Estimating production functions with robustness against errors in the proxy variables

Yingyao Hu, Guofang Huang and Yuya Sasaki

Journal of Econometrics, 2020, vol. 215, issue 2, 375-398

Abstract: This paper proposes a new approach to the identification and estimation of production functions. It extends the literature on the structural estimation of production functions, which dates back to the seminal work of Olley and Pakes (1996), by relaxing the scalar-unobservable assumption about the proxy variables. The key additional assumption needed in the identification argument is the existence of two conditionally independent proxy variables. The proposed generalized method of moment (GMM) estimator is flexible and straightforward to apply. The method is applied to study how rapidly firms in the Chilean food-product industry adjust their inputs in response to shocks to their productivity.

Keywords: Production functions; Proxy variables; Instrumental variables; Optimization errors; Measurement errors (search for similar items in EconPapers)
JEL-codes: C14 (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (18)

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Related works:
Working Paper: Estimating production functions with robustness against errors in the proxy variables (2011)
Working Paper: Estimating Production Functions with Robustness Against Errors in the Proxy Variables (2011)
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Persistent link: https://EconPapers.repec.org/RePEc:eee:econom:v:215:y:2020:i:2:p:375-398

DOI: 10.1016/j.jeconom.2019.05.024

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