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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.
Authors
Research Associate University College London and University of Oxford
Martin is an IFS Research Associate, a Fellow of the Nuffield College and a Professor in the Department of Economics at the University of Oxford.
Matthew Shum
Working Paper details
- DOI
- 10.1920/wp.cem.2017.1217
- Publisher
- The IFS
Suggested citation
H, Moon and M, Shum and M, Weidner. (2017). Estimation of random coefficients logit demand models with interactive fixed effects. London: The IFS. Available at: https://ifs.org.uk/publications/estimation-random-coefficients-logit-demand-models-interactive-fixed-effects (accessed: 28 March 2024).
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