Equilibrium ER

• PPP: – Empirical evidence:

• Define:– Test the behavior of RER

» If RER is non-stationary -> PPP does not hold» If RER is stationary -> PPP might hold» Conclusion (Rogoff (1986)): RER is mean reverting

albeit very slowly with half statistics of mean reversion around 4 years.

This is too long time period to be explained by reasonable nominal rigidities or barriers to arbitrage.

1*

p

ep

p

epRER

*

Rogoff, K. (1996),”The Purchasing Power Parity Puzzle”, Journal of Economic Literature, vol. 34, June 1996, pp.:647-668

Fact: RER is highly persistent• Implications:

– Problems with econometric inference– We need to explain these large swings in RER

• Unfortunately, many theories are lacking micro-foundations• Possibly the best explanations – Balassa-Samuelson efect:

– Poorer countries have cheaper price level– Improvement in productivity in tradable sector (relative to foreign

country) appreciate ER.– Improvement in productivity in non-tradable sector (relative to foreign

country) depreciate ER

Balassa, B. (1964),”The Purchasing Power Parity Doctrine: A Reappraisal”, Journal of Political Economy, vol. 72, December, pp. 584-596

Samuelson, P. (1964),”Theoretical Notes on Trade Problems”, Review of Economics and Statistics, vol. 23, pp.: 1-60

Harrod, R. F. (1933), International Economics, London: James Nisbet and Cambridge University Press

Empirical evidence : B-S effect

y = 0.78x - 3.66

R2 = 0.86

-1.5

-1.0

-0.5

0.0

0.5

3.2 3.4 3.6 3.8 4.0 4.2 4.4 4.6 4.8 5.0 5.2

Logarithm of price level

Logarithm of GDP per capita (in PPP terms) Richer country

More expensive country

B-S is not enough– MacDonald and Ricci (2001): Enlarged standard B-S

framework by distribution sector.– MacDonald and Ricci (2002): Tested implication of new

trade theory on ER. (They focus on imperfect substituability of tradables and on the importance of competitiveness)

– others

• There is no theory (with proper micro-foundations) satisfactory explaining behavior of RER

MacDonald, R. and Ricci, L. (2001),”PPP and the Balassa Samuelson Effect: The Role of the Distribution Sector”, IMF Working Paper, WP/01/38

MacDonald, R. and Ricci, L. (2002),”Purchasing Power Parity and New Trade Theory”, IMF Working Paper, WP/02/32

Example of other theories

• Monetary model of ER:

iymp 21

*2

*1

** iymp *pep

)()( *2

*1

* iiyymme

• Let PPP condition hold only in the long-run, and assume prices are sticky in the short-run -> Dornbusch overshooting model.

• Able to explain excessive volatility of ER

• But: Why are prices sticky?

Slovak price level low

30%

50%

70%

90%

110%

130%

Slovakia Poland CzechRepublic

Hungary England Switzerland

30%

35%

40%

45%

50%

55%

60%

1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003

Slovakia Poland Czech Republic

Hungary weighted CEE average

convergence

Slovak FDI inflows

1994-1998 1999-2002 2003-2006e

average annual ex-privatisation FDI inflows

US$304m US$629m US$1165m

Empirical development

• Various approaches– Most common: BEER and FEER– Persistent behavior of RER -> problems with

econometric estimates– Assumption of non-stationarity cannot be

satisfactory rejected due to ‘short sample’– In all BEER estimations, RER is assumed to be

I(1) – i.e. simple PPP does not hold

BEER

• Most common

• Tries to find direct behavioral link between RER and fundamentals (assumes variables to be I(1)).

• Absolutely no micro foundation

• Fundamentals: everything one suspect might affect RER

REER indices

65

70

75

80

85

90

95

100

105

93 94 95 96 97 98 99 00 01 02 03 04

REER CPI based REER PPI based REER PPI (SK manufacturing) based

appreciate

RER (de-trended)

-15%

-10%

-5%

0%

5%

10%

15%

20%

93 94 95 96 97 98 99 00 01 02 03 04

REER CPI based REER PPI based

REER PPI (SK manufacturing) based REER ULC based

overvaluation

undervaluation

In-sample approach – estimates are likely biased

0.5

1.0

1.5

2.0

2.5

3.0

3.5

4.0

94 95 96 97 98 99 00 01 02 03

example of RER 'true equilibrium' of RER

estimated BEER

-50%

-40%

-30%

-20%

-10%

0%

10%

20%

30%

94

95

96

97

98

99

00

01

02

03

'true deviations from equilibrium

estimated exchange rate misalignment

Unit root tests

• Single time serries– We performed: ADF , KPSS Kwiatkowski-

Phillips-Schmidt-Shin (1992) , Ng-Perron Ng-

Perron (2001) – Conclusion: All series are I(1)

Kwiatkowski, D., Phillips, P. C. B., Schmidt, P. and Shin, Y. (1992),”Testing the Null Hypothesis of Stationary against the Alternative of a Unit Root”, Journal of Econometrics, vol. 54, pp.: 159-178

Ng, S. and Perron, P. (2001),”Lag Length Selection and the Construction of Unit Root Tests with Good Size and Power”, Econometrica, vol. 69, pp.: 1519-1554

Fundamentals• We chose:

» Proxy for Ballassa-Samuelson effect (e.g. relative price of non-tradables vs tradables (NT) or relative labour productivity in tradables vs nontradables (LP))

» (ToT) Terms of trade (i.e. export prices relative to import prices) intend to capture changes in international economic environment.

» (gov) Share of government spending on GDP - intends to capture the effects of fiscal policy.

» (rr) Real interest rate differential. Higher interest rate differential should attract more capital inflows.

» Proxy for country risk. We used following proxies: country rating (rat), spreads on Eurobonds (spread), our currency vulnerability index adjusted for movements in RER (vul); NFA

Est

imat

ion

of B

EE

R

Single country approach

Able to estimate country specific behavior

Short sample (about a decade) , RER is highly persistent Estimates are not robust

RER is likely to be undervalued for longer period in the first phase of transition

Estimates are biased

Plenty of ad hoc-factors affecting early stage of transition

Possibility of structural breaks

Questionable quality of data on the early stage of transition

Measurement error

Cross section approach Missing time series dimension

(Impossible to account for country specific effects)

Panel data approach

In-sample estimates

Out-of-sample estimates

Including only accession countries

Partially helps to solve problems connected with short sample

Estimates are still biased

Using data from early stage is still questionable

Including broader set of countries

Heterogeneity ?

Helps to solve problems connected with short sample

Biased L-R estimates

Biased constant term

Heterogeneity ?

Estimates are not biased finally

No constant for accession country (country-specific effect)Heterogeneity ? (is homogenous long run behavioral assumption for each country plausible?)

+

-

-

-

+

-

+

+

-

Aims to estimate ‘specific’ behavior of countries in transition

Eq. b1 Eq. b2 Eq. b3 Eq. b4 Eq. b5 Eq. b6 Eq. b7

Dyn Static Dyn Static Dyn Static Dyn Static Dyn Static Dyn Static Dyn Static

TN -0.97 -0.35 -0.63 -0.16 -0.22 -0.08

(-4.6) (-4.6) (-3.9) (-2.8) (-2.3) (-1.6)

ToT 3.67 0.6 2.65 0.77 1.54 0.74

-4 -2 -4 -3.5 -3.6 -4.2

Gov 0.65 -0.3 0.74 0.05 0.41 -0.06 0.56 -0.12 1.27 -0.06 1.19 0.2

-2.76 (-3.7) -3.9 -0.7 -3.5 (-1.2) -3.5 (-1.4) -4.7 (-0.5) -5 -2.5

RR 0.94 0.39 0.7 0.2 0.68 0.1 0.46 0.43 0.26 0.22

-4.9 -5.2 -4.1 -3.5 -4.5 -1.9 -5.5 -7.3 -1.9 -3.2

LP 0.36 0.17 0.75 0.37 0.58 0.09

-3.5 -2.4 -4.4 -4.3 -3.1 -1.3

NFA 0.43 0.65

0.42 0.66

-2.5 -10.6 -2.4 -10.4

Rating 0.043 0.041 0.014 0.03

-7.8 -15.2 -2 -12

Vul -0.11 -0.04 -0.04 -0.06

(-5.5) (-5.2) -4.2 (-9.1)

R2

(static e.)

38.8% 67.2% 73.6% 75.7% 62.2% 37.8% 63.7%

-40%

-30%

-20%

-10%

0%

10%

20%

30%

93 94 95 96 97 98 99 00 01 02 03 04

Eq. 1

-25%

-20%

-15%

-10%

-5%

0%

5%

10%

15%

93 94 95 96 97 98 99 00 01 02 03 04

Eq. 2

-15%

-10%

-5%

0%

5%

10%

93 94 95 96 97 98 99 00 01 02 03 04

Eq. 3

-20%

-15%

-10%

-5%

0%

5%

10%

15%

93 94 95 96 97 98 99 00 01 02 03 04

Eq. 4

-20%

-15%

-10%

-5%

0%

5%

10%

93 94 95 96 97 98 99 00 01 02 03 04

Eq. 5

-25%

-20%

-15%

-10%

-5%

0%

5%

10%

15%

93 94 95 96 97 98 99 00 01 02 03 04

Eq. 6

-20%

-15%

-10%

-5%

0%

5%

10%

15%

93 94 95 96 97 98 99 00 01 02 03 04

Eq. 7

In-sample approach - results

Historical ave (YoY) min max

NT 2.10% 20% 100% 1.20%

LP 2.40% 20% 80% 1.20%

Terms of Trade

-0.50% 70% 370% -1.10%

Fiscal spending

-1.80% 0 75% -0.70%

Real IR Differential

0.10% 20% 100% 0.10%

rating 0.5 1.40% 4.30% 1.40%

vulnerability -17.43% -4% -11% 1.30%

nfa 2.40% 40% 70% 1.30%

0.90%

1.07%

LR elasticity Implied Contributions:

midBallasa-Samuelson effect (convergence) 1.20%

Risk Profile 1.40%Sum:

Historical average annual appreciation of REER:

Improvement – panel considerations

• How to estimate?– Assumptions:

• Homogeneous L-R behavior

• Heterogeneous (country specific) short-run behavior

• Data are likely I(1)

• Other country specific conditions affecting L-R:– Fixed effects

Panel Unit root tests

• We performed:– Levin, Lin and Chu t, Levin, Lin and Chu (2002);

Breitung t-stat, Breitung (2000)

– Im, Pesaran and Shin W-stat, Im, Pesaran and Shin

(2003); ADF - Fisher Chi-square, PP - Fisher Chi-square, Maddala and Wu (1999) and Choi(2001)

– Hadri Z-stat, Hadri (2000)

Conclusion: All variables are I(1) rather than I(2) or I(0)

ReferencesLevin, A., Lin, C. F., and Chu, C. (2002),”Unit Root Tests in Panel Data: Asymptotic

and Finite-Sample Properties,” Journal of Econometrics, Vol. 108, pp.:1-24

Breitung, J. (2000),”The Local Power of Some Unit Root Tests for Panel Data,” in Baltagi (ed.), Advances in Econometrics, Vol. 15: Nonstationary Panels, Panel Cointegration, and Dynamic Panels, Amsterdam: JAI Press, pp.:161-178

Im, K. S., Pesaran, M. H., and Shin, Y. (2003),”Testing for Unit Roots in Heterogeneous Panels”, Journal of Econometrics, Vol. 115, pp.: 53-74

Maddala, G. S., and Wu, S. (1999),”A Comparative Study of Unit Root Tests with Panel Data and A New Simple Test, Oxford Bulletin of Economics and Statistics, Vol. 61, pp.:631-652

Choi, I. (2001),”Unit Root Tests for Panel Data,” Journal of International Money and Finance, Vol. 20, pp.:249-272

Hadri, K. (2000).”Testing for Stationarity in Heterogeneous Panel Data,” Econometrics Journal, Vol. 3, pp.:148-161

Cointegration tests

• We used following residual based cointegration tests:– Kao (1997) – Kao (1999) – Pedroni (1995) – Pedroni (1999)

(15 tests together)

critical probability critical probability

Residual based panel cointegration tests

4 explanatory variables (excluding ToT)

3 explanatory variables (excluding ToT and fiscal

spending)

0.70%

Kao (1997)

 DF_Rho -5.1 0.00% -2.5

7.40%

 DF_Rho* -9.5 0.00% -6.4 0.00%

 DF_t_Rho -2.8 0.20% -1.4

3.60% DF_t_Rho* -3 0.20% -1.8

Kao (1999)

7.30%ADF -2.7 0.40% -1.5

Pedroni (1995)

0.00%

 TN1_rho -15.4 0.00% -10.9 0.00%

 t_rho_NT -75.8 0.00% -69.1

0.00% TN2_rho -15.2 0.00% -10.7

Pedroni (1999)

20.00%Standarized Panel V-statistics -0.7 -0.8

Panel V-statistics 18

24.80%

26.2

11.80%Standarized Panel Rho-statistics -7.8 1.2

Panel Rho-statistics -93.6

0.00%

-22.5

19.50%Standarized Panel PP-statistics -7 0.9

Panel t-statistics (nonparametric) -11.2

0.00%

-5.1

0.00%Standarized Panel ADF-statistics -504 -267

Panel t-statistics (parametric) -489

0.00%

-251

Group Rho-statistics -93.8

0.00%

-22.9

1.90%

3 explanatory variables (excluded ToT and fiscal spending)

PLSDV PDOLS PMG

time dummies

time dummies

time dummies

RR 0.34 0.31 0.56 0.52 0.43 1.05

t-ratio 4.4 3 3.3 2.3 3.3 6.9

CP 0.42 0.26 0.38 0.38 0.14 1.16

t-ratio 6.7 1.4 3 1.5 1.3 3.8

risk 0.039 0.04 0.06 0.062 0.062 0.095

t-ratio 5.3 3.8 2.5 2.3 4.9 7.2

No Yes

Fixed effects

Yes Yes Yes Yes Yes Yes

Time effects

No Yes No Yes

4 explanatory variables (ToT  excluded)

SE PDOLS PMG

time dummies

time dummies

time dummies

RR 0.28 0.24 0.43 0.4 0.17 0.94

3.7 2.4 4.5 4.2 1.6 5

CP 0.58 0.54 0.65 0.68 0.45 1.33

9.6 3.3 8 6.5 4.3 4.3

risk 0.04 0.06 0.05 0.06 0.06 0.1

5.9 5.4 3.9 4.4 5.9 8

PS (seasonally adjusted) 0.72 0.72 0.85 0.9 0.82 0.31

8.6 7.8 7.4 8.2 4.5 1.5

No Yes

Fixed effects Yes Yes Yes Yes Yes Yes

Time effects No Yes No Yes

time dummies

time dummies

time dummies

time dummies

RR 0.28 0.24 0.44 0.45 0.55 0.59 0.07 0.64

3.7 2.4 5 5.1 5.8 7.2 0.9 3.7

CP 0.58 0.54 0.67 0.68 0.7 0.68 0.63 1.39

9.6 3.3 9.4 8.3 11.1 11.6 9.2 5

risk 0.04 0.06 0.05 0.06 0.07 0.08 0.04 0.1

5.9 5.4 4.8 5.3 5.5 7.3 4 8.8

PS trend 0.72 0.72 0.85 0.84 0.8 0.73 0.93 0.6

8.6 7.8 8.5 8.9 7.4 7 11.2 2.8

Fixed effects Yes Yes Yes Yes Yes Yes Yes Yes

Time effects No Yes No Yes No Yes No Yes

4 explanatory variables (ToT excluded)

SE PDOLS PMG

Leads and lags = 1 Leads and lags = 2

All five variables

SE PDOLS PMG

time dummies

time dummies

time dummies

RR 0.28 0.24 0.48 0.53 0.07 0.84

3.8 2.5 5.5 6.1 0.78 6.4

CP 0.62 0.59 0.73 0.81 0.39 1.38

8.8 3.5 8.2 8.8 3.89 7.2

risk 0.05 0.06 0.06 0.07 0.06 0.1

5.9 5.6 5.8 6.4 7.24 12

ToT 0.1 0.15 0.27 0.45 -0.01 0.27

0.9 1.2 1 2.3 -0.05 2.2

PS trend 0.74 0.75 0.79 0.84 0.7 0.42

8.6 7.9 7.9 9.4 7.11 2.8

No Yes

Fixed effects Yes Yes Yes Yes Yes Yes

Time effects No Yes No Yes

ResultsEstimate

Historical ave (YoY) min max

CPI/PPI 2.00% 40% 130% 67% 1.35%

Y/L 2.50% 30% 50% 43% 1.06%

Terms of Trade

-0.50% ???

Fiscal spending (trend)

-1.40% 42% 93% 85% -1.20%

Real IR Differential

0.30% 24% 94% 44% 0.10%

Risk Profile 0.2*Rat+vul 22.90% 4% 10% 5.50% 1.30%

<1.3%

1.07%

LR elasticity Implied Contributions:

Ballasa-Samuelson effect (convergence) 1.20%

Sum:

Historical average annual appreciation of REER:

ER misalignments

-15%

-10%

-5%

0%

5%

10%

94

95

96

97

98

99

00

01

02

03

3 variables (IR, Balass-Samuelson, risk)

4 variables (with public spending)

An out-of Sample Experiment

-25%

-20%

-15%

-10%

-5%

0%

5%

1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003

exchange rate misaligtnments

Alternative approach: FEER

• Flow approach: FEER = value of RER consistent with medium achievement of sustainable C/A balance

• Use of econometric models

• Most important: FT equations

FT equations

•

•

Exports Imports

cdummycFDIaforeignDRERreal

)3.0)8(log(%123)log(%153)log(%35)exportslog()6.7()5,4()5.2(

cdummydemandtariffimportRERreal )log(%72)_1(log(%34)importslog()0.31()6.3(

-10%

-8%

-6%

-4%

-2%

0%

2%

4%

6%

8%

10%

12%

93 94 95 96 97 98 99 00 01 02 03

deviations from steady-state

-8%

-6%

-4%

-2%

0%

2%

4%

6%

8%

10%

93 94 95 96 97 98 99 00 01 02 03

deviations from steady-state

External gap at potential level

-15%

-10%

-5%

0%

5%

10%

94 95 96 97 98 99 00 01 02 03

FT as % of GDP (last 12 month) at potential level FT as % of GDP (last 12 month)

FEER

-20%

-15%

-10%

-5%

0%

5%

10%

15%

20%

94 95 96 97 98 99 00 01 02 03 04

ER misalignments according to FEER consistent with 5% gap

ER misalignments according to FEER consistent with 6.8% gap

30

32

34

36

38

40

42

44

46

48

94 95 96 97 98 99 00 01 02 03 04

EUR/SKK

'equilibrium' (FEER) EUR/SKK (5%)

'equilibrium' (FEER) EUR/SKK (6.8%)

Improvement – panel evidence

Slovak data panel Slovak data panel

RER -35% -90% RER*(1-import tariff) 34% 20%

foreign demand 153% 150% (constraine

d)

domestic demand (real) 100%

cFDIa 123% 130% exports (real) 70%

Single country estimations covers period from 3Q93/1Q94 to 4Q03. Panel involves V-4 countries and covers period from 1Q95 to 4Q03.

Estimates of long-run elastic ities

exports imports

72%

OLS DOLS PMG

leads and lags = 1 leads and lags = 2

time dummies

time dummies

time dummies

time dummies

RER_ppi -51.30% -34.40% -93.80% -95.80% -147.80% -172.90% -78.20% -83.30%

-2.8 -2.1 -2.5 -2.6 -4 -5.4 -3.8 -3.9

log(03+cfdia(-8))

103.70% 11.60% 130.40% 119.10% 141.20% 139.60% 152.30% 154.60%

16.6 1 8.8 7 9.9 10.4 21.5 22.1

Fixed effects

Yes Yes Yes

No Yes

Yes Yes Yes Yes Yes

Time effects

No Yes No Yes No Yes

OLS DOLS PMG

time dummies

time dummies

time dummies

RER_PPI*(1-import tariff)

13.40% 19.90% 17.10% 27.40% 11.50% 12.80%

2.2 3.3 1.4 2.3 2.2 3.1

domestic demand 101.70% 99.80% 88.70% 91.60% 60.00% 104.70%

15.8 16.7 6.3 7.2 9.4 24.4

exports 64.50% 74.90% 69.00% 67.70% 81.80% 81.10%

27.2 18.1 14.4 14.1 39.3 29.3

Fixed effects Yes Yes Yes Yes Yes Yes

Yes No YesTime effects No Yes No

Equilibrium estimates (FEER)

FT equation according to:

Targeted C/A deficit

4Q03 2Q04 4Q04

Slovak data 5% 40.21 39.13 38.77

Panel 5% 40.69 39.64 39.27

Slovak data 6.80% 39.67 38.61 38.26

Panel 6.80% 40.17 39.14 38.78

Actual EUR/SKK 41.18 40.09

Conclusion

• Koruna will definitely be appreciating in real terms, at least for the next two decades. This is connected with fact that the country is economically just at 40% of EU average and this huge gap will continue to be diminishing slowly in the future.

• It is tricky to estimate the precise speed of sustainable appreciation. Data problems, short sample, and structural changes are the obvious challenges. First results point to more than 1.7% real appreciation in the years ahead. Then the pace of appreciation is likely to slow down to about 0.5-1.5% in the medium- to longer-term.

• As for the current equilibrium level of Koruna, it is even more tricky to estimate it. According to the preliminary research, koruna is slightly undervalued at present – equilibrium being about Sk39.3/Eur (June). Our estimates comfortably support Sk39/€ in 4Q04 to be fully in line with macro picture or even slightly over-valuated. Furthermore, based on the preliminary (!) data, Koruna could be entering ERMII in 2006 at Sk36-37/€.

• Worries of CB about too strong ER at the moment might not be justified