论文标题
关于基于数据的价格歧视的局限性
On the limitations of data-based price discrimination
论文作者
论文摘要
经典的三度价格歧视（3PD）模型要求了解买方估值的分配以及协变量以将价格设置为协变量。在产生收入方面，经典结果表明3PD至少与统一的价格一样好。如果卖方必须仅根据基础分布的观察结果设定价格，该怎么办？卖方应该参与3pd仍然很明显吗？本文阐明了这些基本问题。特别是，当价格基于样本设定时，在3pd和均匀定价之间的收入绩效比较总体上是模棱两可的。这一发现是不确定性下统计学习的性质：维度的诅咒，还有其他小样本并发症。
The classic third degree price discrimination (3PD) model requires the knowledge of the distribution of buyer valuations and the covariate to set the price conditioned on the covariate. In terms of generating revenue, the classic result shows that 3PD is at least as good as uniform pricing. What if the seller has to set a price based only on a sample of observations from the underlying distribution? Is it still obvious that the seller should engage in 3PD? This paper sheds light on these fundamental questions. In particular, the comparison of the revenue performance between 3PD and uniform pricing is ambiguous overall when prices are set based on samples. This finding is in the nature of statistical learning under uncertainty: a curse of dimensionality, but also other small sample complications.
