While the predictability of excess stock returns is statistically small, their sign and volatility exhibit a substantially larger degree of dependence over time. We capitalize on this observation and consider prediction of excess stock returns by decomposing the equity premium into a product of...

Sometimes the conventional asymptotic theory yields that the limiting distribution changes discontinuously, or that the asymptotic distribution does not approximate accurately the actual finite-sample distribution. In such situations one finds useful an asymptotic tool of drifting...

This paper studies the asymptotic validity of the Anderson-Rubin (AR) test and the J test of overidentifying restrictions in linear models with many instruments. When the number of instruments increases at the same rate as the sample size, we establish that the conventional AR and J tests are...

This paper studies the asymptotic validity of the Anderson–Rubin (<italic>AR</italic>) test and the <italic>J</italic> test for overidentifying restrictions in linear models with many instruments. When the number of instruments increases at the same rate as the sample size, we establish that the conventional <italic>AR</italic> and <italic>J</italic> tests are...

This article proposes a bootstrap method for constructing two-sided confidence intervals for the moving average (MA) parameter in nearly noninvertible models. The confidence intervals are obtained by inverting the acceptance region of the likelihood ratio (LR) test reflecting the asymmetry of...

Many economic time series are charecterized by high persistence which typically requires nonstandard limit theory for inference. This paper proposes a new method for constructing confidence intervals for the impulse response functions of nearly nonstationary processes. The method is based on...

This paper analyzes the sampling properties of the widely documented large negative slope estimates in regressions of future exchange returns on current forward premium. We argue that the abnormal behavior of the slope estimators in these regressions arises from the simultaneous presence of high...

This paper proposes a nonparametric regression using asymmetric kernel functions for nonnegative, absolutely regular processes, and specializes this technique to estimating scalar diffusion models of spot interest rate. We illustrate the advantages of asymmetric kernel estimators for bias...

This paper proposes a bootstrap unit root test in models with GARCH(1,1) errors and establishes its asymptotic validity under mild moment and distributional restrictions. While the proposed bootstrap test for a unit root shares the power enhancing properties of its asymptotic counterpart (Ling...