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Dynamic Panel Analysis under Cross-Sectional Dependence

Published online by Cambridge University Press:  04 January 2017

Khusrav Gaibulloev ,
Todd Sandler  and
Donggyu Sul
Khusrav Gaibulloev
Affiliation:
Department of Economics, American University of Sharjah, Sharjah, UAE. e-mail: kgaibulloev@aus.edu
Todd Sandler*
Affiliation:
School of Economic, Political, and Policy Sciences, University of Texas at Dallas, GR 31, 800 W. Campbell Road, Richardson, TX 75080, USA
Donggyu Sul
Affiliation:
School of Economic, Political, and Policy Sciences, University of Texas at Dallas, GR 31, 800 W. Campbell Road, Richardson, TX 75080, USA. e-mail: d.sul@utdallas.edu
*
e-mail: tsandler@utdallas.edu (corresponding author)
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Abstract

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This article investigates inconsistency and invalid statistical inference that often characterize dynamic panel analysis in international political economy. These econometric concerns are tied to Nickell bias and cross-sectional dependence. First, we discuss how to avoid Nickell bias in dynamic panels. Second, we put forward factor-augmented dynamic panel regression as a means for addressing cross-sectional dependence. As a specific application, we use our methods for an analysis of the impact of terrorism on economic growth. Different terrorism variables are shown to have no influence on economic growth for five regional samples when Nickell bias and cross-dependence are taken into account. Our finding about terrorism and growth is contrary to the extant literature.

Information

Type
Research Article
Information
Political Analysis , Volume 22 , Issue 2 , Spring 2014 , pp. 258 - 273
Creative Commons
Creative Common License - CCCreative Common License - BY
This is an Open-Access article, distributed under the terms of the Creative Commons Attribution license (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted re-use, distribution, and reproduction in any medium, provided the original work is properly cited.
Copyright
Copyright © The Author 2014. Published by Oxford University Press on behalf of the Society for Political Methodology

Footnotes

Authors' note: We have profited from comments provided by two anonymous reviewers and R. Michael Alvarez. Any opinions, findings, conclusions, or recommendations are solely those of the authors, and do not necessarily reflect the views of DHS or CREATE. Replication materials for this article are available from the Political Analysis dataverse at http://hdl.handle.net/1902.1/22448. Supplementary materials for this article are available on the Political Analysis Web site.

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Appendix

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Tables S1-S6

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