While the literature concerned with the predictability of stock returns is huge, surprisingly little is known when it comes to role of the choice of estimator of the predictive regression. Ideally, the choice of estimator should be rooted in the salient features of the data. In case of...

While the literature concerned with the predictability of stock returns is huge, surprisingly little is known when it comes to role of the choice of estimator of the predictive regression. Ideally, the choice of estimator should be rooted in the salient features of the data. In case of...

This paper proposes a new test of the null hypothesis that the parameters in a cointegrated panel data regression are equal across the cross-section. The asymptotic distribution of the new test statistic is derived and simulation results are provided to suggest that it performs very well in...

This paper proposes new unit root tests in the context of a random autoregressive coefficient panel data model, in which the null of a unit root corresponds to the joint restriction that the autoregressive coefficient has unit mean and zero variance. The asymptotic distributions of the test...

Using data covering 38 countries across the 1965–2005 period, this paper shows that former British colonies tend to exhibit higher levels of carbon dioxide emission than other countries.

Practitioners are generally well aware of the fact that most standard approaches for estimation and inference in panel data regressions are based on assuming that the cross-sectional units are independent of each other, an assumption that is surely mistaken in applications, especially in...

It is well known that in the context of the classical regression model with heteroskedastic errors, while ordinary least squares (OLS) is not efficient, the weighted least squares (WLS) and quasi-maximum likelihood (QML) estimators that utilize the information contained in the heteroskedasticity...