Inflation, Financial Deepening, and Economic Growth

By

Mohsin S. Khan *

International Monetary Fund

Paper prepared for the Banco de Mexico Conference on Macroeconomic Stability, Financial Markets and Economic Development, Mexico City, November 12-13, 2002. ___________________________________________________________________________ * I am grateful to Abdelhak Senhadji for helpful discussions on this topic. The views expressed in the paper are my sole responsibility and do not necessarily reflect the opinions of the International Monetary Fund.

I. INTRODUCTION

There is now almost a universal consensus in the profession that macroeconomic stability,

specifically defined as low inflation, is positively related to economic growth. Over the years

the question of the existence and nature of the link between inflation and growth has been the

subject of considerable interest and debate. Although the debate about the precise

relationship between these two variables is still open, the continuing research on this issue

has uncovered some important results. In particular, it is generally accepted that inflation has

a negative effect on medium and long-term growth. 1 Inflation impedes efficient resource

allocation by obscuring the signalling role of relative price changes, the most important guide

to efficient economic decisionmaking (Fischer (1993)).2

If inflation is inimical to growth, it obviously follows that policymakers should aim at a low

rate of inflation. But how low should inflation be? Should it be 10 percent, 5 percent, or for

that matter, zero percent? Or put in other words, is there a level of inflation at which the

relationship between inflation and growth become negative?

1 See Barro (1991, 1995), Fischer (1983,1993), and Bruno and Easterly (1998).

2 It has also been argued that what matters for efficient resource allocation is not so much the level of inflation but its variance. While theory seems to suggest that the variability of inflation should affect growth more than its level, empirical studies show the opposite result (see Fischer 1993).

- 2 -

These are questions that several recent empirical studies have examined, focusing on whether

the relationship between inflation and long-run growth is in fact nonlinear. The hypothesis is

at some (low) rate of inflation, the relationship is nonexistent, or perhaps even positive, but at

higher rates it becomes negative. If such a nonlinear relationship exists then it should be

possible in principle to estimate the inflexion point, or threshold, at which the sign of the

relationship between the two variables would switch. Fischer (1993), in the seminal paper on

the subject, noted the existence of a positive relationship between long-run growth and

inflation at low rates of inflation, and a negative one as inflation rose. Following Fischer

(1993), there have been a number of formal empirical attempts to identify threshold effects in

the inflation-growth relationship. These include, for example, papers by Sarel (1996), Ghosh

and Phillips (1998), Bruno and Easterly (1998), and Khan and Senhadji (2001). These studies

generally find that for economies with initially low rates of inflation, modest increases in the

rate of inflation do not affect long-run rates of real growth. But for economies with initially

high rates of inflation, further increases in the inflation rate have adverse effects on real

growth. In the most recent study of this issue, Khan and Senhadji (2001) find that the

threshold rate of inflation is fairly low—around 1-3 percent for industrial countries, and

7-11 percent for developing countries. With these estimates it is now possible to define

“macroeconomic stability” in quantitative terms, namely that it implies single-digit inflation.

How then does inflation affect growth, and more particularly, what gives rise to the so-called

threshold effect in the relationship? In a recent paper, Khan, Senhadji, and Smith (2001)

argue that the real effects of inflation derive from the consequences of inflation for financial

development, or “financial deepening”. There are good reasons to think so. First, there is now

- 3 -

both empirical and theoretical literature suggesting that financial markets play an important

role in the growth process.3 Thus, if changes in the rate of inflation do affect financial market

development adversely, it is likely that such changes would also have implications for

growth. Second, there is also both theoretical and empirical literature suggesting why the

effects of increases in the rate of inflation on financial deepening might be very different at

initially low versus initially high rates of inflation.4

The theoretical underpinnings of the relationship between financial depth and growth can be

traced back to the work of Schumpeter ,5 and more recently, to McKinnon (1973), and Shaw

(1973). The main policy implication of the McKinnon-Shaw school is that government

restrictions on the banking system (such as interest rate ceilings, high reserve requirements,

and directed credit programs) hinder financial development, and ultimately reduce growth.

Similar conclusions are also reached by the recent papers on endogenous growth theory, in

which services provided by financial intermediaries (such as information collection and

analysis, risk sharing, liquidity provision, etc.) are explicitly modeled. 6 These papers show

convincingly that long-run economic growth depends on financial deepening.

3 See the recent surveys of this literature by Levine (1997) and Khan and Senhadji (2000).

4 This literature is reviewed in Khan, Senhadji, and Smith (2001).

5 See King and Levine (1993a).

6 For an explicit link between financial development and growth, see Greenwood and Jovanovic (1990), Bencivenga and Smith (1991), King and Levine (1993a), Roubini and Sala-i-Martin (1992), and Greenwood and Smith (1997). A comprehensive survey is provided by Levine (1997).

- 4 -

The extensive empirical work on the relationship between financial development and growth

has been surve yed in Levine (1997). One of the more influential studies on the subject is

King and Levine (1993b), which shows a strong positive link between financial development

and growth. 7 King and Levine (1993b) also show that financial development has predictive

power for future growth and interpret this finding as evidence for a causal relationship that

runs from financial development to growth.

This paper argues that the nonlinear link between inflation and growth results from the

threshold relationship between inflation and financial deepening. It reviews the existing

theory and empirical evidence on the effects of inflation on growth and on financial

deepening. The unique aspect of the empirical estimates is that they are obtained using new

econometric methods for threshold estimation and inference. Therefore, they are more

reliable than previous estimates reported in the literature on the subject.

In what follows, Section II looks at the link between inflation and growth. Section III

examines the effects of inflation on financial deepening. The concluding section completes

the picture of the theoretical and empirical relationships among inflation, financial

deepening, and growth.

7 Related papers are Roubini and Sala-i-Martin (1992), Easterly (1996), and Pagano (1993).

- 5 -

II. INFLATION AND GROWTH

To test for the existence of a threshold effect, Khan and Senhadji (2001) estimate the

following model:

ititititititit

ititititittiit

eXIId

IIdyd

++>−+<−

+>−+<−−++=

')}1()]log()[log()1()1{(

)}1()]log()[log()1()1){(1()log(*

2

*1

*

*

θπππππγ

πππππγµµπ

π

(1)

≤>

=*

*

01*

πππππ

it

itit if

ifd i=1,…,N; t=1,…,T

where dlog(yit) is the growth rate of real GDP,8 µi is a fixed effect, µt is a time effect, πit is

inflation based on the CPI index, π* is the threshold level of inflation, *π

itd is a dummy

variable that takes a value of one for inflation levels greater than π* percent and zero

otherwise, and I(πit <1) and I(πit >1) are indicator functionsthat is, functions that take the

value of one if the term between parentheses is true and zero otherwise. Xit is a vector of

control variables which includes investment as a share of GDP (igdp), population growth

(dlog(pop)), the log of initial income per capita (log(yi0)), the growth rate of terms of trade

(dlog(tot)), and the five-year standard deviation of terms of trade (Φtot). The index “i” is the

cross-sectional index while “t” is the time-series index.

8 The growth rate of a variable x is computed as the first difference of log(x).

- 6 -

Note that Xit contains only the most important variables among the large set found in the

empirical growth literature because very few of these variables pass the robustness tests in

Levine and Renelt (1992) and Sala-i-Martin (1997). The effect of inflation on GDP growth is

given by γ1 for countries in which inflation is less or equal to π* percent, and γ2 for countries

with inflation rates higher than π* percent.

In order to smooth out business cycle fluctuations and focus on the medium- and long-term

relationship between inflation and growth, equation (1) has been estimated using five-year

averages of the data in a panel of 140 countries and 39 annual observations each. Therefore,

the time dimension reduces to eight observations: 1960–64, 1965–69, 1970–74, 1975–79,

1980–84, 1985–89, 1990–94, and 1995–98 (the last observation is an average over four

observations only). 9 Potentially the dimension of the panel would be 140 x 8=1120

observations. However, because of missing observations, the dimension of the unbalanced

panel is smaller.

If the threshold were known, the model could be estimated by ordinary least squares (OLS).

Since π* is unknown, it has to be estimated along with the other regression parameters. The

appropriate estimation method in this case is nonlinear least squares (NLLS). Furthermore,

since π* enters the regression in a nonlinear and non-differentiable manner, conventional

9 The initial income variable ly0 is computed as the five-year average of real income per capita in PPP terms for the previous five-year period, allowing the identification of ly0 under fixed effects.

- 7 -

gradient search techniques to implement NLLS are inappropriate. Instead, estimation has

been carried out with method called conditional least squares which can be described as

follows. For any π* , the model is estimated by OLS, yielding the sum of squared residuals as

a function of π*. The least squares estimate of π* is found by selecting the value of π* which

minimizes the sum of squared residuals. Stacking the observation in vectors yields the

following compact notation for equation (1):

eXYd += πβ)log( , πππ ,...,= (2)

where βπ=(µi µt γ1 γ2 θ’)’ is the vector of parameters and X is the corresponding matrix of

observations on the explanatory variables. Note that the coefficient vector β is indexed by π

to show its dependence on the threshold level of inflation, the range of which is given by

π and π . Define S1(π) as the residual sum of squares with the threshold level of inflation

fixed at π. The threshold estimate level π* is chosen so as to minimize S1(π), that is:

},, ),{argmin* 1 ππππππ

…== (S (3)

It is important to determine whether the threshold effect is statistically significant. In

equation (1), to test for no threshold effects amounts simply to testing the null hypothesis

Ho: γ1 = γ2. Under the null hypothesis, the threshold π* is not identified, so classical tests,

- 8 -

such as the t-test, have nonstandard distributions. Hansen (1996, 1999) suggests a bootstrap

method to simulate the asymptotic distribution of the following likelihood ratio test of H0 :

2

100 ˆ/)( σSSLR −= (4)

where S0, and S1 are the residual sum of squares under H0 : γ1 = γ2, and H1: γ1 ≠ γ2,

respectively; and 2σ̂ is the residual variance under H1. In other words, S0 and S1 are the

residual sum of squares for equation (1) without and with threshold effects, respectively. The

asymptotic distribution of LR0 is nonstandard and strictly dominates the 2χ distribution. The

distribution of LR0 depends in general on the moments of the sample; thus critical values

cannot be tabulated. Hansen (1999) shows how to bootstrap the distribution of LR0.

To proceed one can test for the existence of a threshold effect in the relationship between real

GDP growth and inflation using the likelihood ratio, LR0, discussed above. This involves

estimating equation (1) and computing the residual sum of squares (RSS) for threshold levels

of inflation ranging from π to π . The threshold estimate is the one that minimizes the

sequence of RSSs. The test for the existence of threshold effects has been conducted using

the full sample and two subsamples (industrial and developing countries). The results are

summarized in Table 1.

The first column gives the range over which the search for the threshold effect is conducted.

For the full sample, π =1 percent, π =100 percent, and the increment is 1 percent, which

- 9 -

yields 100 panel regressions of equation (1).10 The minimization of the vector of 100 RSSs

occurs at the inflation level of 11 percent. Repeating the same procedure for the subsamples

yields a threshold estimate of 11 percent for developing countries and 1 percent for industrial

countries. An important result is that the threshold level for industrial countries is much

lower than that for developing countries. The column LR0 in Table 1 gives the observed value

of the likelihood ratio. The significance levels have been computed using the bootstrap

distributions (corresponding to the three samples) of LR0. The null hypothesis of no threshold

effects can be rejected at least at the 1 percent significance level for all three samples. Thus

the data strongly support the existence of threshold effects.

Two basic conclusions can be drawn from this set of statistical tests. First, the threshold is

around an inflation rate of 1 percent for industrial economies and 11 percent for developing

countries. Second, these threshold estimates are very precise. One needs to ask why the

threshold level for developing countries is higher than the threshold level for industrial

countries. There are at least two possible conjectures that we can make. First, the long history

of inflation in many developing countries led them to adopt widespread indexation systems

to negate, at least partially, the adverse effects of inflation. Once in place, these indexation

mechanisms make it possible for governments in these countries to run higher rates of

inflation without experienc ing adverse growth effects (because relative prices do not change

that much). Second, to the extent that inflation is viewed as a tax on financial intermediation,

governments, faced with a target level of expenditure will, in the absence of conventional 10 For industrial countries the upper bound has been set to 30 percent.

- 10 -

taxes, levy the inflation tax. Accordingly, the differential threshold levels for the effects of

inflation on growth for industrial and developing countries could reflect the higher level of

conventional taxation in the former than in the latter. Thus, while relatively small increases in

inflation in industrial countries adversely affect investment (by raising the effective cost of

capital goods), productivity, and growth, in developing countries, with relatively low levels

of conventional taxes, a larger inflation tax is required to have the same growth-inhibiting

effects.11

Figure 1 shows the sensitivity of the effect of inflation on growth when the threshold level

varies from 1 percent to 50 percent. The three panels (corresponding to the three samples)

depict the effect of inflation on growth for economies with an inflation rate below the

threshold level (solid line) and for economies with inflation rates above the threshold level

(dotted line). The vertical line indicates the threshold estimate. The following points emerge

from Figure 1: (i) the high- and low-inflation effects are most sensitive to the location of the

threshold over the 1 to 20 percent range; (ii) the positive effect of inflation on growth is only

present for inflation rates lower than 5 percent for industrial countries and 18 percent for

developing countries; (iii) for developing countries, the inflation effect on growth, which is

negative over the whole range, strengthens as the threshold increases, which implies a

worsening of the negative effect of inflation on growth as inflation increases; and (iv) for

industrial countries, the inflation effect, while remaining negative over the entire range, first

11 Roubini and Sala-i-Martin (1995) and Cukierman, Edwards, and Tabellini (1992) have developed models that yield results along these lines.

- 11 -

weakens (in absolute value) as the inflation threshold increases, reaches a minimum around a

threshold of 15 percent, and strengthens thereafter.

Having established that as inflation moves higher it exerts a negative effect on economic

growth, we now move to the relationship between inflation and financial deepening.

III. INFLATION AND FINANCIAL DEEPENING

As mentioned in the Introduction, it is empirically well-established that there are very strong

correlations between various measures of an economy’s financial depth and its long-run real

activity, as reflected in its long-run rate of growth. This is true both for measures of banking

activity, and for measures of stock market development. King and Levine (1993a,b) and

Beck, Levine, and Loyaza (2000), for example, demonstrate that measures of both bank

lending to the private sector, and measures of bank liabilities outstanding, are strongly

positively correlated with an economy’s level of real production, and with its real rate of

growth. Indeed, King and Levine (1993a,b) find that measures of banking activity are the

only “robustly significant” predictors of future growth performance. Similarly, Levine and

Zervos (1998) show that measures of stock market development are strongly associated with

both higher levels of real activity and higher real growth rates. While the direction of

causation is difficult to establish, Beck, Levine, and Loyaza (2000) find evidence that

causality runs from financial development to real development. Finally, Khan and Senhadji

(2000), in the most recent study of this subject, find that the effect of financial development

on growth is positive, and that the size of the effect varies with different measures of

- 12 -

financial development, estimation method, data frequency, and the functional form of the

relationship.

In addition, there are a number of well-understood theoretical mechanisms by which

financial development promotes growth. The earliest contributions (Greenwood and

Jovanovic, 1990; Bencivenga and Smith, 1991) show how information acquisition by the

financial system promotes the efficient allocation of investment capital, and how bank

liquidity provision can alter the social composition of savings in a way that promotes both

physical and human capital accumulation. Subsequent contributions (Huybens and Smith,

1999) demonstrate that secondary capital (equity) markets should also be expected to

contribute to the growth process. It is well known that technological developments alone are

inadequate to promote growth. Agents are willing to tie up resources in new technologies

requiring large scale investments only if the capital markets exist that make these

investments sufficiently liquid.

If inflation affects the development of the financial system, it will almost necessarily have

long-run real effects. Moreover, as discussed in Section II, there is now considerable

evidence that there are thresholds in the empirical relationship between inflation and real

growth. The theories reviewed by Khan, Senhadji, and Smith (2001) deliver the prediction

that there are thresholds in the theoretical relationship between inflation and financial

activity, and that this may explain the threshold in the relationship between inflation and real

activity.

- 13 -

The common theme in all of the theoretical literature is that financial market institutions arise

to address endogenous frictions that are present in the process of allocating credit and

investment capital. Indeed, such frictions seem essential in understanding the role of financial

institutions in development: in the absence of such frictions the Modigliani-Miller Theorem

would obtain, and the nature of finance would be irrelevant for allocations. Moreover, the

severity of financial market frictions is itself endogenous in the models we describe. Inflation

matters because it affects the severity of these frictions.

Suppose that higher rates of inflation are associated with lower long-run real rates of return

on a broad class of assets. Then increases in inflation will be associated with more severe

rationing of credit, reductions in financial depth, and lower levels of real activity. But why

should higher rates of inflation reduce long-run real returns? The answer is that, in any

economy, some agents hold real money balances either voluntarily or involuntarily. For

instance, the banking systems in every economy hold a significant quantity of non-interest-

bearing cash reserves. As is well-understood, higher rates of inflation act like a tax on real

balances or bank reserves. And, if this tax is borne, at least in part, by bank depositors, higher

inflation must lead to lower real returns on bank deposits. Since bank deposits compete with

a variety of assets, it is plausible that reduced real returns on bank deposits will result in

reduced real returns on a variety of assets. Barnes, Boyd and Smith (1999) and Boyd, Levine,

and Smith (2000) establish that this is, in fact, true for all but the highest inflation economies.

Moreover, Barnes, Boyd, and Smith (1999) also show that higher rates of inflation are

associated with lower real returns on short-term assets, government debt, and high grade

bank loans.

- 14 -

Of course the mechanism just described explains why higher rates of inflation might reduce

financial depth, with corresponding adverse consequences for growth. It does not yet explain

why there might be threshold effects associated with the rate of inflation exceeding some

critical level. In order to understand how threshold effects might arise, suppose that, if the

rate of inflation is sufficiently low—and if real rates of return on savings are sufficiently

high—the adverse selection problem in credit markets does not bind. Or, in other words, if

real returns are high enough, credit rationing is not required to induce lenders to lend rather

than borrow. If this transpires, then at low enough rates of inflation the credit market operates

in a totally Walrasian way. Then, in a model that generates a Mundell-Tobin effect in the

absence of credit rationing, the following can occur. If the initial rate of inflation is

sufficiently low, and real rates of return are sufficiently high, an increase in the rate of

inflation causes agents to substitute away from cash and into investments in physical and/or

human capital. As a result, long-run growth is stimulated. However, if the rate of inflation is

increased excessively, real returns will be driven down to the point where credit market

frictions become binding. Once the rate of inflation exceeds this threshold level, further

increases in inflation will lead to credit rationing and have negative consequences for the

financial system and for growth. Thus there is a critical rate of inflation. Below this rate

modest increases in inflation can stimulate real activity and promote financial depth. Above

this threshold increases in the rate of inflation interfere with the efficient allocation of

investment capital, and consequently have negative growth consequences.

- 15 -

While, as discussed above, there has been considerable theoretical analysis of the inflation

and financial depth link, empirical evidence is remarkably scarce. Indeed, the first empirical

study specifically on this is by Boyd, Levine, and Smith (2000) who examine time-averaged

data on bank credit extension to the private sector, the volume of bank liabilities outstanding,

stock market capitalization and trading volume (all as ratios to GDP), and inflation for a

cross-country sample. The empirical model they specify relates the various measures of

financial depth to inflation and a set of control variables. The authors find that, at low-to-

moderate rates of inflation, increases in the rate of inflation lead to markedly lower volumes

of bank lending to the private sector, lower levels of bank liabilities outstanding, and

significantly reduced levels of stock market capitalization and trading volume. They also find

that the relationship between inflation and financial market development becomes “flatter” as

inflation increases: that is, a given percentage point increase in the rate of inflation has a

much larger effect on financial development at low than at high rates of inflation. In addition,

they obtain similar results using non-overlapping panels of data averaged over five-year

intervals.

However, Boyd, Levine, and Smith (2000) do not explicitly test for the presence of threshold

effects in the inflation-financial depth relationship. Nor do their results easily permit a

comparison with the empirical findings on the links between long-run inflation and long-run

growth. To test for the existence of a threshold effect, Khan, Senhadji, and Smith (2001),

drawing upon the work described in Section II, utilized the following empirical model:

- 16 -

ititititititit eXddfd ++−+−−= ')/1/1()/1/1)(1( *2

*1

**

θππγππγ ππ (5)

≤>

=*

*

01*

πππππ

it

itit if

ifd i=1,…,N; t=1,…,T

where fdit is an indicator of financial depth, πit is inflation based on the CPI index, π* is the

threshold level of inflation, and *π

itd is a dummy variable that takes a value of one for

inflation levels greater than π* percent and zero otherwise. Xit is a vector of control variables

which includes the log of income per capita (log(pppgdp)), the degree of openness (open),

the share of public consumption in GDP (cg), a time trend (trend) and three regional

dummies, a dummy for Latin American countries (d_la), a dummy variable for Asian

countries (d_as), and a dummy variable for advanced countries (d_adv).12 The subtraction of

1/π* from 1/πit in equation (1) makes the relationship between financial depth and inflation

continuous at the threshold level π*.13 The first term in equation (1) gives the effect of

inflation for inflation rates below or equal to the threshold. Similarly, the second term

measures the effect of inflation on financial development for inflation rates above the

threshold level.14

12 Because the estimation method requires a large sample, individual equations for these (and other) group of countries cannot be estimated precisely.

13 Continuity of the relationship given in equation (1) is desirable, otherwise small changes in the inflation rate around the threshold level will yield different impacts on financial depth depending on whether inflation is increasing or decreasing.

14 Theoretically, the relationship between financial depth and inf lation may be characterized by multiple thresholds. However, as it is very difficult to estimate multiple thresholds, equation (1) only considers the single-threshold case.

- 17 -

The dataset utilized in this paper includes 168 countries (comprising both industrial and

developing countries) and generally covers the period 1960–99. Data for a number of

developing countries, however, have a shorter span. Because of the uneven coverage, the

analysis is conducted using unbalanced panels. The data come primarily from a new financial

development dataset developed by Beck, Demirgüç-Kunt, and Levine (1999) and the

International Financial Statistics of the International Monetary Fund. Financial depth is

measured by several alternative indicators: (i) fd1: defined as domestic credit to the private

sector as a share of GDP; (ii) fd2: defined as fd1 plus stock market capitalization as a share of

GDP; and (iii) fd3: defined as fd2 plus private and public bond market capitalization as a share

of GDP. By definition, fd3 is the most exhaustive indicator of financial depth, but is only

available for advanced countries and for a shorter time span (starting 1975). By contrast, fd1

is widely available, but is a more limited proxy for financial depth.

We can proceed to test for the existence of a threshold effect in the relationship between

inflation and financial depth using the likelihood ratio, LR0, as discussed in Section II. This

implies estimating equation ( 5) and computing the residual sum of squares (RSS) for

threshold levels of inflation ranging from π to π . Recall that the threshold estimate is the

one that minimizes the sequence of RSSs. The test for the existence of threshold effects has

been conducted using the three selected indicators of financial depth. The results are

summarized in Table 2.

- 18 -

The first column gives the range over which the search for the threshold effect is conducted,

which is 1 percent to 100 percent with increments of 1 percent. This yields 100 panel

regressions of equation (5). Using fd1 as an indicator of financial depth, the minimization of

the vector of 100 RSSs occurs at the inflation level of 6 percent. Repeating the same

procedure for fd2, and fd3 yields threshold estimates of 3 percent and 5 percent, respectively.

The column LR0 in Table 1 gives the observed value of the likelihood ratio. The significance

levels have been computed using the bootstrap distributions (corresponding to the three

indicators of financial depth) of LR0. The null hypothesis of no threshold effects can be

rejected at least at the 1 percent significance level for all three indicators of financial depth.

Thus the data strongly support the existence of threshold effects.

In Figure 2, for each measure of financial depth, the three panels show the effect of inflation

on financial depth as inflation increases from 1 percent to 100 percent. All three indicators of

financial depth yield a similar pattern for the effect of inflation on financial depth. Below the

threshold, an increase in inflation has a small positive but statistically insignificant effect on

financial depth (except for fd1, which shows a small negative but statistically insignificant

effect). Above the threshold, increasing inflation significantly hampers financial depth. And, it

bears emphasizing that the adverse effects of inflation for the financial system are particularly

strong for economies with modest rates of inflation (but ones that exceed the threshold).

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IV. CONCLUSIONS

The recent empirical growth literature has consistently found a negative but nonlinear

relationship between inflation and growth. The nonlinearity in the relationship arises from

the existence of threshold effects, that is, there is a threshold level of inflation below which

inflation has no significant effect on growth, but beyond which inflation significantly

hampers growth. Recent theoretical models provide some interesting insights about this

relationship, arguing that the main mechanism of transmission can be through financial

markets. In the presence of frictions (arising from, for example, adverse selection, moral

hazard, or costly state verification), inflation impedes financial development, and thus

growth, by affecting the severity of these frictions. In particular, higher inflation leads to

increased credit rationing and reduced extension of bank credit and therefore to lower

investment and slower growth. These theoretical models further predict a nonlinear

relationship between inflation and financial development, and thus between inflation and

growth, that is similar to that uncovered in empirical work.

The empirical results reported in this paper strongly support the notion of nonlinear

relationships between inflation and growth, and between inflation and financial deepening.

Inflation starts to exert a negative effect on growth as low as at around 1 percent in industrial

countries and at about 11 percent in developing countries. The threshold level of inflation

beyond which inflation significantly hinders financial deepening is estimated to be in the

- 20 -

3-6 percent range. When combined, these results provide strong support for the view taken in

this paper that financial markets are an important channel through which inflation affects

growth in a nonlinear fashion.

In conclusion, policymakers around the world during the last decade or so have recognized

that low inflation is conducive to the development of financial systems and markets and to

strong growth performance. The goal has been to bring inflation down to single digits and to

keep it there. The results contained in this paper provide strong empirical confirmation of this

strategy. Once the rate of inflation starts to cross the 5-10 percent mark, it will begin to exert

a negative effect on financial deepening, and through this channel, have an adverse effect on

economic growth. Low inflation, financial development, and higher growth appear to go

hand in hand.

- 21 -

Table 1. Test Results of Threshold Effects

Sample

Search Range for Thresholds

Threshold Estimate (%)

LR0

Critical

Values (%)

Significance Levels

All Countries {1, 2,3,…,100} 11 10.59 7.47 0.001

Industrial Countries {1, 2,3,…,30} 1 8.80 6.63 0.005

Developing Countries {1, 2,3,…,100} 11 10.89 6.21 0.000

Table 2. Test Results of Threshold Effects

Dependent variable

Search Range for Thresholds

Threshold Estimate (%)

LR0 Critical Values (1%)

Significance Levels

fd1 {1, 2,3,…,100} 6 246.9 5.93 0.000

fd2 {1, 2,3,…,100} 3 50.20 14.49 0.000

fd3 {1, 2,3,…,100} 5 34.38 13.00 0.000

Note: The second column gives the range over which the search for the threshold effect is conducted, the third column gives the threshold estimate in percent, the column LR0 gives the observed value of the likelihood ratio, the fifth column gives the critical values, and the last column gives the corresponding significance level, both computed using the bootstrap distributions (corresponding to the three samples) of LR0.

For a more detailed discussion on the computation of the bootstrap distribution of LR0, see Hansen (1999).

- 22 -

Figure 1. Sensitivity of the Effect of Inflation on Growth to the Threshold Level

Note: The low (solid line) and high (dotted line) effects are respectively given by the coefficients of equation (1). The threshold varies from 1 to 50 percent, except for industrial countries where the range is from 1 to 30 percent. The vertical line indicates the estimate of the inflation threshold.

-0.02

0.00

0.02

0.04

0.06

0.08

5 10 15 20 25 30

Industrial Countries

-0.010

-0.008

-0.006

-0.004

-0.002

0.000

0.002

5 10 15 20 25 30 35 40 45 50

Developing Countries

-0.010

-0.008

-0.006

-0.004

-0.002

0.000

0.002

5 10 15 20 25 30 35 40 45 50

Full Sample

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Figure 2. Effect of Inflation on Financial Depth

Note: This figure shows the effect of inflation on financial depth (for inflation rates from 1 to 100 percent) using the coefficient estimates of equation (5). Both inflation and financial depth are expressed in percentage terms.

fd1

fd2

fd3

-20

-15

-10

-5

0

5

20 40 60 80 100

Inflation

-50

-40

-30

-20

-10

0

20 40 60 80 100

Inflation

-120

-100

-80

-60

-40

-20

0

20 40 60 80 100

Inflation

- 24 -

REFERENCES

Barnes, Michelle, John H. Boyd, and Bruce D. Smith, 1999, “Inflation and Asset Returns,” European Economic Review, Vol. 43, pp. 737-54. Barro, Robert J., 1991, “Economic Growth in a Cross-Section of Countries,” Quarterly

Journal of Economics , Vol. 106, No. 2, pp. 407-43. Barro, Robert J., 1995, “Inflation and Economic Growth,” Bank of England Quarterly Bulletin , pp. 166-76. Beck, Thosten, Asli Demirgüç-Kunt, and Ross Levine, (1999), “A New Database on Financial Development and Structure,” World Bank, unpublished. Beck, Thorsten, Ross Levine, and Norman Loyaza, 2000, “Financial Intermediation and Growth: Causality and Causes,” Journal of Monetary Economics, forthcoming. Bencivenga, Valerie R., and Bruce D. Smith, 1991, “Financial Intermediation and

Endogenous Growth,” Review of Economic Studies, Vol. 58, pp. 195-209. Boyd, John H., Ross Levine, and Bruce D. Smith, 2000, “The Impact of Inflation on Financial Market Performance,” Journal of Monetary Economics, forthcoming. Bruno, Michael, and William Easterly, 1998, “Inflation Crises and Long-Run Growth,”

Journal of Monetary Economics, Vol. 41, pp. 3-26. Cuikerman, Alex, Sebastian Edwards, and Guido Tabellini, 1992, “Seigniorage and Political

Instability,” American Economic Review, Vol. 82, No. 3, pp. 537-55. Easterly, William, 1996, “When Is Stabilization Expansionary?” Economic Policy, Vol. 7

(April), pp. 67-107. Fischer, Stanley, 1983, “Inflation and Growth,” NBER Working Paper No. 1235

(Cambridge, MA: NBER). Fischer, Stanley, 1993, “The Role of Macroeconomic Factors in Growth,” Journal of

Monetary Economics, Vol. 32, pp. 485-512. Ghosh, Atish, and Steven Phillips, 1998, “Warning: Inflation May Be Harmful to Your

Growth,” IMF Staff Papers , Vol. 45, No. 4, pp. 672-710. Greenwood, Jeremy, and Boyan Jovanovic, 1990, “Financial Development, Growth, and the Distribution of Income,” Journal of Political Economy, Vol. 98, pp. 1076-1107.

- 25 -

Greenwood, Jeremy, and Bruce Smith, 1997, “Financial Markets in Development and the Development of Financial Markets,” Journal of Economic Dynamics and Control, Vol. 21, No. 1, pp. 145-81.

Hansen, Bruce, 1996, “Inference When a Nuisance Parameter Is Not Identified Under the

Null Hypothesis,” Econometrica , Vol. 64 (March), pp. 413-30. Hansen, Bruce, 1999, “Threshold Effects in Non-Dynamic Panels: Estimation, Testing, and

Inference,” Journal of Econometrics , Vol. 93, No. 2, pp. 345–68. Huybens, Elisabeth, and Bruce D. Smith, 1999, “Inflation, Financial Markets, and Long-Run Real Activity,” Journal of Monetary Economics, Vol. 43, pp. 283-315. Khan, Mohsin S., and Abdelhak Senhadji, 2000, “Financial Development and Economic

Growth,” IMF Working Paper WP/00/209; Journal of African Economies, forthcoming.

Khan, Mohsin S., and Abdelhak Senhadji, 2001, “Threshold Effects in the Relationship

Between Inflation and Growth,” IMF Working Paper WP/00/110; IMF Staff Papers, Vo. 48, No. 1, pp. 1-21.

Khan, Mohsin S., Abdelhak Senhadji, and Bruce Smith, 2001, “Inflation and Financial

Depth,” IMF Working Paper WP/01/44. King, Robert G., and Ross Levine, 1993a, “Finance and Growth: Schumpeter Might Be Right,” Quarterly Journal of Economics, Vol. 108, pp. 717-38. King, Robert G., and Ross Levine, 1993b, “Finance, Entrepreneurship, and Growth: Theory and Evidence,” Journal of Monetary Economics, Vol. 32, pp. 513-42. Levine, Ross, 1997, “Financial Development and Economic Growth: Views and Agenda,”

Journal of Economic Literature , Vol. 35, No. 2, pp. 688-726. Levine, Ross, and David Renelt, 1992, “A Sensitivity Analysis of Cross-Country Growth

Regressions,” American Economic Review, Vol. 82, No. 2, pp. 942-63. Levine, Ross, and Sara Zervos, 1998, “Stock Markets, Banks, and Economic Growth,” American Economic Review, Vol. 88, pp. 537-58. McKinnon, Ronald I., 1973, Money and Capital in Economic Development, Washington

D.C., Brookings Institution. Pagano, Marco, 1993, “Financial Markets and Growth: An Overview,” European Economic

Review , Vol. 37, Nos. 2-3, pp. 613-22.

- 26 -

Roubini, Nouriel, and Xavier Sala-i-Martin, 1992, “Financial Repression and Economic Growth,” Journal of Development Economics, Vol. 39, No. 1, pp. 5-30.

Roubini, Nouriel, and Xavier Sala-i-Martin, 1995, “A Growth Model of Inflation, Tax

Evasion, and Financial Repression,” Journal of Monetary Economics, Vol. 35 (April), pp. 275-301.

Sala-i-Martin, Xavier, 1997, “I Just Ran Two Million Regressions,” American Economic

Review , Vol. 87, No. 2, pp. 178-83. Sarel, Michael, 1996, “Nonlinear Effects of Inflation on Economic Growth,” IMF Staff

Papers , Vol. 43, pp. 199-215. Shaw, Edward S., 1973, Financial Deepening in Economic Development, New York, Oxford

University Press.