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Nonparametric estimation of the random coefficients model: An elastic net approach

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  • Heiss, Florian
  • Hetzenecker, Stephan
  • Osterhaus, Maximilian

Abstract

This paper investigates and extends the computationally attractive nonparametric random coefficients estimator of Fox et al. (2011). We show that their estimator is a special case of the nonnegative LASSO, explaining its sparse nature observed in many applications. Recognizing this link, we extend the estimator, transforming it into a special case of the nonnegative elastic net. The extension improves the estimator’s recovery of the true support and allows for more accurate estimates of the random coefficients’ distribution. Our estimator is a generalization of the original estimator and therefore, is guaranteed to have a model fit at least as good as the original one. A theoretical analysis of both estimators’ properties shows that, under conditions, our generalized estimator approximates the true distribution more accurately. Two Monte Carlo experiments and an application to a travel mode data set illustrate the improved performance of the generalized estimator.

Suggested Citation

  • Heiss, Florian & Hetzenecker, Stephan & Osterhaus, Maximilian, 2022. "Nonparametric estimation of the random coefficients model: An elastic net approach," Journal of Econometrics, Elsevier, vol. 229(2), pages 299-321.
  • Handle: RePEc:eee:econom:v:229:y:2022:i:2:p:299-321
    DOI: 10.1016/j.jeconom.2020.11.010
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    More about this item

    Keywords

    Random coefficients; Mixed logit; Nonparametric estimation; Elastic net;
    All these keywords.

    JEL classification:

    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • C25 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions; Probabilities
    • L - Industrial Organization

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