Estimation of random coefficients logit demand models with interactive fixed effects
Hyungsik Roger Moon, Matthew Shum, Martin Weidner
TLDR
This paper extends the BLP demand model by incorporating interactive fixed effects to address endogeneity and persistence in market shares.
Key contributions
- Extends the BLP demand model by adding interactive fixed effects to unobserved product characteristics.
- Accommodates endogeneity and captures strong persistence in market shares through these fixed effects.
- Proposes a novel two-step least squares-minimum distance (LS-MD) estimation procedure.
- Shows the estimator's strong performance and computational ease via Monte Carlo simulations.
Why it matters
This work significantly advances demand model estimation by robustly handling endogeneity and market share persistence, which are common challenges in empirical industrial organization. The proposed method offers an accessible and effective tool for researchers.
Original 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 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.
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