Estimating High-Dimensional Discrete Choice Model of Differentiated Products with Random Coefficients

Masayuki Sawada and Kohei Kawaguchi

Papers from arXiv.org

Abstract: We propose an estimation procedure for discrete choice models of differentiated products with possibly high-dimensional product attributes. In our model, high-dimensional attributes can be determinants of both mean and variance of the indirect utility of a product. The key restriction in our model is that the high-dimensional attributes affect the variance of indirect utilities only through finitely many indices. In a framework of the random-coefficients logit model, we show a bound on the error rate of a $l_1$-regularized minimum distance estimator and prove the asymptotic linearity of the de-biased estimator.

Date: 2020-04
New Economics Papers: this item is included in nep-dcm, nep-ecm, nep-gen and nep-upt
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Persistent link: https://EconPapers.repec.org/RePEc:arx:papers:2004.08791

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