Estimating Production Functions with Robustness Against Errors in the Proxy Variables

Guofang Huang and Yingyao Hu

Economics Working Paper Archive from The Johns Hopkins University,Department of Economics

Abstract: This paper proposes a new semi-nonparametric maximum likelihood estimation method for estimating production functions. The method extends the literature on structural estimation of production functions, started by 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 assumption seems reasonable in many important cases. The new method is straightforward to apply, and a consistent estimate of the asymptotic covariance matrix of the structural parameters can be easily computed.

Date: 2011-10
New Economics Papers: this item is included in nep-ecm
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Citations: View citations in EconPapers (9)

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Related works:
Journal Article: Estimating production functions with robustness against errors in the proxy variables (2020)
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:jhu:papers:583

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