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Estimation of random coefficients logit demand models with interactive fixed effects

Hyungsik Roger Moon, Matthew Shum () and Martin Weidner

Journal of Econometrics, 2018, vol. 206, issue 2, 613-644

Abstract: We extend the Berry, Levinsohn and Pakes (BLP, 1995) random coefficients discrete-choice demand model, which underlies much recent empirical work in IO. We add interactive fixed effects in the form of a factor structure on the unobserved product characteristics. The interactive fixed effects can be arbitrarily correlated with the observed product characteristics (including price), which accommodate endogeneity and, at the same time, capture strong persistence in market shares across products and markets. We propose a two-step least squares-minimum distance (LS-MD) procedure to calculate the estimator. Our estimator is easy to compute, and Monte Carlo simulations show that it performs well. We consider an empirical illustration to US automobile demand.

Keywords: Discrete-choice demand model; Interactive fixed effects; Factor analysis; Panel data; Random utility model (search for similar items in EconPapers)
JEL-codes: C23 C25 (search for similar items in EconPapers)
Date: 2018
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Related works:
Working Paper: Estimation of random coefficients logit demand models with interactive fixed effects (2017) Downloads
Working Paper: Estimation of random coefficients logit demand models with interactive fixed effects (2014) Downloads
Working Paper: Estimation of random coefficients logit demand models with interactive fixed effects (2012) Downloads
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