Estimating Production Functions with Robustness Against Errors in the Proxy Variables
AbstractThis 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.
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Bibliographic InfoPaper provided by The Johns Hopkins University,Department of Economics in its series Economics Working Paper Archive with number 583.
Date of creation: Oct 2011
Date of revision:
Other versions of this item:
- Guofang Huang & Yingyao Hu, 2011. "Estimating production functions with robustness against errors in the proxy variables," CeMMAP working papers CWP35/11, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
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