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How Smart Is my Dummy? Time Series Tests for the Influence of Politics

Published online by Cambridge University Press:  04 January 2017

Tony Caporale  and
Kevin Grier
Tony Caporale
Affiliation:
Department of Economics, 331 Bentley Annex, Ohio University, Athens, OH 45701. e-mail: caporale@ohio.edu (corresponding author)
Kevin Grier
Affiliation:
Department of Economics, 335 Hester Hall, University of Oklahoma, Norman, OK 73019. e-mail: angus@ou.edu
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Abstract

Of necessity, many tests for political influence on policies or outcomes involve the use of dummy variables. However, it is often the case that the hypothesis against which the political dummies are tested is the null hypothesis that the intercept is otherwise constant throughout the sample. This simple null can cause inference problems if there are (nonpolitical) intercept shifts in the data and the political dummies are correlated with these unmodeled shifts. Here we present a method for more rigorously testing the significance of political dummy variables in single equation models estimated with time series data. Our method is based on recent work on detecting multiple regime shifts by Bai and Perron. The article illustrates the potential problem caused by an overly simple null hypothesis, exposits the Bai and Perron model, gives a proposed methodology for testing the significance of political dummy variables, and illustrates the method with two examples.

Before the curse of statistics fell upon mankind we lived a happy, innocent life

—Hilaire Belloc, On Statistics

Type
Research Article
Information
Political Analysis , Volume 13 , Issue 1 , Winter 2005 , pp. 77 - 94
Copyright
Copyright © Society for Political Methodology 2005 

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