In recent years, there has been increasing interest in nonparametric bootstrap inference for economic time series. Nonparametric resampling techniques help protect against overly optimistic inference in time series models of unknown structure. They are particularly useful for evaluating the fit...

There is a widespread tendency in the applied time series literature to interpret rejections of the unit root null hypothesis in favor of a trend stationary process with possible trend breaks as evidence that the data are better characterized as stationary about a broken trend. This...

The half-life of deviations from purchasing power parity (PPP) plays a central role in the ongoing debate about the ability of macroeconomic models to account for the time series behavior of the real exchange rate. The main contribution of this paper is a general framework in which alternative...

Spectral analysis at frequencies other than zero plays an increasingly important role in econometrics. A number of alternative automated data-driven procedures for nonparametric spectral density estimation have been suggested in the literature, but little is known about their finite-sample...

The conventional Edgeworth expansion view of bootstrap confidence intervals suggests that for the bootstrap to exceed the accuracy of the normal approximation one must bootstrap asymptotically pivotal statistics. This paper questions the basic premise of the asymptotic theory used to rationalize...