BLP-2LASSO for aggregate discrete choice models with rich covariates

BLP-2LASSO for aggregate discrete choice models with rich covariates

We introduce the BLP-2LASSO model, which augments the classic BLP (Berry, Levinsohn, and Pakes, 1995) random-coefficients logit model to allow for data-driven selection among a high-dimensional set of control variables using the 'double-LASSO' procedure proposed by Belloni, Chernozhukov, a...

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Bibliographic Details
Main Authors:	Gillen, B.J (Author), Montero, S. (Author), Moon, H.R (Author), Shum, M. (Author)
Format:	Article
Language:	English
Published:	Oxford University Press 2019
Subjects:	big data elections high-dimensional regressors LASSO machine learning Random-coefficients logit model
Online Access:	View Fulltext in Publisher

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