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A Lot More to Do: The Sensitivity of Time-Series Cross-Section Analyses to Simple Alternative Specifications

Published online by Cambridge University Press:  04 January 2017

Sven E. Wilson
Affiliation:
Department of Political Science, Brigham Young University, 732 SWKT, Provo, UT 84602. e-mail: sven_wilson@byu.edu (corresponding author)
Daniel M. Butler
Affiliation:
Department of Political Science, Stanford University, Encina Hall West, Room 100, Stanford, CA 94305. e-mail: daniel_butler@stanford.edu

Abstract

In 1995, Beck and Katz (B&K) instructed the profession on “What to do (and not to do) with time-series, cross-section data,” and almost instantly their prescriptions became the new orthodoxy for practitioners. Our assessment of the intellectual aftermath of this paper, however, does not inspire confidence in the conclusions reached during the past decade. The 195 papers we reviewed show a widespread failure to diagnose and treat common problems of time-series, cross-section (TSCS) data analysis. To show the importance of the consequences of the B&K assumptions, we replicate eight papers in prominent journals and find that simple alternative specifications often lead to drastically different conclusions. Finally, we summarize many of the statistical issues relative to TSCS data and show that there is a lot more to do with TSCS data than many researchers have apparently assumed.

Type
Research Article
Copyright
Copyright © The Author 2007. Published by Oxford University Press on behalf of the Society for Political Methodology 

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