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Durées d’utilisation des facteurs et fonction de production : une estimation par la méthode des moments généralisés en système

  • Eric Heyer
  • Florian Pelgrin
  • Arnaud Sylvain

Although a number of studies have demonstrated the importance of the degree of factor utilization in economic analysis, the impact of the durations of utilization in a production function remains largely unknown, particularly in terms of the duration of equipment utilization. Using French data on industrial firms over the period 1989–2001, the authors estimate a Cobb-Douglas production function that accounts for the volumes and durations of factor utilization. They draw on the framework proposed by Blundell and Bond (2000), assuming that serially correlated shocks allow a dynamic representation of the production function, and they choose the system-generalized method of moments as the reference estimation method. Their estimates yield identical elasticities for shifts of work and capital: the increase in output resulting from doubling the number of work teams is equivalent to that from doubling the stock of capital. Finally, they cannot reject the null hypothesis of constant returns to scale in their sample.

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Paper provided by Bank of Canada in its series Working Papers with number 04-12.

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Length: 43 pages
Date of creation: 2004
Date of revision:
Handle: RePEc:bca:bocawp:04-12
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  1. Nickell, Stephen J, 1981. "Biases in Dynamic Models with Fixed Effects," Econometrica, Econometric Society, vol. 49(6), pages 1417-26, November.
  2. Bond, Stephen & Bowsher, Clive & Windmeijer, Frank, 2001. "Criterion-based inference for GMM in autoregressive panel data models," Economics Letters, Elsevier, vol. 73(3), pages 379-388, December.
  3. Frank Windmeijer, 2000. "A finite sample correction for the variance of linear two-step GMM estimators," IFS Working Papers W00/19, Institute for Fiscal Studies.
  4. Anderson, T. W. & Hsiao, Cheng, 1982. "Formulation and estimation of dynamic models using panel data," Journal of Econometrics, Elsevier, vol. 18(1), pages 47-82, January.
  5. Jacques Mairesse & Bronwyn H. Hall, 1996. "Estimating the Productivity of Research and Development: An Exploration of GMM Methods Using Data on French & United States Manufacturing Firms," NBER Working Papers 5501, National Bureau of Economic Research, Inc.
  6. Gilbert Cette, 1983. "Degrés d'utilisation des facteurs et demande d'investissement et de travail," Revue Économique, Programme National Persée, vol. 34(4), pages 756-793.
  7. 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.
  8. Zvi Griliches & Jacques Mairesse, 1995. "Production Functions: The Search for Identification," NBER Working Papers 5067, National Bureau of Economic Research, Inc.
  9. Craine, Roger, 1973. "On the Service Flow from Labour," Review of Economic Studies, Wiley Blackwell, vol. 40(11), pages 39-46, January.
  10. Arellano, Manuel & Bond, Stephen, 1991. "Some Tests of Specification for Panel Data: Monte Carlo Evidence and an Application to Employment Equations," Review of Economic Studies, Wiley Blackwell, vol. 58(2), pages 277-97, April.
  11. Douglas Staiger & James H. Stock, 1997. "Instrumental Variables Regression with Weak Instruments," Econometrica, Econometric Society, vol. 65(3), pages 557-586, May.
  12. repec:fth:inseep:9730 is not listed on IDEAS
  13. Blundell, R. & Bond, S., 1995. "Initial Conditions and Moment Restrictions in Dynamic Panel Data Models," Economics Papers 104, Economics Group, Nuffield College, University of Oxford.
  14. Hart, Robert A. & McGregor, Peter G., 1988. "The returns to labour services in West German manufacturing industry," European Economic Review, Elsevier, vol. 32(4), pages 947-963, April.
  15. M. Ishaq Nadiri & Sherwin Rosen, 1973. "A Disequilibrium Model of Demand for Factors of Production," NBER Books, National Bureau of Economic Research, Inc, number nadi73-1, December.
  16. Nadiri, M Ishaq & Rosen, Sherwin, 1969. "Interrelated Factor Demand Functions," American Economic Review, American Economic Association, vol. 59(4), pages 457-71, Part I Se.
  17. Eric Heyer & Xavier Timbeau & Valérie Chauvin & Gaël Dupont & Olivier Brossard, 2000. "Croissance.net," Revue de l'OFCE, Programme National Persée, vol. 73(1), pages 115-150.
  18. Gilbert Cette, 1990. "Durée d'utilisation des équipements : l'inversion d'une tendance longue," Économie et Statistique, Programme National Persée, vol. 231(1), pages 33-47.
  19. 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.
  20. Anxo, Dominique & Bigsten, Arne, 1989. " Working Hours and Productivity in Swedish Manufacturing," Scandinavian Journal of Economics, Wiley Blackwell, vol. 91(3), pages 613-19.
  21. Ziliak, James P, 1997. "Efficient Estimation with Panel Data When Instruments Are Predetermined: An Empirical Comparison of Moment-Condition Estimators," Journal of Business & Economic Statistics, American Statistical Association, vol. 15(4), pages 419-31, October.
  22. Éric Heyer & Simon Cueva, 1997. "Fonction de production et degrés d'utilisation du capital et du travail : une analyse économétrique," Économie et Prévision, Programme National Persée, vol. 131(5), pages 93-111.
  23. 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.
  24. Martial DUPAIGNE, 2002. "Travail posté et durée d’utilisation des équipements dans les fluctuations économiques," Annales d'Economie et de Statistique, ENSAE, issue 66, pages 235-256.
  25. Stephen Bond & Céline Nauges & Frank Windmeijer, 2002. "Unit Roots and Identification in Autoregressive Panel Data Models: A Comparison of Alternative Tests," 10th International Conference on Panel Data, Berlin, July 5-6, 2002 C5-4, International Conferences on Panel Data.
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