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University of California Berkeley Department of Economics - - _ University of California Berkeley CENTER FOR INTERNATIONAL AND DEVELOPMENT ECONOMICS RESEARCH Working Paper No. C93-009 Patterns in Exchange Rate Forecasts for 25 Currencies Menzie Chinn and Jeffrey Frankel January 1993 Department of Economics WITHDRAWN POU. AGRICULTURAL N OM CL. LIBRARY MAR 1 !' ben CIDER t CENTER FOR INTERNATIONAL AND DEVELOPMENT ECONOMICS RESEARCH The Center for International and Development Economics Research is funded by the Ford Foundation. It is a research unit of the Institute of International Studies which works closely with the Department of Economics and the Institute of Business and Economic Research. CIDER is devoted to promoting research on international economic and development issues among Berkeley CIDER faculty and students, and to stimulating collaborative interactions between them and scholars from other developed and developing countries. INSTITUTE OF BUSINESS AND ECONOMIC RESEARCH Richard Sutch, Director The Institute of Business and Economic Research is an organized research unit of the University of California at Berkeley. It exists to promote research in business and economics by University faculty. These working papers are issued to disseminate research results to other scholars. Individual copies of this paper are available through IBER, 156 Barrows Hall, University of California, Berkeley, CA 94720. Phone (510) 642-1922, fax (510) 642-5018. UNIVERSITY OF CALIFORNIA AT BERKELEY Department of Economics Berkeley, California 94720 - ,CENTER FOR INTERNATIONAL AND DEVELOPMENT ECONOMICS RESEARCH Working Paper No. C93-009 Patterns in Exchange Rate Forecasts for 25 Currencies Menzie Chinn and Jeffrey Frankel January 1993 Key words: expectations, survey, forward rate, exchange rate JEL Classification: F31, 015 Abstract The properties of exchange rate forecasts are investigated, with a data set encompassing a broad cross section of currencies. Over the entire sample, expectations appear to be biased. This result is robust to the possibility of random measurement error in the survey measures. There appear to be statistically significant differences in the degree of bias in subgroupings of the data: (i) the bias is lower for the high-inflation countries; (ii) the bias is greater for the major currencies studied in earlier papers; and (iii) the bias is also greater for the EMS currencies. Acknowledgements We wish to thank David Bowman, Steve Phillips and two anonymous referees for comments, and Julia Lowell for both comments and assistance in collecting the data. We would also like to thank the Institute of Business and Economic Research, the Institute for International Studies, and the Center for International and Development Economics Research, at U.C. Berkeley for support. This is a revised version of NBER Working Paper No. 3807. Menzie Chinn Jeffrey Frankel Assistant Professor Professor Department of Economics Department of Economics University of California University of California at Berkeley at Santa Cruz Visiting Scholar Institute for International Economics 11 Dupont Circle, Washington, D.C. 20036 1. INTRODUCTION In this paper we apply a new data set to the problem of assessing whether exchange rate expectations are unbiased. It consists of survey data derived from Currency Forecasters' Digest (hereafter CFD). CFD collects and publishes forecasts for over 25 exchange rates, and includes several for newly industrializing countries in Asia, Latin American LDCs, and smaller developed countries in Europe and elsewhere, each month. The hope is that with a much broader and more heterogeneous set of currencies than that in earlier studies of survey data, interesting new patterns can be identified.1 Indeed, we find that (i) the amount of information in the survey'data is much higher with respect to high-inflation countries; (ii) the forecasts for the minor currencies exhibit less bias than those for the main currencies previously studied, and (iii) the EMS currency forecasts exhibit more bias than those for other currencies, especially at the 12 month horizon. It is perhaps reassuring that there is at least some degree of predictive power in the cases of smaller countries with less stable currencies. The data and general approach are discussed in the next section. Section 3 assesses the question whether the exchange rate expectations are biased forecasts of future spot rates for the entire sample. Section 4 examines whether subsamples of the data exhibit differing patterns. Section 5 concludes. 2. DATA AND GENERAL METHODOLOGY Survey data are generally viewed with suspicion by economists. Some argue that, as social scientists, we should pay more attention to what people do, rather than to what they say. Unfortunately, alternative measures of expectations have their own limitations. Consequently, macroeconomists have resorted to various survey measures such as the Livingstone survey of inflationary expectations. Several recent studies have found that survey data do contain useful information about future events (e.g. Dokko and Edelstein, 1989; Englander and Stone, 1989). Indeed, to the extent that the forecasters represented in the CFD survey participate directly in the relevant markets (see below), the case for using such data is perhaps even firmer than that for the aforementioned domestic surveys. The exchange rate forecasts are usually compiled on the fourth Thursday of each month. Our data set runs from February of 1988 to February of 1991, for about 25 exchange rates.' The survey includes some additional exchange rates that we exclude from our sample because they either begin toward the end of the sample period, or appear too intermittently to be useful. The survey respondents are reported to number approximately 45, of which two-thirds are multinational firms and the remainder forecasting firms or the economics departments of banks. We use as the measure of expectations the "consensus forecast" that CFD emphasizes. This measure is the harmonic mean:3 Tc [E1w(1/X)]i -1 Eiwi = 1 where Xi is the individual forecast = 1/N N is the number of forecasts. The spot rates used to compute expected rates of change are the London midday interbank middle rate, as reported in CFD and are contemporaneous with the forecast compilation:: The forward rates are similarly dated London close rates, and are the arithmetic average of the bid and ask rates. The regressions are run on a pooled time series/cross section.' In this paper, we will be investigating the nature of the three and twelve month horizon forecasts. Regressions involving the ability to forecast ex post exchange rates encounter the econometric problem of overlapping observations. Since the data are sampled at intervals finer than the forecast horizon, the regression residuals will exhibit a moving average process of order k-1 (where k is the forecast horizon). Since generalized least squares yields inconsistent estimates, this means that in order to make correct inferences, a Hansen (1982) heteroskedasticity and serial correlation robust estimate of the parameter covariance matrix should be used.6 3. ARE CONDITIONAL EXPECTATIONS UNBIASED? Previous studies examining the issue of unbiasedness in expectations have usually imposed the auxiliary 2 assumption of risk neutrality under which the forward rate equals the expected future rate. Unbiasedness of the forward discount has been overwhelmingly rejected, as it is in our sample (Frankel and Chinn, 1991). But it is impossible to tell whether the rejection of the null hypothesis is due to a bias in investors' expectations or to a risk premium that separates the forward rate from the expected future spot rate, without additional information such as that provided by the surveys. We now move to an explicit evaluation of the forecasting characteristics of our expectations measures. A common procedure is to regress the ex post depreciation on the survey measure of expected depreciation. The unbiasedness proposition is represented by the null hypothesis that the coefficient on expected depreciation equal unity. Such a test attempts to detect what Bilson (1981) called "excessive speculation" or "over-excitability": a coefficient less than one. An equivalent test is to run a regression of the forecast error on expected depreciation. ASt+k "ct,t+k a ± BiAget,t+k 111,t+k (1) Where: •St+k St+k - •gct,t+k get,t+k - St get,t+k is the expected spot rate at time t+k, based on the survey measures taken at time t. Now the unbiasedness hypothesis is represented by the null hypothesis that 1l1=0, and the alternative: if expectations are rational, then the forecast errors which appear as the lefthand-side variable should be purely random. If the alternative, B1 < 0, is accepted, then investors could make better guesses by betting against the consensus forecast. We ran these regressions on both the entire sample, and a sample excluding the three high- inflation countries, Argentina, Brazil and Mexico.' Estimates for the equation are presented in Table 1. Four regressions are reported. Two constrain the intercept for all currencies to be the same, but Chi2 tests for the restriction are rejected. 3 • [TABLE 1 about here] Focusing attention on the unconstrained regressions, one finds that the estimate of B1 is negative, and large in economic terms. One cannot reject the null that the coefficient is -1, at the three month horizon, and can only reject at the 10% level at the 12 month. In both cases, the zero coefficient null is strongly rejected. When the sample excludes the high-inflation countries of Argentina, Brazil and Mexico, then the rejection of a zero-coefficient becomes even more pronounced. Because the error processes for the high-inflation currencies and the other currencies are unlikely to be similar, we choose to report results for both the entire sample and the sample excluding these currencies. Additional results pertaining to this stratification can be found in the 1991 working paper. The finding of conditional bias over the 1988-90 period is interesting because it corroborates results in Frankel and Froot (1987) which noted the persistent errors in the wake of the dollar's mid-1980s rise and fall.
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