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A reinterpretation of interactions in regressions

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  • J. Hirschberg
  • J. Lye

Abstract

Regression specifications in applied econometrics frequently employ regressors, which are defined as the product of two other regressors to form an interaction. Unfortunately, the interpretation of the results of these models is not as straight forward as in the linear case. In this article, we present a method for drawing inferences for interaction models by defining the partial influence (PI) function. We present an example that demonstrates how one may draw new inferences by constructing the confidence intervals for the PI functions based on the traditional published findings for regressions with interaction terms.

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File URL: http://www.informaworld.com/openurl?genre=article&doi=10.1080/13504850701842843&magic=repec&7C&7C8674ECAB8BB840C6AD35DC6213A474B5
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Bibliographic Info

Article provided by Taylor & Francis Journals in its journal Applied Economics Letters.

Volume (Year): 17 (2010)
Issue (Month): 5 ()
Pages: 427-430

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Handle: RePEc:taf:apeclt:v:17:y:2010:i:5:p:427-430

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  1. Wo[ss]mann, Ludger & West, Martin, 2006. "Class-size effects in school systems around the world: Evidence from between-grade variation in TIMSS," European Economic Review, Elsevier, vol. 50(3), pages 695-736, April.
  2. Joshua D. Angrist & Victor Lavy, 1999. "Using Maimonides' Rule To Estimate The Effect Of Class Size On Scholastic Achievement," The Quarterly Journal of Economics, MIT Press, vol. 114(2), pages 533-575, May.
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Cited by:
  1. Adolfo Barajas & Ralph Chami & Reza Yousefi, 2013. "The Finance and Growth Nexus Re-Examined," IMF Working Papers 13/130, International Monetary Fund.

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