We reexamine commodity futures returns for evidence of fractional integration utilizing two estimators based on wavelets. We summarize basic wavelet methods for signal processing and decompose commodity futures returns by wavelet scale. We find the evidence for long memory is not conclusive...

This paper develops a simple bivariate count data regression model in which dependence between count variables is introduced by means of stochastically related unobserved heterogeneity components. Unlike existing commonly used bivariate models, we obtain a computationally simple closed form of...

F tests which test jointly for a unit root and a zero intercept, and so compete against Dickey-Fuller t tests, are shown not to enhance power because they are invariant to the intercept value in the absence of a unit root. Monte Carlo results in the literature that indicate otherwise are shown...

We use a very general bivariate GARCH-M model and quarterly data for five Asian countries to test for the impact of real and nominal macroeconomic uncertainty on inflation and output growth. We conclude the following. First, in the majority of countries uncertainty regarding the output growth...

A firm's announcement that it intends to restructure based on tracking stock is usually associated with a positive stock price reaction, at least in the short run. Typically, this reaction is attributed to expected reductions in a diversification discount, through reduced agency costs or...

This paper reexamines foreign currency markets for evidence of fractional integration, and extends the extant literature in several important dimensions. First, we utilize a new semiparametric wavelet-based estimator, which is far superior to the more prevalent GPH estimator on the basis of mean...

This paper examines the effects of inflation uncertainty on real economic activity by utilizing a flexible, dynamic, multivariate framework that accommodates possible interaction between the conditional means and variances. The empirical model is based on a familiar identified vector...

Unit-root testing strategies are unnecessarily complicated because they do not exploit prior knowledge of the growth status of the time series, they worry about unrealistic outcomes, and they double- or triple-test for unit roots. The authors provide a testing strategy that cuts through these...