生产函数、全要素生产率和收益加成的非参数识别
Nonparametric Identification of Production Function, Total Factor Productivity, and Markup from Revenue Data
摘要：
生产函数和加价估计的常用方法假设企业的产出量可以作为数据来观察，但典型的数据集只包含收入，而不包含产出量。我们研究了非参数识别的生产函数和加价的收入数据时，公司面临的一般nonparametri需求函数下不完全竞争。在标准假设下，我们提供了建设性的非参数识别的各种企业层面的对象：总生产函数，全要素生产率，价格加价超过边际成本，产出价格，产量，需求系统，和一个代表性的消费者的效用函数。
英文摘要：
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.
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