Speaker: | Zhentong Lv |
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Speaker Intro: |
Assistant Professor at The School of Economics, Shanghai University of Finance and Economics. |
Host: | |
Description: |
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 GMM. In the second step, we construct a sieve MD/GMM 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. |
Time: | 2018-10-15(Monday)16:40-18:00 |
Venue: | N302, Econ Building |
Organizer: | WISE&SOE |