One of the more controversial elements of the stabilization programs in the East Asian crisis countries (Indonesia, Korea, and Thailand) was the stance of monetary policy. With the sharp exchange rate depreciations experienced at the onset of the crisis, standard policy prescriptions called for an immediate tightening of monetary policy.
But continued depreciation of the exchange rates—well into the stabilization programs—began to raise doubts about the efficacy of raising interest rates to defend the currency.1 Some commentators, indeed, started suggesting that raising interest rates, far from stabilizing the exchange rate, could actually prove counterproductive: further depreciating the exchange rate instead of appreciating it. The mechanism of this “perverse” effect is straightforward. High (presumably, real) interest rates, by causing widespread bankruptcies (or the expectation thereof), result in larger country risk premiums—so much so that the expected return to investors actually declines as interest rates increase, thus prompting even more capital flight and generating greater downward pressure on the exchange rate.2
Establishing whether tighter monetary policy—often taken to mean an increase in nominal interest rates—appreciates or depreciates the currency turns out to be a surprisingly difficult task. Such studies as do exist typically use regressions or vector autoregressions to correlate exchange rate movements to changes in nominal interest rates. This approach, however, runs into two main problems.3
First, the level of nominal interest rate is simply not a good measure of the monetary stance. To give but the starkest example, in January 1998 interest rates in Indonesia reached almost 60 percent per year (far higher than the interest rates witnessed in the other Asian crisis countries) at a time when the money supply was expanding at a monthly rate of 30 percent—scarcely a tight monetary stance. Second, simple time series correlations or vector autoregressions provide very little structure on the model, and their empirical performance in explaining exchange rate movements—even in the absence of a crisis—is, at best, limited. It is difficult to know what to make of a statement such as “higher interest rates are not correlated with exchange rate appreciations during the East Asian crisis” when the model is mute on what is driving the exchange rate.
In this paper, we propose an alternative approach to examining whether high real interest rates resulted in exchange rate depreciations. We start from the simple proposition that, as the relative price of two monies, the exchange rate should appreciate in response to a contraction of the domestic money supply. This, together with the empirical observation that in the Asian crisis countries there is a somewhat better correspondence between the exchange rate and the money supply (than between the exchange rate and interest rates), suggests that a standard monetary model may be useful for explaining the bulk of the exchange rate dynamics. This allows us to isolate the risk premium, controlling for changes in monetary policy, and permits a direct test of whether higher real interest rates are associated with a larger risk premium—and thus, ceteris paribus, downward pressure on the exchange rate.
By measuring the monetary stance by the money supply, and by using an explicit model of exchange rate determination, our approach goes at least part of the way in addressing the methodological problems identified above. Of course, even if higher real interest rates are correlated with a larger risk premium, it does not necessarily follow that tightening monetary policy is counterproductive for stabilizing the exchange rate. The magnitude of the effect on the risk premium may be small. And, of course, there may be third factors (such as adverse political news) affecting both the real interest rate and the risk premium on the exchange rate. Nonetheless, if the findings suggest no correlation between real interest rates and the risk premium, then the possibility of the perverse effect (of tight monetary policy causing an exchange rate depreciation) can be ruled out.
We apply our methodology to the 1997 currency crises in the three Asian countries and, by way of comparison, to the 1994 Mexican crisis. Our results may be summarized briefly. We find that the pure monetary model does credibly well in explaining much of the observed exchange rate movements (though the stringent cross-equation constraints are rejected). Augmenting this framework to allow for a time-varying risk premium, we find little evidence that high real interest rates are correlated with a larger risk premium in any of the countries except Korea. Once a simple contagion variable is added to the explanatory variables of the risk premium, moreover, the significance of the real interest rate diminishes even in the case of Korea. We conclude that there is little evidence of a “perverse” effect of a monetary tightening on the exchange rate.
The remainder of the paper is organized as follows. Section I provides a brief review of the literature and an overview of exchange rate developments during the crisis. Section II lays out the methodology. Section III reports the parameter estimates of the monetary model. Section IV turns to the behavior of the risk premium. Section V concludes.
Campbell, John Y., and Robert Shiller, 1987, “Cointegration and Tests of Present Value Models,” Journal of Political Economy, Vol. 95 (October), pp. 1062–88.
Furman, Jason, and Joseph E. Stiglitz, 1998, “Economic Crises: Evidence and Insights from East Asia,” Brookings Papers on Economic Activity: 2, pp. 1–35.
Ghosh, Atish R., 1992, “Is It Signalling? Exchange Intervention and the Dollar-Deutschemark Rate,” Journal of International Economics, Vol. 32 (May), pp. 201–20.
Goldfajn, Ilan, and Taimur Baig, 1999, “Monetary Policy in the Aftermath of Currency Crises: The Case of Asia,” IMF Working Paper 98/170 (Washington: International Monetary Fund).
Goldfajn, Ilan, and Poonam Gupta, 1998, “Overshootings and Reversals: The Role of Monetary Policy” (unpublished; Washington: International Monetary Fund).
Kraay, Aart, 1999, “Do High Interest Rates Defend Currencies During Speculative Attacks?” Policy Research Working Paper No. 2267 (Washington: World Bank).
Lane, Timothy, and others, 1999, IMF-Supported Programs in Indonesia, Korea, and Thailand: A Preliminary Assessment, IMF Occasional Paper No. 178 (Washington: International Monetary Fund).
Meese, Richard A., and Kenneth Rogoff, 1983, “Empirical Exchange Rate Models of the Seventies: Do They Fit Out of Sample?” Journal of International Economics, Vol. 14 (February), pp. 3–24.
Woo, Wing T., 1985, “The Monetary Approach to Exchange Rate Determination Under Rational Expectations: The Dollar-Deutschemark Rate,” Journal of International Economics, Vol. 18 (February), pp. 1–16.
Gabriela Basurto is Financial Markets Consultant at the Inter-American Development Bank. Atish Ghosh is a Deputy Division Chief in the IMF’s Policy Development and Review Department. This paper was prepared for the First Annual Research Conference of the International Monetary Fund, November 9–10, 2000. The authors would like to thank Robert Flood, Philip Lane, Timothy Lane, and participants at the Policy Development and Review Department Seminar Series and at the Research Conference for many useful comments on an earlier version of this paper.
IMF-supported programs began in August 1997 in Thailand, November 1997 in Indonesia, and December 1997 in Korea, while the most depreciated exchange rates were in January 1998 in Korea and Thailand and in July 1998 in Indonesia. Lane and others (1999) provides a useful summary.
An important proponent of this school of thought is Joseph Stiglitz; see, for example, Furman and Stiglitz (1998).
A third problem is that of policy endogeneity and causality. Interest rates were raised in East Asia precisely because the exchange rate was depreciating. The issue goes beyond finding appropriate instruments for interest rate policy (itself no easy task): In an environment in which policies are being set in anticipation of reactions of the exchange market, and the market-determined exchange rate embodies expectations of future policy, it becomes virtually impossible to disentangle cause from effect. Kraay (1999) reports results using an instrumental variable technique.
Exchange rates in Indonesia and Korea were not, in fact, pegged, and the exchange rate had already started depreciating, so the onset of the crisis in each country is not precisely defined. Below, we use August 1997 and November 1997, respectively, as the start dates of the “floating period” in Indonesia and Korea.
Goldfajn and Gupta (1998) take another tack and study the behavior of nominal exchange rates in the aftermath of a speculative attack and, in particular, whether higher interest rates are associated with the reversal of the overshooting of the real exchange rate taking place through a nominal exchange rate appreciation rather than through higher inflation. They find that higher interest rates are indeed associated with the real appreciation taking place through the nominal exchange rate, with the important caveat that this result does not apply in countries that also suffered a banking crisis.
In fact, finding pure “policy” interest rates in these countries is not easy. In Korea, for instance, the so-called Bank of Korea discount rate barely moved during the crisis, and actually fell from 5.0 percent to 3.0 percent. In Indonesia, the market-determined interest rate rose to 60 percent even as broad money was expanding at a monthly rate of 30 percent, while Bank Indonesia’s discount rate remained constant at 20 percent per year.
The essential econometric methodology was developed by Campbell and Shiller (1987) in a somewhat different context.
However, other shocks, such as negative shocks to money demand, will be included in the risk premium. Thus, the test proposed here is probably conservative in the sense of being more likely to find a “perverse” effect of higher interest rates on the exchange rate.
In this sense, the test proposed here is similar in spirit to variance bounds tests where the precise model is of less interest than the excess movement of the variable relative to the benchmark bound.
Correspondingly, for the foreign country (the United States) m* – p* = αy* – βi*.
There are some subtle issues concerning the treatment of the real exchange rate. Clearly, the real exchange rate was not constant following the currency crises in these countries, so purchasing power parity (PPP) cannot be imposed. On the other hand, to the extent that the real exchange rate is driven entirely by movements of the nominal exchange rate, the “fundamentals” Δx will spuriously be correlated with the nominal exchange rate movement. In both Mexico and the Asian countries, however, real exchange rate changes were large and persistent, without a return to the pre-crisis level either through nominal appreciation (once the float began) or inflation—suggesting that real factors were also at play. Because our intention here is to create a benchmark model to filter out fundamentals, we include the real exchange rate in x. As a robustness check, we report results instrumenting for Δx with its lagged value.
Ghosh (1992) works with a lagged adjustment money demand function and shows that the quasi-first difference, st - λst–1, should be stationary (where 0 < λ < 1 is a quadratic root that depends on the money demand parameters). The estimated value of λ is typically very close to unity, however; as a simplifying approximation, therefore, we use the first difference directly.
The issue is important because otherwise expectations of looser monetary policy are shifted to the risk premium term (since it is the residual), and the risk premium would be capturing not only credit risk, but also the risk associated with looser monetary policy.
To see this, note that Et Δxt+j = [1 0]’Φjzt. Therefore, [1/(1 +β)] Σ Et Δxt+j (β/(1+β))j = [1/(1+β)] [1 0]’[I–β(1+β)Φ]-1zt.
The pure monetary model also has implications for the other parameters; to wit, Γ1 = 0, Γ2 = 1.
Thailand, July 1997 onward; Indonesia, August 1997 onward, Korea, November 1997 onward. For Mexico there are enough observations to use only the post-float period (December 1994 onward). Monthly data are taken from International Financial Statistics: exchange rate (line af); money plus quasi-money (lines 34+35); consumer price index (line 64); lending interest rate (line 60p); and industrial production (line 66). For Thailand, industrial production was taken from the Bank of Thailand Monthly Bulletin, and for Indonesia, quarterly data from Biropustat Statitistik are interpolated. Data on foreign exchange deposits to adjust the broad money figures are taken from the central bank bulletins or websites.
The order of the VARs was chosen using the Schwartz-Bayes criterion.
That is, we compute
Recall that the model implies Γ1 = 0 and Γ2 = 1. Standard errors were computed numerically as ∇Q’Σ∇Q, where ∇Q is the gradient of Γ with respect to the VAR parameters, and Σ are the White-consistent standard errors.