Estimation of High-Dimensional Contextual Pricing Models with Nonparametric Price Confounders
研究了在自适应定价数据中，如何有效估计包含众多因素和协变量的需求模型，帮助零售商识别影响购买行为的关键因素。
Which factors affect an individual’s purchase behaviors more, and how would a retailer consistently and reliably identify such factors, with data collected on adaptively offered prices that might potentially interfere with such factors? Our research presents novel methods that effectively estimate demand models with many factors and covariates, consistent with adaptive and contextual pricing practice.