Exchange Market Pressure, Currency Crises, and Monetary Policy
Additional Evidence From Emerging Markets

Contributor Notes

Author’s E-Mail Address: etanner@imf.org

This paper extends my previous work by examining the relationship between monetary policy and exchange market pressure (EMP) in 32 emerging market countries. EMP is a gauge of the severity of crises, and part of this paper specifically analyzes crisis periods. Two variables gauge the stance of monetary policy: the growth of central bank domestic credit and the interest differential (domestic versus U.S. dollar). Evidence suggests that monetary policy plays an important role in currency crises. And, in most countries the shocks to monetary policy affect EMP in the direction predicted by traditional approaches: tighter money reduces EMP.

Abstract

This paper extends my previous work by examining the relationship between monetary policy and exchange market pressure (EMP) in 32 emerging market countries. EMP is a gauge of the severity of crises, and part of this paper specifically analyzes crisis periods. Two variables gauge the stance of monetary policy: the growth of central bank domestic credit and the interest differential (domestic versus U.S. dollar). Evidence suggests that monetary policy plays an important role in currency crises. And, in most countries the shocks to monetary policy affect EMP in the direction predicted by traditional approaches: tighter money reduces EMP.

I. Introduction

In emerging markets, currency crises have occurred more frequently in recent years and continue to concern policy makers.2 To explain currency crises, much early work emphasized the role of monetary policy at or around the time of the crisis. In a familiar example, if the increase of the domestic credit portion of the monetary base (usually the counterpart of an unsustainable fiscal deficit) outstrips that of base money demand, foreign exchange reserves will be depleted and the exchange rate regime will collapse.3 Extending this logic, Krugman (1979) and many others thereafter explored the implications of market speculation against an exchange rate regime, including the precise timing of a regime’s collapse.4

Recent empirical work on currency crises has used a broader list of explanatory variables, often with the goal of forecasting currency crises over a medium-term horizon. For example, early warning systems developed by several authors have suggested that certain fundamental indicators (including real exchange rate overvaluation and growth rates of GDP, exports, and banking sector credit) help forecast exchange rate crises in advance (as much as two years).5

In recent years, as Kaminsky and Reinhart (1999) argue, currency crises have been increasingly associated with financial fragilities, like the Mexican and Asian crises. Accordingly, financial sector variables may also help to predict exchange rate crises. And, several researchers have tested for external common shocks or market contagion.6

While fiscal and financial fundamentals may help predict exchange rate crises over the medium term, and contagion may be important, monetary policy may nonetheless play an important role in exchange rate crises, especially at or around the time of the crisis. For example, a country’s central bank might accommodate pressures on the banking system and/or adverse external shocks, expanding the domestic portion of the money supply and sterilizing outflows as it provides liquidity to the banking system.7

In this light, the question of whether monetary policy is effective in preventing or forestalling crises has recently received renewed theoretical attention (Bensaid and Jeanne (1997), Drazen (1999), Furman and Stiglitz (1998), Flood and Jeanne (2000), and Lahiri and Végh (2000). For example, some have suggested that higher interest rates might place undue pressure on the banking system, thus causing a recession and exacerbating problems in exchange markets. Others have noted that without a fiscal adjustment, tighter monetary policy increases the burden on the intertemporal budget and may hence be counterproductive.

To empirically address questions like these, many authors have used measures of exchange market pressure (EMP) that include exchange rate depreciation and movements of international reserves (and, in some cases, the interest rate differential). Such a variable can be used for different exchange rate regimes, providing a more complete picture than either exchange depreciation or reserve movements in isolation.8

This paper extends a previous one also written by myself (Tanner (2001)). Like that paper, this one addresses several questions regarding EMP and monetary policy. For example, are substantial movements in EMP, including exchange rate crises and other periods of turbulence, due mainly to changes in money demand or money supply? Do the relationships between EMP, money supply, and money demand change during periods of common shocks or turbulence in global capital markets? If so, do these relationships change in a consistent way? What can we say about the stance of monetary policy at or around the time of exchange rate crises?

As in the previous paper, EMP is defined herein as the sum of exchange depreciation (in percent) and reserve losses (in percent of the monetary base).9 However, this paper examines 32 countries, as compared to 6 in the previous one. This measure of EMP has three components: a real money demand component, a money supply component and a real exchange rate component.10 Accordingly, this decomposition is well suited to address questions like those posed above.

Next, the relationship between EMP and monetary policy is examined in a vector autoregression (VAR) system that is estimated for most countries in the data sample.11 Such a framework is well suited to examine relationships between monetary policy and EMP in both directions. Does monetary policy affect EMP as expected direction? And, in the other direction, what, if any, is the feedback relationship from EMP to monetary policy? Is outflow sterilization, like that found in Mexico and certain Asian countries, evident elsewhere?

The paper is organized as follows. In Part II, measures of exchange market pressure (EMP) and the stance of monetary policy are discussed. Summary statistics regarding EMP and monetary policy are presented for 34 emerging market countries, including through selected common-shock windows, namely Mexican, Asian, Russian, and Brazilian Crises. In Part III, the VAR model is developed and estimated. Part IV presents a summary and some policy implications.

II. Exchange Market Pressure (EMP) and Its Components

Many countries limit exchange rate flexibility with purchases or sales of international reserves. In such regimes, when measuring exchange market pressures (EMP), the exchange rate and international reserves must be considered jointly. In this regard, Table 1 presents average values for the growth of the nominal exchange rate measured in domestic currency units per dollar (ε) and the change in international reserves (NIR) as a fraction of the monetary base (MB, r = ΔNIR/MB), for 34 emerging market countries in the Western Hemisphere (Latin America and Jamaica, hereafter referred to as WH), Asia, and Europe.

Table 1.

Summary Indicators of Exchange Rate Regime

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INTIND = var (r)/[var(r)+(var(ɛ)], r = ΔR/MB, R = reserves, MB = monetary base, e = % ΔE, E = nominal exchange rate (domestic currency units per dollar).

For WH countries, calculations are limited to recent low inflation periods. For further information, see bottom of next page.

Notes: All variables are computed on a monthly basis. INTIND = var (r)/[var(r)+(var(e)], r = DR/MB, R = reserves, MB = monetary base, e = %DE, E = nominal exchange rate (domestic currency units per dollar).

Table 1 presents weighted regional averages (including calculations for WH countries that omit Argentina, Brazil, and Mexico for WH countries).12 For WH countries, calculations are presented only for the more recent period of lower inflation. Data are presented for both the entire sample period and certain subsamples that correspond to periods generally associated with common global shocks, namely “Tequila Spillover” (94:9-95:5, hereafter referred to as TS), Asian (97:4-98:4), and Russian/Brazilian (98:7-99:7) periods.13

Table 1 also presents calculations of an intervention index, INTIND, defined as the variance of (scaled) reserve movements r as a ratio of the sum of the variances of scaled reserves and exchange depreciation: INTIND = var(r)/[var(r)+var(ε)]). INTIND thus summarizes the degree of exchange market intervention. Under a perfectly fixed exchange rate regime, INTIND is unity.14

This table suggests most countries intervene to some degree in their foreign exchange markets. In this context, several authors have suggested using measures or indices of EMP that include both variables.15 One definition of EMP, due to Girton and Roper (1977) is the sum of exchange rate depreciation and reserve outflows (scaled by base money):

EMPt=εtrt(1)

where ε is the growth of the nominal exchange rate measured in domestic currency units per dollar and r is the change in international reserves as a fraction of the monetary base (ΔNIR/MB).16 To demonstrate the intuition behind this definition of EMP, suppose that the excess supply of money rises by 1 percent. Under a fixed exchange rate, r = -1 percent; under a flexible exchange rate regime, ε = 1 percent, and under a mixed regime, these two variables would move in some combination.17

In an appendix, EMP is shown to contain three elements, namely a nominal money supply element, a real money demand element, and a residual term that includes changes in both the bilateral real exchange rate and foreign (U.S.) inflation:

EMPtδtmt+λt(2)

where, δt is the change in net domestic credit scaled by the monetary base (ΔNDA/MB), mt is the growth of real base money, and λt=πt*+zt, where zt is the change in the bilateral real exchange rate and πt* is foreign inflation. Thus, λt may be thought of as a residual term that includes real exchange rate changes.

Equation (2) underscores the question of how to gauge whether monetary policy is “tight” or “loose.” Much recent work, applied to the U.S. and other industrialized countries, has emphasized interest rates (like the Federal Funds Rate in the U.S.) as an indicator of the stance of monetary policy (higher interest rates mean tighter money) since interest rates are the policy instrument, reflecting the tastes and preferences of policy makers.19

By contrast, older literature emphasizes monetary aggregates to gauge the stance of monetary policy.18 However, for open economies with fixed or managed exchange rates there are advantages to focusing on the domestically determined component of the monetary base (δ) much like the traditional monetary approach.19 A more formal modeling strategy that includes both interest rates and δ is presented in Part III. As an intuitive justification for using δ, note that even if the central bank targets an interest rate ex-ante, domestic credit adjusts ex-post in order that money markets to clear at that interest rate. So, while interest rates may reflect the intentions of the policy makers, domestic credit indicates ex-post whether monetary policy is tight or loose.20 Thus, according to equation (2), EMP increases when real money demand (m) decreases, when the domestic component of the money supply (δ) increases, when the real exchange rate depreciates and/or foreign inflation falls (λ).21

One might also ask about the relative importance of the elements in the right hand side of equation (2). Are movements in EMP primarily due to changes in money demand, money supply, or other factors contained in λ? To address this question, consider next this expression for the variance of EMP:

var(EMP)=var(δ)+var(m)+var(λ)+2[cov(δ,m)+cov(δ,λ)+cov(m,λ)](3)

Table 2 presents the means of EMP, δ, m, and λ, the variance of EMP, and the elements on the right hand side of equation (3) as a fraction of var(EMP), for the 32 emerging market countries. For WH, calculations are presented both for a longer data sample and recent, lower inflation periods. Unsurprisingly, EMP is higher and more variable in the WH and Europe than in Asia. However, much EMP in the WH reflects the high inflation periods in certain countries (notably Brazil). When high inflation periods for WH are excluded EMP falls and becomes less variable.

Table 2.

Exchange Market Pressure and its Components: Means and Variances

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Notes: EMP= exchange market pressure, δt = change in domestic credit scaled by monetary base, mt= percent growth in real money base (deflated by CPI), λt= EMP — δt + mt= residual term (see text). All data are monthly. For time periods, including definitions of Tequila, Asia, and Russia/Brazil windows, and calculation of weighted averages, see Table 1.

An important message of Table 2 is that for most countries and time periods, money supply factors are an important element of EMP. Among WH and Asian countries, var(δ) as a fraction of var (EMP) generally exceeds either var(m) or var(λ). In these regions, in most cases, var(δ)/var(EMP) is close to (if not greater than) unity. In Europe, however, relative to other regions, var(δ)/var(EMP) is somewhat lower while var(m) and especially var(λ) are considerably greater.

The data suggest that periods of increased exchange market pressure are accompanied by expansions of domestic credit by the central bank, reductions in real money demand, and real depreciations. In Table 3, simple bivariate regression coefficients of EMP on δ, m, and λ, estimated country-by-country, are presented. These regressions are intended to summarize the data, not to imply causality. The estimated coefficients ∂EMP/∂δ are positive and almost always significant; those for ∂EMP/∂m are less than zero and in most cases significant; and those for ∂EMP/∂λ, are almost always positive and significant.

Table 3.

Bivariate Regressions of EMP with δ, m, λ

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Regression is: EMPt = a0 + a1 Zt + errort, Zt = (δt, mtt). EMP= exchange market pressure, δ = change in domestic credit scaled by monetary base, m = percent growth in real money base (deflated by CPI), λ = EMP − δ − m = residual term (see text). All data are monthly.