Estimation of random coefficients logit demand models with interactive fixed effects

Hyungsik Moon (), Matthew Shum () and Martin Weidner

No CWP12/17, CeMMAP working papers from Centre for Microdata Methods and Practice, Institute for Fiscal Studies

Abstract: We extend the Berry, Levinsohn and Pakes (BLP, 1995) random coeffcients 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 accommodates endogeneity and, at the same time, captures 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 xed e ects; factor analysis; panel data; random utility model. (search for similar items in EconPapers)
JEL-codes: C23 C25 (search for similar items in EconPapers)
Date: 2017-02-22
New Economics Papers: this item is included in nep-com and nep-dcm
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Citations: View citations in EconPapers (2)

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Related works:
Journal Article: Estimation of random coefficients logit demand models with interactive fixed effects (2018)
Working Paper: Estimation of random coefficients logit demand models with interactive fixed effects (2014)
Working Paper: Estimation of random coefficients logit demand models with interactive fixed effects (2012)
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