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Semiparametric identification and estimation of discrete choice models for bundles

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  • Ouyang, Fu
  • Yang, Thomas Tao
  • Zhang, Hanghui

Abstract

We study (point) identification of preference coefficients in semiparametric discrete choice models for bundles. The approach to the identification uses an “identification at infinity” (Chamberlain, 1986) insight in combination with median independence restrictions on unobservables. We propose two-stage maximum score (MS) estimators and show their consistency. Monte Carlo evidence demonstrates that our approach performs satisfactorily in finite samples.

Suggested Citation

  • Ouyang, Fu & Yang, Thomas Tao & Zhang, Hanghui, 2020. "Semiparametric identification and estimation of discrete choice models for bundles," Economics Letters, Elsevier, vol. 193(C).
    • Handle: RePEc:eee:ecolet:v:193:y:2020:i:c:s0165176520302123
    DOI: 10.1016/j.econlet.2020.109321
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    References listed on IDEAS

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    Citations

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    Cited by:

    1. Christopher R. Dobronyi & Fu Ouyang & Thomas Tao Yang, 2023. "Revisiting Panel Data Discrete Choice Models with Lagged Dependent Variables," Papers 2301.09379, arXiv.org, revised Mar 2024.
    2. Fu Ouyang & Thomas T. Yang, 2023. "Semiparametric Discrete Choice Models for Bundles," Papers 2306.04135, arXiv.org, revised Nov 2023.

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    More about this item

    Keywords

    Bundle choices; Semiparametric model; Median independence; Identification at infinity; Maximum score estimation;
    All these keywords.

    JEL classification:

    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models
    • C35 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions

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