We propose computing HAC covariance matrix estimators based on one-step-ahead forecasting errors. It is shown that this estimator is consistent and has smaller bias than other HAC estimators. Moreover, the tests that rely on this estimator have more accurate sizes without sacrificing its power.

It is well documented that the term structure of interest rates has predictive power for real economic growth. Applying the stepwise superior predictive ability test, we find that superior models contain both a short-term rate and a term spread.

We propose an encompassing test for non-nested linear quantile regression models and show that it has an asymptotic [chi]2 distribution. It is also shown that the proposed test is a regression rank score test in a comprehensive model under conditional homogeneity. Our simulation results indicate...

We give two new approaches to testing conditional exogeneity. This condition ensures unconfoundedness and identification of structural effects. Our approaches permit the presence of treatment effects under the null, thereby complementing methods of Rosenbaum (1987) and Heckman and Hotz (1989).