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Adjustment Costs and the Identification of Cobb Douglas Production Functions

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  • Stephen Bond

    ()
    (Institute for Fiscal Studies and Nuffield College, Oxford)

  • Måns Söderbom

    (Centre for the Study of African Economies, Department of Economcis, University of Oxford, and Institute for Fiscal Studies)

Abstract

Cobb Douglas production function parameters are not identified from cross-section variation when inputs are perfectly flexible and chosen optimally, and input prices are common to all firms. We consider the role of adjustment costs for inputs in identifying these parameters in this context. The presence of adjustment costs for all inputs allows production function parameters to be identified, even in the absence of variation in input prices. This source of identification appears to be quite fragile when adjustment costs are deterministic, but more useful in the case of stochastic adjustment costs. We illustrate these issues using simulated production data.

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Bibliographic Info

Paper provided by Economics Group, Nuffield College, University of Oxford in its series Economics Papers with number 2005-W04.

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Length: 28 pages
Date of creation: 31 Jan 2005
Date of revision:
Handle: RePEc:nuf:econwp:0504

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Web page: http://www.nuff.ox.ac.uk/economics/

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  1. George S Olley & Ariel Pakes, 1992. "The Dynamics Of Productivity In The Telecommunications Equipment Industry," Working Papers, Center for Economic Studies, U.S. Census Bureau 92-2, Center for Economic Studies, U.S. Census Bureau.
  2. James Levinsohn & Amil Petrin, 2000. "Estimating Production Functions Using Inputs to Control for Unobservables," NBER Working Papers 7819, National Bureau of Economic Research, Inc.
  3. Ricardo J. Caballero & Eduardo M. R. A. Engel & John C. Haltiwanger, 1995. "Plant-Level Adjustment and Aggregate Investment Dynamics," Brookings Papers on Economic Activity, Economic Studies Program, The Brookings Institution, vol. 26(2), pages 1-54.
  4. Caballero, Ricardo J., 1999. "Aggregate investment," Handbook of Macroeconomics, Elsevier, in: J. B. Taylor & M. Woodford (ed.), Handbook of Macroeconomics, edition 1, volume 1, chapter 12, pages 813-862 Elsevier.
  5. Fafchamps, Marcel & Pender, John, 1997. "Precautionary Saving, Credit Constraints, and Irreversible Investment: Theory and Evidence from Semiarid India," Journal of Business & Economic Statistics, American Statistical Association, American Statistical Association, vol. 15(2), pages 180-94, April.
  6. Richard Blundell & Steve Bond, 1999. "GMM estimation with persistent panel data: an application to production functions," IFS Working Papers, Institute for Fiscal Studies W99/04, Institute for Fiscal Studies.
  7. Ackerberg, Daniel & Caves, Kevin & Frazer, Garth, 2006. "Structural identification of production functions," MPRA Paper 38349, University Library of Munich, Germany.
  8. Blundell, Richard & Bond, Stephen & Devereux, Michael & Schiantarelli, Fabio, 1992. "Investment and Tobin's Q: Evidence from company panel data," Journal of Econometrics, Elsevier, Elsevier, vol. 51(1-2), pages 233-257.
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