论文标题
收入数据的生产功能，总要素生产率和标记的非参数识别
Nonparametric Identification of Production Function, Total Factor Productivity, and Markup from Revenue Data
论文作者
论文摘要
常用的生产功能方法和标记估计方法假设可以将公司的输出数量视为数据，但是典型的数据集仅包含收入，而不包含输出数量。当公司在不完美的竞争中面临一般的非帕拉姆特里需求功能时，我们检查了生产功能的非参数识别和收入数据的标记。在标准假设下，我们提供了各种公司级对象的建设性非参数识别：总生产功能，总要素生产率，价格上涨的价格高价，产出价格，产出数量，需求系统以及代表性消费者的公用事业功能。
Commonly used methods of production function and markup estimation assume that a firm's output quantity can be observed as data, but typical datasets contain only revenue, not output quantity. We examine the nonparametric identification of production function and markup from revenue data when a firm faces a general nonparametri demand function under imperfect competition. Under standard assumptions, we provide the constructive nonparametric identification of various firm-level objects: gross production function, total factor productivity, price markups over marginal costs, output prices, output quantities, a demand system, and a representative consumer's utility function.
