Estimation of random coefficients logit demand models with interactive fixed effects
在BLP随机系数离散选择需求模型中引入交互固定效应，以因子结构处理未观测产品特征的持久性和内生性，提出两阶段最小二乘-最小距离估计量，并通过蒙特卡洛模拟和美国汽车需求数据验证其有效性。
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.