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Assessing the effects of measurement errors on the estimation of production functions

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  • Carmine Ornaghi

Abstract

This article explores to what extent the poor results that are often found when estimating parameters of production functions can be attributed to measurement errors, due to the use of common price deflators across firms. Because of the lack of detailed micro‐economic data, econometricians have to rely on industry‐wide deflators when computing outputs and intermediate inputs. A unique feature of the longitudinal data used in this paper is that it reports firm‐level prices. This allows for a comparative assessment of production function parameters where the outputs and intermediate inputs are computed using both firm‐specific prices and industry‐wide deflators. The empirical results presented in this paper show that the use of common deflators across firms leads to lower scale estimates, mainly because of a large downward bias in the estimated coefficients for labour. Copyright © 2006 John Wiley & Sons, Ltd.

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  • Carmine Ornaghi, 2006. "Assessing the effects of measurement errors on the estimation of production functions," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 21(6), pages 879-891, September.
    • Handle: RePEc:wly:japmet:v:21:y:2006:i:6:p:879-891
    DOI: 10.1002/jae.887
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    1. Eslava, Marcela & Haltiwanger, John & Kugler, Adriana & Kugler, Maurice, 2004. "The effects of structural reforms on productivity and profitability enhancing reallocation: evidence from Colombia," Journal of Development Economics, Elsevier, vol. 75(2), pages 333-371, December.
    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 & Frank Windmeijer, 2000. "Estimation in dynamic panel data models: improving on the performance of the standard GMM estimator," IFS Working Papers W00/12, Institute for Fiscal Studies.
    4. 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.
    5. 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.
    6. Alonso-Borrego, César & Sánchez Mangas, Rocío, 2001. "GMM estimation of a production function with panel data : an application to Spanish manufacturing firms," DES - Working Papers. Statistics and Econometrics. WS ws015527, Universidad Carlos III de Madrid. Departamento de Estadística.
    7. Olley, G Steven & Pakes, Ariel, 1996. "The Dynamics of Productivity in the Telecommunications Equipment Industry," Econometrica, Econometric Society, vol. 64(6), pages 1263-1297, November.
    8. Mark Bils & Peter J. Klenow, 2004. "Some Evidence on the Importance of Sticky Prices," Journal of Political Economy, University of Chicago Press, vol. 112(5), pages 947-985, October.
    9. Eslava, Marcela & Haltiwanger, John & Kugler, Adriana & Kugler, Maurice, 2004. "The effects of structural reforms on productivity and profitabality enhancing reallocation: evidence from Colombia," Discussion Paper Series In Economics And Econometrics 0408, Economics Division, School of Social Sciences, University of Southampton.
    10. Greenwood, Jeremy & Hercowitz, Zvi & Krusell, Per, 1997. "Long-Run Implications of Investment-Specific Technological Change," American Economic Review, American Economic Association, vol. 87(3), pages 342-362, June.
    11. Arellano, Manuel & Bover, Olympia, 1995. "Another look at the instrumental variable estimation of error-components models," Journal of Econometrics, Elsevier, vol. 68(1), pages 29-51, July.
    12. Zvi Griliches, 1998. "Productivity and R&D at the Firm Level," NBER Chapters, in: R&D and Productivity: The Econometric Evidence, pages 100-133, National Bureau of Economic Research, Inc.
    13. Zvi Griliches, 1984. "R&D, Patents, and Productivity," NBER Books, National Bureau of Economic Research, Inc, number gril84-1, March.
    14. 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.
    15. Joe Beaulieu & Joe Mattey, 1999. "The Effects Of General Inflation And Idiosyncratic Cost Shocks On Within-Commodity Price Dispersion: Evidence From Microdata," The Review of Economics and Statistics, MIT Press, vol. 81(2), pages 205-216, May.
    16. Manuel Arellano & Stephen Bond, 1991. "Some Tests of Specification for Panel Data: Monte Carlo Evidence and an Application to Employment Equations," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 58(2), pages 277-297.
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