On the Identification of Gross Output Production Functions

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...

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Bibliographic Details
Published in:The Journal of political economy 2020-08, Vol.128 (8), p.2973-3016
Main Authors: Gandhi, Amit, Navarro, Salvador, Rivers, David A.
Format: Article
Language:English
Subjects:
Economic theory
Political economy
Prices
Production functions
Transformation
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Summary: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.
ISSN:0022-3808
1537-534X
DOI:10.1086/707736