirit model monetised, but only

- 136 -

partially, due to the foreign exchange exposure of the local financial system. Debt crisis

was thus added to a (reduced in scale) currency depreciation.

Interesting features of the Russian economy prevented a major balance sheet effect of

the depreciation that did happen. First, much of the monetary system of Russia was dol-

larised, as the statistics on foreign currency deposits cited above confirm. Second, raw

material exports constitute significant part of the Russian economy, with proceeds de-

nominated in foreign currency. With the exception of the banking system, real economic

impact of the currency depreciation was therefore positive: GDP fell 4.9% in the year of

the crisis (the figure was also influenced by falling oil prices, not only by the crisis), but

grew 5.4% and 10% in the two years that followed (and on average above 5% in 2001-

2003).

The identification of the crisis points to a variant of the 1st generation crisis model. The

balance sheet impact of the depreciation and default on the local banks was offset by the

positive impact of depreciation on non-bank private sector growth. Therefore, despite

the local bank foreign currency exposure, the crisis could not be described as of a bal-

ance sheet, or self-fulfilling type.

Section 4.6.2 Role of liquidity

In December 1997, the Russian reserves/short term foreign debt indicator at 40%

(Figure 49) was the 6th lowest in the sample of 60 developing countries (or the 3rd low-

est if dollarised Panama, and countries undergoing a currency crisis - Korea and Zim-

babwe are not included). Was low liquidity responsible for the crash? As argued above,

probably not. The Russian crisis was principally a debt and budget deficit issue. As

Antczak (2003) notes,

- 137 -

[…] the contagion effect was weak as it only speeded up what was unavoidable – the deep correction of the exchange rate due to accumulated macroeconomic imbalances.

The Russian crisis of 1998 represents a typical case of the "first generation" model. The balance of payments crisis led to the currency crisis with sovereign debt default and, as a result of weak supervision of financial institutions and poor management in the aftermath of rouble devaluation, resulted in a full-fledged financial crisis with debt default and bank closures.

Just as in any first-generation models, insufficient foreign exchange reserves, while not

directly responsible for the crisis, could have served as a leading indicator for the crash.

The composition of debt, also facilitated the instant, probably randomly timed switch

into the expansive monetary regime and deficit monetisation. The regime could have

lasted longer if debt refinancing requirements had been lower compared with the avail-

able reserves. But the impact of a policy explicitly targeting level of reserves would de-

pend on the fiscal cost of such a policy.

Section 4.6.3 Cost of reserves

The debt maturity problem of Russian economy was an effect of still fresh transition

experience, and lack of credibility, rather than some specific regulations or policies,

which artificially boosted short-term indebtedness. An attempt to introduce law limiting

foreign involvement in energy sector by Russian Duma (parliament) as late as in May

1998 is one example of such a liquidity-detrimental policy.

On the other hand, between 1996 and 1998, the Central Bank’s of Russia (CBR) policy

did attempt to artificially lengthen the maturity of foreign obligations. From August

1996 onwards, foreign investors were allowed to participate in secondary GKO market

(which increased “the temperature” of the capital inflow – the flows could reverse at

two days notice), but were obliged to purchase 3 to 6 month forward foreign exchange

contract (with local banks, which had do the offsetting forward with the CBR) before

repatriation of rouble proceeds. The policy was aimed at prolonging the stay of the in-

- 138 -

vestments in the country in case of a sudden reversal on one hand, and to know the day-

to-day flows well in advance. There are two problems with such policies. First, the 3 or

6 months gained is not enough to allow for policy response, aiming at, say, reducing

domestic demand, or for quick fiscal reforms. Secondly, a capital control targeting debt

maturity can only be effective if it is discriminate enough between short and long ma-

turities. If all GKOs are treated in the same way, the investors will simply take the con-

trol into account in its optimal debt maturity structure calculations, reducing the GKOs

maturity accordingly.

Making the long-term debt cheaper required nothing less than full transformation from

the centrally planned economy, increasing transparency, and reducing budget deficit. It

was not so much that liquidity was allowed to fall – it was simply never allowed to

grow.

Section 4.7 1998 crises in other FSU counties: Ukraine and Moldova

Section 4.7.1 Crises identification

Russia was not the only FSU country suffering a currency crisis in 1998. It was the big-

gest, with highest foreign involvement, and thus the most well known. Most of the

countries with which Russia had significant trade relations suffered. Many FSU coun-

tries however, had their own macroeconomic or structural problems, and depreciation of

their currencies was merely triggered by the Russian rouble collapse. Budget deficit re-

lated problems were common denominator for a few countries involved.

Markiewicz (2003) shows that Ukraine followed a similar path to Russia in 1996-1998.

The central bank was not financing the government until 1997. The IFS does not pro-

vide any data on Ukrainian budget deficit, and for a good reason. The transparency and

- 139 -

accounting practices of the Ukrainian public finances were not up to international stan-

dards. In particular, privatisation proceeds were counted as budget revenue, the gov-

ernment allowed for in-kind tax payments, and cumulative budgetary arrears reached

9.5% of GDP in 1998 (Dąbrowski et al., 1999).

Relatively favourable external financing conditions and Ukrainian banks’ willingness to

extend credit to the government were enough to finance budget deficit growing from

3.4% in 1996 to 6.1% in 1997 and over 7% in early 199839. The currency remained sta-

ble; the foreign exchange reserves were growing (see Figure 52) as the central bank kept

hryvna from appreciating in real terms. 1997 inflation fell to 10.1%, despite money sup-

ply exceeding 30% YoY. The apparent growth in real money demand was occurring

despite the continuing recession.

As fiscal policy remained expansionary, Asian developments of 1997 proved monetary

policy “asymmetric”. When the capital was flowing into the country, the reserve money

was allowed to grow. When it started to flow out, the central bank started to supplement

money supply with credit to the government. It was effectively replacing foreign ex-

change reserves by Ukrainian government t-bills. Such a sterilised intervention, in times

of global retreat from emerging market debt (so portfolio balance arguments did not ap-

ply), was not effective. In a bid to regain credibility, the central bank replaced managed

float with a crawling peg with bands in May 1997. The bands were realigned five times

before February 1999, so no credibility was gained.

39 Markiewicz (2003). The problems described above lead to various estimates of the budget deficit. Official figures point to deficits of 6.8, 4.8, 6.7, 2.0 and 1.5 in the 1995-1999 respectively

- 140 -

Foreign exchange reserves halved from US$2.4bn in early 1998 to US$1bn by the end

of the year (see Figure 52). Over the course of 1998 hryvna depreciated 80%, and in

1999 and 2000 the government had to reschedule large part of its foreign debt (and de-

fault on the small part which was not rescheduled).

Apart from large budget deficit, the other 1st generation crisis indicators do point to the

crisis, but the problems start to be visible only in mid 1997, one year ahead of the crisis.

Reserves/M2 ratio fluctuated wildly, falling below zero (thanks to negative reserves in

May 1994) to over 40% in mid 1997 (Figure 53).

__

Figure 52 Hryvna rate and reserves (US$m)

Figure 53 Ukraine’s reserves/M2

0

1

2

3

4

5

6

1994

M1

1994

M7

1995

M1

1995

M7

1996

M1

1996

M7

1997

M1

1997

M7

1998

M1

1998

M7

1999

M1

1999

M7

2000

M1

2000

M7

0

500

1000

1500

2000

2500

3000

OFFICIAL RATE TOTAL RESERVES MINUS GOLD

0%

5%

10%

15%

20%

25%

30%

35%

40%

45%

Jan-

94

Jul-9

4

Jan-

95

Jul-9

5

Jan-

96

Jul-9

6

Jan-

97

Jul-9

7

Jan-

98

Jul-9

8

Jan-

99

Jul-9

9

Jan-

00

Jul-0

0

Source: IFS Source: IFS

Moldovan experience of 1996-1998 displayed an extreme case of wrong policy mix.

The monetary policy of the National Bank of Moldova (NBM) was very effective. The

leu was introduced in late 1993, and, while floating in theory, in practice served as a

nominal anchor until 1998. Nominal depreciation fell from 15% in 1994 to 5.1 in 1995

and 0.2% in 1997. Real exchange rate to the US$ appreciated 250% (Radziwiłł, 2003

claims the leu-dollar exchange rate was initially undervalued at 3.85 in 1993). As a re-

sult inflation fell from 2000% in 1993 to 11.2% in 1997.

- 141 -

Despite huge budget deficits (25% of GDP in 1992, and 8.8% average in 1993-1998 on

commitment basis40), the NBM’s budget deficit financing support was relatively small

after 1993 until August 1998. Foreign inflows and budget arrears were sufficient. Capi-

tal flight of late 1997 and 1998 resulted at first in a textbook example of exchange rate

defence. The central bank was intervening in the foreign exchange market, reducing

domestic money supply. According to Radziwiłł, cash in circulation fell so much, it be-

came a scarce asset in everyday transactions. As a result, inflation fell to zero in 2-3Q of

1998. Despite shortening the duration of the government debt and a spike in interest

rates, the budget deficit proved unfinanceable. In September NBM engaged in similar

activity to the Ukrainian central bank (providing liquidity to the government still de-

fending the leu) resulting in 80% depreciation two months later (see Figures 54 and 55).

__

Figure 54 Moldovan exchange rate and reserves

Figure 55 Reserves/M2 and deficit monetisation

0

2

4

6

8

10

12

14

Jan-

94

Jul-9

4

Jan-

95

Jul-9

5

Jan-

96

Jul-9

6

Jan-

97

Jul-9

7

Jan-

98

Jul-9

8

Jan-

99

Jul-9

9

100

150

200

250

300

350

400

OFFICIAL RATE TOTAL RESERVES MINUS GOLD

0%

20%

40%

60%

80%

100%

120%

Jan-

94

Jul-9

4

Jan-

95

Jul-9

5

Jan-

96

Jul-9

6

Jan-

97

Jul-9

7

Jan-

98

Jul-9

8

Jan-

99

Jul-9

9

Jan-

00

Jul-0

0

0

200

400

600

800

1000

1200

1400

1600

1800

2000

Reserves/M2 CLAIMS ON CENTRAL GOVERNMENT

Source: IFS Source: IFS

The monetary policy up until mid 1997 in Ukraine and mid 1998 in Moldova could not

be considered particularly expansive. Consequently, no deteriorating trend in

M2/reserves could be seen until about a year ahead of the crisis (Figures 53 and 55).

40 As opposed to cash measure, which does not include budget arrears

- 142 -

Deficit monetisation started (or accelerated in case of Ukraine) only in the final months

before the crisis, validating the speculative attack.

Does this mean a second-generation explanation for the crisis, or rather that of the de-

terministic monetary policy switch? The persistent budget deficits, combined with cur-

rent account deficits and weak growth (Figures 56-57) speak for the latter – the deficit

was unlikely to be sustainable at the exchange pre-crisis exchange rate.

__

Figure 56 Ukrainian growth and CA

Figure 57 Moldovan growth and CA

-13%

-11%

-9%

-7%

-5%

-3%

-1%

1%

3%

5%

1994 1995 1996 1997 1998 1999

CA balance GDP growth

-25.0%

-20.0%

-15.0%

-10.0%

-5.0%

0.0%

5.0%

10.0%

1996 1997 1998 1999 2000

CA/GDP GDP growth

Source: IFS, Markiewicz (2003) Source: IFS, Jarociński (2000)

Section 4.7.2 Role of liquidity

Such crisis interpretation makes international liquidity almost useless in both predicting

and targeting crises. It was useless in predicting crises, because until one year ahead of

the Ukrainian crisis and 6 months ahead of the Moldovan leu collapse nothing wrong

could be seen in liquidity indicators. At the same time, the problems of high budget

deficit, opaque public finances, microeconomic foundations for growth (e.g. legal sys-

tem, bankruptcy law, see Dąbrowski et al., 1999) were making liquidity targeting (issu-

ing long-term foreign currency debt) costly enough to be counterproductive. Russia,

Ukraine, Moldova consumed too much, run excessive budget deficit, which was fine as

- 143 -

long as external financing was sufficient. As budget spending did not lay enough foun-

dation for growth and future budget revenues, the collapse was bound to happen regard-

less of the liquidity position.

Section 4.8 2000-2001 Turkey default and lira collapse

Section 4.8.1 Crisis identification

17th IMF-supported Turkish stabilisation and disinflation programme since 1961 started

in January 2000. It was ambitious, as many reforms were attempted at the same time.

Turkey addressed simultaneously corruption, privatisation, social security (all three cre-

ating political tensions), banking supervision (resulting in several banks’ closures, and

loss of public confidence in the sector), and monetary prudence (which leaves confi-

dence as necessary condition for banking system and fiscal survival)41.

The programme lasted for mere 14 months, and the first serious crisis occurred as early

as November 2000. Either the crisis-generating process must have been very quick, or

the system had a built-in vulnerability.

Given the extent of the reforms, there were many potential issues that could undermine

the stabilisation effort. Political tensions over privatisation strategy started already in

August 2000. From September up until November speculative attack, steady flow of

negative news about the banking sector was undermining confidence of both local de-

41 For accounts of the crisis see e.g. Alper (2001), Akyüz and Boratav (2002), Eichen-

green (2001), Sasin (2001), and Yeldan (2002) and references therein.

- 144 -

positors and foreign investors. Strengthened bank supervision and anti-corruption ac-

tions revealed problems in numerous banks’ balance sheets (Sasin, 2001).

The importance of the events is very high, as Turkey has a long history of large inflation

and monetised excessive fiscal deficits. Sasin (2001c) writes: “Between 1961 and 1999,

Turkey signed 16 agreements with the IMF concerning disinflation and fiscal consolida-

tion – and broke every one of them.” Even though the reserves/M2 ratio at above 30%

in 2000 was high, compared with most developed and many emerging economies

(Figure 59), both transactional demand for money, and demand for Turkish lira as a

store of value were very fragile. The proof for the former is visible during a holiday trip

to Turkey: euro and US$ are just as readily accepted in everyday payments as the lira.

The proof of the latter is the share of foreign currency deposits in the broad money,

jumping from 41.7% in 3Q99 to 49.1% a year later, and then back to 43.9% in the next

three months. What it means for the currency stability, is that a liquidity run on the

banking sector cannot be harmlessly met with central banks’ liquidity injection, because

no-one is going to keep lira in cash with inflation consistently above 50%. So a confi-

dence run on the banking sector is equivalent to the run on the lira.

__

- 145 -

Figure 58 US$/TKL and Turkish reserves

Figure 59 Reserve/M2 and TCMB gov. financing

0

200000

400000

600000

800000

1000000

1200000

1400000

1600000

1800000

Jan-9

7

Jul-97

Jan-9

8

Jul-98

Jan-9

9

Jul-99

Jan-0

0

Jul-00

Jan-0

1

Jul-01

Jan-0

2

Jul-02

15000

17000

19000

21000

23000

25000

27000

29000

MARKET RATE TOTAL RESERVES MINUS GOLD

20%

25%

30%

35%

40%

45%

50%

Jan-

97

Jul-9

7

Jan-

98

Jul-9

8

Jan-

99

Jul-9

9

Jan-

00

Jul-0

0

Jan-

01

Jul-0

1

Jan-

02

Jul-0

2

0

10000

20000

30000

40000

50000

60000

Reserves/M2 CLAIMS ON GOVERNMENT

Source: IFS, reserve jump in Dec-00 represents IMF disimbursement Source: IFS

__

Figure 60 YoY GDP growth and CA balance

Fig 61 Turkey Republic 30, zerocoupon spread

-30%

-25%

-20%

-15%

-10%

-5%

0%

5%

10%

15%

20%

1995Q

1

1995Q

3

1996Q

1

1996Q

3

1997Q

1

1997Q

3

1998Q

1

1998Q

3

1999Q

1

1999Q

3

2000Q

1

2000Q

3

2001Q

1

2001Q

3

2002Q

1

2002Q

3

GDP (YoY%) CA balance (% of GDP, annualised)

200

300

400

500

600

700

800

900

1000

1100

1200

2/1

0/2

000

6/1

0/2

000

10

/10/2

000

2/1

0/2

001

6/1

0/2

001

10

/10/2

001

2/1

0/2

002

6/1

0/2

002

10

/10/2

002

2/1

0/2

003

6/1

0/2

003

10

/10/2

003

2/1

0/2

004

6/1

0/2

004

10

/10/2

004

Source: IFS, Current account not seasonally adjusted Source: ING Financial Markets

In such case, the central bank has two options, both of which were tried in late 2000 and

in early 2001. The first one is to let the reserves flow out, without sterilisation, which is

what happened in November-December 2000. Reserves declined (Figure 58), short-term

interest rates shot up to above 1800%. Another disimbursement from the IMF calmed

the situation until February, when wrangling between the president and the prime minis-

ter on state owned bank supervision strategy resulted in another round of falling confi-

dence. The interest rates reached 6000% after which the central bank caved in, choosing

the second option, and deciding to let go the peg, and save the banking system.

- 146 -

The crisis looks either like a typical liquidity run transforming into currency crisis

(which would point to a self-fulfilling nature of the run), or like a bank solvency crisis,

in which case the programme was doomed to fail right from the beginning. Like in the

2nd generation crisis models, deficit monetisation, shooting up from March 2001 on-

wards validated the run (see Figure 59). But then, informational equivalence stressed

out by Flood and Hodrick (1986) means that the first generation class of models in

which fiscal and monetary expansion (due to ailing and undercapitalised banking sector)

was bound to happen, would point to exactly the same policy actions. As in the case of

the Asian crisis, even if the underlying problem was deterministic, the element of self-

fulfilling nature was also at play – the banking system bailout costs after even a short

spell of 6000% interest rates were certainly higher than without it42.

Section 4.8.2 The role and cost of liquidity

From the Turkish policy perspective, the distinction between self-fulfilling and determi-

nistic nature of the crisis may not be so important. Regardless whether the banking sys-

tem required capital injection or a mere liquidity help, tightening of the banking super-

vision should be attempted before, or long into the stabilisation programme. Even if the

government is capable of dealing with the insolvent banks without deficit monetisation

(which would point to sustainability of the peg in the absence of a liquidity run), coun-

tries facing stabilisation programmes do not generally have resources for honour blanket

deposit guarantees for the whole banking system (the problem they deal with is break-

42 Alper (2001) blames the explosion of the current account deficit in 2000. CA deficit stood at –21% of GDP that year. However, with growth averaging 7%, and with the time span of the process so short, the responsibility of the current account deficit for the crisis creation seems stretched. Both intra-year and annual CA volatility in Turkey is high, 2001 bought the reversal to +8.8%, see Figure 60.

- 147 -

ing with deficit monetisation in day-to-day budgeting process, let alone systemic bank

failure). Longer spell of stable currency and lower inflation, on the other hand, increases

chances of resolving temporary banking confidence problem using liquidity injection by

the central bank, as the deposit run does not have to translate into a run of the local cur-

rency in such case.

The lifespan of the stabilisation plan - less than 14 months before the total collapse, and

less than 11 months before serious crisis suggests that a policy targeting liquidity may

have not played such a great role in the crisis, even if the direct reason of the collapse of

the Turkish 2000 stabilisation plan was a confidence crisis. With debt service burden as

it was, the only way to rebuild liquidity was to keep confidence high and watch the

capital flow in. In times of oil price jump and interest rate hikes in the US, this was ex-

tremely difficult, even without the added bonus of privatisation slips, political uncer-

tainty, and bank clean-up.

Foreign exchange reserves were an exogenous variable to the monetary policy, as they

usually are in an exchange rate anchor stabilisation programmes. Arguably, the central

bank could have issued Eurobonds for the sole purpose of increasing international li-

quidity in very early stages of the programme. This, however, would create competition

to the government financing, needed so much in the absence of deficit monetisation.

Section 4.9 The end of Argentine currency board

Section 4.9.1 Crisis identification

Argentine’s stabilisation attempt started in 1991, and thus lasted almost 10 years longer

than the Turkish one. There are two main hypotheses on the source of the Argentine cri-

sis. One, represented by Mussa (2002) is that the collapse was nothing else but a debt

- 148 -

crisis, caused by irresponsible fiscal policy pursued since the inception of the Converti-

bility Plan. Second explanation (see e.g. Eichengreen, 2001) blames exchange rate over-

valuation for the recession, fiscal problems, and the ultimate collapse43.

Mussa (2002) points to 12% of GDP public debt increase during the 1993-1998, years

of good, over 5% growth (with the exception of 1994). This happened despite signifi-

cant debt write-offs (Brady plan), and privatisation receipts. The public debt expansion

was faster than the sums of official budget deficits (scaled by nominal GDP growth)

could suggest. Off-balance sheet accounting was apparently prevalent, as in many other

countries. Such artificial lowering of the budget deficit could include denying sufficient

funding for state social security, local governments, health care, and other public of-

fices, and forcing them to borrow in the private sector (and outside of the central budget

accounting). Payment arrears are another method, but normally not used (with the ex-

ception of former Soviet Union countries) until serious crisis occurs44.

43 See the Appendix 1 for the extended chronology of the crisis, reproduced from Stan-dard & Poor’s (2002), as well as Edwards (2002) for a more sketchy (but also more ana-lytical) chronology.

44 The translation of budget deficits into debt accumulation is just one of concepts that the budget deficit indicator tries to capture, which leads to additional difficulties. In 2003 Poland had five measures of budget deficit, all used in public debate on fiscal pol-icy. First there were two official measures of deficit, and two European System of Ac-counting 95 standard deficits (accruals-based) – one of each not counting funded pen-sion system subsidies. Then, there was the “economic deficit,” quoted by the central bank (see e.g. NBP 2003) trying to capture the domestic demand impact of fiscal policy, which treated G3 mobile telephony licence fees as financing items, similar to privatisa-tion, and included estimates of social security and healthcare debt build-up, but did not include government subsidies to the funded, obligatory pension plan. There is a debate on the ways to account for the latter (see e.g. Eurostat 2004). There are three reasons behind excluding such subsidies (filling the gap created in the pay-as-you go system by directing some of the contributions to the funded part). One is that that pension fund money represents savings, not dis-savings of the economy. Another is that in normal times such subsidy is a self-financing item (pension funds keep up to 60% of their port-

- 149 -

The process of debt accumulation in Argentina, even if slower, looks remarkably similar

to the experience of Moldova or Ukraine. Hyperinflation and Brady plan helped Argen-

tina to start with relatively low public debt to GDP at 29% in 1993 (Mussa, p. 10).

While economic structure, and thus possibility of debt servicing of Moldova and

Ukraine had been far worse in than that of Argentina in early nineties, they started off

their independence with zero debt thanks to the fact Russia took over all communist era

debts (Radziwiłł, 2003). But both Ukraine and Moldova quickly caught up. Foreign debt

grew to 21% in 1993, 82% of GDP in 1998 and 129% in 1999 in Moldova (Radziwiłł,

2003), and to 38% in 1998 and 56% in 1999 in Ukraine. Argentina saw debt climbing to

41% of GDP in 1998 and above 50% in the following two years.

Mussa presents arguments why debt of that size was a problem for Argentina, while it is

generally considered not an issue for developed countries (average EU-12 debt in 2003

was some 10 percentage points higher than the 60% required by Maastricht), or coun-

tries aspiring to the developed market status (Poland and Hungary had 45.4% and 51%

debt-to-GDP ratios respectively in 2003, ING 2004).

folios in treasury bonds, see e.g. KNUiFE, 2004). The third reason is that the payments (and the pension system reform) reveal implicit debt towards future pensioners, also present in non-reformed systems of countries like Germany, or France. In judging rela-tive compliance with e.g. Maastricht criteria, it makes sense to level the playing field, and not punish the countries for pension system reforms. From the point of view of debt sustainability though, the arguments are not valid, speaking for inclusion of the debt to private pension funds in the public debt statistics. Private pension funds are not obliged to buy government bonds (at least in Poland), so they could still refuse to roll-over gov-ernment debt. Also, the implicit debt resulting from the promise of pension benefit pay-ments is “softer” than the government obligation – the regulations on the level of pen-sions paid are not as clearly defined as the debt coupon and principal payments (Rostowski, 2004).

- 150 -

First, the ability of the government to raise taxes in Argentina was low compared with

developed countries. Total tax revenue/GDP ratio was around 20% in Argentina, and is

close to 50% in both EU-12 and the converging Central European economies45.

As in the case of FSU countries, Argentine fiscal situation looked bad not only because

of the level of debt, but also the speed of debt accumulation. The fact that debt widened

by 12% of GDP in times of good growth, combined with higher growth risk characteris-

ing developing countries46, was making the situation look even less sustainable.

Second group of Mussa’s arguments concerned the fact that a large share of Argentine

debt was denominated in US$: “Argentina faced the dual challenge of persuading credi-

tors that it was capable both of raising sufficient fiscal revenues to service its debt and

of being able to convert these revenues into foreign exchange with an exchange rate that

was rigidly pegged to the US dollar.” (page 16). But this argument is wrong. Debt de-

nomination argument may have little relevance not only from the point of view peg sus-

tainability, but also, in the Argentine case, from the point of view of debt sustainability.

Standard view (see e.g. Eichengreen, 1997 p. 16) is that peso-denominated debt, for the

government, has the advantage of non-default exit strategy option of money-printing.

But it is not immediately clear, why investors’ losses coming from foreign currency

debt default should be bigger than losses coming from depreciation-induced fall in the

45 For this difference to influence crisis vulnerability it must be assumed that spending can also be adjusted in the times of payments crisis. If the level of fiscalisation (spend-ing to GDP) is sticky, the ability to raise more taxes increases the probability of a peg survival only when the voters’ dislike for debt default could be higher than the prefer-ence for cutting down on public healthcare, pensions, etc.

46 Growth variance in a sample of 55 non-industrial countries was 8.9 times higher than in 22 industrial ones in 1990s

- 151 -

value of local currency debt. If the government is not able to generate enough real assets

to pay back, the investors will take losses either through depreciation or through pay-

ment arrears and debt rescheduling. Neither depreciation nor sovereign default is a bi-

nary event (see e.g. Easton and Rockerbie, 1999 for a model taking this into account),

and both the scale of monetary expansion and the extent of the arrears can be adjusted

gradually.

From the point of view of the local policymaker, conversely, it is not obvious that the

costs of deficit monetisation are lower than these of a sovereign debt default. The case

of Russia, which defaulted on its local currency debt underscores the dilemma – the

Russian policymakers decided full-scale debt monetisation would be inferior to the de-

fault47. In short, restricting the definition of unsustainability of debt to outright default is

not the right strategy. The currency of denomination has little impact if we treat moneti-

sation of deficits as a partial default48.

What is the influence of the debt denomination on the peg sustainability? In the cur-

rency board case (or, in fact in case of any serious currency peg, entailing non-sterilised

47 The dilemma: “monetise or default” moves to another level when independent central bank refuses to credit the government. Banking sector strain, resulting from defaulting government can still force the central bank to bail-out the banking system, instead of the government.

48 The typical way of disentangling the foreign exchange risk from the default risk is comparing the dollar-denominated bond yields with local currency yields. The problem with this approach is that the risk of outright default is smaller for peso-denominated debt (the government may ask the central bank for local currency to pay back debt). Foreign exchange risk internalises the default risk, provided the central bank does, at some stage resort, to deficit monetisation. Therefore, foreign exchange risk estimated this way would be biased downwards. The spread between the local and foreign cur-rency debt is dependent on the “non-default-related” foreign exchange risks, and depre-ciation expectations related to the monetary regime (e.g. in the crawling peg regime, the

- 152 -

interventions), withdrawal of funds from local treasury papers, either through their sale

to residents, or just refusal to roll them over, results in monetary tightening. This hap-

pens regardless of the currency of denomination of the debt. If the amount withdrawn is

higher than the stock of reserves available for non-sterilised intervention (which tends to

be less than the total stock of reserves – Ukraine in 1994 and Sweden in 1992 were the

only countries in this case study which had the reserves falling to zero), the peg fails.

So, on a purely technical level, both foreign currency debt, and local currency debt

could trigger the peg collapse.

However, the composition of the public debt does make a difference for incentive struc-

ture for the government. While more foreign currency debt reduces government incen-

tives to devalue, more local currency debt increases incentives to do so. This simple re-

sult requires that the government has some degree of control over monetary, or ex-

change rate policy and that it considers the costs of default as higher than the costs of

inflation, but Mussa’s argument about conflict of foreign currency debt and a currency

board is not very convincing. Another reason why foreign currency debt is not making

the peg any less vulnerable is the fact that that the secondary market foreign-currency

bond transactions are neutral for the monetary policy. It does not need to be the case for

the local-currency bonds – foreign investors getting rid of the sovereign local currency

assets are more likely to get rid of the local currency as well.

There is a long way from saying that the debt currency of denomination does not influ-

ence the probability of a peg collapse to saying that the existence of foreign debt does

change of the annual rate of parity devaluation should correspond to the lowering of the local currency yields).

- 153 -

play a role in creating vulnerabilities. Falling government’s creditworthiness translates

in such case translates into pressure on the currency (regardless of the denomination of

debt) – capital flows out of the country via maturing foreign currency bonds or through

proceeds from the local currency bonds converted into foreign currency.

Fiscal problems were not the only ones troubling the Argentine economy. Eichengreen

(2001) lists several issues: poor growth, large exposure of local banks to sovereign debt,

and, the key issue, the real exchange rate. According to Eichengreen, inflation fell insuf-

ficiently fast given the nominal exchange rate anchor, which resulted in chronic current

account problems, later aggravated by €/US$ and oil price movements. Wage rigidities

were too high for non-devaluationary adjustment of the real exchange rate. A quick look

at US$/peso exchange rate and annual inflation since 1995 reveals real depreciation: in

the seven years between 1994 and 2001, consumer price level rose mere 1.7% (with

constant US$/peso exchange rate). But these numbers do not give the full picture. Cu-

mulative inflation in the first three years following the 1991 stabilisation was 44% (yet

the currency board exchange rate set in Jan-91 was almost 70% weaker than a US$/peso

a month before), US productivity growth exceeded that of Argentina in the 1990s (Ed-

wards, 2002), the nominal DM/peso rate strengthened by over 20% in the period, and

Brazilian Real devaluation also undercut Argentine competitiveness in 1999.

While current account deficits in a fast-growing economy, following macroeconomic

reforms could well be sustainable, Argentina in the last three years ahead of the crisis

run an average 3% current account deficit amid investments falling on average 13.3%

per annum. This confirms the real exchange rate overvaluation problem.

Poor fiscal performance in the years of strong growth suggests that while both real ex-

change rate and fiscal policy factors were at play in generating the crisis, debt sustain-

- 154 -

ability problem was the most important in generating the crisis. A possible explanation

linking the two issues would be large budget financing needs resulting in crowding out

of private investments (resulting from upward pressure on real interest rates and compe-

tition for local bank funds). This slowed down productivity growth, making Argentine

economy vulnerable to external shocks hitting in 1999-2001 (€/US$, oil prices, Real

devaluation). Resulting low growth accelerated debt accumulation, and further aggra-

vated interest rate burden on the private sector.

Section 4.9.2 The role of liquidity

Argentine’s reserves/M2 measures were stable almost by definition. The currency board

ensured sufficient coverage of the monetary base. Reserves/M2 stayed between 25 and

30% between 1996 and 2000 to fall to 20% in the final run up to the crisis in 2001. De-

terioration of the reserves/short-term foreign debt indicator started one year earlier, fal-

ling to low 50% by the end of 2001. The level of short-term debt was below the 100%

danger level, throughout the nineties, which means that total loss of confidence would

force unlimited monetary contraction with the currency board intact.

The increasing prevalence of short-term debt in the run-up to the crisis could have

served as a vulnerability indicator, but the fiscal statistics makes the reliance on short-

term debt more similar to the FSU countries than to East Asian ones. Since the Mexican

crisis, reserves/short term debt fell below 75% and stayed there until the crisis. This was

happening despite the governments attempts to issue as much long-term bonds as possi-

ble, even as late as in 2000 (Mussa, 2002). In short, debt level and fiscal unsustainabil-

ity were inevitably leading to financing stops.

- 155 -

The Fig 62 shows that foreign currency spread on long US$ bond yields became totally

prohibitive only in mid 2001. The picture does not tell, however, how the spread would

change in response to increased borrowing. Argentina struggled with financing its

budget deficit starting from 2000, and additional debt, even for the sole purpose of pro-

viding liquidity, could push the cost of financing higher still.

Fig 62 Argentina Discount Brady bond zerocoupon spread (bps)

0

500

1000

1500

2000

2500

3000

3500

4000

4500

5000

Jan

93

Jan

94

Jan

95

Jan

96

Jan

97

Jan

98

Jan

99

Jan

00

Jan

01

Jan

02

Jan

03

Jan

04

Source: ING Financial Markets

_

Section 4.10 Case study conclusions

The most striking feature of the recent currency crises is the existence of competing ex-

planation of the crises, the existence of several vulnerabilities reinforcing each other.

For example, Argentina and FSU countries were vulnerable to confidence reversals, re-

sulting from debt maturity structure, but the underlying problems were of a fiscal na-

ture.

“Pure” liquidity crises are rare; Ireland, Korea, possibly Malaysia and Indonesia could

be seen as such. It can be claimed that if everything is right in the country, low liquidity

does not have to be a problem. Without fiscal deficits (Bulgaria, Argentina, FSU coun-

tries, Italy, Finland), low growth (the UK, Finland, Sweden, Italy, Argentina), current

- 156 -

account concerns (Mexico, most of the East Asian crisis economies, Turkey, Argentina)

the crises would probably not happen. As Krugman points out, almost all countries are

guilty of one fundamental crisis cause or another; it is just that some of them are

unlucky to get hit by the crisis. Low liquidity makes luck dry out faster, especially if

some other countries experience crises at the same time.

But the cases described above do not convincingly show how to remedy the problem of

low liquidity. In the crisis extending liquidity is too costly. Before the crisis the possi-

bility of deliberate policy directed to keep liquidity high is there. But maturity structure

of the debt usually reflects fiscal, monetary and political trends. If these issues are not

addressed, extending maturity of the debt will only aggravate fiscal problems. For fis-

cally sound countries, however, there might be the case for policies explicitly targeting

liquidity: such countries included Mexico, Korea, Thailand, Indonesia and Malaysia

(with the latter taking into account foreign stock market investments as a potential

short-term liability of the central bank). Examples of such policies would be promotion

of foreign direct investments or explicit long-term sovereign borrowing to boost re-

serves relative to short-term debt.

- 157 -

Figure 63 Summary of the case studies

Country Main crisis cause Secondary issues Role of liquidity The UK Overvalued exchange rate and weak

growth Deep interbank markets, vulnerability of the econ-omy to interest rate hikes, devaluations elsewhere

Ireland Pure self-fulfilling crisis, all exchange rate consequences reversed in the next two years.

Devaluations elsewhere, high unemployment

Italy, Finland

Excessive budget deficits, 1st generation type

Growth collapse in Finland

Pure liquidity possibly an issue on a techni-cal level (determining day and hour of the collapse), but deliberate government’s bowing to the speculative pressure was dominating any liquidity issues in the longer horizon

Mexico Current account and real exchange rate overvaluation

Low (albeit growing until the first attack) re-serves/short-term debt, low reserves/M2. Accommoda-tive monetary policy re-sponse.

Level, not trends important for identifying vulnerability before 1994. Reserves, used up to finance current account deficit throughout 1994 should have been supple-mented by tighter monetary policy to allow for smoother demand adjustment and smaller depreciation.

Bulgaria Accelerating, monetised budget deficit. 1st generation crisis in a floating ex-change rate environment.

Young transformation economy, low trust in local currency.

Very low reserves facilitated 1:1 transmis-sion of monetised budget deficit into depre-ciation. Managed floating impossible with reserve level so small.

Thailand Capital account reversal sped up by very high short-term external debt used by finance companies for property investments.

Poor bank and finance companies’ supervision; international trade compe-tition, overvalued ex-change rate.

Finance companies exposed to major matur-ity mismatch with construction investments collateral and short-term liabilities.

Indonesia High total private dollar debt with short-term debt and annual debt service costs exceeding 3x the available re-serves leading to vulnerability to fi-nancing stops

Political concerns, banking sector supervision, falling return on assets.

Reserve growth inconsistent with 1st genera-tion crisis models, but reserve to M2 and reserve to short term debt ratios low. Micro fundamentals seem more problematic than liquidity in crisis creation.

Malaysia High overall leverage and short term debt of local companies making interest rate defence of the peg too costly. Port-folio capital outflow validated currency weakness through its impact on stock exchange, local balance sheets, and thus investments.

High current account defi-cit, crises in the rest of the region.

Short-term foreign debt limited to the bank-ing sector, and relatively small overall. Foreign equity investments created vulner-ability through the corporate and private balance sheets

Korea Extremely low international liquidity, and foreign debt made the financing stop self-fulfilling through investments crippled by shrinking balance sheets in case of the falling stock exchange and depreciating won.

Yen depreciation, falling investment efficiency, crises elsewhere in the region

Central, short-term debt stimulated by bar-riers for FDIs

Russia Excessive budget deficits Terms of trade shock, Asian crisis a year before

Extremely high short-term debt/reserves; trends in M2/reserves consistent with 1st generation models.

Ukraine Large public debt accumulation, ulti-mately monetized

Crisis in Russia Very low short-term foreign debt.

Moldova Large public debt accumulation, ulti-mately monetized, despite textbook defence of the leu.

Crisis in Russia Very low short-term foreign debt relative to reserves

Turkey The economy exposed to self-fulfilling runs due to limited confidence in the lira, bank confidence loss, political uncertainty over stabilization pro-gramme.

Oil price jump, US interest rates hike, high current account deficit.

Stabilisation period very short, not allowing for liquidity targeting policy actions. High reserves/M3 counterbalanced by low trans-action demand for money and high oppor-tunity cost of holding cash.

Argentina Excessive budget deficits soft budget constraints for the provinces, leading to fiscal sustainability problems

Real exchange rate over-valuation, continuing re-cession, €/US$ fall

High reserves/M3, but relatively low re-serves/short-term foreign debt (below 75% in the 90s) accentuated refinancing prob-lems in 2001.

Source: Author

- 158 -

Chapter 5 International liquidity targeting: a model49

In this chapter I attempt to utilise an optimising policymaker model taking into account

costs and benefits of holding foreign exchange reserves to determine what level of li-

quidity countries should hold if reserves do protect from currency crises.

Section 5.1 Crisis and its costs

The model stands on somewhat “empirical” assumption, which, on one hand, may be

questionable from the strictly theoretical point of view, but on the other, is the most

widely used formulation in the literature on the leading indicators of the currency crises.

The assumption is that the probability of a currency crisis happening in time t (yt=1) is

equal to:

1 1 1

1 1 1

( )

( )( 1)

1

t t t

t t t

l REER G

t l REER G

eprob y

e

α β γ δ

α β γ δ

− − −

− − −

+ + +

+ + += =

+ (5.1)

where l is international liquidity (defined as a ratio of foreign exchange reserves to

short-term debt), REER is real effective exchange rate overvaluation, and G is the

budget deficit50. α, γ, δ>0, β<0.

While no foreign exchange crisis model yield the exact probability function, the formu-

lation above can be justified on two grounds. First, because most of the multiple equilib-

ria models say nothing about what contributes to the switch between them (a crisis),

such an ad-hoc assumption is not inappropriate; given the fundamental/liquidity vari-

ables are in the indeterminate region (see e.g. Chang and Velasco, 1999, Sachs et al.

49 An early version of this model was published as Szczurek (2003)

50 The function can be trivially extender to include other leading indicator variables

- 159 -

1996). Secondly, because the function is so widely used in the empirical study, it can be

claimed that it is believed by both policy-makers and the creditors to be true representa-

tion of the currency crisis risk. It suffices for the analysis of the policy-maker’s optimi-

sation that follows.

The functional form of the crisis probability function has powerful implications for the

policy options faced by the government/central bank. In particular, regardless of how

bad the fundamentals are, the central bank could come up with liquidity in t-1 suffi-

ciently high to prevent the crisis in time t, as shown in Figure 64. Probability of a run

[P(y=1)] is close to one when liquidity is low and fundamentals are bad (upper left cor-

ner of the graph). The ability to survive (for a short period of time) a massive specula-

tive pressure, even with bad fundamentals is a plausible assumption. It can be done,

provided the government has enough liquidity (and is willing to engage in unsterilised

foreign exchange interventions).

Figure 64 Probability of a crisis vs. international liquidity and a budget deficit

02.5

57.5

100

2

4

6

00.250.5

0.75

1

02.5

57.5

10

Budget deficit

liquidity

P(y=1)

Source: Author

More questionable is the policymaker’s ability to choose any desired level of liquidity.

The subject is discussed in the following section.

- 160 -

A crisis in period t results in real depreciation in the same period51. This is the only ef-

fect of the crisis on the fundamental variables. The scale of the crisis-triggered deprecia-

tion is assumed to be a function of the liquidity and the other country-specific variables

in t-1.

( )1 1 1 1t t t t t tREER REER y l REER Gφ λ µ θ− − − −= − + + + (5.2)

where µ, θ > 0; λ < 0 and yt is one when crisis occurs, and zero otherwise.

In the model this is the only possibility for the real exchange rate to move. A crisis and

devaluation/depreciation is possible even with undervalued real exchange rate, provided

international liquidity, or other fundamentals are bad enough. Formulation above en-

sures that the two consecutive crises in a country are possible, yet unlikely – the worse

the fundamentals leading to the first crisis, the bigger the depreciation, and bigger the

improvement in the external stability outlook in the following period.

Here, I explicitly assume lack of three effects, which could make a crisis in subsequent

period more likely after a crisis in t. First is the feedback effect on the international li-

quidity. Even though crisis in t usually results in the outflow of reserves, this does not

have to result in a lower liquidity and higher probability of the crisis in t+1. If interna-

tional liquidity is defined (as in the empirical exercises that follow) as a ratio of reserves

to short term debt, the feedback effect depends on the scale of the capital outflow and

relative amounts of reserves and debt due. In fact, in the sample used, international li-

quidity increases one year after a crisis. While the numerator of the liquidity ratio (re-

51 Real depreciation is just one example of the reverse feedback from the crisis itself to the crisis driving variable. It could also be current account, budget balance, or interna-tional liquidity itself. The empirical study below shows that current account deficit could easily replace (or supplement) the real exchange rate here.

- 161 -

serves) decreases during the crisis, so does the denominator – short term foreign debt

usually falls very quickly towards zero.

Second ignored effect here is the loss of reputation of the policy makers. A currency

crisis, and subsequent devaluation/major depreciation can cause a severe loss of credi-

bility of the exchange rate regimes that follow. This can cause either runaway inflation

and further large depreciations or unsustainability of any exchange rate commitments,

and thus could make subsequent crisis more likely. An effect of a similar kind, but

working in the opposite direction is facilitation of reforms in the face of a currency cri-

sis, which could reduce the scope of crises in the future. Such a “purgatory” effect of a

currency crisis can be implemented by the government of the concerned country, which

can justify unpopular or painful reforms by either grave economic situation, or the con-

ditionality of IMF rescue packages. The recent experience, however, shows that the cri-

ses rarely have significant positive impact on the policies of the affected countries.

Antczak, Markiewicz and Radziwiłł (2003) argue that IMF was not very effective in

enforcing the effective use of its funds in the Former Soviet Union countries in the

1990s. Bulgaria and Hungary are probably the only examples of successful reforms fol-

lowing crises in the region.

Finally, the third ignored potential effect is the impact of the currency crisis on the

budget deficit. Crises could be related to increased pressure on some government spend-

ing, e.g. related to social support, bailouts, bank rescue operations, riot control, public

debt service costs. However, IMF conditionality and financing problems usually offset

the spending pressure. The assumption is justified by the estimations shown in Figure

73, which failed to confirm a significant link between crisis occurrence and future

budget deficits.

- 162 -

Apart from algebraic complication, waiving the first and the third assumption above

would increase the long-term value of foreign exchange reserves. Preventing a crisis in

time t would also help to prevent the crisis in time t+1 (international liquidity and

budget surplus would both stay higher without a crisis than with it), so any factor pro-

tecting from the crisis goes a longer way protecting also from subsequent disturbances.

The empirical data does not indicate the need to enhance the model by the inclusion of

the two effects. The credibility loss, while making future depreciations more likely,

would, in real world also reduce the social and economic costs of the future crises, as

economic agents get used to the increased depreciation and inflation risk.

A crisis in time t results in certain costs χt to the economy and the policy makers. One

could argue that the cost should be some function of the severity of the crisis (or mis-

alignment of the fundamental variables and insufficient liquidity), reflecting the adjust-

ment costs (presumably higher with high current account deficit, high public debt grow-

ing in line with real exchange depreciation), distress to the banking system, etc. This

type of cost can be observed empirically as, e.g., the deviation of the post-crisis GDP

growth from its long-term trend. In some cases, the real economy part of cost χt could

even be negative, as the UK’s 1992 example showed.

The overall crisis cost to the policy-maker, however, includes a second type of cost:

reputation loss. It is much more difficult to assess empirically in an explicit way, no ex-

plicit form of the total crisis cost function will therefore be considered here. Presuma-

bly, the reputation cost is the function of the degree of the rigidity of the foreign ex-

change regime, and the length for which the regime was maintained, past inflation ex-

perience, but also personality of the central banker, behaviour of the countries consid-

ered similar (political contagion modelled by Drazen, 1999) etc.

- 163 -

The actual expected gain from the additional unit of reserves in t-1 is therefore:

( )

( )

1 1 1

1 1 1

( )

2( )1 1

( 1)

1

t t t

t t t

l REER Gt t

t tl REER G

t t

E P y e

l l e

α β γ δ

α β γ δ

χ βχ χ

− − −

− − −

+ + +

+ + +− −

∂ ∂ == =

∂ ∂ +, where χt<0, (5.3)

which is the decrease in expected value of the policy maker’s crisis cost in t as a result

of the higher international liquidity in t-1. The convention adopted here sets crisis cost

χt below zero (so that higher liquidity would bring positive effects for the policymaker).

Apart from the liquidity’s influence on the financing costs (considered in the following

section), this is the only benefit from international reserves in the model.

The marginal gain reflects the shape of the probability surface, and looks as in Figure 65

(assuming cost independent of REER).

Figure 65 Marginal return to international liquidity vs. liquidity and REER

0

2

4

6

liquidity

0

0.2

0.4

0.6

0.8

1

overvaluation

0

0.05

0.1

0.15

0.2

US$ c

0

2

4

6

liquidity

Source: Author

- 164 -

The peak of the marginal return to reserves is reached for higher levels of liquidity, as

the fundamentals get worse. The reason is that when fundamentals are really bad, a

marginal increase in liquidity from zero will not markedly reduce the probability of the

crisis. Alternatively, if the fundamentals are really good, an increase in already high li-

quidity will not reduce the probability of a crisis, because it is very close to nil anyway.

The level at which the surface is located depends on the expected crisis cost χt.

Section 5.2 International liquidity and its cost

At each non-crisis point of time, the policy maker faces the following choice: he can

either keep his foreign exchange reserves (receiving international yield i* and benefiting

from the increased security it brings), or it can get rid of a portion of them using the

cash to pay off his foreign debt, avoiding paying interest i. I assume that when there is

no run on the currency, the policy maker can both easily borrow on the international

bond markets and lower its international debt up to the size of foreign exchange reserves

(to allow a possibility to vary international liquidity between zero to infinity)52.

The real alternative cost of the foreign exchange reserves is thus the difference between

the country’s international bond and US treasury yield, equal to i-i*, which is the coun-

try risk premium over the international borrowing rate. This is the only direct cost of

holding foreign exchange reserves. The way the reserves are acquired does not matter

for the policy maker’s choice – it can always run down or increase reserves holding af-

terwards.

52 Concentrating on “the policymaker” avoids institutional complications, and division of powers between the central bank and the government. In practice, the former has con-trol over foreign exchange reserves, the latter over debt.

- 165 -

The formulation leaves open two important constraints. One is the ability to run down

on debt in every moment. In a hypothetical situation of all the debt maturing in a distant

future, and creditors unwilling to be paid back earlier (one of the reasons why this could

be the case is local institutional arrangements in creditors countries; some of the Paris

Club members debt agencies, including Belgium and France would have to pay taxes on

profits on debt paid back earlier), a country would not be able to freely reduce its inter-

national liquidity53. Also, a country with no external debt at all (and some foreign ex-

change reserves) would enjoy infinite liquidity with no way of running down on it! Even

more difficult would be influencing private external debt. In practice, because sovereign

debt does play significant role for most of the countries, there is a room for manoeuvre

in liquidity targeting. For countries that do not have long term sovereign debt to get rid

of, the alternative cost of their foreign exchange reserves for the policymaker is low –

there is no way to save money by running down on liquidity. Optimum reserve holdings

would then be higher than predicted by the model in such case.

Second problem is the ability to borrow long term in order to boost international liquid-

ity. Countries in the middle of financial markets distress can rarely sell long-term for-

eign currency debt. From the model point of view, however, it is not a serious issue: the

ability to issue debt comes down to the proper (meaning “high” preceding the crisis)

yield, reflected in the market prices for existing debt.

53 Selling foreign exchange reserves for local currency is possible, but it complicates monetary policy. Such option could indeed save money for countries suffering from structural overliquidity in the banking system (where the central bank must constantly extract cash from the market to keep desired monetary policy). In such case, selling re-serves reduces the costs of regular central bank liquidity drainage operations.

- 166 -

Because of the definition of the international liquidity (reserves/short-term debt ratio),

the actual liquidity cost also depends on the total stock of short-term debt. Higher short-

term debt requires more long-term borrowing to cover it54.

The risk premium faced by the policy makers depends on the credit assessment by the

foreign investors, which is directly related to the probability of the crisis:

* ( 1)ti i P yε ξ− = + = (5.4)

The rationale for this formulation is that currency crisis, while not affecting the foreign

currency debt directly, tends to be related to sovereign defaults. Local-currency value of

foreign debt rockets up in such case, which threatens the solvency of the government, if

the tax base does not follow. Liquidity problems are often in the roots of the currency

crashes – and lack of local currency financing affects the external solvency as well. The

overall spread may also be affected by country-specific factors not related to the prob-

ability of the currency crisis (ε), likely to reflect past default cases, etc. This is a very

simplistic formulation; however, what really matters for the argument below is only the

average impact of higher liquidity on the spread. In the empirical research, the actual

data on interest rate spreads can be used, so the ε would be both country- and time-

specific to account for the set of factors other than the risk of a currency crisis55.

54 We ignore the fact that long bonds become short-term obligations, leading to a tempo-rary increase in short-term debt in the future.

55 Another way would be to model the spread directly as a function of international li-quidity. This, however would presumably have to be highly non-linear function of for-eign exchange reserves (investors do not care if a county has US$200bn or US$230bn reserves, whereas the difference between zero and 30bn makes all the difference be-tween safe and an unstable economy.

- 167 -

Because an improvement of the credit assessment makes servicing the existing foreign

debt cheaper, the marginal, immediate cost of reserves πt consists of two elements. One

is the cost of additional reserves, the other is the impact of lower interest rate (thanks to

lower crisis probability) on existing debt.

( ) ( ) ( )

( )

1 1 1

1 1 1

1 1 1

11

21

1*

1

t t t

t t t

t t t

l REER Gt tt t l REER G

tl REER G

t

e l Di i l De

l e

α β γ δ

α β γ δ

α β γ δ

βπ ε ξ

− − −

− − −

− − −

+ + +−− + + +

+ + +−

+ + + ∂ − + = = +∂ +

(5.5)

where Dt is the amount of foreign debt to be rolled over in t. It is the change in the total

cost of debt as a result of acquiring additional unit of liquidity. Because β is less than

zero, it is possible that πt falls below zero, given the existing debt is high enough. For

that to happen, the improvement of the country’s reputation, resulting from better li-

quidity, would have to offset the costs of keeping the borrowed funds as a war-chest.

Large financing needs increase the gains from lower sovereign bond spreads (as was

experienced by e.g. Italy in the final stages of nominal convergence ahead of the EMU),

but they also tend to pump up the spreads themselves.

I assume the level of taxation is constant, so an increase in international liquidity in t-1

increases Gt by the cost πt.

The immediate cost of reserves is not the only cost faced by the policy maker. Second-

round effects also play a role. There are two dynamic problems to worry about. First, is

the negative impact of debt servicing costs on budget deficit in the subsequent period56.

56 This cost can be negative in a special case, when marginal costs are also negative, i.e, when the benefits of cheaper financing outweigh the cost of the additional unit of re-serves.

- 168 -

To keep probability of the crisis in the following period unchanged, higher reserves

must offset the higher budget deficit, in line with the crisis probability equation (5.1). It

can be done by reserve borrowing higher by tδπ

β− , where δ and β are parameters relat-

ing probability of the crisis with budget deficit and international liquidity respectively.

The cost of this offsetting operation is r

t

++

11π

, where r is the policy maker’s discount

rate.

Second cost is much less straightforward, and is related to the fact, that crises in t and

t+1 are not independent events. A crisis in t makes the subsequent crisis less likely, be-

cause of the real depreciation assumed in (5.2). Therefore, by borrowing reserves in or-

der to protect the country from a crisis in t, we make the crisis in t+1 more likely, be-

cause the probability of the “cleansing” effect of the crisis in t decreases. The amount of

the reserves needed to counterbalance the effect is equal to:

[ ]1 1 1

1

( 1) t t tt

t

l REER GP y

l

γ φ λ µ θ

β− − −

−

+ + +∂ =

∂ (5.6)

(5.6) is a probability weighted equivalent to (5.5); If the liquidity increase were to fully

protect from the otherwise certain crisis, real exchange rate overvaluation REER in the

following period would be higher by 1 1 1t t tl REER Gφ λ µ θ− − −+ + + , in line with (5.2).

This makes the crisis in the following period more likely. As in the case of higher

budget deficit, to offset for this, the future reserves must be higher by the amount de-

pending on the probability-weighted lack of real exchange rate adjustment, scaled by

the parameters linking crisis probability with real exchange rate and international liquid-

ity (γ and β respectively).

- 169 -

To complete the analysis one should take into account higher debt service cost in subse-

quent periods caused by the above-mentioned additional borrowing. The cost of re-

serves in the future periods require additional borrowing in the periods to follow. The

marginal total cost MTC of reserves, therefore, is equal to:

( )

( ) ( ) ( )

1 1 11

0

( 1)

1 1 1

t nt t t

t tt t

n

P yl REER G

lMTC

r r r

γ φ λ µ θδπ δπ

π πβ β β

− − − ∞−

=

∂ = + + + ∂

= + − − + + +

∑

(5.7)

The first term (πt) is the immediate marginal cost of reserves; the second

( )

( )

1 1 11

( 1)

1

tt t t

t

P yl REER G

l

r

γ φ λ µ θ

β

− − −

−

∂ = − + + + ∂

− +

is the cost of postponing the cleansing

effect of the crisis – the term is positive with increasing reserves (provided the crisis

leads to real depreciation), as both β and the probability of the crisis are smaller than

zero; the third term ( )1

t

r

δπ

β−

+ is the cost of higher deficit associated with increased

reserves (it is again positive). Finally, the last part of the equation

( )0 1

n

n r

δπ

β

∞

=

− +

∑ takes into account the impact of the costs above on future budgets57.

57 The total marginal cost equation can be expanded to following, ( )

( ) ( ) ( )( ) ( ) ( ) ( )( )( )

( ) ( )

2

4

2 2 1 2 2

1

L REER G

L REER G

e r G L REER r Cosh L REER G L Cosh L REER G Sinh L REER G

e r

α β γ δ

α β γ δ

β γ θ λ µ φ α β γ δ ε ζ βζ ε ζ α β γ δ ζ α β γ δ

β β δ

+ + +

+ + +

2 + + + + + + + + + + + + + + + + + + + + +

+ + +

- 170 -

The discount rate r matters for the cost equations. Large r means that the effects of fu-

ture budgetary costs, and the lack of cleansing effect of the quick crisis do not bother

the policy maker much. The optimal r, which should be close to the inter-temporary

consumption discount rate (probably related to the average real interest rate), may be

completely different to the policy makers’ r. For example, if the government is on its

way to lose the elections, it could risk postponing the (almost) inevitable currency crash,

by borrowing foreign exchange reserves at a large cost, and making the crisis virtually

certain, but only after the elections. In such case, (5.7) collapses to (5.5).

Section 5.3 Optimisation problem

Combining the marginal benefit equation (5.3) and marginal cost formula (5.7) we are

able to complete the analysis. Optimising policy maker tries to minimise the following

loss function by targeting the liquidity level:

( )( )1 1

1 1 110 0

t tl lt

t t tt

EL l MTCdl dl

l

χ− −

− − −

−

∂= +

∂∫ ∫ (5.8)

First term of (5.8) is the total cost of reserves (the area below the cost curve in Figure

66), while the second is (minus) total benefit from a particular level of reserves (or li-

quidity).

where sinh(x) and cosh(x) are hyperbolic sine 2

x xe e− −

and cosine 2

x xe e− +

respec-

tively

- 171 -

Figure 66 Optimal international liquidity – marginal cost and benefit

1 2 3 4 5Reserves/GDP

50

100

150

200

250

300

350

400

US$m

Cost

Benefit

Source: Author

Both definite integrals in the loss functions are solvable, but the result is totally intrac-

table, which makes algebraic solution to the optimisation problem impossible. Because

of this, the minimum must be sought numerically (see Appendix 2 for the Mathematica

5 code for minimising the loss function subject to liquidity parameter).

In the example above (and all of the empirical cases tried below), there are two local

minima. One is at international liquidity equal to zero. It is the global solution, if in-

creasing liquidity costs more than it brings (fundamentals are too bad for a slight im-

provement of liquidity to change the probability of a crisis). Countries in the middle of a

crisis fit in that category – the borrowing costs for their long-term debt are likely larger

than the benefit of reduced likelihood of a crisis they could ever bring. The second loss

function minimum is at the point where downward sloping marginal benefit and mar-

ginal cost curves cross. The second local minimum is a global minimum only if L(lt-

1)<0. In the example above, this is the optimal level of liquidity: the total gain (which is

the surface below the marginal benefit curve) exceeds the total cost.

The model has several advantages:

- 172 -

• It takes into account not only the obvious costs of liquidity, but also the dynamic

effects – the costs of postponing the crisis. The effect is likely to be negligible

for relatively healthy economies, but significant for the ones faced with major

overvaluation of the real exchange rate. Admittedly, in the model formulation

estimated below, the effect was not sizeable. For an extreme case of zero poli-

cymaker’s discount rate, the effect would top 0.1% of GDP for the most affected

countries. For the more plausible 10% discount rate, the effect would be 0.09%

of GDP annually. This is because the fall in marginal crisis probability resulting

from higher liquidity is small. The secondary effects thus differ between the

countries solely due to the differences in costs of external borrowing.

• Despite the complexity of the loss function, the model is relatively simple to es-

timate numerically. The benefit function (logit analysis of the reserves’ impact

on the probability of the crisis) is deeply rooted in the existing literature on lead-

ing crisis indicators. Similarly, data for the depth-of-crisis function, and interest

rate premium relationship is available for a broad range of countries.

• Assuming the model is correct, it allows for an estimation of the reputation cost

of the foreign exchange crisis (which is the only residual variable in the whole

structure).

Section 5.4 Empirical application: Introduction

The above model was used for two empirical applications. First, we tried to estimate

what is the optimal (safe, and reasonably cheap – “best value for money”) holding of

international liquidity. This requires assumptions regarding the perceived cost of the

currency crisis. This application requires estimation of the logit crisis probability equa-

- 173 -

tion, with binary crisis variable as the dependent variable, and a vector of explanatory

variables, including international liquidity, budget surplus, and a range of control vari-

ables. As a result, the marginal crisis probability decrease resulting from higher liquidity

could be evaluated - it would presumably be dependent not only on the level of liquid-

ity, but also on the range of other fundamental variables). In order to receive the fully

specified gain from reserves, this function must be multiplied by an unknown cost to

policymaker.

Second function needed to evaluate the optimal reserves holding is the liquidity cost.

Dependent variable is the spread of the foreign currency denominated sovereign bonds

of the country in a particular period of time, while the explanatory variables include the

fitted crisis probability, and a combination of control variables. The results of the esti-

mation are then plugged in the dynamic version of the cost equation (5.7).

Because it is not possible to solve the loss function analytically, the solution to the prob-

lem of optimal reserve holding requires finding the minimum of the loss function nu-

merically for a range of crisis cost parameter (see below).

Second application involve finding out what is the perceived cost of the currency crisis

to the policy-maker. By assuming the countries analysed hold optimal (from the point of

view of the policy maker and the model) international liquidity, we are able to estimate

“how much the crisis is feared”, or the total expected cost the currency crisis (including

the reputation cost), as viewed by the policymaker.

Section 5.5 Model calibration

The sample of the countries used for the empirical application of the model included a

panel of non-industrial economies in the 1990-2002. The exclusion of the developed

- 174 -

countries was dictated by the experience of the EMS crisis, in which the dominant li-

quidity variable was likely different than in the case of most developing or emerging

economies (reserves/M2 ratio rather than reserve/short-term external debt). Also, the

institutional arrangements of the EMU and cooperation between central banks of other

developed countries make the foreign exchange reserve stock a non-meaningful indica-

tor of assets available at a short notice. Data concerns on one hand, and lack of access to

the world bond markets led to exclusion of the least developed countries. For the final

estimation only the countries for which foreign currency bond prices were available

were used. See the Appendix 4 for the full country list used.

Section 5.5.1 Data

The macro data for the empirical section comes mostly from the IMF IFS CD-ROM.

The variables used were:

Crisis, crisis dummy. Two main classes of this variable have been tried (see Section 3.3

“What is a currency crisis?” above for references). The first was based on an exchange

rate depreciation threshold. In the benchmark case, Crisis equalled one if two conditions

were met. First, local currency had to depreciate at least 25% QoQ against the US$ in

one of the quarters of the year. Secondly, the depreciation had to be at least 10 percent-

age points larger than the average depreciation in the preceding four quarters. This con-

dition is necessary to filter out hyperinflation cases.

Second group of crisis definitions is based on EMP, exchange market pressure index,

defined as a weighted average of quarterly reserve loss (scaled by money+quasi

money), and exchange rate depreciation. In the base case, the weights were chosen to

equalise global variance of the two components (as in as in Eichengreen and Rose, 1997

- 175 -

and numerous other studies). Other specifications with equal weights given to reserve

losses and exchange rate movements were also tried. Crisis indicator was 1 when EMP

exceeded the country-specific mean by a threshold value (1.75% country-specific stan-

dard deviations in the base specification).

REER, a measure of exchange rate overvaluation. In the base specification REERt is as a

percentage deviation from a trend calculated using annual data until t-1. Restricting the

trend estimation period to the years preceding the period in question prevents spurious

importance of the real exchange rate overvaluation as a predictor of a crisis. After all,

crises do result in real exchange rate depreciation (as shown in the estimation of equa-

tion (5.2), shown in Figure 72). If the depreciated local currency persists long enough,

the REER ahead of the crisis would have to be higher than trend by construction. How-

ever, if the crisis is just a violent mean of bringing the exchange rate back to the funda-

mental value, there is no particular reason to restrict the estimation to the period ahead

of the potential crisis. Thus, an alternative specification included the whole 1980-2003

period (shorter for if data was not available) in trend real exchange rate estimation.

Positive value of REER means real exchange rate overvaluation.

CA, is the current account balance, as a percentage of GDP. It is a more direct measure

of external imbalance than the REER indicator above. Higher current account surplus

should reduce the risk of a crisis, while higher real exchange rate overvaluation should

increase the risk.

LLBIS, a measure of international liquidity, calculated as a ratio of foreign bank debt

maturing within one year (taken from BIS/OECD/WB/IMF database) to foreign ex-

change reserves. Alternative versions of the variable include M3/reserves (defined as

- 176 -

money+quasimoney, rebased to US$ at the year-end exchange rate). All liquidity meas-

ures are expected to reduce the probability of a crisis.

G, is budget balance as a percentage of GDP. Higher surplus is expected to result in

lower crisis risk.

Elections, is a dummy variable which is 1 when the country faces elections in a particu-

lar year. The data comes mostly from ElectionGuide.org and Psephos Adam Carr's

Election Archive.

GDP is real YoY GDP growth (in percent). The working assumption is that higher GDP

growth reduces the risk of a crisis by giving more political power to the policymakers,

helping to tackle fiscal problems or outright speculative attack.

SPREAD, benchmark bond spread over US treasury of the same maturity. This variable

was taken from ING Financial Markets database. For each country, a government’s, or

semi-government’s (like Korean Development Bank’s) bond with a longest maturity

was chosen. Year-end spread to the US zero-coupon yield curve was used.

Section 5.5.2 The results

The first step is to estimate the impact of international liquidity, budget deficit, and

other, control variables on the probability of a currency crisis. In the base specification,

the model uses FXCrisis (25% quarterly depreciation as a crisis definition).

- 177 -

Figure 67 Probability of a crisis as a function of key variables only

Logit estimates Number of obs = 366

LR chi2(4) = 13.11

Prob > chi2 = 0.0107

Log likelihood = -97.221245 Pseudo R2 = 0.0632

------------------------------------------------------------------------------

fxcrisis | Coef. Std. Err. z P>|z| [90% Conf. Interval]

-------------+----------------------------------------------------------------

llbis | -.0027063 .0016151 -1.68 0.094 -.0053629 -.0000498

reerlag | .0081712 .008348 0.98 0.328 -.0055601 .0219024

budgettogdp | -.0992664 .0490675 -2.02 0.043 -.1799754 -.0185575

catogdp | -.0255196 .0148287 -1.72 0.085 -.0499106 -.0011285

_cons | -2.171212 .3928533 -5.53 0.000 -2.817398 -1.525026

------------------------------------------------------------------------------

Marginal effects after logit

y = Pr(fxcrisis) (predict)

= .06603458

------------------------------------------------------------------------------

variable | dy/dx Std. Err. z P>|z| [ 90% C.I. ] X

---------+--------------------------------------------------------------------

llbis | -.0001669 .00009 -1.81 0.070 -.000318 -.000015 219.383

reerlag | .0005039 .0005 1.01 0.314 -.00032 .001328 -14.7304

budget~p | -.0061222 .00301 -2.03 0.042 -.011075 -.00117 -1.86167

catogdp | -.0015739 .00091 -1.73 0.084 -.00307 -.000077 -2.00767

------------------------------------------------------------------------------

Source: Author

Figure 68 Crisis probability as a function of all main variables

Logit estimates Number of obs = 328

LR chi2(7) = 20.63

Prob > chi2 = 0.0044

Log likelihood = -80.534655 Pseudo R2 = 0.1135

------------------------------------------------------------------------------

fxcrisis | Coef. Std. Err. z P>|z| [90% Conf. Interval]

-------------+----------------------------------------------------------------

llbis | -.0025036 .0018589 -1.35 0.178 -.0055613 .0005541

reerlag | .0083855 .009764 0.86 0.390 -.0076748 .0244458

budgettogdp | -.0787541 .0574131 -1.37 0.170 -.1731902 .0156821

catogdp | -.027093 .0152823 -1.77 0.076 -.0522301 -.0019558

gdpgrowth | -.0490748 .0516475 -0.95 0.342 -.1340274 .0358777

elections | -.3129361 .6040235 -0.52 0.604 -1.306466 .6805942

m3yoy | .0018843 .0009914 1.90 0.057 .0002535 .003515

_cons | -2.090355 .5260962 -3.97 0.000 -2.955706 -1.225004

------------------------------------------------------------------------------

Marginal effects after logit

y = Pr(fxcrisis) (predict)

= .05988693

------------------------------------------------------------------------------

variable | dy/dx Std. Err. z P>|z| [ 90% C.I. ] X

---------+--------------------------------------------------------------------

llbis | -.000141 .0001 -1.44 0.151 -.000302 .00002 221.021

reerlag | .0004721 .00053 0.89 0.375 -.000404 .001348 -15.9713

budget~p | -.0044339 .00324 -1.37 0.172 -.00977 .000902 -1.92409

catogdp | -.0015253 .00086 -1.78 0.075 -.002933 -.000118 -2.05457

gdpgro~h | -.0027629 .00289 -0.96 0.339 -.007514 .001988 4.15183

electi~s*| -.016223 .0286 -0.57 0.571 -.063274 .030828 .192073

m3yoy | .0001061 .00006 1.75 0.080 6.4e-06 .000206 42.8585

------------------------------------------------------------------------------

(*) dy/dx is for discrete change of dummy variable from 0 to 1

Source: Author

- 178 -

Figure 69 Final benchmark model of crisis probability

Logit estimates Number of obs = 346

LR chi2(5) = 19.33

Prob > chi2 = 0.0017

Log likelihood = -89.980965 Pseudo R2 = 0.0970

------------------------------------------------------------------------------

fxcrisis | Coef. Std. Err. z P>|z| [90% Conf. Interval]

-------------+----------------------------------------------------------------

llbis | -.002734 .0017002 -1.61 0.108 -.0055305 .0000626

reerlag | .0045443 .0070016 0.65 0.516 -.0069723 .0160609

budgettogdp | -.0909478 .0507733 -1.79 0.073 -.1744624 -.0074332

catogdp | -.0246133 .014945 -1.65 0.100 -.0491956 -.000031

m3yoy | .0018947 .0009874 1.92 0.055 .0002705 .0035189

_cons | -2.267834 .4159016 -5.45 0.000 -2.951931 -1.583736

------------------------------------------------------------------------------

Marginal effects after logit

y = Pr(fxcrisis) (predict)

= .06640829

------------------------------------------------------------------------------

variable | dy/dx Std. Err. z P>|z| [ 90% C.I. ] X

---------+--------------------------------------------------------------------

llbis | -.0001695 .0001 -1.76 0.079 -.000328 -.000011 222.707

reerlag | .0002817 .00043 0.65 0.513 -.000427 .00099 -15.1208

budget~p | -.0056386 .00311 -1.81 0.070 -.010752 -.000525 -1.88757

catogdp | -.001526 .00093 -1.65 0.100 -.003052 -1.5e-07 -2.10491

m3yoy | .0001175 .00007 1.79 0.073 9.7e-06 .000225 41.5509

------------------------------------------------------------------------------

-------- True --------

Classified | D ~D | Total

-----------+--------------------------+-----------

+ | 3 3 | 6

- | 26 314 | 340

-----------+--------------------------+-----------

Total | 29 317 | 346

Classified + if predicted Pr(D) >= .3

True D defined as fxcrisis != 0

--------------------------------------------------

Sensitivity Pr( +| D) 10.34%

Specificity Pr( -|~D) 99.05%

Positive predictive value Pr( D| +) 50.00%

Negative predictive value Pr(~D| -) 92.35%

--------------------------------------------------

False + rate for true ~D Pr( +|~D) 0.95%

False - rate for true D Pr( -| D) 89.66%

False + rate for classified + Pr(~D| +) 50.00%

False - rate for classified - Pr( D| -) 7.65%

--------------------------------------------------

Correctly classified 91.62%

--------------------------------------------------

Source: Author

The results above show three models. The simplest version includes only the variables

mentioned in the theoretical model (with the addition of the current account deficit). Us-

ing (lagged values of) REER, LLBIS, BUDGET deficit, CA surplus, the sample size is

the biggest: 366 observations, with 29 crisis occurrences. Current account, budget defi-

cit, international liquidity are all significant at 10%, all with proper signs (higher budget

and current account surplus, and higher international reserves relative to short-term debt

all reduce the probability of the crisis). Marginal effects (reported below the estimation

- 179 -

results) show that an increase of reserves by 1 percent of short-term debt at the sample

mean of 219% reduces the probability of the crisis by 0.017%. 1 percent of GDP lower

budget deficit reduces the crisis risk by 0.61% and 1% of GDP lower current account

deficit cuts the risk by 0.16%.

Adding control variables, lagged GDP and M3 growth and non-lagged elections dummy

does not change the parameters’ values much, but it does reduce significance of the key

variables. Removing GDP growth and election dummy (the former had the right sign,

but both were totally insignificant), yields the final version of the baseline crisis risk

equation reported in Figure 69.

The marginal effects are similar to those reported above, with budget having slightly

lower impact (0.56%), and LLBIS losing some significance. Money supply growth

faster by 1 percent increases the crisis risk by 0.011%. It is worth noting, that this effect

stands despite the crisis definition excluding the cases of long-lasting hyperinflation.

The results are not very strong (neither of the variables is significant at 5% level), and

the scale of effects is not economically dramatic at the sample mean. Money supply

growth and budget deficit are the most significant variables influencing crisis risk in the

model. The model suggests that a country with foreign exchange reserves at 30% of the

short term debt, and 6% budget and current account deficits has over 16% chance of ex-

periencing a currency crisis in any given year. However, the results, especially concern-

ing the liquidity indicator variables, are quite robust in terms of parameter value, which

is important for this calibration exercise58.

58 The liquidity impact on the crisis probability here is smaller by a factor of four, com-pared to the results reported in Szczurek (2003). The difference between the two comes

- 180 -

Neither of the driving variables above (money supply growth, budget and current ac-

count deficits) is significantly influenced (unconditionally on the crisis occurrence) by

previous period’s level of liquidity LLBIS. Figure 67 is a sample test for this. Current

account in t is autoregressive, tends to show a smaller deficit when budget is in surplus,

and, unsurprisingly a bigger deficit when GDP growth is higher. A currency crisis sig-

nificantly lowers the current account deficit. The international liquidity, however, is to-

tally insignificant in influencing the current account (as is the case with REER or M2

growth, not reported). This ensures the theoretical model does not underestimate the

benefits of the international liquidity by ignoring potential pass-through from liquidity

to other driving variables.

down to sample selection. Szczurek (2003) evaluates the crisis probability during the crisis bouts (1994, 1997 and 1998). The sample here is not restricted to the global or regional contagious emerging markets episodes.

Varying the crisis depreciation threshold from 25 to 20% reduce the significance of the current account, while reducing the z statistics of budget and liquidity measures. The parameter values remain robust. Stress testing of the model also involved using a differ-ent crisis variable, which would take into account also the reserve changes. The results, showed similar (and more significant) size of liquidity effect on crisis probability, twice as high, but insignificant effect of the budget, and current account giving way to REER as a more important crisis predictor. Reserves/M3 are generally a less reliable measure of international liquidity than the reserves/BIS debt.

- 181 -

Figure 70 OLS results of the impact of liquidity, lagged fundamental variables and

crisis dummy on the current account (full sample)

Source | SS df MS Number of obs = 292

-------------+------------------------------ F( 8, 283) = 34.83

Model | 65379.0414 8 8172.38017 Prob > F = 0.0000

Residual | 66399.6141 283 234.627612 R-squared = 0.4961

-------------+------------------------------ Adj R-squared = 0.4819

Total | 131778.655 291 452.847613 Root MSE = 15.318

------------------------------------------------------------------------------

dca | Coef. Std. Err. t P>|t| [95% Conf. Interval]

-------------+----------------------------------------------------------------

empcrisis | 8.584769 2.504711 3.43 0.001 3.654541 13.515

reerlag | .0017893 .0234412 0.08 0.939 -.0443518 .0479305

m3 | -.0012467 .0044009 -0.28 0.777 -.0099093 .0074159

llbis | -.0018082 .0044923 -0.40 0.688 -.0106507 .0070344

budget | .3965856 .2369456 1.67 0.095 -.0698138 .8629851

ca | -1.056518 .0645418 -16.37 0.000 -1.183561 -.9294752

gdp | -.4788246 .1979822 -2.42 0.016 -.8685291 -.0891201

elections | -.9059621 2.517093 -0.36 0.719 -5.860563 4.048639

_cons | -.0934417 1.864917 -0.05 0.960 -3.764311 3.577428

------------------------------------------------------------------------------

Source: Author

Crisis dummies (defined both as major depreciation, and significant exchange market

pressure) significantly influence budget deficit, the current account, real exchange over-

valuation, and GDP growth, as expected. This seems to allow to use the general specifi-

cation of equation (5.2) (REER in response to crisis), extended to include other vari-

ables than just real exchange rate measure.

The OLS estimates in the sample restricted to the crisis occurrences are different to

those estimated for the whole sample. In particular, current account deficits increases

(CA goes down) with higher GDP growth and tend to revert to zero (significantly nega-

tive sign of the previous period current account parameter); but these variables become

insignificant and utterly dominated by the crisis occurrence (which reduces the current

account deficit by 4.5% of GDP). Of all the variables tried, the crisis dummy (constant

in the reduced sample) was the only one significant influencing the current account

change.

- 182 -

Real exchange rate overvaluation falls by one half, and the constant parameter points to

the additional 29 percentage point reduction of the REER variable in the crisis year. In-

terestingly, the current account deficit parameter has a wrong sign (pointing to faster

depreciation in a crisis for countries with smaller current account deficits) and is insig-

nificant.

Budget deficit is not significantly affected by the crisis (regardless of the sample size).

Unsurprisingly, elections in the year of the crisis worsen the fiscal position by an aver-

age of 7% of GDP. The result, while significant statistically, must be taken with caution,

as there were only three elections in the crisis sample.

On average, GDP growth falls in the year of the crisis, by about 7% in the sample be-

low. The following chapter deals with the output costs of the currency crises in more

detail. In particular, the output growth loss in the crisis year reported here is heavily af-

fected by pre-crisis growth trends. Taking into account long-term trends yields a much

lower growth impact of crises.

Figure 71 OLS results of the impact of liquidity, lagged fundamental variables on

the current account (crisis sample)

Source | SS df MS Number of obs = 22

-------------+------------------------------ F( 3, 18) = 0.78

Model | 24.5691127 3 8.18970423 Prob > F = 0.5200

Residual | 188.789064 18 10.4882813 R-squared = 0.1152

-------------+------------------------------ Adj R-squared = -0.0323

Total | 213.358177 21 10.1599132 Root MSE = 3.2386

------------------------------------------------------------------------------

dca | Coef. Std. Err. t P>|t| [95% Conf. Interval]

-------------+----------------------------------------------------------------

m3 | -.0012952 .0011542 -1.12 0.277 -.0037202 .0011297

llbis | -.0078299 .0092843 -0.84 0.410 -.0273356 .0116757

elections | -1.7809 2.024014 -0.88 0.391 -6.033196 2.471396

_cons | 4.458154 1.551277 2.87 0.010 1.199041 7.717266

------------------------------------------------------------------------------

Source: Author

- 183 -

Figure 72 OLS results of the impact of liquidity, lagged fundamental variables on

the real exchange rate (crisis sample)

Source | SS df MS Number of obs = 22

-------------+------------------------------ F( 5, 16) = 4.64

Model | 6286.58182 5 1257.31636 Prob > F = 0.0083

Residual | 4337.10885 16 271.069303 R-squared = 0.5918

-------------+------------------------------ Adj R-squared = 0.4642

Total | 10623.6907 21 505.890032 Root MSE = 16.464

------------------------------------------------------------------------------

dreer | Coef. Std. Err. t P>|t| [95% Conf. Interval]

-------------+----------------------------------------------------------------

reerlag | -.5310663 .2247821 -2.36 0.031 -1.007583 -.0545495

m3 | .0042323 .0061753 0.69 0.503 -.0088587 .0173233

llbis | .0625423 .0561286 1.11 0.282 -.056445 .1815295

budget | -.2260036 .7740251 -0.29 0.774 -1.866864 1.414856

elections | 29.14448 10.34971 2.82 0.012 7.204073 51.08489

_cons | -29.24335 9.112382 -3.21 0.005 -48.56074 -9.925965

------------------------------------------------------------------------------

Source: Author

Figure 73 OLS results of the impact of liquidity, lagged fundamental variables on

budget deficit (crisis sample)

Source | SS df MS Number of obs = 22

-------------+------------------------------ F( 5, 16) = 2.63

Model | 365.03143 5 73.006286 Prob > F = 0.0644

Residual | 444.919467 16 27.8074667 R-squared = 0.4507

-------------+------------------------------ Adj R-squared = 0.2790

Total | 809.950897 21 38.5690903 Root MSE = 5.2733

------------------------------------------------------------------------------

dbudget | Coef. Std. Err. t P>|t| [95% Conf. Interval]

-------------+----------------------------------------------------------------

reerlag | -.0912139 .071995 -1.27 0.223 -.2438365 .0614086

m3 | .0002624 .0019779 0.13 0.896 -.0039304 .0044553

llbis | -.0163527 .0179773 -0.91 0.377 -.0544629 .0217575

budget | -.6599344 .2479109 -2.66 0.017 -1.185482 -.1343868

elections | -7.851061 3.314888 -2.37 0.031 -14.87831 -.8238128

_cons | .5140572 2.918586 0.18 0.862 -5.673068 6.701183

------------------------------------------------------------------------------

Source: Author

Figure 74 OLS results of the impact of liquidity, lagged fundamental variables on

GDP growth (crisis sample)

Source | SS df MS Number of obs = 22

-------------+------------------------------ F( 5, 16) = 0.67

Model | 176.683746 5 35.3367491 Prob > F = 0.6508

Residual | 841.809415 16 52.6130884 R-squared = 0.1735

-------------+------------------------------ Adj R-squared = -0.0848

Total | 1018.49316 21 48.4996743 Root MSE = 7.2535

------------------------------------------------------------------------------

dgdp | Coef. Std. Err. t P>|t| [95% Conf. Interval]

-------------+----------------------------------------------------------------

reerlag | -.0753639 .0990304 -0.76 0.458 -.2852989 .1345712

m3 | .0021651 .0027206 0.80 0.438 -.0036023 .0079325

llbis | .0210043 .0247281 0.85 0.408 -.0314169 .0734256

budget | -.208041 .3410058 -0.61 0.550 -.9309411 .514859

elections | -2.028263 4.559687 -0.44 0.662 -11.69437 7.637841

_cons | -7.61359 4.014566 -1.90 0.076 -16.12409 .8969103

------------------------------------------------------------------------------

Source: Author

In light of the results above, the theoretical model should be revised to include either

current account alone, or a combination of current account and real exchange as the ad-

ditional variables both driving the crisis probability, and being influenced by it.

- 184 -

The final step is evaluating how sovereign spreads depend on the fundamentals and in-

ternational liquidity. For this purpose MODEL variable was created from the fitted val-

ues of the crisis probability equation. The results do not confirm the prior hypothesis,

showing that the direct impact of international liquidity on international bond spreads is

rather insignificant. Foreign public debt as a percentage of GDP is relevant though,

which alters the potential direction of the borrowing to increase liquidity on costs. 10%

of GDP higher foreign debt increases the costs of additional borrowing by 40 basis

points. The dominating factor by far, however, is the incident of a currency crisis – not

surprisingly, international bond spreads go up by over 400bps in the year of the crisis.

Other variables tried included JP Morgan’s Emerging Market Bond Index+ as a meas-

ure of world borrowing conditions. The index proved to be insignificant in the annual,

panel formulation, even though much of the intra-year variations of the individual coun-

tries’ spreads can be explained to a large extent by the emerging market investors over-

all sentiment (not reported). Including the fixed effects for the annual data restricted the

“within” samples too severely. Measures of international liquidity, and the composite

measure of the crisis probability (model) had right signs, but proved insignificant in ex-

plaining the borrowing costs.

Figure 75 International bond spreads as a function of liquidity, currency crises and

foreign debt

Source | SS df MS Number of obs = 80

-------------+------------------------------ F( 3, 76) = 6.61

Model | 3513981.28 3 1171327.09 Prob > F = 0.0005

Residual | 13464594.5 76 177165.717 R-squared = 0.2070

-------------+------------------------------ Adj R-squared = 0.1757

Total | 16978575.8 79 214918.68 Root MSE = 420.91

------------------------------------------------------------------------------

laggedspread | Coef. Std. Err. t P>|t| [95% Conf. Interval]

-------------+----------------------------------------------------------------

llbis | -.1473485 .2761847 -0.53 0.595 -.6974181 .402721

laggedcrisis | 435.042 138.295 3.15 0.002 159.6036 710.4804

foreigndeb~p | 4.11251 1.895304 2.17 0.033 .3376851 7.887334

_cons | 252.1734 94.4107 2.67 0.009 64.13823 440.2087

------------------------------------------------------------------------------

Source: Author

- 185 -

The results thus require yet another amendment to the theoretical model. Increasing li-

quidity by means of additional, long-term borrowing is costly not only because of the

additional debt service costs, but also because of widening spreads. Paying back debt

with reserves, on the other hand, while reducing liquidity, tends to cut the costs of new

borrowing.

Two additional assumptions should be made for the final implementation of the model:

first, the policy maker’s discount rate r was set to 10% (the results were not very re-

sponsive to the changes in this variable, see below), and the “reasonable” cost of the

currency crisis. The latter was much more difficult to choose, as indicated in the Section

5.1 “Crisis and its cost” section above. We avoided the problem by presenting the whole

curve of optimal liquidity holding, dependent on the estimation of the prospective crisis

cost.

Section 5.6 Model application: best value for money liquidity

Before answering this question it is worth showing how much is at stake. Figure 76 pre-

sents an estimate of alternative cost of liquidity maintenance as percent of GDP. It is

calculated as the integral of the Equation (5.7) between zero and actual value of interna-

tional liquidity held. The figure is mostly correlated with the sovereign spreads, and to a

much lesser degree to the state of the fundamentals (responsiveness of the crisis risk to

liquidity changes). Venezuela, Bulgaria and Philippines pay the most for their reserve

stock, between 0.8 and 0.95% of GDP. Croatia pays the least, about 0.1% of GDP annu-

ally.

- 186 -

Figure 76 Annual costs of keeping foreign exchange reserves

0.2 0.4 0.6 0.8%of GDP

ArgentinaBrazil

BulgariaChile

ChinaColombia

CroatiaDominicana

HungaryMexico

PhilippinesPoland

SingaporeSlovak-Republic

ThailandUruguay

VenezuelaMedian

Source: Author

What is the right level of international liquidity to hold? The answer depends very much

on the cost of the crisis the reserves are to protect from – on how much the policymak-

ers risk. While the GDP cost of the crisis may be similar in all exchange rate regimes

(albeit the results of the following chapter deny even that) – capital outflow, real depre-

ciation costs, etc. are also dangerous in a float (yet one could argue that some sort of FX

risk illusion keeps the real economy’s exposure to the foreign exchange risk larger in

fixed exchange rate countries), the reputation cost should be different. In the extreme

float case, the central bank ignores the foreign exchange fluctuations, however rapid and

large they are; the reputation cost should thus be set to zero. Another complication

arises due to the fact that the government’s loss function is something completely dif-

ferent to the “economy’s loss function”, the former being influenced by the political cy-

cle.

The results of the next section do support expectations that currency regime choice in-

fluences policymakers’ aversion to the currency crises.

The model’s answers to the question what liquidity to hold is summarised in Figure 77.

Horizontal scale represents optimal liquidity (as reserves/short-term debt ratio) corre-

- 187 -

sponding to the assumed cost of the currency crisis on the vertical axis (as a percentage

of GDP). The figure includes charts for the sample analysed (the choice of the sample

was dictated by availability of foreign currency denominated bond spread data in the

snapshot year, which allowed for the calculation of reserve costs). The last chart is the

“median country” which is characterised by median current account, short term debt,

GDP, foreign exchange reserves, cost of borrowing, etc. The vertical line represents the

actual level of foreign exchange reserves relative to BIS-reported short term debt.

The calculation of the curves requires numerical integration of the cost and benefit

curves (see Figure 66) and finding the global minimum of the loss function (5.8) for a

range of crisis cost parameter (from 0 to 80% of GDP). For low values of crisis cost, the

optimum level of liquidity is zero (the negative results can hardly be implemented, as

negative value of liquidity happens only in the most extraordinary circumstances). Total

costs of keeping reserves are always higher than the benefits they bring in such case. If

borrowing costs are high enough, there is thus a discontinuity in the curve: the global

loss function minimum falls to zero for a range of small crisis cost values.

The results allow to judge the “Guidotti rule59” of keeping foreign exchange reserves

stock equal to the short-term foreign debt. First, for a median country the recommenda-

tion implies about 7% of GDP total crisis cost. This is in line with several crisis cost

studies (see references in the following chapter), and also in line with average GDP

growth loss in the year of the crisis estimated in Figure 74.

- 188 -

Figure 77 Optimal liquidity holding versus cost of the crisis, sample average.

16 18 20 22 24 26 28 30-200-150-100-50

050

100150

Uruguay

10 15 20 25 30 35 40-200

-100

0

100

200

300

Venezuela

6 8 10 12 14 16 18 20

0

100

200

300

400

500

Median

50 60 70 80 90 100

-100

-50

0

50

100

150Singapore

6 8 10 12 14 16 18 20-100

0

100

200

300

400

500Slovak-Republic

6 8 10 12 14 16 18 20

200

300

400

500

600

700Thailand

0 5 10 15 20-200

0

200

400

600

800Mexico

10 15 20 25 30

-200

-100

0

100

200

Philippines

6 8 10 12 14 16 18 20

200

300

400

500

600

700Poland

0 5 10 15 20-250

0

250500

750

1000

1250Croatia

10 12 14 16 18 20

-250-200-150-100-50

050

Dominicana

0 5 10 15 20

0

200

400

600

800

Hungary

6 8 10 12 14 16 18 20

-200

-100

0

100200

300

400Chile

0 5 10 15 20400

600

800

1000

1200

China

6 8 10 12 14 16 18 20

200

300

400

500

600

700Colombia

10 15 20 25 30

-300

-200

-100

0

100

200

Argentina

0 5 10 15 20-600

-400

-200

0

200

Brazil

10 15 20 25 300

100200300400500600700

Bulgaria

Note: % of GDP crisis cost on horizontal axis, international liquidity as % of short-term debt on vertical axis

Source: Author

59 Named after Pablo Guidotti, ex-Argentine deputy finance minister, who is credited with it. The rule was later mentioned by Alan Greenspan, who advocated weighing re-

- 189 -

The 100% short-term debt reserves coverage rule, however, is too general, as both bor-

rowing conditions, and the state of the fundamentals varies considerably across the

countries in the sample (and, presumably, so does the expected total cost of a crisis).

The charts above show that the costs of keeping 100% liquidity can suffice to cover

from less than 1% potential crisis costs (Croatia) to over 80% of GDP (Singapore).

Section 5.7 Model application: How much policymakers fear the crisis?

The final empirical application of the model involves finding the cost of the crisis as

seen (or expected) by the policymaker. Assuming that the amount of international li-

quidity held by the central banks is rational (in the model sense), we can find out what is

the expected crisis cost by the policymakers. The process involves finding out the value

of -χ (implicit estimation of crisis cost by the policymaker) for which marginal cost

curve of the liquidity crosses marginal benefit curve of the liquidity at the level of actu-

ally held international reserves. The answer is given in the horizontal scale at the point

of intersection of the two lines in Figure 77.

Figure 78 Expected crisis cost to the policy maker, as of 2001

Country Implied crisis cost Country Implied crisis cost

Argentina 21% Mexico 4% Brazil 11% Philippines 25% Bulgaria 29% Poland 8% Chile 11% Singapore 90% China 3% Slovak Republic 11% Colombia 6% Thailand 7% Croatia 1.1% Uruguay 26% Dominican Republic 19% Venezuela 31%

Hungary 4% Median country 9% Note: Countries in Bold have fixed exchange rates, countries underlined have managed exchange rates

Source: Author

serves and short term debt by their volatility.

- 190 -

Figure 78 shows the summary of the results, cost of the currency crises expected by the

governments and central banks of the countries listed, as of end-2001. Figure 79 shows

graphs of the 4Q01 liquidity’s marginal cost and benefits curves of the countries in the

sample, as well as implicit expected crisis cost - χ (as percent of GDP).

Figure 79 Marginal liquidity cost and benefit curves in emerging markets

100 200300400 500600 700LLBIS

0.002

0.004

0.006

0.008

%GDP

UruguayActualêDesiredliquidity: 76.9ê82.9472

crisis cost at 26 %of GDP

100200300 400500 600700LLBIS

0.0010.0020.0030.0040.0050.0060.007

%GDP

VenezuelaActualêDesiredliquidity: 277.4ê281.558

crisis cost at 31 %of GDP

100 200300 400500 600700LLBIS

0.0005

0.001

0.0015

0.002

0.0025

%GDP

MedianActualê Desiredliquidity: 198.322ê197.676

crisis cost at 9 %of GDP

100 200300400 500600 700LLBIS

0.0010.0020.0030.0040.0050.0060.007

%GDP

Singapore

ActualêDesiredliquidity: 123.6ê119.662crisis cost at 90 %of GDP

100200 300400 500600 700LLBIS

0.00050.001

0.00150.002

0.00250.003

0.0035%GDP

Slovak-Republic

ActualêDesiredliquidity: 284.3ê276.341crisis cost at 11 %of GDP

100200 300400 500600 700LLBIS

0.000250.0005

0.000750.001

0.001250.0015

%GDP

Thailand

ActualêDesiredliquidity: 310.8ê305.874crisis cost at 7 %of GDP

100 200300 400500 600700LLBIS

0.0002

0.0004

0.0006

0.0008

0.001

%GDP

MexicoActualêDesiredliquidity: 159.2ê139.205

crisis cost at 4 %of GDP

100200300 400500 600700LLBIS

0.0010.0020.0030.0040.0050.006

%GDP

PhilippinesActualêDesiredliquidity: 198.3ê197.699

crisis cost at 25 %of GDP

100 200300 400500 600700LLBIS

0.0005

0.001

0.0015

0.002

%GDP

PolandActualêDesiredliquidity: 354.8ê350.189

crisis cost at 8 %of GDP

100200 300400 500600 700LLBIS

0.000050.0001

0.000150.0002

0.000250.0003

0.00035

%GDP

CroatiaActualêDesiredliquidity: 171.8ê162.194

crisis cost at 1.1 %of GDP

100200300 400500 600700LLBIS

0.001

0.002

0.003

0.004

%GDP

DominicanaActualêDesiredliquidity: 54.2ê48.5442

crisis cost at 19 %of GDP

100 200300 400500 600700LLBIS

0.00020.00040.00060.00080.001

0.0012

%GDP

HungaryActualêDesiredliquidity: 210.6ê215.59

crisis cost at 4 %of GDP

100 200300 400500 600700LLBIS

0.0005

0.001

0.0015

0.002

0.0025

%GDP

Chile

ActualêDesiredliquidity: 155.1ê143.32crisis cost at 11 %of GDP

100200 300400 500600 700LLBIS

0.0002

0.0004

0.0006

0.0008

%GDP

China

ActualêDesiredliquidity: 557.3ê579.793crisis cost at 3 %of GDP

100200300400500600700LLBIS

0.00050.00075

0.0010.001250.0015

0.001750.002

0.00225%GDP

Colombia

ActualêDesiredliquidity: 212.2ê222.511crisis cost at 6 %of GDP

100 200300400 500600 700LLBIS

0.0010.0020.003

0.0040.0050.006

%GDP

ArgentinaActualêDesiredliquidity: 65.ê68.1016

crisis cost at 21 %of GDP

100200 300400 500600 700LLBIS

0.00050.001

0.00150.002

0.00250.003

0.0035

%GDP

BrazilActualêDesired liquidity: 96.8ê101.221

crisis cost at 11 %of GDP

100200 300400 500600 700LLBIS

0.002

0.004

0.006

%GDP

BulgariaActualêDesiredliquidity: 740.6ê746.043

crisis cost at 29 %of GDP

Source: Author

- 191 -

The results show a wide disparity of implied currency crisis cost to the policy makers.

The figures range from 90% for Singapore to 1.1% for Croatia. As should be expected,

currency board and fixed exchange rate countries do exhibit higher than average aver-

sion to currency crises: Argentina (21%), Bulgaria (29%) or Venezuela (31%) all had

fixed exchange rates. China is the exception here with its 3% implied crisis cost. Three

CE countries listed (Poland, Hungary and Slovakia) show close to average aversion to

crises (4,8 and 11% of GDP respectively). Singapore, with its managed float is by far

the most crisis-averse country in the sample (90%).

The power of the result confirming peggers’ aversion to the crises is lessened by the

dominance of financing costs in the implied crisis costs determination. Figure 81 shows

very high correlation of implied crisis costs and the cost of sovereign borrowing. Singa-

pore really stands out confirming its aversion to crises.

Singapore also stands out in another aspect – the total marginal benefit that can be

bought by keeping higher reserves is the lowest in the group (because Singapore has

both current account and budget surplus). The cumulative gains from reserves for Sin-

gapore (integral of the lowest curve in Figure 80) are about one fourth of the average

country in the sample, and one fifth of Colombia, which is represented by the uppermost

curve in the chart below. Assuming 10% of GDP expected crisis cost, reserves being

seven times higher than short term debt bring almost 1.4% of GDP annually.

- 192 -

Figure 80 Marginal benefit from international liquidity for sample countries

100 200 300 400 500 600 700LLBIS

0.00005

0.0001

0.00015

0.0002

0.00025

0.0003

0.00035

%GDP

Colombia

Singapore

Source: Autor

Still, the results below could suggest some other mechanism at work here. High correla-

tion of implied crisis costs and sovereign spreads could indicate countries targeting the

level of reserves or liquidity, rather than crisis probability, as assumed in the model.

Figure 81 Implied crisis costs and sovereign spreads

y = 0.0002x + 0.0967

R2 = 0.0795

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

0.0 200.0 400.0 600.0 800.0 1000.0 1200.0

Reserves/BIS ST debt (%)

Imp

lied

cri

sis

co

st

Singapore

Bulgaria

Source: Author

- 193 -

If the central banks do not hold the reserves for the sole purpose of crisis protection, the

governments/central banks of the countries are not rational in the model’s sense. Model-

rationality may be far from the rationality though. Four interpretations (model short-

comings) immediately come to mind.

One is that the alternative cost of reserves is lower than suggested by the model. This

could happen if the policymakers had no control over the level of liquidity (no sover-

eign debt to pay back using reserves, or side-effect of countries’ attempts to combat

capital inflow - Singapore is a good example here again). In such case, the alternative

cost of the keeping reserves would be close to zero and the implied crisis aversion

would be biased upwards.

Second possibility is that international liquidity is actually much higher than suggested

by the data, e.g. thanks to international arrangements, stand-by agreements, etc.

The third possibility is that the policymakers’ discount rate is much higher than as-

sumed in the calculations. The second round effects included in the model, however do

not influence the cost of borrowing enough to explain the dependence of implied costs

on sovereign spreads. The impact of second round effects on expected crisis costs does

not exceed two percent of GDP.

Fourthly, the cost of holding official reserves is not always equivalent to the sovereign

spread. For example, Government of Singapore Investment Corporation has a mandate

to invest the country’s reserves in much higher-yielding (and more risky) bonds than the

US Treasuries. In such case, a country could actually earn on some of its official re-

serves, again, resulting in an upward bias in implied crisis cost.

- 194 -

Finally, and most importantly, crisis protection is not the only purpose of foreign ex-

change reserves and international liquidity. In particular, reserves are likely to be held

for operational purposes in the currency board countries, as modelled by Frenkel and

Jovanovic (1981).

Section 5.8 Conclusions

The chapter presents a model of optimal liquidity holding by the policy maker in the

spirit of Frenkel and Jovanovic’s (1981) inventory model of foreign exchange reserves,

in which optimal liquidity held depends on the fundamentals, international borrowing

costs, and the potential cost of the crisis to the policy maker.

The model presented in the paper appears to be a promising way to deal with costs and

benefits of international liquidity in the face of currency crises risk. The calibration of

the parameters (estimated over the sample of emerging market countries) confirmed in-

ternational liquidity (defined as a percentage of short-term BIS-reported debt) does in-

fluence crisis probability, as indicated in the majority of the leading-indicators litera-

ture. Other variables helpful in crisis prediction include budget deficit, money supply

growth and current account.

Estimation of the curve of reasonable holdings of the foreign exchange reserves, de-

pendent on expected crisis costs showed that the “Guidotti rule” of holding 100 percent

reserve coverage of short term debt is reasonable for a median country. It implies 7-8

percent of GDP crisis costs, which is on the upper end, but within the empirical esti-

mates range of post-crisis output loss (see Chapter 6). But the 100 percent rule gives

varying results for different countries, mostly due to borrowing cost differences. In par-

ticular, following the rule blindly would unlikely to be optimal for the countries with

- 195 -

easy access to world debt markets. Such countries could afford cheap protection by ex-

tending their debt duration by issuing long bonds for the sole purpose of liquidity man-

agement.

The model also allowed estimating the weight the governments/central banks attach to

the risk of a currency crisis. We found out that the policymakers of the countries ana-

lysed, behave, as if they predicted the prospective crisis would cost between 78% (Sin-

gapore) and 1.5% (Croatia) of the GDP. This result includes not only explicit budgetary

costs of the currency crisis, but also the reputation loss of the central bank, or political

losses of the government. To our knowledge it is the first estimation of this kind. The

range of the implied crisis cost for the analysed countries is extremely wide, and it while

it is related to the exchange rate arrangements (fixed exchange rate countries tend to

have higher implied crisis loss, in line with higher expected reputation loss of a large

currency depreciation), but it is also strongly related to the costs of external borrowing.

The extremely high Singapore result can be explained not only by high crisis aversion

of the authorities predicted by the model, but also by the macroeconomic and opera-

tional policies in the country.

The chapter leaves scope for further research. Main issues worth addressing include

enlarging the data sample (it was limited to the IMF IFS data in the paper, which re-

duced the sample to 24 in some equations), and combining the original Frenkel and

Jovanovic’s model’s specification (which takes into account reserve volatility) with the

one including the reserves as the crisis risk reduction tool.

- 196 -

Chapter 6 The output cost of currency crises

Section 6.1 Introduction

This chapter tries to evaluate the cost of recent currency crises. As indicated in the sec-

tion above, the notion of cost can include a wide range of issues, from output, through

political effects.

Fiscal and quasi fiscal costs can come from many different sources. One is higher debt

service cost related to higher local interest rates, increasing country risk premium, and

falling value of local currency. The actual long-term impact of crisis on debt service is

not totally obvious though, weakening of the nominal exchange rate accompanied by

equivalent jump in price level leaves real value of foreign debt unchanged, while wiping

out a portion of local-currency debt60. A currency crisis can (but does not have to) bring

lower tax intake due to output disruptions (if present). Finally, the crisis can force

higher spending as implicit and explicit government guarantees become due. The latter

issue includes banking sector bail-outs as well as corporate rescue operations.

Social consequences of currency crises could include higher unemployment and fall in

real wages (reported in most of the countries analysed by Błaszkiewicz and Paczyński,

2003, with the exception of Latin American economies), decrease in wealth, health stan-

60 See e.g. Froot and Rogoff (1991) for an explicit model taking this into account. In the sample of non-G7 countries analysed above, the crisis was related to the depreciation of the real exchange rate, so this argument would not necessarily apply, depending on the currency composition of debt. For example, debt to GDP rose more than quadrupled between 1997 and 2001 in Indonesia (Błaszkiewicz and Paczyński, 2003)

- 197 -

dards, education as a result of the above, or inflation-related wealth changes61. Argen-

tine placateiros movement of 2001-2004 show how crises can result in social unrest.

Many of the issues mentioned above occur only if output loss is associated with the cur-

rency crisis. The question of the GDP cost of currency crises is therefore of key impor-

tance. If the currency crises are violent, but still optimal way of removing imbalances in

the economy, there is little reason for the policy makers to worry about them (albeit

hedge fund managers would still have to care). Generalising such situation, however,

would be extreme – there are strong theoretical reasons why crises do bring unnecessary

costs62.

Section 6.2 Crises and output: the theory

Balance sheet approach to currency crises (see Jeanne and Zettelmeyer, 2002 for the

framework encompassing several models of this kind) provides several possible chan-

nels of transmission between exchange rate depreciation and output loss. One channel,

described in Chang and Velasco (2000), and Rodrik and Velasco (1999) stresses real

investment liquidation costs associated with sudden reversal of confidence and capital

account reversals. In a sense, output loss and the currency crisis occurs simultaneously

61 Cutler et al. (2000) show rise in mortality rates followed currency crises in Mexico in 1980-2000, McKenzie (2003) analyses household survey data on various social group’s income impact of currency crises; Oxfam (1999) describes the effect of the Asian crisis on education in the region

62 Which still makes it possible that there is no viable way to avoid crises. For example, if insurance were not available, full protection against bank runs would require one to one backing of the deposits with reserves. This would probably be suboptimal for the economy.

- 198 -

in the crisis of this kind; both are influenced by the foreign creditors’ run on domestic

institutions. For this channel to work, a maturity mismatch is necessary.

Second channel (see e.g. Krugman, 1999) does not require maturity mismatch, but is

based on currency mismatch. It stresses the impact of exchange rate on corporate net

worth, and, consequently, the ability of firms to borrow and invest. Depreciating real

exchange rate increases the value of foreign-currency liabilities relative to the assets (or

stream of future income, denominated in the local currency). Even if affected firms do

not collapse, their investment potential falls together with their net worth, and so does

the subsequent output. A variant of such a source of economic contraction is banking

sector problem created by sudden depreciation. Bank losses resulting from large swings

in asset markets could translate into credit crunch, as banks’ capital adequacy becomes a

problem.

The third channel through which the balance of payments crisis could hit the output was

described by Obstfeld and Rogoff (2000). Sudden reversal or reduction of the current

account deficit results in traded goods becoming scarce forcing relative price adjust-

ments under plausible assumptions on short-term consumption and production trad-

ables-non tradedables substitutability. Because relative wages in non-traded sector can-

not easily adjust to the lower level necessary to avoid unemployment, and due to in-

complete short-term purchasing power parity adjustments of the import prices, only an

extreme depreciation can ensure full employment and lack of output costs. Current ac-

count financing stops are not equivalent to currency crises, but often (see Goldfajn and

Valdez, 1999) associated with them, so the mechanism is relevant. However, in this

case, the larger the depreciation, the smaller the output impact of the crisis.

- 199 -

This underscores the fact that currency crises impact on output does not have to be

negative at all. The ERM-2 crisis of 1992 was a very good example of this – in all cri-

sis-affected countries GDP grew faster in 1994 than it did in 1992 (albeit Italy, Spain

and Ireland did experience slowdown in 1993). The mechanisms described above show

that the balance sheet effects of even a quick depreciation could be positive: export ori-

ented economies, or otherwise ones not exposed to the currency mismatch can only

benefit from the depreciation. The positive reaction of the Brazilian stock exchange in

the day following the peg collapse in 1999 was the best example of the mechanism at

work.

As Forbes (2002) calls it, at the firms’ level, the crisis means that “cheap labor meets

costly capital”. The net impact depends on relative labour and capital intensity on one

hand and on the firms customers’ and prices on the other.

Osakwe and Schembri (1999) use a stochastic version of the Dornbush (1976) model to

show that a fixed exchange rate regime (long in place, but not collapsed yet) becomes a

source of increased output volatility. The argument goes that the prediction errors on the

future exchange rate increase together with the time spent under the peg and increased

probability of the collapse. Exchange rate prediction errors influence the output gap,

through its impact on the price level, not backed by eventual exchange rate movements.

Section 6.3 Empirical treatments

The empirical research on the impact of is much less common than the studies on the

causes, or leading indicators of the currency crises (Błaszkiewicz and Paczyński, 2003).

There are several methods to approach the problem.

- 200 -

First is descriptive statistics: tracking the evolution of various variables in the “crisis

window”, run-up and in the period following the crisis. The data can then be aggregated

at different levels (regional, global, by the time of occurrence), and compared with the

evolution in countries not affected. The advantage of the method is the ability to analyse

the dynamics of a very wide range of variables with short track records, which is espe-

cially useful for transition economies. It allows for addressing the problem of underly-

ing trends masking the crisis impact (e.g. sharp recession in the run-up to the crisis

makes falling GDP after the crisis much less significant). The non-parametric nature of

the analysis may be a disadvantage, as little quantitative conclusions can be reached this

way. The examples of such analyses include IMF (1998), Bordo and Schwartz (2000),

Milesi-Ferretti and Razin (1998) or Aziz et al. (2000) and Błaszkiewicz and Paczyński

(2003). The latter found out, that the output losses following currency crises in Latin

America tend to be much smaller than the ones observed as a result of currency crashes

in other regions. Their hypothesis explaining this regularity was that the economies in

South America are much better used to the bouts of hyperinflation and rapid devalua-

tions than those of e.g. South East Asia.

Second method is a detailed study concentrating on a particular episode of a crisis (pos-

sibly in various countries), or several episodes in a particular country. The use of com-

parable data, and the ability to use all the data available for a particular country is cer-

tainly an advantage, but “overfitting” (inability to generalise the results) is a problem in

such an analysis. Examples of such studies include Calvo and Mendoza (1996), Lane

and Philips (1999).

Finally, there is a group of various regression studies trying to explain output changes

by a combination of crisis and other variables. Such studies can be divided into two

- 201 -

groups, based on sample selection. One includes all countries in an extended time

frame, and tries to explain growth using a combination of crisis variables and other fac-

tors. Second group restricts the sample to the countries stricken by a crisis. In effect,

such studies try to explain the variation of growth impact conditional on the crisis hap-

pening, not necessarily the impact of the crisis itself, relative to the influence of other

factors. Rodrik and Velasco (1999) and Calvo and Reinhard (1999) are examples of

such a study.

The important issue that must be addressed in modelling the impact of crisis on output

are the underlying growth trends, and the influence of exogenous or country specific

variables on growth. The typical approach for tackling the possible autoregressive na-

ture of growth is to analyse changes in deviation from trend, instead of the growth level

(albeit it does make interpretations of the results slightly more difficult). Taking into

account lagged growth, country specific fixed effects, or both, are other ways, more

suitable for countries with extremely short track records (what really was the growth

trend in Russia in the 1993-1994 period, between the start of the transformation and the

first crisis?).

Apart from past growth trends, other factors, like world interest rates, real exchange rate

changes, openness, or budget deficits could be responsible for growth variations, and

they must be taken into account in the overall calculations.

Even though the majority of the studies focus on growth rate losses (either as a sum of

differences between actual and trend GDP growth level, the sum of differences between

actual and average in the period before the crisis as in Bordo et al., 2001, or as a pa-

rameter in the GDP growth equation), the approach is not the only one possible. First, if

the crisis is a result of unsustainable growth, the output losses calculated that way will

- 202 -

overestimate the real, long-term impact of the currency crashes. On the other hand, as

Mulder and Rocha (2000) argue, if the cut-off time for measuring crisis impact is in the

year when output growth rate gets back to the trend level, output will remain depressed,

compared with the theoretical value implied by no crisis and sustained trend.

Barro (2001) estimates his 5-year grouped panel regressions including a wide range of

fundamental growth factors, like education, health, investments, rule-of-law index. In-

clusion of the 5-year-group time effect constant is a way to (relatively cheap statisti-

cally) address the problem of exogenous global factors influencing growth. The non-

crisis variables are meant to provide a benchmark average growth estimate within the 5-

year window and the divergence from that level can be attributable to the crisis occur-

rence (and random error). Barro finds that in the sample of 67 countries the average

GDP growth was 2 percentage points lower for countries with the crisis during a 5-year

period. Hutchinson and Neuberger’s (2001) interpretation of the result (10% cumulative

output loss) is problematic though, because of the problem with such grouped panel ap-

proach: the crises occurring by the end of the 5-year window would presumably influ-

ence growth in the following 5-year period (luckily, with the exception of Brazil, 1999

was quite a quiet year in that respect).

Bordo et al. (2001) use the longest sample, spanning from 1880 to 1997 to find out that

the cumulative impact of currency crises stayed between 5 and 10 percent of GDP in

emerging markets, and around 2-3% in the industrial economies throughout this long

- 203 -

period. Interwar years were the exception with over three times higher average crisis

costs for both type of economies63.

After estimating a model explaining output deviation from Hodrick-Prescott filtered real

GDP (level), trend with real depreciation, money supply changes, budget deficit, world

output, and US interest rates, Moreno (1999) adds crisis dummies to the model. Real

depreciation in 6 East Asian countries under study proved to be contractionary in the

1975-1998 period, and the added currency crisis dummy was only marginally signifi-

cant in explaining output falls in East Asia.

Hutchinson (2001) looks at a group of 67 non-industrial countries, to find that crisis re-

duces GDP growth by less than one percentage point in the year of the crisis and

slightly more than one percentage point in the year after the crisis.

Hutchinson and Neuberger (2001) concentrate on emerging markets alone (with easier

access to capital) to find the effect of crises on growth higher in such countries. Balance

of payments and currency crises result in a (relatively evenly distributed) GDP growth

falls in the two-three years by the total of 5-8 percentage points. The authors control for

real exchange rate, world growth, budget surplus/GDP, money supply growth, and trade

openness, and a country-specific dummy.

Gupta et al. (2001), in a sample restricted to crisis episodes find that over 40% of the

crises in developing countries in the last 30 years have been expansionary. Average cri-

sis resulted in 1.2 percentage point lower growth in the two years following the crisis,

compared with the 3-year average tranquil period before.

63 Bordo et al. did not, however, include many structural growth-driving control vari-

- 204 -

The crisis output cost estimates thus vary from 1.2 to 10% of GDP, with the lowest cost

in industrial countries, and the highest in emerging market economies.

Section 6.4 Research concept and data used

This chapter is meant to accompany the liquidity holding analysis from Chapter 5

above. The aim is to contrast the currency crisis costs implied by the model (applied to

the set of emerging market economies) with the actual GDP losses modelled as a func-

tion of control variables in the sample of crisis-hit countries. The model can then be ap-

plied to the snapshot of counties in their recent (2001) state, showing the GDP loss in

case of a potential crisis. The results can then be deducted from the numbers in Figure

78, showing the “goodwill loss” expected by the policymakers in case of a prospective

crisis (expected crisis cost minus expected output loss).

This line of research suggests an analysis in the spirit of Rodrik and Velasco (1999),

Gupta et al. (2001) or Hutchinson and Neuberger (2001), with the sample restricted to

the crisis episodes. The idea also requires the sample selection mechanism to be identi-

cal to the one employed in Chapter 5 above. In particular, in the baseline study, 25%

depreciation within a quarter is the threshold required for the crisis to happen.

Second complication is the issue of consecutive crises. While it was not crucial to deal

with it when choosing international liquidity (on the contrary, the model stressed the

importance of the cleansing effect of crises and falling probability of subsequent ones),

it is not quite clear how to account for the costs of subsequent crises. Using the 25% de-

preciation threshold supplemented by the condition of depreciation higher than 10%

ables in their samples

- 205 -

compared with the average in the previous four quarters still yielded several cases of

multiple, escalating crises. These happen if the pace of depreciation increases fast

enough to jump over the 10% acceleration threshold.64 In the analysis below, we assume

that the crisis costs cumulate. It is quite a strong assumption, and an unusual one (in

most of the early crisis warning, and crisis output impact studies, the data points includ-

ing the second occurrence of the crisis are simply excluded: see e.g. Frankel and Rose

(1996) or Kaminsky and Reinhard (1999)). But the cost cumulating assumption can be

defended. For example, the banking sector weakened by the depreciation could be fin-

ished off by the subsequent depreciation; credit crunch resulting from liabilities value

growing with depreciating local currency could well be aggravated with subsequent

step-depreciation. The same applies to the consecutive crisis defences, and related

jumps in nominal interest rates. Inclusion of a “previous year crisis” dummy variable

showed a significant and negative impact on output relative to trend, confirming that

two consecutive crises are worse for growth than one.

The dependent variable is a measure of output loss, calculated as a sum of deviations

from the Hodrick-Prescott (1980) filtered real output levels (estimated over the period

up to the year before the crisis) in the year of the crisis and the year after that.

Deviation of the output from long-term, country specific trend does eliminate the need

for substantial number of the control variables, or “structural growth determinants”.

Savings rate, investments ratio, population growth, workforce education, state of the

64 The cases of multiple currency crises included Belarus in 1997-2000, Brazil in 1991-1994, Ghana in 1999-2000, Indonesia in 1997-1998, Mexico in 1994-1995, Mongolia in 1991-1993, Venezuela in 1994-1996 and Zimbabwe in 1997-1998. Some of them, due to the data shortages did not make it to the final sample (including Belarus and Mongo-lia).

- 206 -

legal or political system, should all be taken into account by medium-term output trends

(and, the intra-country time variations in fundamental growth-influencing variables

should not be substantial for the 15-years long sample).

The control variables should include either the factors changing rapidly and which could

have an exogenous but significant impact on growth, or the indicators of vulnerability to

sudden depreciation or speculative attack. The first group include world growth or in-

terest rates, domestic monetary policy stance (proxied by the level of real interest rates),

and the fiscal policy (budget deficit). The second group included international liquidity

(higher liquidity reduces the need to liquidate physical investments if financing stops

temporarily), foreign debt level (increasing the balance sheet impact of depreciation on

investments), exports to GDP ratio, imports to GDP (the former increasing the positive

output impact of depreciation, the later working in the opposite direction), and a meas-

ure of real exchange rate overvaluation ahead of the crisis. Bigger real exchange over-

valuation ahead of the crisis could offset the costs of the crisis with the benefit of re-

gained competitiveness.

Section 6.5 The results

The results confirm the common opinion that currency crises are costly in terms of out-

put. They are not universally costly though, as shown in the histogram of output loss

(compared with the trend). The average output loss in the year of the crisis was 0.56%

(with the hypothesis of zero output loss rejected at 92% significance level in favour of

negative output impact), while the average cumulative loss in the two years was 2.15%

(zero output loss hypothesis rejected at 99.98% level). The crises resulted in output loss

in 62% of the cases. Figure 82 shows a histogram of the output loss (dependent vari-

able) results in the sample.

- 207 -

Figure 82 Output loss in first and two first years of a crisis

0%

5%

10%

15%

20%

25%

30%

35%

40%

-14.7 -11.6 -8.5 -5.4 -2.2 0.9 4.1 7.2 More

Cumulative ouput relative to trend (%)

crisis year

first two years

Source: Author

The results of an OLS regression including all the variables are not very encouraging,

even though the model is significant overall (F=1.95). Just two variables stand out in

their significance: bisdebt being the (total, not just short-term) debt in the foreign bank-

ing system as a percentage of GDP, and the occurrence of a crisis a year before.

Figure 83 Output crisis cost in 2 years of the crisis; all variables

Source | SS df MS Number of obs = 38

-------------+------------------------------ F( 9, 28) = 1.95

Model | 293.855467 9 32.6506075 Prob > F = 0.0850

Residual | 468.384614 28 16.7280219 R-squared = 0.3855

-------------+------------------------------ Adj R-squared = 0.1880

Total | 762.240081 37 20.6010833 Root MSE = 4.09

------------------------------------------------------------------------------

cummloss | Coef. Std. Err. t P>|t| [95% Conf. Interval]

-------------+----------------------------------------------------------------

realrates | .0017254 .0033499 0.52 0.611 -.0051366 .0085874

budget | -.1362304 .1701797 -0.80 0.430 -.4848278 .212367

worldrates | .2279289 .7446795 0.31 0.762 -1.297478 1.753336

bisdebt | -.1056256 .0377298 -2.80 0.009 -.1829116 -.0283395

llbis | .0030208 .0044966 0.67 0.507 -.0061902 .0122317

ca | .1163642 .243194 0.48 0.636 -.381796 .6145244

importstogdp | .0515411 .1125727 0.46 0.651 -.1790535 .2821357

exportstogdp | .0458459 .1186125 0.39 0.702 -.1971208 .2888125

conseq | -2.373483 1.363342 -1.74 0.090 -5.100170 0.353201

_cons | -2.275739 4.200282 -0.54 0.592 -10.87963 6.328147

------------------------------------------------------------------------------

Source: Author

A more parsimonious version of Figure 83 is shown in Figure 84. It shows the overall

regression significant at 96.1% level, and earlier mentioned two variables: debt and past

- 208 -

crises being joined by exports to GDP as the most important drivers of output crisis

costs. Countries with 10% of GDP higher exports tend to suffer 0.9% lower GDP loss

during the crisis. Debt has an impact similar both in terms of size and the significance.

Foreign debt higher by 10% of GDP boosts the potential cumulative output loss during

and year after the crisis by 0.7% of GDP. Finally, contrary to the general research prac-

tice, currency crises effects do tend to cumulate: past crisis occurrence deepens the out-

put loss by almost 2%.

Figure 84 Output crisis cost in 2 years of the crisis; parsimonious version

Source | SS df MS Number of obs = 43

-------------+------------------------------ F( 3, 39) = 3.74

Model | 182.417467 3 60.8058223 Prob > F = 0.0187

Residual | 634.001961 39 16.2564605 R-squared = 0.2234

-------------+------------------------------ Adj R-squared = 0.1637

Total | 816.419427 42 19.4385578 Root MSE = 4.0319

------------------------------------------------------------------------------

cummloss | Coef. Std. Err. t P>|t| [95% Conf. Interval]

-------------+----------------------------------------------------------------

bisdebt | -.0746998 .0293192 -2.55 0.015 -.1340035 -.015396

exportstogdp | .0855215 .0315668 2.71 0.010 .0216717 .1493714

conseq | -1.967618 1.464066 -1.34 0.073 -4.928971 .993736

_cons | -.6731593 1.123671 -0.60 0.553 -2.945998 1.599679

------------------------------------------------------------------------------

Source: Author

Interestingly, the initial output costs (deviation of real GDP from the long-term trend in

the year of the crisis) model results point to a different set of variables. Figure 85 shows

the kitchen sink version of the model, equivalent to Figure 83, but with the dependent

variable including output deviation from the trend only in the year of the crisis. This

time, trade, current account, debt and liquidity indicators prove to be insignificant.

- 209 -

Figure 85 Output crisis cost in the year of a crisis; all variables

Source | SS df MS Number of obs = 38

-------------+------------------------------ F( 9, 28) = 2.41

Model | 210.424325 9 23.3804806 Prob > F = 0.0363

Residual | 271.85873 28 9.70924034 R-squared = 0.4363

-------------+------------------------------ Adj R-squared = 0.2551

Total | 482.283055 37 13.0346772 Root MSE = 3.116

------------------------------------------------------------------------------

growthloss | Coef. Std. Err. t P>|t| [95% Conf. Interval]

-------------+----------------------------------------------------------------

realrates | .0040934 .0025521 1.60 0.120 -.0011344 .0093213

budget | .229804 .1296517 1.77 0.087 -.0357754 .4953835

worldrates | 1.020454 .5673352 1.80 0.083 -.1416792 2.182588

bisdebt | -.0234258 .0287445 -0.81 0.422 -.0823063 .0354548

llbis | -.0015578 .0034258 -0.45 0.653 -.0085752 .0054595

ca | .1518196 .1852777 0.82 0.419 -.2277046 .5313437

importstogdp | .052898 .0857636 0.62 0.542 -.1227809 .2285768

exportstogdp | .0405455 .0903651 0.45 0.657 -.144559 .22565

conseq | -3.739563 1.350276 -2.77 0.010 -6.505477 -.9736487

_cons | -4.952114 3.199991 -1.55 0.133 -11.507 1.60277

------------------------------------------------------------------------------

Source: Author

Eliminating the insignificant variables showed results as in Figure 86. Exports to GDP

show the same impact as in the 2-year analysis, albeit the significance of it tends to be

higher. This result supports a view that emerging market economies export competitive-

ness gains appear quite quickly, but die out, due to domestic inflation.

Figure 86 Crisis year output loss; final model

Source | SS df MS Number of obs = 40

-------------+------------------------------ F( 5, 34) = 4.25

Model | 186.777579 5 37.3555158 Prob > F = 0.0042

Residual | 299.186586 34 8.79960548 R-squared = 0.3843

-------------+------------------------------ Adj R-squared = 0.2938

Total | 485.964165 39 12.4606196 Root MSE = 2.9664

------------------------------------------------------------------------------

growthloss | Coef. Std. Err. t P>|t| [90% Conf. Interval]

-------------+----------------------------------------------------------------

realrates | .0041487 .0022702 1.83 0.076 .0003099 .0079875

budget | .2263584 .1135088 1.99 0.054 .0344236 .4182932

worldrates | .7841101 .456905 1.72 0.095 .0115183 1.556702

exportstogdp | .0757109 .0243872 3.10 0.004 .034474 .1169477

conseq | -3.533595 1.226914 -2.88 0.007 -5.608214 -1.458977

_cons | -4.434481 2.423432 -1.83 0.076 -8.532321 -.3366406

------------------------------------------------------------------------------

Source: Author

1% of GDP lower budget deficit tend to be associated with smaller (by 0.23%) severity

of currency crises. This could have two explanations. One is that there are some non-

- 210 -

Keynesian fiscal effects at work: lower deficit increases private demand due to expecta-

tions for less taxation and higher external stability. Second, and a more plausible expla-

nation is that lower budget deficit brings less real economy disturbances in case of a

sudden financing stop (as suggested by e.g. Corsetti et al. 1999). Countries with sounder

public finances can afford to support the banks weakened by the crisis, or to ease the

pressure on the private sector by higher spending. Government facing default has little

choice but to tighten the fiscal policy in case of a crisis.

More intriguing is the positive effect of both world and domestic real rates on the crisis

year output. Domestic real interest rates’ influence on post-crisis performance is not

particularly large and could be a result of hyperinflationary countries distorting the

overall picture. Eliminating such observations reverses the sign, and reduces the signifi-

cance level of realrates parameter (while keeping other parameters mostly unchanged).

The influence of world interest rates is both significant and large, though: crises occur-

ring with world interest rates at a one percentage point higher level, result in costs lower

by almost 0.8%. While it could be argued that currency crises do occur more frequently

when world interest rates go up (as foreign financing becomes scarcer), the same argu-

ment apparently cannot be translated into higher crisis costs. One rationalization of this

result is that countries hit by a crisis in times of low US interest rates have deeper prob-

lems (years of missed investments stimulated by wrong policies, political crisis). High

world interest rates-induced crises are merely a symptom of portfolio reweighing, not

leaving as much influence on growth as the crises brewed internally. Monsoonal effects

(Mason, 1999) seem to matter more for exchange rate volatility than for growth.

- 211 -

Finally, conseq dummy, carries higher significance and weight than in the case of “year

zero” analysis than it was in the cumulative output impact model. This is because gen-

erally higher 2nd year previous crisis’ output loss adds to the initial year number.

Section 6.6 Crisis costs conclusions

The results of the study show that currency crises do bring non-negligible output costs

for the countries involved. In the emerging market sample analysed, the rapid 25% de-

preciation wiped out over 2% of the GDP on average. This result falls on the lower-end

of the past research results, partially because the sample used includes transition

economies, for which underlying (positive) fundamental changes often mask the nega-

tive crisis consequences. The main determinants of total crisis costs (estimated here as a

cumulative 2-year deviation from long term output trend) are external indebtedness (in-

creasing potential costs) and openness of the economy (decreasing it). Contrary to find-

ings of Rodrik and Velasco (1999), international liquidity had a much less significant

influence on crisis costs than the total amount of foreign debt. The results show the im-

portance of trade competitiveness, that can be regained by devaluation, and of the bal-

ance sheets problems, which could be aggravated by large external debt inflation. In

other words, Forbes’ (2002) “cheap labor meets costly capital” is confirmed by these

results.

The short-term impact of the crises seems depend on a different set of causes. In par-

ticular, higher budget deficit prior to the crisis, and lower world interest rates signifi-

cantly boost the “year-zero” output loss. Worse shape of public finances makes the gov-

ernment unable to address e.g. banking sector problems, while crises occurring with US

interest rates at a low level tend to indicate deeper adjustment needs troubling the coun-

try in question.

- 212 -

Combining the results of estimation with the results of the previous chapter yields the

non-output loss related implied total gain from holding foreign exchange reserves. For a

median country, such an implied “goodwill” loss from a crisis (which could include,

among others all the non-crisis related benefits of holding foreign exchange reserves,

reputation and political costs of potential crisis, the policymakers not actively managing

the level of liquidity) is over 7% of GDP, or over three times above the average output

loss in a crisis.

Figure 87 Expected output loss, and total implied crisis cost (% of GDP)

Estimated output loss

Implied cost to policymakers

Implied goodwill loss

Argentina 3.8 21 17.2 Brazil 2.0 11 9 Bulgaria 2.5 29 26.5 Chile 1.5 11 9.5 China -0.4 3 3.4 Colombia 1.9 6 4.1 Croatia 2.5 1.1 -1.4 Dominicana 0.6 19 18.4 Hungary -1.3 4 5.3 Mexico 0.0 4 4 Philippines 1.3 25 23.7 Poland 0.1 8 7.9 Singapore 2.8 90 87.2 Slovak Republic -3.0 11 14 Thailand -0.4 7 7.4 Uruguay 3.2 26 22.8 Venezuela 0.3 31 30.7 Median 1.4 9 7.6 Source: Author

- 213 -

Chapter 7 Final conclusions

Since the early days of currency crisis literature, international liquidity took prominent

role in crisis modelling. Subsequent studies, both theoretical and empirical, showed li-

quidity is related one way or another to many kinds of currency crises. Low liquidity

can be a signal of incoming crisis (Krugman, 1979, Russia 1998), it can be a factor ena-

bling the crisis (Sachs et al., 1996a, Mexico 1994), or can be a key reason for the crisis

(Chang and Velasco, 2000, Korea 1997).

But the knowledge about importance of foreign exchange reserves gained in the last 15

years does not leave easy policy prescriptions. International liquidity is not a remedy for

countries patching their fiscal problems with money printing; neither is it a way out of

an ongoing crisis. The common reason for this is the cost of liquidity, which could eas-

ily aggravate fiscal problems, or to worsen the access to debt markets. The costs of

maintenance of the reserve stock could exceed potential output losses from a currency

crisis.

This work presents a model framework enabling the optimisation of the international

liquidity level subject to the foreign borrowing costs, and the country’s crisis vulnerabil-

ity. The results suggest the Pablo Guidotti rule of full coverage of short term debt with

foreign exchange reserve is not without merit, but it can lead to suboptimal results espe-

cially for countries facing either extremely steep or very low borrowing costs. On aver-

age the emerging market policymakers are willing to pay 0.3% of GDP to finance their

reserves, behaving as if they were pricing in 9% of GDP crisis costs, but the countries in

the sample pay from 0.05 to 0.9% of GDP annually to maintain international liquidity,

with the revealed crisis aversion ranging from 1 to 90% of GDP.

- 214 -

The model, despite considerable complication, still leaves several deficiencies which

could be addressed in further research. One is the assumption that the policymakers are

free to choose international liquidity as they please. In particular, decreasing liquidity is

not always feasible in a way described in the model, if a country has a low stock of

long-term debt. Another issue worth addressing is adding the risk of increased future

debt service costs as an additional, dynamic benefit of higher reserves, as suggested by

the simple sovereign spread determinants model. Finally, an extension including reserve

volatility as a factor calling for higher liquidity would constitute a promising way to

merge with Frenkel and Jovanovic’ (1981) approach to reserve level modelling.

The discussion about appropriate foreign exchange reserves is not an easy one not only

because of modelling or cost issues. Additional difficulty comes from the conflict be-

tween governments (worried about fiscal costs) and central banks (concerned about

monetary stability). It could explain the wide discrepancy between probability and ex-

pected output costs of currency crises and the costs of reserve maintenance. But the lat-

ter makes the debate worthwhile. If a developing country’s central bank pays its foreign

creditors 0.5% of GDP annually in order to keep the war-chest for bailing them out dur-

ing a crisis, it should at least know how bad the crisis would have to be for the invest-

ment to pay back.

- 215 -

References

Abiad, Abdul (2003), “Early Warning Systems: A Survey and a Regime-Switching Ap-proach,” IMF Working Paper 03/32.

Agénor, Pierre-Richard and J. Aizenman (1997), “Contagion and Volatility with Imper-fect Credit Markets,” NBER Working Paper No. 6080

Agénor, Pierre-Richard, Jagdeep S. Bhandari and Robert P. Flood (1992), “Speculative Attacks and Models of Balance of Payments Crises,” NBER Working Paper No. 3919

Aizenman, Joshua and Nancy Marion (1999), “Reserve Uncertainty and the Supply of International Credit,” NBER Working Paper No. 7202

Aizenman, Joshua and Stephen J. Turnovsky (1999), “Reserve requirements on sover-eign debt in the presence of moral hazard – on debtors or creditors?” NBER Working Paper No. 7004

Akyüz, Yýlmaz and Korkut Boratav (2002) “The Making of the Turkish Crisis” UNCTAD, Cenevre. http://www.bagimsizsosyalbilimciler.org/yazilar/AkyuzBoratav.htm

Alper, C. Emre (2001) “The Turkish Liquidity Crisis of 2000: What Went Wrong…” Russian and East European Finance and Trade Vol. 37, No. 6, pp. 51-71.

Antczak, Małgorzata (2001), “The 1997 Currency Crisis in Thailand,” in The Episodes of Currency Crisis in Latin American and Asian Economies, Marek Dąbrowski (ed.), CASE Reports 39, Warsaw

Antczak, Rafał (2003), “The Russian Currency Crisis of 1998,” in Currency Crises in Emerging Markets, Marek Dąbrowski (ed.), (Dordrecht: Kluwer Academic Pub-lishers)

Antczak, Rafał, Małgorzata Markiewicz and Artur Radziwiłł (2003), “The Failure of the IMF in Preventing Currency Crises in CIS Countries,” in Currency Crises in Emerging Markets, Marek Dąbrowski (ed.), (Dordrecht: Kluwer Academic Pub-lishers)

Apoteker, Thierry and Sylvain Barthelemy (2001), “Genetic Algorithms and Financial Crises in Emerging Markets”, paper presented at the 18th International Confer-ence in Finance, Namur, June 2001 organised by the AFFI, http://www.tac-financial.com/publ/affi-namur-2001.pdf, accessed in December 2004

Aziz, Jahangir, Francesco Caramazza and Ranil Salgado (2000), “Currency Crises: In Search of Common Elements,” IMF Working Paper No. 00/67

Bacchetta, P. and E. van Wincoop (1998), “Capital Flows to Emerging Markets: Liber-alisation, Overshooting, and Volatility,” NBER Working Paper No. 6530

Baig, T. and I. Goldfajn (1998), “Financial Market Contagion in the Asian Crisis,” IMF Working Paper No. 98/155

Barro, Robert J. (2001), “Economic growth in East Asia before and after the financial crisis,” NBER Working Paper 8330

Berg, Andrew, and Catherine Pattillo (1999), “Predicting Currency Crises: The Indica-tors Approach and an Alternative,” Journal of International Money and Finance, Vol. 18, (August), pp. 561-86.

- 216 -

Bertola, Giuseppe and Lars E. O. Svensson (1993), "Stochastic Devaluation Risk and the Empirical Fit of Target-Zone Models," Review of Economic Studies, vol. 60(3), pp 689-712, July.

Bilson, John F. O. (1979), “Leading Indicators of Currency Devaluations,” Columbia Journal of World Business, Vol. 14 pp. 62-76.

Błaszkiewicz, Monika (2001), “The South Korean Currency Crisis, 1997–1998”, in The Episodes of Currency Crisis in Latin American and Asian Economies, Marek Dąbrowski (ed.), CASE Reports 39, Warsaw

Błaszkiewicz, Monika and Wojciech Paczyński (2003), “The Economic and Social Consequences of Currency Crises”, in Currency Crises in Emerging Markets, Marek Dąbrowski (ed.), (Dordrecht: Kluwer Academic Publishers)

Blejer, Mario, I. and Liliana Schumacher (1998), “Central Bank Vulnerability and the Credibility of Commitments: A Value-at-Risk Approach to Currency Crises,” IMF Working Paper No. 98/65

Bordo, M. D. and Anna J. Schwartz (1999), “Under what circumstances, past and pre-sent, have international rescues of countries in financial distress been success-ful?,” Journal of International Money and Finance 18, pp. 683-708

Bordo, M. D. and Anna J. Schwartz (2000), “Measuring Real Economic Effects of Bail-outs: Historical Perspectives on How Countries in Financial Distress Have Fared With and Without Bailouts.” NBER Working Paper No. 7701.

Bordo, Michael, Barry Eichengreen, Daniela Klingebiel and Maria Soledad Martinez-Peria (2001). "Is the Crisis Problem Growing More Severe?" Economic Policy, 16(32), April, pp. 53-82.

Bruggemann, Axel, and Thomas, Linne (2000), “Are the Central and Eastern European Transition Countries Still Vulnerable to a Financial Crisis?: Results fkom the Signals Approach,” Bank of Finland Institute for Economies in Transition Dis-cussion Paper (Helsinki).

Buiter, Willem, Giancarlo Corsetti and Paolo Pesenti (1998), Financial Markets and European Monetary Cooperation. The Lessons of the 1992-93 ERM Crisis, Cambridge University Press, Cambridge, U.K.

Burkart, Olivier, and Virginie Coudert (2000), “Leading Indicators of Currency Crises in Emerging Economies,” Notes D’Études et de Recherche, Banque de France (May).

Burkett, Paul and Donald G. Richards (1993), “Exchange market pressure in Paraguay, 1963-88: monetary disequilibrium versus global and regional dependency.” Ap-plied Economic, 25, pp. 1053-63

Bussière, Matthieu and Christian Mulder (1999a), “Political Instability and Economic Vulnerability,” IMF Working Paper 99/46.

Bussière, Matthieu and Christian Mulder (1999b), “External Vulnerability in Emerging Market Economies: How High Liquidity Can Offset the Weak Fundamentals and the Effect of Contagion,” IMF Working Paper No. 99/88

Calvo, Guillermo A. and Enrique Mendoza (1996), “Reflections on Mexico’s Balance-of-Payments Crisis: A Chronicle of A Death Foretold,” Journal of International Economics 41

Calvo, Guillermo A. and Mendoza, E.G (1999), “Rational Contagion and the Globalisa-tion of the Securities Markets,” NBER Working Paper No. 7153

- 217 -

Calvo, Guillermo A. and Carmen M. Reinhart (1999), “When Capital Inflows Come to a Sudden Stop: Consequences and Policy Options,” http://www.puaf.umd.edu/faculty/papers/reinhart/imfbook.pdf unpublished manuscript, University of Maryland.

Caramazza, Francesco, Luca Ricci, and Radnil Salgado (2000), “Trade and Financial Contagion in Currency Crises,” IMF Working Paper 00/55.

Carr, Adam (2004), Psephos Adam Carr's Election Archive, http://psephos.adam-carr.net/

Cerra, Valerie, and Sweta Chaman Saxena (2002), “Contagion, Monsoons, and Domes-tic Turmoil in Indonesia’s Currency Crisis,’’ Review of International Economics 10( l), pp. 36-44 (February).

Chang, Roberto and Andrés Velasco (1998), “The Asian Liquidity Crisis,” NBER Working Paper No. 6796

Chang, Roberto and Andrés Velasco (1999), “Financial Crises in Emerging Markets,” FRBA, Vol. 84, no. 2, pp. 4-17.

Chang, Roberto and Andrés Velasco (2000), “Liquidity Crises in Emerging Markets: Theory and Policy,” in NBER Macroeconomics Annual 1999, ed. by Ben S. Bernanke and Julio Rotemberg (Cambridge, Massachusetts: MIT Press).

Chinn, Menzie D., Michael P. Dooley, Sona Shrestha (1999), “Latin America and East Asia crises in the context of an insurance model of currency crises,” Journal of International Money and Finance 18, pp. 659-681

Chinn, Menzie D., (2000), "Before the fall: were East Asian currencies overvalued?," Emerging Markets Review, vol. 1(2), pp. 101-126, 9

Chui, Michael, Rasanna Gai and Andrew G Haldane (2000), “Sovereign liquidity crises: analytics and implications for public policy,” Bank of England Working Paper no. 121

Collins, Susan M. (2001), “A Model of the Timing of Currency Crises.” Georgetown University, unpublished manuscript, August.

Collins, Susan M (1995), “The Timing of Exchange Rate Adjustment in Developing Countries,” (unpublished; Washington: Georgetown University, 1995)

Connolly, Michael and Jose Dantas da Silveira (1979), “Exchange Market Pressure in Postwar Brazil: An Application of the Girton-Roper Monetary Model,” Ameri-can Economic Review, 69(3), pp.448-54

Corsetti, Giancarlo, Paolo Pesenti and Nouriel Roubini (1999), “Paper tigers? A model of the Asian crisis,” European Economic Review 43, pp. 1211-1236

Cumby, Robert, and Sweder van Wijnbergen, “Financial Policy and Speculative Runs with a Crawling Peg: Argentina 1979-8 1,” Journal of International Economics, Vol. 17 (August 1989), pp. 11 1-27.

Cutler, DM., F. Knaul, R. Lozano, O. Méndez and B. Zurita (2000), “Financial Crisis, Health Outcomes and Aging: Mexico in the 1980s and 1990s”, NBER Working Paper 7746.

Dąbrowski, Marek (ed), M. Dekhtiarchuk, Urban Górski, P. Kovalev, Y. Kuz’min and K. Sultan (1999), “Ukraine: From Fragile Stabilisation to Financial Crisis,” CASE, Studies and Analyses, No. 158, (Warsaw, CASE foundation).

Detragiache, Enrica and Antonio Spilimbergo (2001), “Crises and Liquidity: Evidence and Interpretation,” IMF Working Paper 01/2

- 218 -

Diamond, D. and P. Dybvig (1983), “Bank Runs, Deposit Insurance, and Liquidity,” Journal of Political Economy 91, pp. 401-419

Dooley, Michael P. (1997), “A Model of Crises in Emerging Markets,” NBER Working Paper No. 6300

Dominguez, Kathryn M. and Jeffrey A. Frankel (1993), Does Foreign Exchange Inter-vention Work?, IIF, Washington, DC

Dornbusch, Rudiger (1976), “Expectations and exchange rate dynamics,” Journal of Po-litical Economy 84, pp. 1161-1176.

Dornbusch, Rudiger, Ilan Goldfajn, and Rodrigo O. Valdés, “Currency Crises and Col-lapses,” Brookings Papers on Economic Activity, No. 2 (1995), pp. 219-95.

Drazen, A. (1999), “Political Contagion in Currency Crises,” NBER Working Paper No. 7202

Easton, Stephen T. and Duane W. Rockerbie (1999), “What's in a default? Lending to LDCs in the face of default risk,” Journal of Development Economics, vol. 58, issue 2, pp. 319-332

Edin, Per-Anders, and Anders Vredin, “Devaluation Risk in Target Zones: Evidence from the Nordic Countries,” The Economic Journal, Vol. 103 (January 1993), pp. 161-75.

Edison, Hali J. (2000), “Do Indicators of Financial Crises Work? An Evaluation of an Early Warning System.” Federal Reserve Board of Governors, International Fi-nance Discussion Papers; No. 675, pp. 1-74, July.

Edwards, Sebastian (1985), “On the Interest-Rate Elasticity of the Demand for Interna-tional Reserves: Some Evidence from Developing Countries,” Journal of Inter-national Money and Finance, No. 4, pp. 287-95.

Edwards, Sebastian and Peter J. Montiel (1989), “Devaluation Crises and the Macro-economic Consequences of Postponed Adjustment in Developing Countries,” Staff Papers, International Monetary Fund, Vol. 36 (December 1989), pp. 875-903.

Edwards, Sebastian (1989), Real Exchange Rates, Devaluation, and Adjustment: Ex-change Rate Policy in Developing Countries (Cambridge, Massachusetts: MIT Press).

Edwards, Sebastian, and Julio Santaella (1993), “Devaluation Controversies in the De-veloping Countries: Lessons from the Bretton Wood Era,” in A Retrospective on the Bretton Woods System: Lessons for International Monetary Reform, ed. by Michael D. Bordo and Barry Eichengreen (Chicago: University of Chicago Press, 1993), pp. 405-55.

Edwards, Sebastian (1999), “Crisis Prevention: Lessons from Mexico and East Asia,” NBER Working Paper No. 7233

Edwards, Sebastian (2002), “This Argentine scheme,” The Financial Times, 21 January, Edwards (2002), “The Argentine Debt Crisis of 2001-2002: A Chronology and Some

Key Policy Issues”, mimeo, University of California, Los Angeles, January, http://www.anderson.ucla.edu/faculty/sebastian.edwards/Chronology.pdf

Eichengreen, Barry, Charles Wyplosz (1993), “The unstable EMS,” Brooking Papers on Economic Activity 1, 51-143

Eichengreen, Barry, Andrew K. Rose, Charles Wyplosz (1995), “Speculative attacks on pegged exchange rates: An empirical exploration with special reference to the European Monetary System,” Economic Policy, October

- 219 -

Eichengreen, Barry, Andrew K. Rose, Charles Wyplosz (1996), “Contagious Currency Crises: First Tests,” Scandinavian Journal of Economics, Vol. 98, No. 4, pp. 463-484.

Eichengreen, Barry (1997). "The Baring Crisis in a Mexican Mirror," Center for Inter-national and Development Economics Research, Working Paper Series 1031, Center for International and Development Economics Research, Institute for Business and Economic Research, UC Berkeley.

Eichengreen, Barry (2001), “Crisis Prevention and Management: Any New Lessons from Argentina and Turkey?”, mimeo, http://emlab.berkeley.edu/users/eichengr/crisis101901.pdf

Eliasson, Ann-Charlotte, and Christof Kreuter (2001), “On Currency Crisis Models: A

Continuous Crisis Definition.” Deutsche Bank Research Quantitative Analysis unpublished working paper; http://www.economia.uniroma2.it/ceis/confer-enze_convegni/banking2001/papers/mercoledi/Eliasson-Kreuter.pdf

Esquivel, Gerardo, and Felipe Larrain, (2000), “Explaining Currency Crises,” El Tri-mestre Economico 67(2), pp. 19 1-237 (April-June).

EUROSTAT (2004) – decision on funded pension schemes Far Eastern Economic Review (1998), “Politics and the Peg: Hong Kong fends off

speculators at the price of credibility,” by Alkman Granitsas, Henny Sender, Salil Tripathi, 27/08/1998

Feldstein, Martin (1999), “Self-Protection for Emerging Market Economies,” NBER Working Paper No. 6907.

FitchRatings (2004), “Country Ceiling Ratings and Rating Above the Sovereign,” Crite-ria Reports, June http://www.fitchratings.com/corporate/reports/report_frame.cfm?rpt_id=211294

Flood, Robert and Peter Garber (1984) "Collapsing exchange rate regimes: some linear examples", Journal of International Economics 17, pp. 1-13

Flood, Robert and Robert Hodrick (1986), “Real Aspects of Exchange Rate Regime Choice with Collapsing Fixed Rates,” Journal of International Economics 21, pp. 215-232

Flood, Robert, P. and Nancy P. Marion (1996), “Speculative Attacks: fundamentals and self-fulfilling prophecies,” NBER Working Paper No. 5789.

Flood, Robert, and Nancy Marion (1997), “The Size and Timing of Devaluations in Capital-Controlled Economies,” Journal of Development Economics 54, pp. 123-147

Flood, Robert P. and Nancy P. Marion (1998), “Perspectives on the Recent Currency Crisis Literature,” IMF Working Paper No. 98/130

Flood, Robert and Peter Garber (1989) “The linkage between speculative attack and tar-get zone models of exchange rates,” NBER Working Paper No. 2918

Flood, Robert P. and Oliver Jeanne (2000), “An Interest Rate Defence, of a Fixed Ex-change Rate,” IMF Working Paper No. 00/159

Flood, Robert P. and Nancy P. Marion (2002), "Holding International Reserves in an Era of High Capital Mobility," IMF Working Papers 02/62

Forbes, Kristin J. and Roberto Rigobon (1999), "No Contagion, Only Interdependence: Measuring Stock Market Co-movements," NBER Working Paper 7267,

Forbes, Kristin J. (2002), "Cheap Labor Meets Costly Capital: The Impact of Devalua-tions on Commodity Firms," NBER Working Paper 9053

- 220 -

Frankel Jeffrey A. and Andrew K. Rose (1996), “Currency Crashes in Emerging Mar-kets: An Empirical Treatment,” Journal of International Economics 41, pp 351-368

Frankel Jeffrey A. and Sergio L. Schmukler (1996), “Crisis, Contagion, and Country Funds: Effects on East Asia and Latin America,” in Managing Capital Flows and Exchange Rates: Perspectives from the Pacific Basin, ed. Reuven Glick, Cambridge University Press, Cambridge, UK

Frenkel, Jacob, and Boyan Jovanovic, (1981), “Optimal International Reserves: A Sto-chastic Framework,” Economic Journal 91 (June), pp. 507-14.

Froot, Kenneth A. and Kenneth Rogoff (1991), “The EMS, the EMU, and the transition to a common currency,” NBER Working Paper No. 3684

Frydl, Edward (1999), “The Length and Cost of Banking Crises,” IMF Working Paper No. 99/30

Ganev, Georgi (2003), “The Bulgarian currency crisis of 1996-1997,” in Currency Cri-ses in Emerging Markets, Marek Dąbrowski (ed.), (Dordrecht: Kluwer Aca-demic Publishers)

Garber, Peter M. and Svensson, Lars E.O (1994). "The Operation and Collapse of Fixed Exchange Rate Regimes" NBER Working Paper No. 4971.

Gelos, Gaston, R and Ratna Sahay (1999), “Financial Market Spillovers in Transition Economies,” IMF Working Paper 99/71

Ghosh, Swati, and Atish Ghosh (2003), “Structural Vulnerabilities and Currency Cri-ses,” International Monetary Fund Staff Papers: Vol 50, No 3.

Girton, Lance and Don Roper (1977), “A Monetary Model of Exchange Market Pres-sure Applied to Postwar Canadian Experience,” American Economic Review 67, pp. 537-48

Glick, Reuven and Andrew K. Rose (1999), “Contagion and trade: Why are currency crises regional?,” Journal of International Money and Finance 18, pp. 603-617

Goldberg, L. S. (1991). Collapsing exchange rate regimes: shocks and biases. Journal of International Money and Finance 10, 252-263.

Goldfajn, Ilan and Rodrigo O. Valdés (1997), ”Are Currency Crises Predictable?,” IMF Working Paper 97/159

Goldfajn, Ilan and Rodrigo O. Valdés (1999), ‘The Aftermath of Appreciations” Quar-terly Journal of Economics, Vol. 114, no. 1 (February): 229-262

Goldstein, Morris (1996), "Presumptive Indicators/ Early Warning Signals of Vulner-ability to Financial Crises in Emerging-Market Economies". Institute for Inter-national Economies, Washington, DC

Goldstein, Morris, Graciela L. Kaminsky, and Carmen M. Reinhart (2000), Assessing Financial Vulnerability: An Early Warning System for Emerging Markets. (Washington: Institute for International Economics).

Grier, Kevin B., and Robin M. Grier (2001), “Exchange Rate Regimes and the Cross-Country Distribution of the 1997 Financial Crisis,” Economic Inquiry 39(1), pp. 139-48 (January).

Gupta, Poonam, Deepak Mishra and Ratna Sahay (2001), “Ouput [sic] Response to Cur-rency Crises,” mimeo, IMF

Hamilton, James D. (1994), Time Series Analysis, Princeton University Press. Hamilton, James D., and Oscar Jorda (2002), “A Model of the Federal Funds Rate Tar-

get,” Journal of Political Economy 110(5), pp. 113-167 (October).

- 221 -

Hawkins, John, and Marc Klau (2000), “Measuring Potential Vulnerabilities in Emerg-ing Market Economies.” BIS Working Paper No. 91, October.

Herrera, Santiago and Conrado Garcia (1999), “User’s Guide to an Early Warning Sys-tem for Macroeconomic Vulnerability in Latin American Countries.” World Bank Working Paper 2233, November.

Hodrick, R. and E. Prescott (1980), “Post-war U.S. Business Cycles: An Empirical In-vestigation,” unpublished manuscript, Carnegie Mellon University.

Hotelling, Harold (1931), “The Economics of Exhaustible Resources,” Journal of Politi-cal Economy, 39, pp. 137-25

Humberto, Juan M. Julio, Santiago A. Herrera (1991), “Crisis Cambiaria en un Sistema de Minidevaluaciones: El Caso de Colombia,” Ensayos Sobre Politica Económi-ca, Vol. 20, pp. 7-52.

Hutchinson, Michael (2001), “A Cure Worse than the Disease? Currency Crises and the Output Costs of IMF-Supported Stabilization Programs” NBER Working Paper 8305 (May).

Hutchinson, Michael and Ilan Neuberger (2001), “Output Costs of Currency and Bal-ance of Payments Crises in Emerging Markets,” mimeo, September

IFES (2004), ElectionGuide.org, http://www.ifes.org/eguide/elecguide.htm IMF (1988), Summary Proceedings of the Forty-Third Annual Meeting of the Board of

Governors (Washington), pp. 78–85. IMF (1998) "World Economic Outlook". (May). Financial Crises: Causes and Indica-

tors. ING Financial Markets (2004), Directional Economics, June 2004. Jarociński, M. (2000), “Moldova in 1995-1999: Macroeconomic and Monetary Conse-

quences of Fiscal Imbalances,” CASE, Studies and Analyses, No. 205 Jeanne, Olivier D. and Jeromin Zettelmeyer (2002), ""Original Sin," Balance Sheet Cri-

ses and the Roles of International Lending," IMF Working Papers 02/234 Kamin, Steven B. (1988) “Devaluation, External Balance, and Macroeconomic Per-

formance: A Look at the Numbers,” Studies in International Finance, No. 62

Kamin, Steven B. (1999), “The current international financial crisis: how much is new?,” Journal of International Money and Finance 18, pp. 501-514

Kamin, Steven B., John W. Schindler, and Shawna L. Samuel (2001), “The Contribu-tions of Domestic and External Factors to Emerging Market Devaluation Crises: An Early Warning Systems Approach.” Board of Governors of the Federal Re-serve System, International Finance Discussion Paper No. 711 (September).

Kaminsky, Graciela Saul Lizondo, and Carmen Reinhart (1998), “Leading Indicators of Currency Crises,” International Monetary Fund Staff Papers, 45, No. 1, March,1-48.

Kaminsky, Graciela. L. and Sergio L. Schmukler (1999), “What triggers market jitters? A chronicle of the Asian crisis,” Journal of International Money and Finance 18, pp. 537-560

Kaminsky, Graciela and Carmen M. Reinhard (1999), “The Twin Crises: The Causes of Banking and Balance-of-Payments Problems,” American Economic Review 89, no. 3 (June), pp. 473-500

Kaufmann, Daniel, Gil Mehrez, and Sergio Schmukler (1999), “Predicting Currency Fluctuations and Crises: Do Resident Firms Have an Informational Advantage?” World Bank Working Paper No. 2259, December.

- 222 -

Kim, W. and Wei, S. (1999), “Foreign Portfolio Investors Before and During a Crisis,” NBER Working Paper No. 6968

Klein, Michael W., and Nancy Marion (1994), "Explaining the Duration of Exchange-Rate Pegs,” NBER Working Paper No. 4651 (Cambridge, Massachusetts: Na-tional Bureau of Economic Research, February).

KNUiFE (2004), Open Pension Funds in Poland 2003, http://www.knuife.gov.pl/english/pension/publica-tions/Rynek%20OFE%202003%20English.pdf

Krkoska, Libor (2001), “Assessing Macroeconomic Vulnerability in Central Europe,” Post-Communist Economies 13(l), pp. 41-55 (March).

Krugman, Paul (1979) “A model of balance of payments crises”, Journal of Money, Credit, and Banking 11, pp. 311-325

Krugman, Paul and Julio Rotemberg (1992a), “Speculative attacks on target zones,” in P. Krugman and M. Miller (eds.), Exchange Rate Targets and Currency Bands, Cambridge University Press, Cambridge

Krugman, Paul and M. Miller (1992b) (eds.), Exchange Rate Targets and Currency Bands, Cambridge University Press, Cambridge

Krugman, Paul (1996), “Are Currency Crises Self-Fulfilling?” NBER Macroeconomics annual.

Krugman, Paul (1998), “What happened to Asia?” mimeo (Cambridge, Massachusetts: MIT), http://www.pkarchive.org/crises/DISINTER.html, (accessed on 29/12/2004)

Krugman, Paul (1999), “Balance Sheets, The Transfer Problem, and Financial Crises,” in International Finance and Financial Crises: Essays in Honor of Robert P. Flood, Jr., ed. by Peter Isard, Assaf Razin, and Andrew K. Rose (Boston: Klu-wer Academic; Washington: International Monetary Fund).

Kuan C.M. and H. White, (1994), "Artificial neural networks: An econometric perspec-tive" with reply, Econometric Reviews, 13, 1-91 and 139-143.

Kumar, Manmohan, Uma Moorthy, and William Perraudin (2002), “Predicting Emerg-ing Market Currency Crashes,” IMF Working Paper 02/07 (Washington: Inter-national Monetary Fund).

Kwack, Sung Yeung (2000), “An Empirical Analysis of the Factors Determining the Financial Crisis in Asia,” Journal of Asian Economics 11(2), pp. 195-206 (Sum-mer).

Lall, Subir (1997), “Speculative Attacks, Forward Market Intervention and the Classic Bear Squeeze,” IMF Working Paper No. 97/164

Lane, Timothy and Steven Phillips (1999), “Macroeconomic Environment” in Lane, Timothy et al. (eds.), IMF-Supported Programs in Indonesia, Korea, and Thai-land: A Preliminary Assessment, IMF Occasional Paper 178.

Markiewicz, Małgorzata (2003), “The Ukrainian Currency Crisis of 1998,” in Currency Crises in Emerging Markets, Marek Dąbrowski (ed.), (Dordrecht: Kluwer Aca-demic Publishers)

Martinez-Peria, Maria Soledad (2002), “A Regime Switching Approach to Studying Speculative Attacks: A Focus on EMS Crises,” Empirical Economics 27(2), pp 299-334.

Masson, P. (1999), “Contagion: macroeconomic models with multiple equilibria,” Jour-nal of International Money and Finance 18, pp. 587-602

- 223 -

McKenzie, David J. (2003) "How do Households Cope with Aggregate Shocks? Evi-dence from the Mexican Peso Crisis," World Development, Elsevier, vol. 31(7), pages 1179-1199, 7

McLachlan, G. J. (1992): Discriminant Analysis and Statistical Pattern Recognition, Wiley, New York.

Mendoza, E.G. and Uribe, M. (1999), “The Business Cycles of Balance-of-Payments crises: A Revision of a Mundellian Framework,” NBER Working Paper No. 7045

Messe, R. A. and K. Rogoff (1983), “Empirical exchange rate models of the seventies: do they fit out of sample?”, Journal of International Economics, 14, pp. 3-24

Milesi-Ferretti Gian Maria and Assaf Razin (1996). ”Current Account Sustainability, Selected East Asian and Latin America Experiences,” IMF Working Paper No. 96/10.

Milesi-Ferretti, Gian Maria and Assaf Razin (1998), “Current Account Reversals and Currency Crises: Empirical Regularities,” IMF Working Paper No. 98/89

Mishkin, Frederic S. (1999), “Lessons from the Asian Crisis,” Journal of International Money and Finance 18, pp. 709-723

Mishkin, Frederic S. (1998), “International Capital Movements, Financial Volatility and Financial Instability,” Schriften des Vereins fur Socialpolitik Gelleschaft fur Wirtscharges und Socialwissenschafter, pp. 11-40

Mizen, Paul (1999), “Can foreign currency deposits prop up a collapsing exchange-rate regime?,” Journal of Development Economics, Vol. 58, pp. 553-562

Montiel, P. and Carmen M. Reinhart (1999), “Do capital controls and macroeconomic policies influence the volume and composition of capital flows? Evidence from the 1990s,” Journal of International Money and Finance 18, pp. 619-635

Moreno, Ramon (1995), “Macroeconomic Behavior During Periods of Speculative Pressure or Realignment: Evidence from Pacific Basin Countries,” Economic Review, Federal Reserve Bank of San Francisco, No. 3 (1995), pp. 3-16.

Moreno, Ramon (1999), “Depreciation and Recessions in East Asia.” Federal Reserve Bank of San Francisco Economic Review, 3, pp. 27-40

Morris, Stephen and Shin, Hyun Song (1998), "A Theory of the Onset of Currency At-tacks," Economics Papers 149, Economics Group, Nuffield College, University of Oxford.

Morris, Stephen & Shin, Hyun Song (2004), "Coordination risk and the price of debt," European Economic Review, vol. 48(1), pp. 133-153, 2.

Mulder, Christian and Manuel Rocha (2000), “The Soundness of Estimates of Output Losses in Currency Crises,” unpublished manuscript, IMF.

Mulder, Christian, Roberto Perrelli, and Manuel Rocha (2002), “The Role of Corporate, Legal and Macroeconomic Balance Sheet Indicators in Crisis Detection and Pre-vention,” International Monetary Fund Working Paper: WP/02/59, March.

Mundell, Robert A. (1960), “The Monetary Dynamics of International Adjustment un-der Fixed and Flexible Exchange Rates,” Quarterly Journal of Economics, v. LXXIV no. 2, pp. 227-257

Mussa, Michael (2002), “Argentina and the Fund: From Triumph to Tragedy,” Policy Analyses in International Economics 67, IIE, Washington, DC.

- 224 -

Nag, Ashok, and Amit Mitra (1999), “Neural Networks and Early Warning Indicators of Currency Crisis,” Reserve Bank of India Occasional Papers 20(2), pp. 183-222 (Monsoon).

NBP (2003), Opinion of the Monetary Policy Council to the budget draft 2004, October Nitithanprapas, Ekniti, and Thomas D. Willett (2000), “A Currency Crisis Model that

Works: A Payments Disequilibrium Approach.” Claremont Colleges Working Papers in Economics No. 2000-25

Obstfeld, Maurice. (1994) “The Logic of Currency Crises” Cahiers Économiques et monétaires, No. 43, p. 189, Banque de France

Obstfeld, Maurice. (1995), “The Mirage of Fixed Exchange Rates,” Journal of Eco-nomic Perspectives Vol 9, No. 4, pp. 73-96

Obstfeld, Maurice. (1996), “Models of currency crises with self-fulfilling features,” European Economic Review 40, pp. 1037-1047

Obstfeld, Maurice. (1998), “The Global Capital Market: Benefactor or Menace?,” un-published, his web page

Obsfeld, Maurice and Kenneth Rogoff (2000), “Perspectives on OECD Economic Inte-gration: Implications for US Current Account Adjustment,” International Trade 0012004, Economics Working Paper Archive at WUSTL

Osakwe, Patrick and Lawrence Schembri (1999), "Real Effects of Collapsing Exchange Rate Regimes: An Application to Mexico," Working Papers 99-10, Bank of Canada

Osband, Kent, and Caroline Van Rijckeghem (1998), “Vulnerability to Currency Cri-ses,” IMF Staff Papers 47(2), pp. 238-58.

Ötker, Inci and Ceyla Pazarbaşioğlu (1994), “Exchange Market Pressures and Specula-tive Capital Flows in Selected European Countries," IMF Working Paper WP/94/21

Ötker, Inci and Ceyla Pazarbaşioğlu (1995), “Speculative Attacks and Currency Crises: The Mexican Experience,” IMF Working Paper WP/95/112

Ötker, Inci and Ceyla Pazarbaşioğlu (1997), “Speculative Attacks and macroeconomic fundamentals: evidence from some European currencies,” European Economic Review 41, pp. 847-860

Oxfam (1999), Education Now: Break the Cycle of Poverty http://www.caa.org.au/oxfam/

Ozkan, F. Gulcin and Alan Sutherland (1998), “A currency crisis model with an opti-mising policymaker,” Journal of International Economics, 44, pp. 339-364

Paczyński, Wojciech (2001), “The Mexican Peso Crisis 1994–1995” in ”, in The Epi-sodes of Currency Crisis in Latin American and Asian Economies, Marek Dąb-rowski (ed.), CASE Reports 39, Warsaw

Poret, Pierre (1998), “Liberalising Capital Flows: Lessons from Asia,” OECD Observer, October/November

Radelet, S. and Jeffrey Sachs (1998a), “The Onset of the East Asian Financial Crisis,” NBER Working Paper No. 6680

Radelet, S. and Jeffrey Sachs (1998b), “The East Asian Financial Crisis: Diagnosis, Remedies, Prospects.” Paper prepared for the Brookings Panel. Washington D.C., March 26-27

- 225 -

Radziwiłł, Artur (2003), “The Moldovan Currency Crisis of 1998,” in Currency Crises in Emerging Markets, Marek Dąbrowski (ed.), (Dordrecht: Kluwer Academic Publishers)

Rawdanowicz, Łukasz (2003), “Propagation of Currency Crises – the Case of the Rus-sian Crisis,” in Currency Crises in Emerging Markets, Marek Dąbrowski (ed.), (Dordrecht: Kluwer Academic Publishers)

Rodrik, Dani and Andrés Velasco (1999), “Short Term Capital Flows,” NBER Working Paper No. 7364

Rostowski, Jacek (2004), “The Stability and Growth Pact - Essential and Unfeasible,” CASE, Studies and Analyses, No. 275, Warsaw

Rybiński, Krzysztof and Mateusz Szczurek (2003), “Disinflation Policy, Capital Inflow, and the Current-Account Balance,” in Disinflation in Transition Economies, ed. by Marek Dąbrowski (Budapest: CEU Press)

Sachs, J., Aarón Tornell and Andrés Velasco (1996a), “The Mexican Peso Crisis: Sud-den Death or Death Foretold?” Journal of International Economics 41

Sachs, J., Aarón Tornell and Andrés Velasco (1996b), “Financial Crises in Emerging Markets: The Lessons from 1995,” Brookings Paper, Vol. 27, no. 1 pp: 147-199.

Sachs, J., Aarón Tornell and Andrés Velasco (1996c), “The Collapse of the Mexican Peso: What Have We Learned?,” Economic Policy 22

Salant, S and Henderson, D., (1978) "Market Anticipation of Government Policy and the Price of Gold," Journal of Political Economy 86, pp. 627-648

Sarno, L. and Mark P. Taylor (1999a), “Moral hazard, asset price bubbles, capital flows, and the East Asian crisis: the first tests,” Journal of International Money and Fi-nance 18, pp. 637-657

Sarno, Lucio and Mark P. Taylor (1999b), “Hot money, accounting labels and the per-manence of capital flows to developing countries: an empirical investigation,” Journal of Development Economics, Vol. 59, pp. 337-364

Sasin, Marcin (2001a), “The Malaysian Currency Crisis,” in The Episodes of Currency Crisis in Latin American and Asian Economies, Marek Dąbrowski (ed.), CASE Reports 39, Warsaw

Sasin, Marcin (2001b), “The Indonesian Currency Crisis,” in The Episodes of Currency Crisis in Latin American and Asian Economies, Marek Dąbrowski (ed.), CASE Reports 39, Warsaw

Sasin, Marcin (2001c), “The Turkish 2000 Financial Markets Crisis of Confidence,” in The Episodes of Currency Crisis in the European Transition Economies, Marek Dąbrowski (ed.), CASE Reports 40, Warsaw

Svensson, L. E. O. (1993), “Assessing target zone credibility: mean reversion and de-valuation expectations in the EMS 1973-1992,” European Economic Review, 37, pp. 763-802.

Standard & Poor's (2002), “Argentine Chronology of Events”, RatingsDirect, available at http://www.standardandpoors.com/europe/francais/Fr_news/Argentine-Chronology-

of-Events_12-04-02.html (accessed in December 2004) Szczurek, Mateusz (2003), “International Liquidity and Currency Crisis Costs,” in Cur-

rency Crises in Emerging Markets, Marek Dąbrowski (ed.), (Dordrecht: Kluwer Academic Publishers)

Tanner, Evan (1999), “Exchange Market Pressure and Monetary Policy: Asia and Latin America in the 1990s,” IMF Working Paper No. 99/114

- 226 -

Tornell, Aarón. (1999), “Common Fundamentals in Tequila and Asian Crises,” NBER Working Paper No. 7139

Transparency International (1997), “The 1997 CPI,”, http://wwwuser.gwdg.de/~uwvw/corruption.cpi_olderindices_1997.html (ac-cessed July 2004)

Transparency International (2003), “The framework document,”, http://wwwuser.gwdg.de/~uwvw/downloads/FD_CPI_2003.pdf (accessed July 2004)

Van Rijckeghem, Caroline and Beatrice Weder (1999), “Sources of Contagion: Finance or Trade?” IMF Working Paper No. 99/146

Velasco, Andrés (1996), “Fixed exchange rates: Credibility, flexibility and multiplic-ity,” European Economic Review, 40, pp. 1023-1035

Vlaar, Peter J.G. (2000), “Currency Crises Models for Emerging Markets,” De Neder-landsche Bank Staff Report No. 45 (November).

Weller, Christian E. (2001), “Financial Crises after Financial Liberalisation: Excep-tional Circumstances or Structural Weakness?“ Journal of Development Studies 38(l), pp. 98-127 (October).

Weymark, Diana N. (1998), “A general approach to measuring exchange market pres-sure,” Oxford Economic Papers, 50, pp. 106-121

Willman, Alpo (1988), “The Collapse of the Fixed Exchange Rate Regime with Sticky Wages and Imperfect Substitutability Between Domestic and Foreign Bonds,” European Economic Review 32, pp. 1817-1838

Wohar, Mark E. and Bun Song Lee (1992), “Application of the Girton-Roper monetary model of exchange market pressure: the Japanese experience, 1959-1986,” In-dian Journal of Economics, 72, pp. 379-407.

Yeldan, Erinç (2002), “Behind the 2000/2001 Turkish crisis: Stability, Credibility, and Governance, for Whom?,” mimeo, Bilkent University, Ankara

Zhang, Zhiwei (2001), “Speculative Attacks in the Asian Crisis,” IMF Working Paper No. 01/189

- 227 -

Appendix 1. Chronology of recent currency crises

Chronology of the Mexican crisis

January 1994 – peasant rebellion in the Chiapas province.

February 1994 – U.S. interest rates increase

23 March 1994 – Assassination of the presidential candidate of the ruling party.

end of March – April – Financial turbulence in Mexico: exchange rate depreciates by around 10% reaching the ceiling of the band, Bank of Mexico reserves shrink by 9 billion USD, interest rate rise significantly.

April – December 1994 – Government substitutes its short term peso denominated debt with dollar indexed debt

21 August 1994 – Ernesto Zedilo wins the presidential elections; interest rates fall

28 September 1994 – Assassination of the ruling party leader

October – November – Capital outflow continues, Bank of Mexico reserves decline by further US$4.7bn

1 December 1994 – president Zedilo takes office.

20 December 1994 – Finance Ministers announces widening of the exchange rate corridor by 15%.

22 December 1994 – Under pressure from financial markets the authorities announce free floating the peso.

29 December 1994 – Appointment of the new Finance Minister, a few days later an-nouncement of the government economic program.

3 January 1995 – IMF expresses its support for the program, announces the estab-lishment of the Exchange Stabilisation Fund.

1st quarter 1996 – economic growth (0.1%) resumes to average at close to 7% during the follwing three quarters

Source: Paczyński (2001)

Chronology of the Bulgarian Crisis

March 1990 - Unilateral default of Bulgaria on its official foreign debt.

February 1991 - Beginning of partial reforms in Bulgaria: liberalization of some prices, interest and exchange rates. Initial drop in output, beginning of rent seeking through soft budget constraints due to lack of financial discipline and property rights enforcement.

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28 July 1994 - First payment to the London Club according to the renegotiated for-eign debt service agreement. Bulgaria started facing serious payments every six months. The first major post-transformation instance of a hard budget constraint.

30 November 1995 - Acquisition of Agrobusinessbank by the BNB for BGN 1. Be-ginning of explicit banking crisis, to be followed by many other liquidations of banks.

March 1996 - Grain and bread crisis. Caused by rent seeking operations preying on state controlled prices, the crisis led to loud public outcry and exacerbated the politi-cal position of the government.

19 April 19 - The Bulgarian lev loses 2 percent of its value against the dollar in one day. The beginning of the currency crisis, during which the Bulgarian lev depreciated by 3500 percent in approximately 300 days.

17 May 1996 - The BNB put Mineralbank, a large state owned bank, and First Pri-vate Bank, the largest private bank, under receivership. The banking crisis enteres its trough. Trust in the system was shaken, flight from the Bulgarian lev began.

August 1996 - First tranche from a new agreement with IMF received. Temporary slowdown in exchange rate depreciation and a pick up in privatization, predomi-nantly of separate parts rather than of whole enterprises.

23 September 1996 - The BNB puts another 9 banks under receivership and adopts a set of measures for recovering the financial stability. The set of measures announced by the BNB did not remove the fundamental factors for the crisis and had no impact on economic agents’ behavior and on macroeconomic turbulence.

26 October – 2 November 1996 - Two rounds of presidential elections. The opposi-tion candidate wins by a large margin.

6 November 1996 - An IMF mission proposes introduction of a Currency Board Ar-rangement (CBA) as a was out of the crisis. A heated public debate in which the government claims it had capacity to implement a CBA, while the opposition denied the existence such capacity and political will.

22 December 22 1996 - Resignation of the government of the Bulgarian Socialist Party. Beginning of a political crisis, in which the Socialist Party was trying to form a government and the opposition and the public demanded early elections.

27-28 December 1996 - The Parliament votes to provide three BNB loans for a total of BGL 115 bln., 6 % of 1996 GDP, to the Ministry of Finance. The stage was set for hyperinflation during the first six weeks of 1997.

4 February 1997 - After a month of public protests and strikes, the Socialist party gives up its attempts to form a new government. The newly elected President ob-tained the opportunity to appoint a caretaker government and to set a date for early elections.

12 February 1997 - Caretaker government appointed, new elections scheduled. Be-ginning of a recovery program enjoying high public confidence and international support.

14 February 1997 - Peak of the BGN/USD exchange rate. End of the currency crisis. The US$/BGL starts falling.

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21 May 1997 - A new center-right government, enjoying an absolute Parliamentary majority sworn in. Beginning of implementation of the reform package, starting with the legislation setting up a CBA.

1 July 1997 - Official start of the Currency Board in Bulgaria.

Source: Ganev (2003), pp. 217-218

Chronology of Thai crisis

March 1997 - First explicit sign of trouble. BoT and MoF announce that 10 unnamed finance companies would need to raise capital.

March-June 1997 - Public confidence in finance companies erodes. Deposit with-drawals. Large and secret liquidity support from the authorities to 66 finances com-panies.

June 1997 - BOT suspends 16 finance companies and announces that their creditors are expected to bear part of companies’ losses.

2 July 1997 - The baht is floated, then it depreciates by 32 percent against U.S. dollar during July. In the context of IMF program negotiations, BoT and MoF issue a joint statement

August 1997 - detailing measures to strengthen confidence in the financial system.

Additional 42 finance companies have their operations suspended (altogether 58 out of 91 finance companies) and are given 60 days to present rehabilitation plans to the authorities. Government announces blanket guarantee to banks and remaining fi-nance companies backed by unlimited FIDF support (in baht).

14 August 1997 - First Thailand’s IMF Letter of Intent.

20 August 1007 - The IMF Executive Board approves a three-year Stand-By Ar-rangement, amounting to 4 billion U.S. dollars (505 percent of quota).

17 October 1997 - Emergency Financing Procedures by the IMF.

25 November 1997 - Second Thailand’s IMF Letter of Intent. MoF announces a clo-sure of 56 finance companies.

December 1997 - BoT intervention at Bangkok Metropolitan Bank - capital of exist-ing shareholders is written down, management is changed, and the bank is recapital-ized by authorities via debt-equity swap.

8 December 1997 - First quarterly review of the policy package. Strengthening of the program, implementation of addi-tional fiscal measures. Indicative range for interest rates is raised, and a specific timetable for finan-cial sector restructuring is an-nounced.

January 1998 - First Bangkok City Bank and Siam City Bank are intervened and dealt with the same fashion as BMB in the previous month. These three banks ac-count for about 10 percent of banking system deposits. A new state-owned commer-cial bank, Radanasin Bank, is established in order to take control over the higher-quality assets. A majority stake in Thai Danu Bank is acquired by foreign investors (Development Bank of Singapore). Baht begins to strengthen against the U.S. dollar

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as improvements in the policy settings revived mar-ket confidence. Contracting do-mestic demand helps to keep inflation in check and contributed to larger-than-expected adjustment in the current account.

24 February 1998 - Third Thailand’s IMF Letter of Intent.

February – May 1998 - Strengthening of baht.

March 1998 - Agreement on compensation reached with creditors of 42 finance companies under rehabilitation program. Cautious reduction of interest rates viewed as consistent with exchange rate developments.

4 March 1998 - Second quarterly review of the policy package. Under the revised program, monetary policy contin-ues to focus on the exchange rate stabilization, with interest rates to be maintained high until evidence of a sustained stabilization emerged. The program includes measures to strengthen financial sector.

March – April 1998 - Banks start to recapitalize with many foreign deals. New loan classification and provisioning rules are introduced.

May 1998 - Additional 7 finance companies are intervened and merged with KTT (a large government owned finance company).

26 May 1998 - Fourth Thailand’s IMF Letter of Intent.

June 1998 - Bank of Asia acquired by ABN-AMRO Bank.

10 June 1998 - Third quarterly review of the policy package. International reserves strengthen in the larger-than ex-pected scope, but recession deepens. Adjustment in fiscal policy allows for an increase in the fiscal deficit target for 1997/98 from 2 per-cent to 3 percent of GDP.

June –July 1998 - The exchange rate weakens. Fiscal and monetary policies have been tighter than programmed, activ-ity is weaker than expected, and exports fail to pick up. The large adjustment in current account re-flects a sharp compression of im-ports. Growing difficulties in corporate sector.

August 1998 - Union Bank of Bangkok and Laem Thong Bank are intervened. Laem Thong Bank is merged with Radanasin Bank. Union Bank of Bangkok together with 12 intervened finance companies merged with Krung Thai Thanakit (KTT), the state owned finance company and subsidiary of the state-owned Krug Thai Bank (KTB). First Bangkok City Bank is merged with KTB. Introduction of financial sector re-structuring package..

25 August 1998 - Fifth Thailand’s IMF Letter of Intent.

11 September 1998 - Fourth quarterly review of the policy package. Foreign ex-change market conditions are relatively stable (in spite of the Russian crisis), provide room for interest rates lowering to pre-crisis level.

19 October 1998 - As of this date, 12.2 billion of U.S. dollars of total financing package for Thailand (17 billion of U.S. dollars) has been disbursed, including 3 bil-lion of U.S. dollars from the IMF and 9.2 billion of U.S. dollars from other multilat-eral and bilateral sources.

1 December 1998 - Sixth Thailand’s Letter of Intent.

23 March 1999 - Seventh Thailand’s Letter of Intent.

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April 1999 - Establishment of Bank Thai from merger of Union Bank of Bangkok and 12 finance companies.

May 1999 - Siam Commercial Bank raises over 1.5 billion of U.S. dollars in new capital.

July 1999 - Nakomthon Bank is intervened.

August – November 1999 - Auctions and further asset of finance companies sales to the state owned Asset Management Com-pany.

September 1999 - Nakomthon Bank is sold to Standard Chartered Bank.

21 September 1999 - Eighth Thailand’s Letter of Intent.

November 1999 - The sale of Radanasian Bank to United Overseas Bank of Singa-pore is finalized.

8 May 2000 - The IMF completes Final Review of the Thai stabilization program.

Source: Antczak (2001), pp. 52-53

Chronology of the Malay crisis

1997

28 March - Malaysian central bank restricts loans to property and stocks to head off a crisis.

early-May - Japanese officials, concerned about the decline of the yen, hinted that they might raise interest rate. Investors start gradual withdrawal from South East Asian markets.

mid-May - The BNM defends ringgit with few days of very high interest rates.

2 July - Thai baht collapses.

8 July - Malaysian central bank, Bank Negara, has to intervene aggressively to de-fend the ringgit. The intervention temporarily works (the currency slightly appreci-ates).

14 July - Malaysian central bank abandons the defence of the ringgit and engages in stabilizing domestic money market with relatively loose monetary policy.

24 July - Ringgit hits 38-month low of 2.65/US$.

26 July - Prime minister Mahathir blames George Soros and other "rogue specula-tors" for the attack on the ringgit.

4 September, Ringgit breaks through 3.00/US$.

20 September - Mahathir tells the public, that speculation is immoral and should be stopped.

1 October - Mahathir repeats his call for tighter regulation, or a total ban on forex trading. The ringgit falls 4% in less than 2 hours to a low of 3.4/US$.

17 October - Malaysia tightens budget.

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5 December - Malaysia finally and radically changes its policy and imposes tough re-forms in order to deal with a crisis. These include an 18% cut in government spend-ing, restriction on large-volume import, on bank credit and in stock market regula-tions. There were to be "no question of bailout" for financially ailing companies.

1998

January-February - Several increases in BNM's intervention interest rate were planned to stop the currency from depreciating and restrict inflationary pressures

March - The severity of the crisis is gradually recognized and the fiscal policy changes to more expansionary. The fiscal package of MYR3bn (1% of GDP) is an-nounced and a drastic revision of federal budged aims the deficit of 2.6% of GDP.

July - Another additional fiscal package (MYR7bn, 2.5% of GDP) announced in or-der to stimulate the economy.

January-August - Despite the austerity fiscal measures and firm monetary policy the crisis and the capital outflow continues.

1 September - Malaysia introduces capital controls; financial investment can be repa-triated only after a 1-year period. Rental and profits from sales can be repatriated.

1999

5 February - Malaysia replaces one year holding period with exit tax. Repatriation of principal and profits will be subjected to a maximum levy of 30%.

Source: Sasin (2001b), p. 75

Chronology of the Indonesian crisis

1997

May - Thai currency comes under speculative pressure.

July - Thai, Malaysian, Philippine, and Indonesian currencies all depreciate.

14 August - Indonesia abolishes its system of a managed exchange rate. The rupiah starts to depreciate

16 September - 15 government "mega-projects" are postponed.

8 October - Indonesia says it will ask the IMF for financial assistance.

31 October - Indonesia's IMF package is unveiled. It provides for more than US$23bn in aid.

1 November - Sixteen banks are closed as the first step in IMF package, what causes panic and bank runs among depositors.

5 November - IMF approves a US$10 billion loan for Indonesia as part of the mas-sive international package.

5 December – Aging president Soeharto takes 10 days rest after a 12-day world tour and misses ASEAN summit.

9-12 December - The finance minister fails to negotiate the debt rollover in Wash-ington.

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1998

6 January - Indonesia unveils an expansionary 1998/99 budget, contrary to IMF de-mands of a budget surplus. The rupiah loses half its value over a five-day period.

9 January - Ratings agency Standard & Poor downgrades Indonesia's currency to sub-investment grade status.

mid-January - Calls start for a change of the political regime.

15 January - Soeharto signs new IMF agreements.

January till mid-February - Anti-Chinese food riots take place in at least a dozen places throughout Indonesia.

mid-January - All but 22 of the 286 companies listed on the Jakarta stock exchange are technically bankrupt. Property companies are the worst shape.

27 January - Government announces a moratorium on repaying debts and interest, and promises to guarantee all deposits of commercial banks.

February - Soeharto proposal of a currency board is announced, criticized and finally turned down.

February - Talks with a steering committee of private bank creditors concerning the restructuring of interbank and corporate debt begin

10 March - Soeharto is re-elected to a seventh five-year term with Habibie as vice president.

4 May - Fuel prices are increased by up to 71 percent. Three days of riots follow.

9 May - Soeharto leaves for a week-long visit to Egypt.

12 May - The army troops shoot four students at Jakarta protest.

13-14 May - Rioting spreads throughout Jakarta. Estimated 1200 people die in two days. When Soeharto returns from Egypt, he faces a flood of calls to resign.

21 May - Soeharto resigns and hands power to Habibie.

4 June - Agreement concerning debt restructuring is reached in Frankfurt.

17 June - The rupiah hits 17,000 against the dollar again.

29 July - The central bank certificates auctions system was improved and changed in attempt to regain control over monetary aggregates.

24 September - Paris Club reschedules US$4.2 billion of sovereign debt. Annual in-flation rises to 82.4 percent in September.

29 September - Indonesia strengthens bank recapitalization scheme.

October - Monetary stability gradually returns, inflationary pressure eases and the rupiah stabilizes around 9000/US$.

10 November - Special session of the Parliament begins to discuss election and po-litical reforms.

1999

13 March - Government closes 38 insolvent banks.

7 June - Indonesia holds first democratic election since 1955.

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6 August – The finance minister admits there were "irregularities" in loan-recovery process. The scandal prompts IMF and World Bank to threaten loan suspension.

1 October - Indonesia announces seventh month of deflation, with annual inflation of 1.25 percent.

20 October - Wahid elected as the president.

Source - Sasin (2001c), p. 99

Chronology of the Korean crisis

1997

January - The 14th largest conglomerate Hanbo Steel Co. goes bankrupt. The long-term rating of three Korean banks with high exposure to Hanbo was lowered. Yet, the sovereign risk for Korea did not deteriorate, indicated the clear separation of the sovereign rating and rating related to the private financial institutions' problem.

March-April - Further defaults including those of the top thirty chæbols including Sammi Steel on 19 March and Jinro Group on 21 April.

July - Kia Motors asked its creditors for the workout agreement on its debt of US$8 billion to avoid receivership.

August - In spite of the intervention, the National Bank of Korea was not able to de-fend the won exchange rate at the level of 900/US$. At the same time the govern-ment announced its readiness to guarantee foreign currency liabilities of Korea's fi-nancial institutions. This materialized on the 14 October, when the government in-jected with money Korea First Bank and some other merchant banks.

Early October - various credit rating agencies downgrade Korea (S&P, Euromoney, Moody’s), because of the governmental decisions to rescue Korea First Bank and undertake Kia Motors.

27 October - Bloomberg reports the free fall of Korean won raised concerns the country would need IMF assistance. The government denies it.

29 October - Korean newspapers announce the bond market would be opened from 1998 to attract foreign investors. It did not prevent the currency’s further deprecia-tion.

30 October - Foreign press speculates that the Bank of Korea official reserves of US$30bn did not include dollars sold through forward transactions as the Korean government ordered banks to stop accumulating dollars.

8 November – The government accuses foreign press of spreading unjustified ru-mours about Korea.

18 November - Bank of Korea makes emergency loans to 5 major commercial banks worth US$1bn, still denying it would need IMF assistance.

20 November - The currency band widened from 2.5 to 10 percent daily.

21 November - The minister of finance and the economy announced it would ask a rescue package from the IMF.

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4 December - IMF Executive Board approves a US$21 billion stand-by credit for Korea which, together with the World Bank, ADB and individual government loans constituted US$58 billion.

Source - Błaszkiewicz (2001), p. 121

Chronology of the Russian Crisis

2 July 1997 -Devaluation of Thai baht, beginning of the Asian Crisis.

July 1997 – February 1998 - Containment of the main wave of the Asian crises, con-tagion and spill-over effects. Devaluation or depreciation of currencies in Indonesia, Malaysia, Philippines, South Korea.

October 1997 - Withdrawal of foreign funds from Russia. Dropping stock market in-dices, increase in the CBR (Central Bank of Russia) and market interest rates.

11 November 1997 - Pressure on foreign exchange market. Widening the band of rouble-dollar exchange rate fluctuation from ±5 to ±15 percent and introduction of rouble central parity based on three-year average at the level of 6.2/US$. Heavy in-terventions of the CBR in the foreign exchange market leading to decline in official reserves by US$5.9 billion in 4Q1997.

February – April 1998 - Preliminary arrangements reached among IMF and the Asian countries, a new inflow of foreign capital to Russia. Lessening pressure on the Russian markets. Decline in interest rates starting from mid-March, increase in stock market indices. Foreigners in possession of approximately half of GKO/OFZ mar-kets.

May – June 1998 - Stock market crash in Moscow. Main RTS index drops by 40 and 21 percent in dollar terms in May and June, respectively.

End-June 1998 – Major outflow of foreign capital from Russia. A decline in CBR re-serves by over US$8 billion, increase in GKO/OFZ yields to 130 percent.

16 July 1998 - Signing a memorandum between the Russian government and the IMF, which implied an introduction of radical stabilisation package under Prime Minister Sergei Kiriyenko. Improvements in market moods in Russia.

11 August 1998 - Publication of report by the Japanese Agency of Planning warning on the danger of crisis in Japan. Yen reaches the lowest level of 147.64/US$ and Dow Jones Industrial Index drops by 300 points.

13 August 1998 - George Soros publishes a critical letter to the Russian government in the “Financial Times” on the IMF program suggesting devaluation of the rouble by 15-25 percent, introduction of currency board, and warning about the possibility of crisis. Band wagon effect of withdrawal investors from Russia.

17 August 1998 - Devaluation of exchange rate band by over 33 percent, announce-ment of 90-day moratorium on private external obligations and compulsory restruc-turing of the domestic public debt. Trading of GKO/OFZ suspended, the rouble starts to depreciate – the beginning of currency crisis.

23 August 1998 - The government of Prime Minister Sergei Kiriyenko dismissed. In-creased volatility in the markets.

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2 September 1998 - Abandoning of the exchange rate band. Depreciation of the rou-ble by 20 percent to 12.8/US$ on 3 September.

September to end-October 1998 - Banking panic, bankruptcies of banks and financial institutions. Industrial production down by 15 percent, import halve in dollar value, rouble depreciates by 150 percent (since August), increase in CPI inflation to 7 per-cent monthly. Beginning of full-fledged financial crisis.

Source - Antczak (2003), p. 255

Chronology of the Ukrainian crisis

Before the crisis

Mid 1997 –Beginning of foreign portfolio capital outflows.

Autumn 1997 – The NBU (National Bank of Ukraine) starts to participate in primary market of government securities. Depletion of foreign exchange reserves of the NBU from US$2,854m in August 1997 to US$2,374, in the end of 1997 and US$900m in the end of August 1998.

October 1997 and January 1998 – Changes in the parameters of the crawling band (before the final abolishment of the system). Increase in general government deficit from 3.4% of GDP in 1996 to 6.1% of GDP in 1997 and 7% in the first quarter of 1998.

November 1997 – the NBU increases discount rate from 16% to 23.4%, then to 25%, and finally to 35%

March 1998 – IMF halts disbursement of its Stand-by credit due to the lack of pro-gress in reforms and failure to meet the performance criteria.

17 August 1998 – Beginning of the currency crisis in Russia

28 August 1998 – Hryvna exchange rate reaches upper band of the corridor (sched-uled for a change on 1 January 1999)

4 September 1998 – IMF approves three-year Extended Fund Facility for Ukraine of US$2.2bn

5 September 1998 – The parameters of the exchange rate corridor realigned

Fall 1998 – government and the NBU approve anti-crisis measures; restructuring of government debt takes place

31 December 1998 – Parliament approves 1999 budget

Q4 1999 – Real GDP growth turns positive

July 2000 – The last restrictions in the foreign exchange market abolished. A free-floating exchange rate regime starts.

Source: Markiewicz (2001), p. 62

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Chronology of the Moldovan Crisis

January - August 1998 - macroeconomic situation in Moldova aggravated by declin-ing GDP; interventions of National Bank of Moldova (NBM) supporting exchange rate of leu; weak fiscal revenues and increasing interest rates on T-bills; inflation is oscillating around zero.

August 1998 - Russian crisis results in capital flight from Moldova

August - October 1998 - National Bank of Moldova intervenes massively, selling USD 81 million out of the total initial stock of USD 224 million of its gross interna-tional reserves, exchange rate depreciates from 4.7 leu per dollar in the beginning of August to 5.0 in mid-October, in real terms leu appreciates strongly against devalued currencies of major trade partners (Russia and Ukraine).

September 1998 - monthly exports to Russia decrease by 80% in comparison to the same month of the previous year, industrial output in Moldova down by 32.5%.

August - December 1998 - several ad hoc budget expenditures cuts introduced.

September-October 1998 - dramatic fall in the demand for government securities, de-spite issuing 7-14 day T-bills rolling-over maturing T-bills becomes impossible; NBM provides liquidity to the government in order to prevent the default on T-bills.

Second half of October 1998 - reserve requirement ratio raised from 8% to 25%, commercial banks required to invest 10% of their assets into T-bills; leu continues to depreciate, approaching 6.0 leu per dollar by the end of October.

2 November 1998 - NBM stops interventions at the Interbank Currency Exchange, the official exchange rate being set as a weighted average of rates on banks' foreign exchange transactions.

November 1998 - exchange rate depreciates to 9.5 leu per US$ and stabilizes; until the end of 1998 it temporarily appreciates to 8.3/US$

November - December 1998 - monthly inflation rates averages 8%.

End of 1998 - beginning of 1999 - new reformist government appointed, memoran-dum of economic policies signed with the IMF, situation on the foreign exchange and T-bill markets stabilizes.

Source - Radziwiłł (2003), p. 291

The chronology of the Turkish crisis

1 January 2000 - The beginning of the 3-year disinflation program

August - Disagreement among ruling coalition, mainly over privatization issues

September - The anti-corruption drive accelerates, 2 banks are taken over, total num-ber of banks closed within 2 years reaches 10

October-November - More shocking revelations about alleged asset mismanagement in the banking sector.

November - The stock market begins to gradually decline

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mid-November - Liquidity squeeze on the market, unnerved foreign investors start selling Turkish assets

17 November - The central bank decides to intervene on the interbank market, inter-est rates ease, but investors lose confidence, stock market collapse, panic begins

22 November - Panic reaches its peak, Turkish assets are dumped, capital outflows is counted in several hundreds million USD daily

29 November - The central bank has already pumped US$3bn more than it was al-lowed by the IMF agreement

30 November - The central bank decides to cut off liquidity support to save disinfla-tion program, interest rates explode

2 December - Turkish government negotiates with the IMF

4 December - Interest rates reach unimaginable 1950%, while cumulative capital out-flow exceed US$7bn

5 December - Rating agencies downgrade Turkey and Turkish banks, first news about the IMF agreement leak to the public

6 December - Larger than expected IMF aid package is announced. The aid amounts to US$7.5bn in addition to already available 2.9bn

mid-December, Capital markets calm down and investors regain confidence, interest rates go down

16-22 February 2001, President Ahmet Necdet Sezer accuses the Prime Minister Bu-lent Ecevit of challenging his decision further to investigate state-owned banks sus-pected of corruption. The prime minister issues a statement that read - "The president had directed a serious allegation at me (…) Of course, this is a serious crisis (…)". Within minutes, the Istanbul stock exchange dropped 10%, and overnight interest rates jumped to from 40% to 100%. Turkish bankers immediately recognized that the political crisis would bring an end to the ambitious disinflation program. (…). Around US$7.5bn withdrawn from Turkey in a single day.

The IMF warned that no new emergency loans would be granted for Turkey and ad-vised devaluation but the government decided to continue defending the peg. Over-night interest rates reached 6000%. Another 3 billion USD left the country before, prompted by bankers' warnings against possible financial system collapse, the gov-ernment finally decided to float the currency on Thursday, 22 February. The lira de-preciates approximately 40%.

Source: Sasin (2001c), p. 97

Chronology of the Argentine crisis of 2001

This is a full text of the report reproduced from Standard & Poor's RatingsDirect, avail-

able at http://www.standardandpoors.com/europe/francais/Fr_news/Argentine-Chronology-of-

Events_12-04-02.html

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Nov. 6, 2001–Sovereign Default. The sovereign credit rating was downgraded to SD on Nov. 6, 2001, following the government's decision to carry out a distressed debt exchange.

Nov. 30, 2001–Deposit Run. Total collapse of confidence resulted in the acceleration of the deposit run. During the day, deposits decreased $1.8 billion (2.7%) and inter-bank rates reached 900%.

Dec. 3, 2001–Bank Deposit Freeze ("Corralito")/Foreign Exchange Controls. The De la Rua administration imposed restrictions on deposit withdrawals, limiting with-drawals from checking and savings accounts to $1,000 per month, although the funds deposited could be used as a means of payment (electronic transfers, credit and debit cards, and checks). All new lending granted by local banks had to be dollar denomi-nated. Cross-border transfers were restricted to foreign trade transactions and credit card international clearing, while transfers abroad to honor financial obligations were subject to consent from the Central Bank of Argentina. No authorizations were granted (decree 1570/01).

Dec. 7, 2001–Foreign Exchange Controls: Export Repatriation Requirement. Pro-ceeds of exports had to be transferred to Argentina, though funds could be main-tained in the original currency, with no need of conversion into pesos. Central Bank regulation specifically established that while certain cross-border transfers would have "automatic" approval by the Central Bank (i.e., public debt service, delivery versus payment operations resulting from securities brokerage), some others would require Central Bank authorization (trade finance, private debt service; CB res. 3382). Still, no authorizations were granted.

Dec. 11, 2001–Foreign Exchange Controls. The Central Bank communicated to fi-nancial entities that they were authorized to make payments abroad to honor their fi-nancial obligations due in December (CB telephone res. 3893).

Dec. 13, 2001–Foreign Exchange and Trade Regulations. Some of the trade-related transfer regulations were changed again. Proceeds of exports destined to pay the debt service of future-flow transactions were exempted from the requirement of transfer to Argentina, as was payment of obligations originated in prefinance and finance of ex-ports with inflows into the Argentine financial system after Dec. 6. The changes fa-cilitated the payment of exporters' financial obligations, while paying imports was made more cumbersome. Under certain conditions, transfers abroad of funds that were introduced into the financial system after Dec. 3 were authorized (CB res. 3394).

Dec. 20, 2001–Presidential Resignation. Following riots, looting, and demonstra-tions, Minister of the Economy Cavallo and President De la Rua resigned within a few hours.

Dec. 21-26, 2001–Banking Holiday. Banking operations were virtually nonexistent, and clearing of operations was unavailable, as the Central Bank established bank and foreign exchange holidays between Dec. 21 and Dec. 26, and then extended the for-eign exchange holiday.

Dec. 24, 2001–Presidential Appointment/Debt Moratorium. The National Assembly appointed Rodriguez Saa as new president. In his inaugural speech, he stated that payments on the Argentine external debt were to be suspended, and that devaluation

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and dollarization were not under consideration. Mr. Saa's economic plan included the issue of a second currency (the "argentino").

Dec. 30, 2001–Presidential Resignation. After a new round of demonstrations trig-gered by the appointment of officials believed to have been involved in illegal activi-ties in the past, as well as other worrisome political and economic signs, Rodriguez Saa resigns.

Jan 2, 2002–Presidential Appointment. Eduardo Duhalde was appointed president. His term was scheduled to end in December 2003.

Jan. 6-10, 2002–Banking Holiday/Peso Devalued. Banking operations were virtually nonexistent and clearing of operations was unavailable as the Central Bank estab-lished bank and foreign exchange holidays. Mr. Duhalde's new administration pro-moted the end of the convertibility regime and established a dual foreign exchange market. The official parity was fixed at Argentine peso (ArP) 1.4 per dollar (Eco-nomic Emergency Law 25.561). Other provisions of the law include:

• Pesification of most debts with original amounts below $100,000.

• Freeze of tariffs and other obligations emerging from private contracts origi-nally in dollars for 180 days, during which agreements and renegotiations were to take place.

• The government is to implement measures to preserve the dollar-denominated savings of depositors trapped in the financial system. The law also entitles the government to restructure the maturity of deposits as the financial system's solvency evolves.

• The government is entitled to impose a tax on oil exports to compensate banks for the cost of pesification of assets.

The official market coexisted with a free market, although the government claimed that its ultimate goal was a floating exchange-rate regime. Although the legal frame-work was not clear-cut, according to some interpretations of the Central Bank regula-tion of foreign exchange markets issued on Jan. 10, 2001, (CB res. 3425) cross-border transfers were not prohibited as long as the issuers acquired the dollars in the "free market"; that is, if the transfer did not imply a reduction in the Central Bank re-serves. The free market was not deep, however, with scarcity of dollar bills and small operations, which made it virtually impossible for companies to acquire the neces-sary amounts of dollars to pay obligations abroad. In any case, because the free mar-ket price of the dollar was much higher than the official parity (although the Central Bank injected small amounts in the free market to cap the increase), this alternative became increasingly costly for private entities. Additionally, the Central Bank in-creased restrictions on the use of bank deposits as a means of payment, compulsorily converting into long-term CDs (extending maturities up to four years) most deposits (CB res. 3426).

Jan. 11, 2002–Foreign Exchange Holiday Lifted. The government lifted the ban on foreign exchange transactions that had lasted three weeks.

Jan. 23, 2002–Bankruptcy Bill Passed by Senate. The Senate approved a new bank-ruptcy bill, which if finally enacted, would not only unilaterally impose a morato-rium on most private-sector foreign debt, but would provide debtors with significant incentives and legal protection to default and restructure both local and foreign cur-

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rency debt, leading to an indefinite delay in the restoration of credit for Argentine firms. Moreover, the attempt to modify the Bankruptcy Law, a fundamental law, through an improvised emergency bill, added uncertainty to the already critical eco-nomic environment.

Jan. 30, 2002–Bankruptcy Bill Modified by Lower Chamber. The Lower Chamber approved the bill reforming the bankruptcy law that had been passed by the Senate on Jan. 23. There was considerable pressure by multilaterals and other governments for the Argentine government to veto the law.

Feb. 1, 2002–Supreme Court Ruling on Deposits. The Supreme Court ruled against the restrictions on deposit withdrawals in response to claims filed by certain indi-viduals. On prior occasions, the Supreme Court had ruled in favor of the restrictions, but after a period of continuous demonstrations against the court's members, and the initiation of impeachment proceedings by the Argentine Congress, the Supreme Court finally ruled in favor of lifting restrictions.

Feb. 3, 2002–Banking Holiday/Economic Plan Announcement/Pesification of the Economy. The Central Bank established a banking holiday for Feb. 4-5 to gain time to solve the problems raised by the Supreme Court's ruling of Feb. 1, and to prepare the banks to adjust to the new economic plan. The day's announcements included the plan to fully float the peso starting Feb. 6, to lift restrictions on cross-border transfers once multilateral financial assistance is granted, to lift restrictions on cash withdraw-als of payroll accounts, to target a fiscal deficit of $3 billion for 2002, not to exceed a monetary target of an additional $3.5 billion (newly printed currency) for the whole year, and other measures concerning the pesification of the economy (decree 214/2002). The most important measures included in the decree were:

• Pesification of all debts at the 1:1 parity, regardless of original amount or na-ture, within or outside the financial system, including those transferred to trusts. They are to be indexed according to inflation and a maximum interest rate will be established by the Central Bank;

• Pesification of dollar deposits at the 1.4 parity, also to be indexed according to inflation. A minimum interest rate to be established by the Central Bank;

• Despite the adjustment of debts and deposits to preserve purchasing power, new contracts or obligations are not allowed to include indexation clauses;

• The government will issue a bond to compensate banks for the difference be-tween the rate of conversion into pesos of assets and deposits;

• Depositors have the option to require the replacement of their dollar deposits with a new dollar government bond, up to a maximum of $30,000. Banks will have to transfer assets to the government sufficient to finance the obligation;

• Dollar bills held by banks will have to be deposited in the Central Bank and converted into pesos at a 1.4 parity. This clause effectively prevented banks from selling dollars once banking activities restarted, and sought to make the realization of the populace's desire to escape from the peso more difficult. Af-ter considerable protests, this provision was reversed by a new decree the fol-lowing day; and

• All legal actions against the deposit restrictions are suspended for 180 days. Although the government devised this provision to counter the Supreme

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Court ruling, allegations of its unconstitutionality had already been filed in local courts by Feb. 4. In any case, the legal framework remained uncertain and from this date on, banks started to suffer considerable additional with-drawals (estimated at $30 million per day for the system) when depositors who had previously initiated legal actions approached banks with a court rep-resentative to seize funds.

Feb. 5, 2002–Banking Holiday. The Central Bank extended the banking holiday for the rest of the week (until Feb. 8).

Feb. 8, 2002–Foreign Exchange Controls and Trade Regulations. The Central Bank issued new regulations on the foreign exchange market and trade-related transac-tions, effective on Feb. 11. The most important measures concerning the foreign

exchange market were the following (CB res. 3471):

• There will be only one foreign exchange market, in which the price of the dollar will result from the free interaction of supply and demand.

• Authorized entities will be able to sell dollars against peso bills.

• Foreign currency will be sold against money deposited in the financial system only when the transfer abroad is originated by expenses related to the promo-tion of exports, trade-related transactions, the payment of financial obliga-tions that don't require Central Bank authorization or in which the authoriza-tion has been granted, or dividends with Central Bank's specific authoriza-tion.

• Cross-border transfers destined to meet the payment of the principal of finan-cial obligations require Central Bank authorization for the following 90 days. Indebtedness involving multilateral creditors is exempted from this require-ment. As no reference is made to interest payments, cross-border transfers to pay interest no longer require Central Bank authorization.

The most important measures concerning the trade related transactions were (Com 3473):

• Collections resulting from exports, net of prefinancing loans, are to be liqui-dated in the free foreign exchange market within the period established by other regulatory entities. The pesos resulting from the liquidation of exports proceeds will be deposited in sight accounts in the local financial system.

• Imports will require a minimum financing period (from 180-360 days). Criti-cal goods (i.e., medicine, certain raw goods, etc.) will be exempted from this requirement and will be subject to be paid in advance.

Feb. 11, 2002–Floating Exchange Regime. The peso started to float, the restrictions on deposit withdrawals were effectively lifted for payroll accounts, and banks re-sumed almost normal activity. The Central Bank suspended payment and prepayment of loans for Feb. 11-13, however, with the sole exception of credit card financing. The exchange rate closed at 2.15 pesos per dollar.

Feb. 14, 2002–Duties on Oil Exports. Although strong lobbies against the tax on oil exports created by the Economic Emergency Law 25.561 (Jan. 6) suggested that it was not going to be implemented. The government finally signed a decree (decree 310/02) establishing a 20% duty on oil exports.

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Feb. 15, 2002–Bankruptcy Law Partial Veto and Signed into Law. The reform of the bankruptcy law was signed into law by the president, after he vetoed some of the provisions included in the bill approved by the Congress. In general, the new law opted for the protection of debtors' rights over those of creditors, which, combined with the pesification and restructuring of debts instructed by Decree 214 (Feb. 3, 2002), virtually forced all issuers into default, destroying the incentive structure needed for a healthy credit culture and indefinitely delaying the restoration of credit. The most relevant measures of the law were:

• The exclusivity period during which firms that have filed for reorganization proceedings (similar to filing for protection under Chapter 11) are entitled to submit proposals to their creditors is extended from 30 to 180 days, and the ceiling that the previous law set on the reduction in the original amount owed that debtors could present was eliminated.

• Judicial or extra judicial foreclosures are suspended for 180 days, including those of mortgages and other pledged loans, and those provided for in the Se-curitization Law. New bankruptcy requests were also suspended.

• The section of the Bankruptcy Law governing "cram down" is eliminated. This was an alternative that provided for the acquisition of troubled compa-nies by creditors, which besides being a valid option for debtors and credi-tors, discouraged abusive behavior on the part of debtors during the negotia-tion period.

Feb. 27, 2002–Agreement Between Federal Government and Provinces. An agree-ment between the federal and the provincial governments was finally signed. The agreement included the removal of the fixed amount that had to be transferred to provinces (with the objective of sharing the costs of Argentina's deteriorating eco-nomic activity with the provinces), the inclusion of 30% of the financial transactions tax in the revenues shared, and the restructuring of the provincial debt. The last in-cluded a plan to issue a central government bond to assume the provincial debt (while debt service was to be discounted from coparticipation revenue), the pesifica-tion of the debt at the exchange rate of ArP1.4 per dollar, and the instrumentation of a still-undefined foreign exchange hedge for provincial multilateral debt. It was also agreed that provincial debt issued in foreign markets was to receive the same treat-ment as central government foreign debt. A precondition for the debt restructuring was a reduction of about 60% in the provincial fiscal deficit. The new Coparticipa-tion Law was to be passed by the end of 2002. A highly controversial issue that was not included in the agreement regarded limiting the issuance of provincial currencies.

Feb. 28, 2002–Inflation. During February, consumer prices and wholesale prices in-creased 3.1% and 11% respectively, despite the continuing deep recession.

March 1, 2002–Liquidity Reserve Requirements. The Central Bank changed liquidity regulations, imposing a requirement of 40% for most deposits (CB res. 3498). Prior to this change, "old deposits" had an average 18% requirement, while deposits ac-quired from other institutions had a 100% requirement, since the Central Bank needed funds to grant repos in the context of a flight-to-quality within the financial system. With the new regulations, the Central Bank estimated a similar amount of li-quidity reserves for the whole system, but ensured that banks would be more willing to attract funds as they would not have to place 100% of new deposits in reserves.

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March 4, 2002–Government Bonds for Depositors and Banks/Pesification of Public Debt/Duties on Exports/Foreign Exchange Controls/Other Economic Measures An-nounced. The Minister of Economy announced a new set of measures. Most rele-

vant were:

• Depositors will have the option to receive new government bonds in ex-change for rescheduled deposits up to $30,000. Dollar depositors will be enti-tled to choose between a peso bond or two dollar-denominated bonds. Both new dollar bonds will have 10-year maturities: one with an interest rate of 2% and principal payable in annual installments; the other with an interest rate of Libor + 1%, both interest and principal payable at its maturity. The peso bond is to be issued with a five-year maturity, indexed with inflation and a 3% in-terest rate. The period to choose government bonds in exchange for resched-uled deposits expires April 15. Banks will be able to reduce their exposure to the Argentine government. In exchange for the reduction of liabilities that will result from depositors choosing government bonds instead of deposits, banks will transfer part of their public sector holdings to the Treasury. The to-tal amount of original dollar deposits subject to be exchanged by dollar gov-ernment bonds is approximately $35 billion.

• A new peso government bond will be issued to compensate banks for the asymmetric pesification of assets and liabilities (dollar loans were converted into pesos at the 1:1 parity, whereas deposits were converted at 1:1.4). The total amount of the compensation for the financial system is approximately $15 billion.

• All government debt issued under Argentine law (municipal, provincial, and federal indebtedness) will be converted into pesos at the 1.40 parity and in-dexed to inflation. Loans that replaced government securities in last Novem-ber's debt exchange are also included. The total amount of public sector debt subject to this pesification was aproximately $52 billion. Individual investors and local pension funds afterwards filed legal actions against this measure.

• Pesified loans will have maximum interest rates of 4% for individuals and 7% for corporates.

• Futures and forward markets will continue operating in dollars.

• Banco Nación is to establish a $1 billion credit line to finance certain produc-tive activities (export financing, SME working capital, tourism, agricultural sector, etc.). Other initiatives of this kind were said to be under implementa-tion.

• A general tax on exports was established (10% for primary goods and 5% for manufactured goods). Collections of this new tax were estimated at about $1.4 billion annually.

A new Central Bank regulation (CB res. 3501) removed the need to request Central Bank authorization to make transfers to meet principal payments on cross-border debt, if at least 80% of the maturing principal amount was refinanced for at least 180 days. This regulation provided both debtors and creditors with significant incentives to restructure principal, as creditors could feel compelled to enter into these renego-tiations to avoid the uncertainties regarding Central Bank approval to transfer funds.

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March 5, 2002–Federal Budget Approved. The Congress approved the federal budget for 2002. The main assumptions of the law included a decrease of GDP and tax col-lections of 4.9%, a fiscal deficit target of $3 billion (1% of GDP), and inflation of 14%. These assumptions did not seem realistic at the time of the approval, since tax collections had already fallen by 20% both in January and February, and consumer prices had increased 5.4% in the first two months of the year.

March 12, 2002–Government Bonds for Banks. The government issued a decree (N 494) describing the new government bonds to be issued to compensate depositors up to an amount of $30,000 (see description of terms and conditions under the set of measures announced on March 4, 2002), and to compensate banks for the pesifica-tion, including the reduction in equity caused by the banks' dollar-denominated cross-border debt, which was no longer backed by dollar assets after the pesification of the economy. Banks will be compensated by a peso bond for the difference of 0.4 that resulted from the conversion of dollar assets into pesos at the 1:1 parity, while dollar deposits were converted at the 1:1.4 parity. Banks will be entitled to receive a dollar bond to compensate the loss in equity caused by the dollar liabilities that were not subject to pesification (mainly cross-border debt).

March 13, 2002–Pesification of Economy Regulated. The Central Bank issued regu-lations implementing the conversion into pesos at the 1:1 parity of most dollar-denominated debts or contracts within the financial system or among private parties (Com 3507). Besides the pesification itself, other important provisions of this

regulation were the following:

• Debts originated from foreign trade transactions, future and forwards con-tracts, and obligations issued under or ruled by foreign law are not subject to pesification, and remain dollar denominated.

• For a period of six months (from April 2 to Aug. 3, 2002), ongoing debt ser-vice (both interest and principal) will maintain its original schedule and in-stallments will be converted into pesos at the 1:1 parity. After this period, these payments will be complemented by an additional amount that will result from the application of the coefficient adjusting for inflation (CER), and from then on, all new payments will be adjusted according to inflation.

• From April 2 to Aug. 3, 2002, bullet principal payments will be granted a six-month grace period and will be adjusted according to inflation.

• Annual interest rates will be capped at 3.5% for pesified mortgages and 6% for other guaranteed loans to individuals and companies. Annual interest rates will be capped at 5% and 8% for other pesified unsecured debt.

Interbank loans will be converted into pesos at the 1.4 parity, except for those credit lines destined to provide foreign trade financing, which will remain dollar denomi-nated.

March 25, 2002–Measures to Control Dollar Price/Foreign Exchange Controls. The rising exchange rate (reaching ArP4 per dollar at one point) led the government to impose a series of measures (mostly through the Central Bank) to control the price of the dollar by inducing sales of foreign currency in the local foreign exchange market by exporters and banks. Main measures were:

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• The Central Bank reduced the hours during which exchange houses could open (CB res. 3530; which seemed counterproductive to the objective of calming the population's desperate demand for dollars).

• A Central Bank regulation established that the conversion of the export pro-ceeds into pesos could not take longer than 10 days after the foreign currency funds were deposited in the local bank involved in the trade transaction or were made available in foreign accounts (CB res. 3534).

• The Central Bank announced that all banks whose net foreign exchange hold-ings exceeded 5% of equity had to reduce their position before Apr. 19, or would be subject to penalties and prevented from operating in the foreign ex-change market (CB res. 3511 and 3512).

• A new Central Bank regulation established that the payment of both interest and principal external financial obligations required Central Bank authoriza-tion. In previous regulations, the restrictions were on the cross-border trans-fers to meet principal payments of financial obligations (interest payments did not require authorization), and not on the payment of the obligations themselves. Therefore, if the bank or corporation had funds abroad, they could be used to pay the obligations without requesting authorization. Al-though the new language of the regulation would not leave room for that al-ternative, when contacted, Central Bank representatives said that it had not been their intention to require authorization for the "payment" of obligations, but for making "transfers" to pay the obligations. Although the regulation was addressed to banks, because corporations operate in the foreign exchange market through financial institutions, all firms were potentially affected by these new restrictions. In any case, the ambiguity of the text added to the general uncertainty. The regulation also emphasized that the authorization had to be granted for "financial obligations," implying that foreign trade transactions were excluded from this new requirement (CB res. 3537)

March 26, 2002–Foreign Exchange Controls. The Central Bank announced that the regulation that had been issued the day before regarding new restrictions on cross-border transfers (CB res. 3537) was to expire 30 days after its publication (CB res. 3543). This announcement was just another indication of the degree of improvisation in the implementation of new measures.

March 29, 2002–Inflation/Tax Collections. During March, consumer prices and wholesale prices increased 4% and 11.2%, respectively, accumulating increases of 5.9% and 25.7% for the first quarter and seriously diminishing the purchasing power of salary, thus contributing to increased social tensions. Tax collections decreased only 7.3% against the previous year, which implied an improvement from January and February figures (negative 20%).

April 3, 2002–Social Plan Announced. The government announced a plan of subsi-dies for the unemployed (decree 565/02), which would amount to $3 billion (appar-ently to be financed with new duties on exports), in an attempt to ease social tensions and stimulate a reactivation of the economy through consumption.

April 4, 2002–Deposits to be released. The Central Bank issued a regulation stating that, from January 2003, banks would be entitled to give all rescheduled deposits back to investors if they chose to (CB res. 3555). Apparently, the Ministry of Econ-

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omy was not in agreement, and rumors of the measure being withdrawn started to gain strength.

April 5, 2002–Duties on Exports. The Ministry of Economy established new duties on exports. The export tax on grains and vegetable oils was raised to 20% (grains and processed oilseeds increased from 10%, vegetable oils and meals increased from 5%). The government estimated the tax increase could raise additional collections of $1 billion. There were no changes on taxes on industrial and agro-industrial exports, which remained at 10% and 5%, respectively, nor on petroleum exports, which re-mained at 20%.

Source: Standard and Poor’s (2002)

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Appendix 2: Alternative set of model equations

The set of model equations below take into account the results of the calibration exer-

cise. The main differences are the form of the crisis reverse feedback to fundamentals,

and different and simpler sovereign spread equation (debt dependent, not crisis prob-

ability dependent, and basing on the exogenous country, and time-specific spreads).

Probability of the crisis now negatively depends on international liquidity, current ac-

count surplus, budget surplus and negative of M3 growth in the previous periods.

1 1 1 t-1

1 1 1 t-1

( 3 )

( 3 )( 1)1

t t t

t t t

l CA G M

t l CA G M

eprob y

e

α β γ δ ι

α β γ δ ι

− − −

− − −

+ + + +

+ + + += = =

+�

Current account surplus increases (or deficit falls) in case of a crisis, by a fixed percent-

age of GDP, φ.

1t t tCA CA y φ−= + , where φ > 0

The cost of the reserves is equal to the spread between local and foreign interest rates.

The spread depends on a set of country-specific factors εc, and grows with the total

amount of external debt, Dc,t-1

( )

, 1

*

c t

i i

Dξ

−

∂ −=

∂

Increasing international liquidity l requires long-term borrowing higher by a multiple of

short-term debt. This means the marginal cost of reserves equals to

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, 1c t

BIS BISMC

GDP GDPε ζ−

= +

,

where εc, t-1 is the actual foreign currency long bond spread faced by country c in the

previous period, BIS is the stock of short-term debt, and GDP is the nominal GDP.

The marginal costs of reserves extended including the dynamic effects of postponing the

crisis and quasi fiscal costs of additional borrowing are then:

( ) ( )0

11 1 )

n

n

MC rMC MC llTMC MCr r r MC

β β γφγφ δδ

β β β β δ

∞

=

∂ ∂ − −− + ∂ ∂= + = + + − −

∑

��

,

where MC is immediate marginal cost of reserves, φ is the impact of crisis on the cur-

rent account, while γ, δ, β are the parameters setting the impact of, respectively, current

account, budget, and international liquidity influencing the probability of the currency

crisis �.

The policymaker tries to minimise the loss function L, subject to liquidity stock lt-1

( )

( )( )( )

1 1

3 1

11 1

1 1 110 0

21

2 2t t

M t

tt t

l l

t t tt

le MC r MC Sinh

MC r ll l

Cosh Cosh CA GL l MTCdl dl

l r MC

ι βγ φ χ β β δ

ββ β

α γ δ

χβ β δ

− −

−

−− −

− − −

−

+ + −

+ −

+ + + + ∂ = − =∂ + −∫ ∫�

MC is the immediate marginal cost of reserves, χ is the (positive) crisis cost, and sinh(x)

and cosh(x) are hyperbolic sine 2

x xe e− −

and cosine 2

x xe e− +

respectively.

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Appendix 3: Model optimisation Mathematica© 5 code

Variable and libraries initialisation, setting calibrated parameter (params) values, ini-tialising a set of median country variable values (ceteris) for testing.

Setting up the model. � is the probability of the crisis, ∆CA is the current account fol-lowing the crisis.

Loading the data from kbn2.txt and setting up variable substitution tables.

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Setting up evaluated marginal cost (koszt[country number]) and marginal benefit (zysk[country number]) functions with the variables and parameters substituted with actual data. kosztsmall function excludes the second round fiscal effects of reserve borrowing and postponing the crisis.

Key function definitions. Zyskkoszt takes the country number and crisis cost χ as in-puts, and produces the chart of marginal costs and benefits. International liquidity is on the horizontal axis. The headers show crisis cost χ used, actual liquidity, and im-plied liquidity for the assumed χ. The function does not display the chart (it retains it for use in the chart sets).

NCalka[optimum] function embedded in the definition of zyskkoszt is numerical defi-nite integration of marginal cost between zero and optimum international liquidity. Later, FindMinimum[NCalka] function is used to find the liquidity value minimising the loss function.

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Opticurve takes the country number and minimum and maximum values of interna-tional liquidity as inputs, and produces optimal liquidity chart, with crisis costs on the horizontal axis and suggested liquidity on the vertical axis. A horizontal line is added, indicating actual liquidity held by the country. As above, minimum of the loss func-tion is found numerically by a combination of NCalka and FindMinimum.

Optitable is a text version of Opticurve, used for finding the crisis cost value χ closest matching the one implied by the actual policymakers' decisions on international liquid-

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ity. It takes the country name and minimum value of crisis cost as input, and returns single value of the crisis cost, representing intersection of Opticurve and horizontal line of the actual country's liquidity.

The following (rather inelegant) code displays the set of marginal liquidity cost and benefit charts for the countries in the sample. Zyskkoszt function uses the output of op-titable as input, so that the charts represent marginal cost and benefit curves for the crisis costs implied by actual international liquidity of the country in question.

The code below shows optimal liquidity curves for all the countries in the sample, in a similar way as the code above.

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The following displays the costs of liquidity for the countries in the sample, being the definite numerical integration of the marginal cost curves between zero and actual in-ternational liquidity held.

Second chart is the set of marginal benefit curves for the countries in the sample.

The final command produces a table including the size of dynamic effects (fiscal im-pact of reserve borrowing, and costs of postponing the crisis) in % of GDP

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Appendix 4: The list of countries used for estimations in

Chapter 5

Albania Algeria Argentina Bangladesh Belarus Bolivia Botswana Brazil Bulgaria Chile China Colombia Costa Rica Côte d'Ivoire Croatia Cyprus

Czech Republic Dominicana Ecuador Egypt Estonia Georgia Ghana Honduras Hong Kong Hungary India Indonesia Israel Jordan Kazakhstan Kenya

Korea Latvia Lithuania Malaysia Mauritius Mexico Moldova Morocco Mozambique Nigeria Pakistan Panama Peru Philippines Poland Romania

Russia Singapore Slovak Republic Slovenia South Africa Sri Lanka Tanzania Thailand Tunisia Turkey Ukraine Uruguay Venezuela, Rep.

Bol. Zimbabwe