Nonparametric Identification of Production Function, Total Factor Productivity, and Markup from Revenue Data
Nonparametric Identification of Production Function, Total Factor Productivity, and Markup from Revenue Data
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DOI：
10.2139/ssrn.3720324
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发表时间：
2020-10
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通讯作者：
Hiroyuki Kasahara;Y. Sugita
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文献类型：
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作者：
Hiroyuki Kasahara;Y. Sugita
常用的生产函数估计方法假设企业的产出数量可以作为数据进行观察，但典型的数据集仅包含收入，而不包含产出数量。当企业在不完全竞争下面临一般非参数需求函数时，我们研究了收入数据对生产函数的非参数识别。在标准假设下，我们提供了各种企业层面对象的建设性非参数识别：总生产函数、全要素生产率、边际成本的价格加成、产出价格、产出数量、需求系统和代表性消费者效用函数。
Commonly used methods of production function 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 from revenue data when a firm faces a general nonparametric 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.