Semi-Nonparametric Estimation of Random Coefficient Logit Model for Aggregate Demand
Author | : Zhentong Lu |
Publisher | : |
Total Pages | : 71 |
Release | : 2020 |
ISBN-10 | : OCLC:1300228712 |
ISBN-13 | : |
Rating | : 4/5 ( Downloads) |
Download or read book Semi-Nonparametric Estimation of Random Coefficient Logit Model for Aggregate Demand written by Zhentong Lu and published by . This book was released on 2020 with total page 71 pages. Available in PDF, EPUB and Kindle. Book excerpt: In this paper, we propose a two-step semi-nonparametric estimator for the widely used random coefficient logit demand model. In the first step, exploiting the structure of logit choice probabilities, we transform the full demand system into a partial linear model and estimate the fixed (non-random) coefficients using standard linear sieve generalized method of moment (GMM). In the second step, we construct a sieve minimum distance (MD) estimator to uncover the distribution of random coefficients nonparametrically. We establish the asymptotic properties of the estimator and show the semi-nonparametric identification of the model in a large market environment. Monte Carlo simulations and empirical illustrations support the theoretical results and demonstrate the usefulness of our estimator in practice.