Estimation of random coefficients logit demand models with interactive fixed effects

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

No CWP20/14, 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 coefficients discrete choice demand model, which underlies much recent empirical work in IO. We add interactive fi xed effects in the form of a factor structure on the unobserved product characteristics. The interactive fixed eff ects 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 application to US automobile demand.

Date: 2014-04-25
New Economics Papers: this item is included in nep-com and nep-dcm
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Citations: View citations in EconPapers (12)

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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 (2017)
Working Paper: Estimation of random coefficients logit demand models with interactive fixed effects (2012)
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