Identification of Semiparametric Panel Multinomial Choice Models with Infinite-Dimensional Fixed Effects
提出一种半参数识别和估计方法，允许消费者效用中存在无穷维固定效应，利用参数指标的多元单调性和跨期不等式来识别模型，并通过蒙特卡洛模拟和爆米花销售数据展示其实用优势。
Abstract This paper proposes a robust method for semiparametric identification and estimation in panel multinomial choice models, where we allow for infinite-dimensional fixed effects that enter into consumer utilities in an additively nonseparable way, thus incorporating rich forms of unobserved heterogeneity. Our identification strategy exploits multivariate monotonicity in parametric indices, and uses the logical contraposition of an intertemporal inequality on choice probabilities to obtain identifying restrictions. We provide a consistent estimation procedure, and demonstrate the practical advantages of our method with Monte Carlo simulations and an empirical illustration on popcorn sales with the NielsenIQ data.