A reinterpretation of interactions in regressions
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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Volume (Year): 17 (2010)
Issue (Month): 5 ()
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- Ludger Wößmann & Martin R. West, 2002.
"Class-Size Effects in School Systems Around the World: Evidence from Between-Grade Variation in TIMSS,"
Kiel Working Papers
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- 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.
- Wößmann, Ludger & West, Martin R., 2006. "Class-size effects in school systems around the world: Evidence from between-grade variation in TIMSS," Munich Reprints in Economics 19673, University of Munich, Department of Economics.
- Woessmann, Ludger & West, Martin R., 2002. "Class-Size Effects in School Systems Around the World: Evidence from Between-Grade Variation in TIMSS," IZA Discussion Papers 485, Institute for the Study of Labor (IZA).
- 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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