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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- Yingyao Hu & Susanne M. Schennach, 2008. "Instrumental Variable Treatment of Nonclassical Measurement Error Models," Econometrica, Econometric Society, vol. 76(1), pages 195-216, 01.
- Ulrich Doraszelski & Jordi Jaumandreu, 2007.
"R&D and productivity : estimating production functions when productivity is endogenous,"
Economics Working Papers
we078652, Universidad Carlos III, Departamento de Economía.
- Doraszelski, Ulrich & Jaumandreu, Jordi, 2008. "R&D and Productivity: Estimating Production Functions when Productivity is Endogenous," CEPR Discussion Papers 6636, C.E.P.R. Discussion Papers.
- Doraszelski, Ulrich & Jaumandreu, Jordi, 2006. "R&D and productivity: Estimating production functions when productivity is endogenous," MPRA Paper 1246, University Library of Munich, Germany.
- Daniel Ackerberg & Xiaohong Chen & Jinyong Hahn, 2011. "Asymptotic Variance Estimator for Two-Step Semiparametric Estimators," Cowles Foundation Discussion Papers 1803, Cowles Foundation for Research in Economics, Yale University.
- Stephen Bond & Måns Söderbom, 2005.
"Adjustment Costs and the Identification of Cobb Douglas Production Functions,"
2005-W04, Economics Group, Nuffield College, University of Oxford.
- Steve Bond & Måns Söderbom, 2005. "Adjustment costs and the identification of Cobb Douglas production functions," IFS Working Papers W05/04, Institute for Fiscal Studies.
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