The Rationality and Heterogeneity of Survey Forecasts of the Yen-Dollar Exchange Rate: A Reexamination

This paper examines the rationality and diversity of industry-level forecasts of the yen-dollar exchange rate collected by the Japan Center for International Finance. In several ways we update and extend the seminal work by Ito (1990). We compare three specifications for testing rationality: the ”conventional” bivariate regression, the univariate regression of a forecast error on a constant and other information set variables, and an error correction model (ECM). We find that the bivariate specification, while producing consistent estimates, suffers from two defects: first, the conventional restrictions are suffcient but not necessary for unbiasedness; second, the test has low power. However, before we can apply the univariate specification, we must conduct pretests for the stationarity of the forecast error. We find a unit root in the six-month horizon forecast error for all groups, thereby rejecting unbiasedness and weak effciency at the pretest stage. For the other two horizons, we find much evidence in favor of unbiasedness but not weak effciency. Our ECM rejects unbiasedness for all forecasters at all horizons. We conjecture that these results, too, occur because the restrictions test suffciency, not necessity. In our systems estimation and micro- homogeneity testing, we use an innovative GMM technique (Bonham and Cohen (2001)) that allows for forecaster cross-correlation due to the existence of common shocks and/or herd e ects. Tests of micro-homogeneity uniformly reject the hypothesis that forecasters across the four industries exhibit similar rationality characteristics.