Back Matter
  • 1, International Monetary Fund


The Dependent Variables

Three dependent variables-indices of exchange rate pressure- are used, in turn, in this model. The principal dependent variable, called IND, is essentially a weighted average of the percentage change in the exchange rate, and the negative of the percentage change in international reserves.22 The higher the value of the index, the more severe the crisis in the country.

The index is a weighted average, since its two components, the percentage change in the exchange rate and the negative of the percentage change in reserves, have different volatilities. Therefore, their conditional variance must be equalized. This is accomplished by weighting each component by the inverse of its variance, and dividing by the sum of the inverses of the variances of the two components. We get:


Here, EX is the percentage change in the exchange rate, and RES is the percentage change in reserves over the relevant interval. σ2Ex and σ2RES are the variances of the percentage changes in the exchange rate and international reserves respectively. Table 2 presents the values of IND for each country in each crisis episode. The variances used were calculated using the annual change in the exchange rate and reserves over the previous 10 years. When IND was used to define crisis periods, the sample variances of the monthly percentage changes in the exchange rate and reserves for the entire period (1990-99) were used as weights.

Used by ERW, KLR, Kaminsky and Reinhart (1996), and STV, among others, this index has become a standard feature of empirical work on currency crises. ERW also include the level of the domestic interest rate in their index. However, because data on these are missing for certain countries in the sample, this component was dropped, following KLR, Kaminsky and Reinhart (1996) and STV. The data for the exchange rate and international reserves were obtained from the International Financial Statistics. The exchange rate used is the end-of-period monthly exchange rate vs. the U.S. dollar (IFS line ae). The figure used for international reserves is the entry under Total Reserves Minus Gold (IFS line 1L.D).

Since crises often last for over a month (the frequency of our data), we require an interval over which to measure the change in the exchange rate and reserves, which fully reflects the extent to which a country suffers as a result of a currency crisis. Hence the index was constructed using the period 1994M11-1995M4, 1997M5-1997M10, and 1998M7-1998M10. This essentially follows the methodology of STV/T and BM, and allows us, as mentioned earlier, to distinguish between the incidence and severity of currency crises.

Two other crisis indices were tried. The first is called DEP and simply measures the depreciation of a country’s currency. The intervals used were 1994M11-1995M9, 1997M5-1998M2,1998M5-1998M10, for the 1995, 1997 and 1998 crises respectively.23 One attraction of this approach is that since individual crises end at different points in time, while the period over which the index is computed is fixed for a particular episode, reserves could very well rise, in the aftermath of a crisis, either because of “profit taking” or buybacks or both. So, including reserves in the index might not give a wholly accurate picture of the intensity of a crisis. The second index was devised by BM, and is identical to IND, except that gold holdings are included in reserves. One justification for the use of this methodology is that the liquidity of gold has increased substantially in recent years. The intervals used are the same as for IND except that the interval used for 1997 is 1997M7-1997M10, following BM. The variable is called BMG. Both these indices are also presented in Table 2.

Independent Variables
Real Effective Exchange Rate Depreciation (RER)

The more appreciated the real effective exchange rate relative to its equilibrium value, the greater the adjustment that will be required in the nominal exchange rate, to ensure external balance.24 Hence, an overly appreciated real effective exchange rate is an indicator of the impending need for adjustment in the nominal exchange rate. Such an adjustment can come in one of two ways, by a fall in the price level, without a rise in the nominal exchange rate, or by a fall in the nominal exchange rate. Given the difficulty of engineering the former, at least in the short run, markets correctly presume that the government will be compelled to correct real exchange rate overvaluation by abandoning the exchange rate regime and devaluing the currency. The variable used here is the change in the real effective exchange rate over a three-year period preceding the crisis year. That is, the change in the real effective exchange rate between December of the year preceding the year in which the crisis started, and December three years earlier. The data was obtained from the IMF’s INS database

The ratio of M2 to international reserves (M2/I)

Also termed “reserve adequacy,” this ratio is an important indicator of the extent to which a country’s financial system is vulnerable to a run by investors. Its use in gauging vulnerability to currency crises was first suggested by Guillermo Calvo, in an influential 1995 paper.25 Prior to this, the convention was to use the ratio of reserves to the value of one month of imports. Calvo argued, persuasively, that what was relevant was not the government’s ability to finance the current account in the short term, but rather the ability of players in financial markets to purchase domestic currency that could, with relative ease, be converted to foreign currency at the prevailing price.26

The arguments for using reserve adequacy to estimate vulnerability to currency crises are grounded in the view that such crises bear a basic similarity to bank runs. Suppose depositors, or investors, in the case of currency crises, feel that a bank or country will not be able to honor its obligations tomorrow. In the case of the bank, this would mean not being able to give them their money if they asked for it, in the case of a country it would mean not being able to give them their money at the pegged exchange rate. In that case, the depositors or investors will withdraw their money today.27 When higher-order beliefs are factored in, banks or countries are shown to be even more vulnerable, as a collapse could occur if investors think other investors think (and so on) that the bank or country would not be able to honor its obligations.

The variable is constructed by dividing the sum of Money (IFS line 34) and Quasi Money (IFS line 35) by the product of Total Reserves Minus Gold (IFS line 1L. D), henceforth denoted by I,’ and the exchange rate (IFS line ae). For a given country in a given crisis period, the value of M2/I in December of the year preceding the crisis year is used.

Domestic Credit (CRED)

This variable is the percentage change in the ratio of domestic credit to GDP over a three-year period. If this ratio rises very fast in a short period of time, however, it is likely that the country is experiencing a lending boom. The increased vulnerability of countries to currency crises as a result is two-fold. As Gavin and Hausman (1995) and Rojas-Suarez and Weisbrod (1995) have argued, in the presence of a lending boom, banks’ portfolios are likely to be more vulnerable to fluctuations in the business cycle.28 Hence, a government faced with an unsustainable current account deficit or a fall in capital flows or both, will be less willing to engineer a recession to achieve external balance and will instead choose to go the devaluation route.29 In addition, as Chang and Velasco (1998) have stressed, a high rate of growth of this ratio increases the danger that banks themselves will be subject to self-fulfilling runs. In this scenario, the central bank will be in the unenviable position of having to choose between bailing out domestic banks (by extending credit and printing more money) and defending the exchange rate peg (which will then come under more pressure as the central bank’s domestic liabilities increase).

Claims on the Private Sector at Current Prices (IFS line 32D) are divided by nominal GDP to obtain the ratio of domestic credit to GDP on an annual basis. The variable used in the model is the percentage change in this ratio over a two-year period ending in December of the year preceding the crisis year.

Exports (EXP)

This variable gives us an idea of the incentive the government has to devalue in order to boost exports, since export led growth is a goal that has been popular among policymakers in developing countries. If exports are sluggish, a government may devalue, in order to boost them.

There are, of course, caveats to be kept in mind here. For one, if a country’s exports have a high import content, then, unless the countries from which it imports these intermediate contents are also expected to devalue, a devaluation would increase the cost of production of the export sector, and have an adverse effect on competitiveness. The reasons for the decline in exports are also important. If exports are declining because of supply side reasons, a devaluation might not be the best solution. This variable is the percentage growth in the domestic currency value of exports (IFS line 70) over the previous year.

Stock Prices (ST)

This variable is the percentage change in the major stock price index of the country over the year prior to the crisis. It gives us an idea of the difficulty the government faces in reversing capital flows and the extent to which the outflows are a permanent exit from an unattractive economy rather than a temporary retreat from a troubled one. Put differently, it is a proxy for the overall unattractiveness of an economy to portfolio investors, among the most volatile movers in international financial markets and a major force in equity markets, which could translate into their finding the currency unattractive as well.

In the context of the coordination of expectational shifts that was discussed earlier, this provides some indication to portfolio investors as to how pessimistic their comrades are about a country. Kumar et. al. (1998) point out that rising stock prices could, however, be taken to be indicative of a speculative bubble, and hence contribute to investor pessimism, However, even they admit that the data indicates that crises have largely been preceded by declining stock prices. The data was obtained from the Global Financial Database and the IFC Emerging Stock Markets Factbook. The variable is the change in the index given in the publication over the previous year.

Short Term Debt/Reserves (SD)

Like M2/I this variable measures the amount of domestic money that can be converted to foreign exchange easily. In fact, it has to be converted to foreign exchange in under 12 months. This variable does not, however, give us the whole picture. The currency composition of debt needs to be ascertained before one can estimate the effects it has on vulnerability. In particular, if a large share of the debt is denominated in foreign currency, a devaluation might actually make matters worse. However, the data needed to make these adjustments is difficult to assemble, and particularly so for our sample of emerging market economies. We therefore rely on this cruder formulation. The data on short term debt was obtained from the BIS webpage, while the data on reserves is simply IFS line 1L.D. We use the semi-annual interval immediately prior to the crisis episode in question.

Current Account Deficit (CAD)

The size of the current account deficit is an indication of how large the adjustment in the real exchange rate will have to be in order to restore external balance, in the event of a fall in capital flows. A large current account deficit implies the necessity of a large capital inflow, to cover the deficit, and consequently of high confidence in the economy on the part of foreign investors. It is not unusual for emerging market countries to show large current account deficits, since these countries are net importers of capital. If, however, the deficit is too large, assuming each marginal investor is less committed to investing in the country, such a situation could leave countries highly vulnerable to switches in expectations. The data (in U.S. dollars) was obtained from the IFS (line 78), The variable is IFS line 78 divided by IFS (line 99b) for the previous year.


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The author would like to thank Peter B. Kenen for his comments and for enormous support, advice, and encouragement on related research done at Princeton; Manmohan Kumar, Andy Berg, Luis Catao, Gabriela Basurto and T.N Srinivasan for numerous helpful suggestions; Ranil Salgado and Luca Ricci for sharing data; and Celia Burns for invaluable assistance with formatting.


This view implies that such crises are not really “contagious” in the epidemiological sense. While they owe to weaknesses in the same fundamentals, and while some have argued that these weaknesses might owe to a common cause, a crisis in one country does not, in this scheme of things, “cause” a crisis in another.


We do not enter into a theoretical discussion of this idea of contagion. It has, however, been formalized (although not in the context of modelling contagion) elsewhere. Shiller (1995) discusses the idea of signals from one financial market influencing events in another. Chari and Jagannathan (1988) present a theoretical model of bank runs where expectational shifts are coordinated by an observable variable-the “length” of the line outside the bank. The idea, here, is that there are other observable variables that could coordinate expectations in currency markets


While this “second-generation” characterization of currency crises is widely accepted there has been recent theoretical work that calls into question the idea of multiple equilibria in currency markets, demonstrating that under imperfect information the equilibrium can be unique. See Morris and Shin (1998).


We also consider similarities between the country for which the observation is being taken and all other countries experiencing crises, in addition to testing for wake-up calls.


Corsetti et. al. (in press) present a theoretical framework in which to view the welfare effects of competitive devaluations.


Closely related to this approach is the concept of “monsoonal effects,” discussed at length in Masson (1998). This line of reasoning holds that contagious currency crises are a set of individual crises, caused by macroeconomic troubles in the countries concerned, which owe their origin to a common cause. This approach has not been explicitly pursued in empirical work on currency crises, although a number of papers have attempted to explain vulnerability to contagious crises in terms of macroeconomic fundamentals.


Following STV, transition economies such as Hungary, Poland and China have been excluded, as have members of the EU such as Greece and Portugal.


See World Bank (1996) for a detailed history and analysis of private capital flows to emerging markets.


The first four variables are the top four in KLR’s ranking of variables on the basis of their accuracy in signaling currency crises in advance. The next three are used by STV/T and BM, among other studies.


In the case of Mexico, for the 1994 Tequila crisis, we use November 1994, rather than December 1994 as the “end of the year.” Also, for ST in the 1998 episode we use the annualized change since the end of the previous crisis period, for those countries that experienced crises in 1997.


Other thresholds have been tested and the results are robust to the choice of threshold.


For the sake of mathematical precision, for exports and stock prices, the Xi denote the negative of those series, since low values of the variables signal crises.


This is because the eighties were a decade characterized by macroeconomic turmoil in many Latin American economies. The nineties are generally seen as a decade significantly distinct and delinked from the 1980’s when speaking of economic circumstances in Latin America.


Although Russia is not part of our sample, we calculate signals for it, for 1998, which are presented along with the signals for other countries in Table 4.


Leaving these observations in raises the R2 substantially. However, since these were the crises that triggered the contagious episodes, whereas the crises that came later happened more or less simultaneously, the crisis index for these data points cannot be explained by the number of other countries in crisis.


Taken alone, this would suggest that the marginal explanatory power of location is modest. Other results, discussed below, indicate otherwise.


Since WC1, CT, and CR are collinear, we cannot any of them as regressors together.


These variables are labeled DM2, DRER, and so on.


By including the economic variables in the regression equation, we have already controlled for common economic weaknesses.


A similar variable, which was a dummy which took the value 1 if a majority of the countries in crisis were in the same region as the country for which the observation was being taken, also turned out to be insignificant.


It should be noted that this index takes into account the fact that currency crises do not have to be manifested in falling exchange rates. Rather, the central bank could be defending a peg under pressure by running down reserves.


A number of different measurement intervals were tried, including the STV/T and BM intervals. The results are robust to the intervals used, and we show the best fit obtained.


The reason for this is straightforward. While the policy instrument the government controls is the nominal exchange rate, the variable the current account responds to is the real exchange rate.


Calvo(1996) has since amended his earlier proposal, suggesting that in comparing countries with significant structural differences, the ratio of M2 to international reserves be adjusted by its first log difference standard deviation. He made this observation in the context of comparing Mexico to Austria. Here, since the countries being compared are rather similar (with the possible exception of Singapore), structurally, in that they are all emerging markets, this adjustment is perhaps less necessary.


The assumption here is that capital controls are not an option.


This is the essence of the classic model of bank runs proposed by Diamond and Dybvig (1983). Chang and Velasco (1998) propose a theoretical model of currency crises based on this idea.


Bank loans to the private sector are made on the basis of expectations that economic growth will occur at a certain rate. During lending booms, these expectations tend to be unusually optimistic-because banks have excess funds to lend, they are willing to lend to riskier projects. Hence the increased vulnerability of their portfolios to economic contractions.


The former would hurt the banking sector by raising interest rates and reducing growth, at a time when its loan portfolios have an unduly high proportion of loans that are risky, in that they will be repaid only if economic growth is high. This has, of course, to be considered in the context of the currency composition of the liabilities of the banking sector. If a high proportion of liabilities, relative to assets, is denominated in foreign currency, then a devaluation will also hurt banks, by increasing their liabilities by more than their assets. If, however, a large proportion of liabilities is denominated in domestic currency, the devaluation will be a blessing.

Discriminating Contagion: An Alternative Explanation of Contagious Currency Crises in Emerging Markets
Author: Pavan Ahluwalia