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Demand Estimation with High-Dimensional Product Characteristics

Gillen, Benjamin J. and Moon, Hyungsik Roger and Shum, Matthew (2014) Demand Estimation with High-Dimensional Product Characteristics. In: Bayesian Model Comparison. Advances in Econometrics. No.34. Emerald Group Publishing Limited , Bingley, UK , pp. 301-323. ISBN 9781784411855 . http://resolver.caltech.edu/CaltechAUTHORS:20160329-104400446

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Abstract

Structural models of demand founded on the classic work of Berry, Levinsohn, and Pakes (1995) link variation in aggregate market shares for a product to the influence of product attributes on heterogeneous consumer tastes. We consider implementing these models in settings with complicated products where consumer preferences for product attributes are sparse, that is, where a small proportion of a high-dimensional product characteristics influence consumer tastes. We propose a multistep estimator to efficiently perform uniform inference. Our estimator employs a penalized pre-estimation model specification stage to consistently estimate nonlinear features of the BLP model. We then perform selection via a Triple-LASSO for explanatory controls, treatment selection controls, and instrument selection. After selecting variables, we use an unpenalized GMM estimator for inference. Monte Carlo simulations verify the performance of these estimators.


Item Type:Book Section
Related URLs:
URLURL TypeDescription
http://dx.doi.org/10.1108/S0731-905320140000034020DOIBook chapter
http://www.emeraldinsight.com/doi/abs/10.1108/S0731-905320140000034020PublisherBook chapter
ORCID:
AuthorORCID
Shum, Matthew0000-0002-6262-915X
Additional Information:Copyright 2014 by Emerald Group Publishing Limited. We are grateful to David Brownstone, Martin Burda, Garland Durham, Jeremy Fox, Stefan Holderlein, Ivan Jeliazkov, Dale Poirier, Guillame Weisang, Frank Windmeijer, and seminar participants at the Advances in Econometrics Conference on Bayesian Model Comparison and the California Institute of Technology for helpful comments. We owe special thanks to Alexander Charles Smith for important insights early in developing the project.
Subject Keywords:BLP demand model, high-dimensional product characteristics, LASSO, Post-LASSO, shrinkage estimation
Classification Code:JEL: L15, C01, C26, C55
Record Number:CaltechAUTHORS:20160329-104400446
Persistent URL:http://resolver.caltech.edu/CaltechAUTHORS:20160329-104400446
Official Citation: Benjamin J. Gillen , Matthew Shum , Hyungsik Roger Moon (2014), Demand Estimation with High-Dimensional Product Characteristics, in Ivan Jeliazkov , Dale J. Poirier (ed.) Bayesian Model Comparison (Advances in Econometrics, Volume 34) Emerald Group Publishing Limited, pp.301 - 323
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:65742
Collection:CaltechAUTHORS
Deposited By: Susan Vite
Deposited On:30 Mar 2016 19:27
Last Modified:08 Sep 2017 23:22

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