In this paper, we test the Prebish–Singer (PS) hypothesis, which states that real commodity prices decline in the long run, using two recent powerful panel data stationarity tests accounting for cross-sectional dependence and a structural break. We find that the hypothesis cannot be rejected...

This paper proposes the use of covariate unit root tests and the exploitation of the information on the cross-sectional dependence when the panel data null hypothesis of a unit root is rejected or when N is relatively small in order to help the interpretation of the test results. In particular,...

In this paper, we propose new cointegration tests for single equations and panels. In both cases, the asymptotic distributions of the tests, which are derived with N fixed and T going to infinity, are shown to be standard normals. The effects of serial correlation and cross-sectional dependence...

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...

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...