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Estimating Semi-Parametric Panel Multinomial Choice Models Using Cyclic Monotonicity

Shi, Xiaoxia and Shum, Matthew and Song, Wei (2018) Estimating Semi-Parametric Panel Multinomial Choice Models Using Cyclic Monotonicity. Econometrica, 86 (2). pp. 737-761. ISSN 0012-9682. http://resolver.caltech.edu/CaltechAUTHORS:20180418-092636075

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Abstract

This paper proposes a new semi‐parametric identification and estimation approach to multinomial choice models in a panel data setting with individual fixed effects. Our approach is based on cyclic monotonicity, which is a defining convex‐analytic feature of the random utility framework underlying multinomial choice models. From the cyclic monotonicity property, we derive identifying inequalities without requiring any shape restrictions for the distribution of the random utility shocks. These inequalities point identify model parameters under straightforward assumptions on the covariates. We propose a consistent estimator based on these inequalities.


Item Type:Article
Related URLs:
URLURL TypeDescription
https://doi.org/10.3982/ECTA14115DOIArticle
https://www.econometricsociety.org/publications/econometrica/2018/03/01/estimating-semi-parametric-panel-multinomial-choice-modelsPublisherArticle
https://arxiv.org/abs/1604.06145arXivDiscussion Paper
ORCID:
AuthorORCID
Shum, Matthew0000-0002-6262-915X
Additional Information:© 2018 Econometric Society. We thank Khai Chiong, Federico Echenique, Bruce E. Hansen, Jack R. Porter, and seminar audiences at Johns Hopkins, Northwestern, NYU, UC Riverside, UNC, and the Xiamen/WISE Econometrics Conference in Honor of Takeshi Amemiya for useful comments. Pengfei Sui and Jun Zhang provided excellent research assistance. Xiaoxia Shi acknowledges the financial support of the Wisconsin Alumni Research Foundation via the Graduate School Fall Competition Grant.
Funders:
Funding AgencyGrant Number
Wisconsin Alumni Research FoundationUNSPECIFIED
Record Number:CaltechAUTHORS:20180418-092636075
Persistent URL:http://resolver.caltech.edu/CaltechAUTHORS:20180418-092636075
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:85934
Collection:CaltechAUTHORS
Deposited By: Tony Diaz
Deposited On:18 Apr 2018 16:35
Last Modified:18 Apr 2018 22:32

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