In this paper we propose residual-based tests for the null hypothesis of cointegration with a structural break against the alternative of no cointegration. The Lagrange Multiplier (LM) test is proposed and its limiting distribution is obtained for the case in which the timing of a structural...

In this paper we propose residual-based tests for the null hypothesis of cointegration with structural breaks against the alternative of no cointegration. The Lagrange Multiplier test is proposed and its limiting distribution is obtained for the case in which the timing of a structural break is...

This study proposes constructing a confidence set for the date of a one-time structural change using a point optimal test. Following Elliott and Mler (2007), we first construct a test for the break date that maximizes the weighted average of the power function. The confidence set is then...

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...