This research was supported financially by the Netherlands Organisation for Scientific Research (NWO). We are grateful to two anonymous referees, Alain Hecq, Marco Lippi and Franz Palm for helpful comments and discussions. Special thanks go to Peter Boswijk for comments that fundamentally improved the article.
On the Applicability of the Sieve Bootstrap in Time Series Panels*
Article first published online: 9 JAN 2013
© 2013 The Department of Economics, University of Oxford and John Wiley & Sons Ltd.
Oxford Bulletin of Economics and Statistics
Volume 76, Issue 1, pages 139–151, February 2014
How to Cite
Smeekes, S. and Urbain, J.-P. (2014), On the Applicability of the Sieve Bootstrap in Time Series Panels. Oxford Bulletin of Economics and Statistics, 76: 139–151. doi: 10.1111/obes.12005
- Issue published online: 9 JAN 2014
- Article first published online: 9 JAN 2013
- Final Manuscript Received: October 2012
In this article, we investigate the validity of the univariate autoregressive sieve bootstrap applied to time series panels characterized by general forms of cross-sectional dependence, including but not restricted to cointegration. Using the final equations approach we show that while it is possible to write such a panel as a collection of infinite order autoregressive equations, the innovations of these equations are not vector white noise. This causes the univariate autoregressive sieve bootstrap to be invalid in such panels. We illustrate this result with a small numerical example using a simple DGP for which the sieve bootstrap is invalid, and show that the extent of the invalidity depends on the value of specific parameters. We also show that Monte Carlo simulations in small samples can be misleading about the validity of the univariate autoregressive sieve bootstrap. The results in this article serve as a warning about the practical use of the autoregressive sieve bootstrap in panels where cross-sectional dependence of general form may be present.