Modeling the Distribution of Price Sensitivity and Implications for Optimal Retail Pricing
使用随机系数logit模型，基于两个产品类别的面板数据估计消费者价格敏感度的分布，并结合成本数据推导最优零售定价策略，检验了参数分布假设。
This article focuses on the distribution of price sensitivity across consumers. We employ a random-coefficient logit model in which brand-specific intercepts and price-slope coefficients are allowed to vary across households. The model is estimated with panel data for two product categories. The implications of the estimated model are deduced through an optimal retail pricing analysis that combines the panel data with chain-level cost figures. We test parametric distributional assumptions using semiparametric density estimates based on series expansions.