In this paper, we consider the role of “leads” of the first difference of integrated variables in the dynamic OLS estimation of cointegrating regression models. Specifically, we investigate Stock and Watson’s [J.H. Stock, M.W. Watson’s, A simple estimator of cointegrating vectors in...

It is widely known that structural break tests based on the long-run variance estimator, which is estimated under the alternative, suffer from serious size distortion when the errors are serially correlated. In this paper, we propose bias-corrected tests for a shift in mean by correcting the...

We examine finite sample properties of estimators for approximate factor models when N is small. Contrary to the “rule-of-thumb”, we find that the principal component analysis estimator and the quasi-maximum likelihood estimator perform well even when N is small.

This paper develops a simple test à la Pesaran (2007) for the null hypothesis of stationarity in heterogeneous panel data with cross-sectional dependence in the form of a common factor in the disturbance. We also allow for serial correlation.

In this paper, we analyze feasible bias-reduced versions of point estimates for predictive regressions: The plug-in estimates, which are based on the augmented regressions proposed by Amihud and Hurvich (2004) and Amihud, Hurvich and Wang (2010), and the grouped jackknife estimate by Quenouille...

In this paper, Mallows'(1973) Cp criterion, Akaike's (1973) AIC, Hurvich and Tsai's (1989) corrected AIC and the BIC of Akaike (1978) and Schwarz (1978) are derived for the leads-and-lags cointegrating regression. Deriving model selection criteria for the leads-and-lags regression is a...

This paper examines a point optimal invariant (POI) test for the null hypothesis of cointegration. Our test is different from Jansson's (2005) test in that we consider location invariance in wider directions and that we assume an unknown variance-covariance matrix for the error term, while it is...