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Fitting and interpreting correlated random-coefficient models using Stata


  • Oscar Barriga Cabanillas

    (University of California Davis)

  • Jeffrey D. Michler

    (University of Saskatchewan)

  • Aleksandr Michuda

    (University of California Davis)

  • Emilia Tjernström

    (University of Wisconsin)


In this article, we introduce the community-contributed command randcoef, which fits the correlated random-effects and correlated random-coef- ficient models discussed in Suri (2011, Econometrica 79: 159–209). While this approach has been around for a decade, its use has been limited by the compu- tationally intensive nature of the estimation procedure that relies on the optimal minimum distance estimator. randcoef can accommodate up to five rounds of panel data and offers several options, including alternative weight matrices for estimation and inclusion of additional endogenous regressors. We also present postestimation analysis using sample data to facilitate understanding and inter- pretation of results.

Suggested Citation

  • Oscar Barriga Cabanillas & Jeffrey D. Michler & Aleksandr Michuda & Emilia Tjernström, 2018. "Fitting and interpreting correlated random-coefficient models using Stata," Stata Journal, StataCorp LP, vol. 18(1), pages 159-173, March.
  • Handle: RePEc:tsj:stataj:v:18:y:2018:i:1:p:159-173
    Note: to access software from within Stata, net describe

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    Cited by:

    1. Osmani, Ahmad Reshad & Okunade, Albert A., 2019. "Cancer survivors in the labor market: Evidence from recent US micro-panel data," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 80, pages 202-221.


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