Nonlinearity in Deviations from Uncovered Interest Parity: AnExplanation of the Forward Bias Puzzle*We provide empirical evidence that deviations from the uncovered interest rate parity (UIP) condition display significant nonlinearities, consistent with theories based on transactions costs or limits to speculation. This evidence suggests that the forward bias documented in the literature may be less indicative of major market inefficiencies than previously thought. Monte Carlo experiments allow us to reconcile these results with the large empirical literature on the forward bias puzzle since we show that, if the true process of UIP deviations were of the nonlinear form we consider, estimation of conventional spot-forward regressions would generate the anomalies documented in previous research.JEL Classification: F31

This paper examines whether deviations from PPP are stationary in the presence of nonlinearity, and whether the adjustment towards PPP is symmetric from above and below. Using alternative nonlinear models, our results support mean reversion and asymmetric adjustment dynamics. We find differences in magnitudes, frequencies and durations of the deviations of exchange rates from fixed and time-varying thresholds, both between over-appreciations and over-depreciations and between developed and developing countries. In particular, the average cumulative sum of deviations during periods when exchange rates are below forecasts is twice that during periods of over-appreciation and larger for developing than advanced countries. Copyright © 2005 John Wiley & Sons, Ltd.

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This paper estimates the responsiveness of sectoral subindex returns to changes in the domestic market portfolio, and compares predictions of nonsystematic risk using GARCH and EGARCH specifications of the error variance. Our results show that returns for the portfolios of Commercial Banks and Conglomerates respond more than proportionately to changes in the market portfolio, and that nonsystematic volatility appears to have been greater during periods of macroeconomic instability and political unrest.

This paper suggests tests for the heterogeneity of parameters in linear least-squares estimation. The tests are based on the properties of resampled estimates, and test the hypotheses that the parameters have a common mean, or that they are independently and identically distributed.The tests can be viewed as the analogue of those based on recursive residuals, in cross-sectional models. We analyse the properties of tests based on jack-knifed estimates in the linear regression model, and compare their performance in a small empirical application.

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