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Assessing the effectos of measurement errors on the estimation of the production function

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  • Ornaghi, Carmine

Abstract

This article explores the reasons why GMM estimators of production function parameters are generally found to produce unsatisfactory results. I attribute this finding to the inaccurate construction of the variables used in production function analysis. In particular, I suggest that the problem lies in the use of common price deflators as well as in a capital variable that does not reflect the true flow of capital services because of short-run equilibrium effects. I show that the practice of using industry-wide deflators leads to lower scale estimates, mainly due to a relevant downward bias in the labour coefficient. At the same time, it introduces a large upward bias in estimating the elasticity of output with respect to technological innovation. Moreover, a significant improvement in the estimates of capital coefficients is obtained if the information on the degree of capacity utilization is adequately exploited.

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  • Ornaghi, Carmine, 2002. "Assessing the effectos of measurement errors on the estimation of the production function," UC3M Working papers. Economics we023314, Universidad Carlos III de Madrid. Departamento de Economía.
  • Handle: RePEc:cte:werepe:we023314
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    References listed on IDEAS

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    1. Zvi Griliches & Jacques Mairesse, 1995. "Production Functions: The Search for Identification," NBER Working Papers 5067, National Bureau of Economic Research, Inc.
    2. Klette, Tor Jakob & Griliches, Zvi, 1996. "The Inconsistency of Common Scale Estimators When Output Prices Are Unobserved and Endogenous," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 11(4), pages 343-361, July-Aug..
    3. Richard Blundell & Stephen Bond, 2000. "GMM Estimation with persistent panel data: an application to production functions," Econometric Reviews, Taylor & Francis Journals, vol. 19(3), pages 321-340.
    4. Ornaghi, Carmine, 2006. "Spillovers in product and process innovation: Evidence from manufacturing firms," International Journal of Industrial Organization, Elsevier, vol. 24(2), pages 349-380, March.
    5. Hall, Robert E, 1988. "The Relation between Price and Marginal Cost in U.S. Industry," Journal of Political Economy, University of Chicago Press, vol. 96(5), pages 921-947, October.
    6. Garcia, Angel & Jaumandreu, Jordi & Rodriguez, Cesar, 2004. "Innovation and jobs: evidence from manufacturing firms," MPRA Paper 1204, University Library of Munich, Germany.
    7. John Haltiwanger & Russell Cooper & Laura Power, 1999. "Machine Replacement and the Business Cycle: Lumps and Bumps," American Economic Review, American Economic Association, vol. 89(4), pages 921-946, September.
    8. Tor Jakob Klette, 1996. "R&D, Scope Economies, and Plant Performance," RAND Journal of Economics, The RAND Corporation, vol. 27(3), pages 502-522, Autumn.
    9. Hall, Bronwyn H. & Mairesse, Jacques, 1995. "Exploring the relationship between R&D and productivity in French manufacturing firms," Journal of Econometrics, Elsevier, vol. 65(1), pages 263-293, January.
    10. Berndt, Ernst R. & Fuss, Melvyn A., 1986. "Productivity measurement with adjustments for variations in capacity utilization and other forms of temporary equilibrium," Journal of Econometrics, Elsevier, vol. 33(1-2), pages 7-29.
    11. Mark E. Doms & Timothy Dunne, 1998. "Capital Adjustment Patterns in Manufacturing Plants," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 1(2), pages 409-429, April.
    12. Manuel Arellano & Stephen Bond, 1991. "Some Tests of Specification for Panel Data: Monte Carlo Evidence and an Application to Employment Equations," Review of Economic Studies, Oxford University Press, vol. 58(2), pages 277-297.
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    1. Ornaghi, Carmine, 2006. "Spillovers in product and process innovation: Evidence from manufacturing firms," International Journal of Industrial Organization, Elsevier, vol. 24(2), pages 349-380, March.

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