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Interactions in Regressions

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Abstract

Regression specifications frequently employ regressors that are defined as the product of two other regressors to form an interaction. Unfortunately, these models have a number of potential difficulties when it comes to interpretation. In this paper, we discuss two common aspects of these specifications that can lead to difficulties. The first is the change in parameter estimates and tstatistics when different definitions of dummy variables are used. The second involves an application of Fieller’s theorem to draw appropriate inferences from a regression with interaction variables.

Suggested Citation

  • J. Hirschberg & J. Lye, 2005. "Interactions in Regressions," Department of Economics - Working Papers Series 952, The University of Melbourne.
  • Handle: RePEc:mlb:wpaper:952
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    File URL: http://www.economics.unimelb.edu.au/downloads/wpapers-05/952.pdf
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    Keywords

    Interaction effects; dummy variables; linear transformation; Fieller method;

    JEL classification:

    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation

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