We thank S. Popp for his contributions in the early stages of this work. Comments from audiences at the University of Oxford, at the Institute for Advanced Studies at Vienna and at the Third Italian Congress of Econometrics and Empirical Economics at Ancona are gratefully acknowledged. We are especially grateful to R. Cerqueti, J. Dolado, L. Gutierrez, R. Kunst, P.K. Narayan, P. Paruolo, M. Wagner, J. Westerlund and D. Zaykin for comments and discussion on the paper or specific parts of it. None of them is responsible for any remaining error. We are pleased to thank Y. Chang and W. Song for having provided their data and GAUSS code. Comments from an Editor and three anonymous referees greatly helped us in improving on previous versions of the paper. The implementation of the panel unit root test described in this paper is part of the ongoing R (RDevelopment Core Team, 2011) project punitroots and is freely available from the R-Forge website (see Kleiber and Lupi, 2011).
A Simple Panel-CADF Test for Unit Roots*
Version of Record online: 30 JAN 2012
© Blackwell Publishing Ltd and the Department of Economics, University of Oxford 2012
Oxford Bulletin of Economics and Statistics
Volume 75, Issue 2, pages 276–296, April 2013
How to Cite
Costantini, M. and Lupi, C. (2013), A Simple Panel-CADF Test for Unit Roots. Oxford Bulletin of Economics and Statistics, 75: 276–296. doi: 10.1111/j.1468-0084.2012.00690.x
- Issue online: 4 MAR 2013
- Version of Record online: 30 JAN 2012
- Final Manuscript Received: December 2011
In this paper, we propose a simple extension to the panel case of the covariate-augmented Dickey–Fuller (CADF) test for unit roots developed in Hansen (1995). The panel test we propose is based on a P values combination approach that takes into account cross-section dependence. We show that the test has good size properties and gives power gains with respect to other popular panel approaches. An empirical application is carried out for illustration purposes on international data to test the purchasing power parity (PPP) hypothesis.