Why Is the Forward Exchange Rate Forecast Biased? A Survey of Recent Evidence

Charles Engel
September 1995
RWP 95-06
Research Division
Federal Reserve Bank of Kansas City

ABSTRACT

Forward exchange rate unbiasedness is rejected in tests from the current floating exchange rate era. This paper surveys advances in this area since the publication of Hodrick's (1987) survey. It documents that the change in the future exchange rate is generally negatively related to the forward premium. Properties of the expected forward forecast error are reviewed. Issues such as the relation of uncovered interest parity to real interest parity, and the implications of uncovered interest parity for cointegration of various quantities are discussed. The modeling and testing for risk premiums is surveyed. Included in this area are tests of the consumption CAPM, tests of the latent variable model, and portfolio-balance models of risk premiums. General equilibrium models of the risk premium are examined and their empirical implications explored. The survey does not cover the important areas of learning and peso problems, tests of rational expectations based on survey data, or the models of irrational expectations and speculative bubbles.

Charles Engel is a professor of economics at the University of Washington and a research associate with the National Association of Economic Research. He would like to thank Robert Hodrick and Nelson Mark for detailed comments on an earlier draft. He would also like to thank Fischer Black, Jeffrey Frankel and participants at seminars at the Federal Reserve Board, the Federal Reserve Bank of Kansas City and New York University for useful comments, and Mike Hendrickson for excellent research assistance. Some of the work on this paper was completed while the author was a visiting scholar at the Federal Reserve Bank of Kansas City and at the Board of Governors of the Federal Reserve System. The views expressed in this paper are his own and do not necessarily reflect those of the Federal Reserve. The author also acknowledges assistance from the National Science Foundation, NSF grant #SBR-932078.

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