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Interactions in Fixed Effects Regression Models

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  • Giesselmann, Marco
  • Schmidt-Catran, Alexander

Abstract

An interaction in a fixed effects (FE) regression is usually specified by demeaning the product term. How-ever, algebraic transformations reveal that this strategy does not yield a within-unit estimator. Instead, the standard FE interaction estimator reflects unit-level differences of the interacted variables. This property allows interactions of a time-constant variable and a time-varying variable in FE, but may yield unwanted results if both variables vary within units. In such cases, Monte Carlo experiments confirm that the standard FE estimator of z∙x is biased if x is correlated with an unobserved unit-specific moderator of z (or vice-versa). A within estimator of an interaction can be obtained by first demeaning each variable and then demeaning their product. This “double-demeaned” estimator is not subject to bias caused by unobserved effect heterogeneity. It is, however, less efficient than standard FE and only works with T > 2.

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  • Giesselmann, Marco & Schmidt-Catran, Alexander, 2020. "Interactions in Fixed Effects Regression Models," SocArXiv m78qf, Center for Open Science.
    • Handle: RePEc:osf:socarx:m78qf
    DOI: 10.31219/osf.io/m78qf
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    1. Marco Giesselmann & Carsten Schröder & Johannes Giesecke & John Haisken-DeNew & Anika Rasner & Jule Specht, 2015. "Editorial: From Panel Data to Longitudinal Analytical Designs: a Note on Contemporary Research Based on Data from the Socio Economic Panel Study (SOEP)," Schmollers Jahrbuch : Journal of Applied Social Science Studies / Zeitschrift für Wirtschafts- und Sozialwissenschaften, Duncker & Humblot, Berlin, vol. 135(1), pages 1-11.
    2. Jeffrey M Wooldridge, 2010. "Econometric Analysis of Cross Section and Panel Data," MIT Press Books, The MIT Press, edition 2, volume 1, number 0262232588, April.
    3. Hausman, Jerry, 2015. "Specification tests in econometrics," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 38(2), pages 112-134.
    4. Jason Abrevaya, 2006. "Estimating the effect of smoking on birth outcomes using a matched panel data approach," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 21(4), pages 489-519.
    5. Reinhard Schunck, 2013. "Within and between estimates in random-effects models: Advantages and drawbacks of correlated random effects and hybrid models," Stata Journal, StataCorp LP, vol. 13(1), pages 65-76, March.
    6. Schober, Pia S. & Stahl, Juliane F., 2016. "Expansion of Full-Day Childcare and Subjective Well-Being of Mothers: Interdependencies with Culture and Resources," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 32(5), pages 593-606.
    7. Mundlak, Yair, 1978. "On the Pooling of Time Series and Cross Section Data," Econometrica, Econometric Society, vol. 46(1), pages 69-85, January.
    8. Giesselmann, Marco & Windzio, Michael, 2014. "Paneldaten in der Soziologie: Fixed Effects Paradigma und empirische Praxis in Panelregression und Ereignisanalyse," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 66(1), pages 95-113.
    9. Chris Frost & Simon G. Thompson, 2000. "Correcting for regression dilution bias: comparison of methods for a single predictor variable," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 163(2), pages 173-189.
    10. repec:zbw:espost:167662 is not listed on IDEAS
    11. Daniel Oesch & Oliver Lipps, 2011. "Does Unemployment Hurt Less if There Is More of It Around?: A Panel Analysis of Life Satisfaction in Germany and Switzerland," SOEPpapers on Multidisciplinary Panel Data Research 393, DIW Berlin, The German Socio-Economic Panel (SOEP).
    12. Giesselmann, Marco & Bohmann, Sandra & Goebel, Jan & Krause, Peter & Liebau, Elisabeth & Richter, David & Schacht, Diana & Schröder, Carsten & Schupp, Jürgen & Liebig, Stefan, 2019. "The Individual in Context(s): Research Potentials of the Socio-Economic Panel Study (SOEP) in Sociology," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 35(5), pages 738-755.
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    6. Jungkunz, Sebastian & Marx, Paul, 2021. "Income Changes Do Not Influence Political Participation: Evidence from Comparative Panel Data," IZA Discussion Papers 14198, Institute of Labor Economics (IZA).
    7. Paul F. Skilton & Ednilson Bernardes, 2022. "Normal misconduct in the prescription opioid supply chain," Journal of Supply Chain Management, Institute for Supply Management, vol. 58(4), pages 6-29, October.
    8. Alfano, Vincenzo & Capasso, Salvatore & Ercolano, Salvatore & Goel, Rajeev K., 2022. "Death takes no bribes: Impact of perceived corruption on the effectiveness of non-pharmaceutical interventions at combating COVID-19," Social Science & Medicine, Elsevier, vol. 301(C).
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    11. Jungkunz, Sebastian & Marx, Paul, 2021. "Income changes do not influence political participation: Evidence from comparative panel data," ifso working paper series 11, University of Duisburg-Essen, Institute for Socioeconomics (ifso).
    12. Alexander Deryigin & Irina Filippova & Igor Arlashkin, 2021. "Impact of intraregional tax decentralization on the development of the income base of the regions [Влияние Внутрирегиональной Налоговой Децентрализации На Развитие Доходной Базы Регионов]," Ekonomicheskaya Politika / Economic Policy, Russian Presidential Academy of National Economy and Public Administration, vol. 2, pages 8-33, April.
    13. Sebastian Jungkunz & Paul Marx, 2021. "Income Changes Do Not Influence Political Participation: Evidence from Comparative Panel Data," SOEPpapers on Multidisciplinary Panel Data Research 1129, DIW Berlin, The German Socio-Economic Panel (SOEP).
    14. Morgenroth, Nicolas & Schels, Brigitte & Teichler, Nils, 2022. "Are Men or Women More Unsettled by Fixed-Term Contracts? Gender Differences in Affective Job Insecurity and the Role of Household Context and Labour Market Positions," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 38(4), pages 560-574.
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    16. Bellia, Mario & Heynderickx, Wouter & Maccaferri, Sara & Schich, Sebastian, 2020. "Do CDS markets care about the G-SIB status?," JRC Working Papers in Economics and Finance 2020-02, Joint Research Centre, European Commission.

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    JEL classification:

    • C33 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Models with Panel Data; Spatio-temporal Models
    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation

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