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

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  • Carmine Ornaghi

    (Economics Division, School of Social Sciences, University of Southampton, Southampton, UK)

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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Bibliographic Info

Article provided by John Wiley & Sons, Ltd. in its journal Journal of Applied Econometrics.

Volume (Year): 21 (2006)
Issue (Month): 6 ()
Pages: 879-891

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Handle: RePEc:jae:japmet:v:21:y:2006:i:6:p:879-891

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  1. Klette, T.J., 1992. "The Inconsistency of Common Scale Estimators when Output Prices are unobserved and Endogenous," Harvard Institute of Economic Research Working Papers 1586, Harvard - Institute of Economic Research.
  2. G. Steven Olley & Ariel Pakes, 1992. "The Dynamics of Productivity in the Telecommunications Equipment Industry," NBER Working Papers 3977, National Bureau of Economic Research, Inc.
  3. Mark Bils & Peter J. Klenow, 2002. "Some Evidence on the Importance of Sticky Prices," NBER Working Papers 9069, National Bureau of Economic Research, Inc.
  4. 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.
  5. Richard Blundell & Steve 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.
  6. 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 921-47, October.
  7. 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 342-62, June.
  8. César Alonso-Borrego & Rocío Sánchez-Mangas, 2001. "Gmm Estimation Of A Production Function With Panel Data: An Application To Spanish Manufacturing Firms," Statistics and Econometrics Working Papers ws015527, Universidad Carlos III, Departamento de Estadística y Econometría.
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Cited by:
  1. Lubomir Lizal & Kamil Galuščák, 2012. "The Impact of Capital Measurement Error Correction on Firm-Level Production Function Estimation," William Davidson Institute Working Papers Series wp1026, William Davidson Institute at the University of Michigan.
  2. Michaela Trax & Stephan Brunow & Jens Suedekum, 2012. "Cultural diversity and plant‐level productivity," Norface Discussion Paper Series 2012029, Norface Research Programme on Migration, Department of Economics, University College London.
  3. Smeets, Valerie & Warzynski, Frederic, 2013. "Estimating productivity with multi-product firms, pricing heterogeneity and the role of international trade," Journal of International Economics, Elsevier, vol. 90(2), pages 237-244.
  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. Enghin Atalay, 2012. "Materials Prices and Productivity," Working Papers 12-11, Center for Economic Studies, U.S. Census Bureau.
  6. Jaumandreu, Jordi & Mairesse, Jacques, 2006. "Using price and demand information to identify production functions," MPRA Paper 1247, University Library of Munich, Germany.
  7. Doan, Tinh & Nguyen, Ha, 2013. "Productivity dispersion and the roles of quality of labour input and competition: A case of Vietnamese manufacturing sector," MPRA Paper 48357, University Library of Munich, Germany.
  8. Ornaghi, Carmine & Castiglionesi, Fabio, 2009. "On the determinants of TFP growth: evidence from Spanish manufacturing firms," Discussion Paper Series In Economics And Econometrics 0912, Economics Division, School of Social Sciences, University of Southampton.
  9. Ziga Zarnic, 2010. "European Electricity Market Reforms: Any Signs of Efficiency Improvements?," LICOS Discussion Papers 26210, LICOS - Centre for Institutions and Economic Performance, KU Leuven.

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