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Unobserved Heterogeneity in the Binary Logit Model with Cross-Sectional Data and Short Panels: A Finite Mixture Approach

Author

Listed:
  • Anders Holm

    (Department of Sociology, University of Copenhagen)

  • Mads Meier Jæger

    (Danish National Centre for Social Research, Copenhagen)

  • Morten Pedersen

    (Department of Sociology, University of Copenhagen)

Abstract

This paper proposes a new approach to dealing with unobserved heterogeneity in applied research using the binary logit model with cross-sectional data and short panels. Unobserved heterogeneity is particularly important in non-linear regression models such as the binary logit model because, unlike in linear regression models, estimates of the effects of observed independent variables are biased even when omitted independent variables are uncorrelated with the observed independent variables. We propose an extension of the binary logit model based on a finite mixture approach in which we conceptualize the unobserved heterogeneity via latent classes. Simulation results show that our approach leads to considerably less bias in the estimated effects of the independent variables than the standard logit model. Furthermore, because identification of the unobserved heterogeneity is weak when the researcher has cross-sectional rather than panel data, we propose a simple approach that fixes latent class weights and improves identification and estimation. Finally, we illustrate the applicability of our new approach using Canadian survey data on public support for redistribution.

Suggested Citation

  • Anders Holm & Mads Meier Jæger & Morten Pedersen, 2008. "Unobserved Heterogeneity in the Binary Logit Model with Cross-Sectional Data and Short Panels: A Finite Mixture Approach," CAM Working Papers 2009-04, University of Copenhagen. Department of Economics. Centre for Applied Microeconometrics.
  • Handle: RePEc:kud:kuieca:2009_04
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    File URL: http://www.econ.ku.dk/cam/wp0910/2009-04.pdf/
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    References listed on IDEAS

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    1. Leslie McCall & Lane Kenworthy, 2007. "Inequality, Public Opinion, and Redistribution," LIS Working papers 459, LIS Cross-National Data Center in Luxembourg.
    2. Holm, Anders, 2002. "The effect of training on search durations: a random effects approach," Labour Economics, Elsevier, vol. 9(3), pages 433-450, July.
    3. Browning, Martin & Carro, Jesus M., 2014. "Dynamic binary outcome models with maximal heterogeneity," Journal of Econometrics, Elsevier, vol. 178(2), pages 805-823.
    4. Bearse, Peter & Canals-Cerd , Jos & Rilstone, Paul, 2007. "Efficient Semiparametric Estimation Of Duration Models With Unobserved Heterogeneity," Econometric Theory, Cambridge University Press, vol. 23(02), pages 281-308, April.
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    Keywords

    binary logit model; unobserved heterogeneity; latent classes; simulation;

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