This paper demonstrates that unit root tests can suffer from inflated Type I error rates when data are cointegrated. Results from Monte Carlo simulations show that three commonly used unit root tests - the ADF, Phillips-Perron, and DF-GLS tests - frequently overreject the true null of a unit...

A meta-analysis (MA) aggregates estimated effects from many studies to calculate a single, overall effect. There is no one, generally accepted procedure for how to do this. Several estimators are commonly used, though little is known about their relative performance. A complication arises when...

This study uses Monte Carlo experiments to produce new evidence on the performance of a wide range of panel data estimators. It focuses on estimators that are readily available in statistical software packages such as Stata and Eviews, and for which the number of crosssectional units (N) and...

This study uses Monte Carlo experiments to produce new evidence on the performance of a wide range of panel data estimators. It focuses on estimators that are readily available in statistical software packages such as Stata and Eviews, and for which the number of cross-sectional units (N) and...

This paper shows how to bootstrap hypothesis tests in the context of the Parks (Efficient estimation of a system of regression equations when disturbances are both serially and contemporaneously correlated 1967) estimator. It then demonstrates that the bootstrap outperforms Parks's top...

A meta-analysis is a tool for aggregating estimates of a similar "effect" across many studies. Publication bias is the phenomenon where literature is sample selected in favor of studies having statistically significant results and/or having estimates that satisfy pre-conceived expectations. A...