On the Identification of Gross Output Production Functions

• 成果类型: Article
• 署名作者: Gandhi, Amit; Navarro, Salvador; Rivers, David A.
• 署名单位: University of Pennsylvania; Western University (University of Western Ontario)
• 刊物名称: JOURNAL OF POLITICAL ECONOMY
• ISSN/ISSBN: 0022-3808
• DOI: 10.1086/707736
• 发表日期: 2020
• 页码: 2973-3016
• 关键词: research-and-development; rational-expectations; trade liberalization; SIMULTANEOUS-EQUATIONS; panel-data; DYNAMICS; inputs; performance; EFFICIENCY; variables

摘要

We study the nonparametric identification of gross output production functions under the environment of the commonly employed proxy variable methods. We show that applying these methods to gross output requires additional sources of variation in the demand for flexible inputs (e.g., prices). Using a transformation of the firm's first-order condition, we develop a new nonparametric identification strategy for gross output that can be employed even when additional sources of variation are not available. Monte Carlo evidence and estimates from Colombian and Chilean plant-level data show that our strategy performs well and is robust to deviations from the baseline setting.