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Interpreting interaction terms in linear and non-linear models: A cautionary tale

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  • Drichoutis, Andreas

Abstract

Interaction terms are often misinterpreted in the empirical economics literature by assuming that the coefficient of interest represents unconditional marginal changes. I present the correct way to estimate conditional marginal changes in a series of non-linear models including (ordered) logit/probit regressions, censored and truncated regressions. The linear regression model is used as the benchmark case.

Suggested Citation

  • Drichoutis, Andreas, 2011. "Interpreting interaction terms in linear and non-linear models: A cautionary tale," MPRA Paper 33251, University Library of Munich, Germany.
    • Handle: RePEc:pra:mprapa:33251
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    File URL: https://mpra.ub.uni-muenchen.de/33251/1/MPRA_paper_33251.pdf
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    References listed on IDEAS

    as
    1. Greene, William, 2010. "Testing hypotheses about interaction terms in nonlinear models," Economics Letters, Elsevier, vol. 107(2), pages 291-296, May.
    2. Brambor, Thomas & Clark, William Roberts & Golder, Matt, 2006. "Understanding Interaction Models: Improving Empirical Analyses," Political Analysis, Cambridge University Press, vol. 14(1), pages 63-82, January.
    3. Andreas C. Drichoutis & Rodolfo M. Nayga, 2011. "Marginal Changes in Random Parameters Ordered Response Models with Interaction Terms," Econometric Reviews, Taylor & Francis Journals, vol. 30(5), pages 565-576, October.
    4. Ai, Chunrong & Norton, Edward C., 2003. "Interaction terms in logit and probit models," Economics Letters, Elsevier, vol. 80(1), pages 123-129, July.
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    Cited by:

    1. Swain, Swadhina Shikha & Mishra, Pulak, 2021. "How does cleaner energy transition influence standard of living and natural resources conservation? A study of households’ perceptions in rural Odisha, India," Energy, Elsevier, vol. 215(PB).
    2. Michalis Drouvelis & Robert Metcalfe & Nattavudh Powdthavee, 2015. "Can priming cooperation increase public good contributions?," Theory and Decision, Springer, vol. 79(3), pages 479-492, November.
    3. Stephen Hynes & Ingrid Mateo-Mantecón & Eamonn O’Connor & Andreas Tsakiridis, 2020. "Relative size and technical efficiency in peripheral port markets: evidence from Irish and North Atlantic Spanish ports," Maritime Economics & Logistics, Palgrave Macmillan;International Association of Maritime Economists (IAME), vol. 22(3), pages 383-402, September.
    4. Hynes, S. & Mateo-Mantecón, I. & O’Connor, E. & Tsakiridis, A., 2019. "Examining the relationship between relative size and technical efficiency in peripheral port markets: Evidence from Irish and North Atlantic Spanish ports," Working Papers 309603, National University of Ireland, Galway, Socio-Economic Marine Research Unit.

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    More about this item

    Keywords

    interaction terms; ordered probit; ordered logit; truncated regression; censored regression; nonlinear models;
    All these keywords.

    JEL classification:

    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
    • C24 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Truncated and Censored Models; Switching Regression Models; Threshold Regression Models
    • C25 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions; Probabilities

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