IDEAS home Printed from https://ideas.repec.org/p/ifs/ifsewp/05-04.html
   My bibliography  Save this paper

Adjustment costs and the identification of Cobb Douglas production functions

Author

Listed:
  • Stephen Bond

    (Institute for Fiscal Studies and Nuffield College, Oxford)

  • Måns Söderbom

    (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.

Suggested Citation

  • Stephen Bond & Måns Söderbom, 2005. "Adjustment costs and the identification of Cobb Douglas production functions," IFS Working Papers W05/04, Institute for Fiscal Studies.
  • Handle: RePEc:ifs:ifsewp:05/04
    as

    Download full text from publisher

    File URL: http://www.ifs.org.uk/wps/wp0504.pdf
    Download Restriction: no
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. Marcel Fafchamps & John Pender, "undated". "Precautionary Saving Credit Constraints and Investment: Theory and Evidence from Semi-Arid India," Computing in Economics and Finance 1997 37, Society for Computational Economics.
    2. 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.
    3. 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.
    4. Caballero, Ricardo J., 1999. "Aggregate investment," Handbook of Macroeconomics, in: J. B. Taylor & M. Woodford (ed.), Handbook of Macroeconomics, edition 1, volume 1, chapter 12, pages 813-862, Elsevier.
    5. 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.
    6. James Levinsohn & Amil Petrin, 2003. "Estimating Production Functions Using Inputs to Control for Unobservables," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 70(2), pages 317-341.
    7. Blundell, Richard & Bond, Stephen & Devereux, Michael & Schiantarelli, Fabio, 1992. "Investment and Tobin's Q: Evidence from company panel data," Journal of Econometrics, Elsevier, vol. 51(1-2), pages 233-257.
    8. Kenneth L. Judd, 1998. "Numerical Methods in Economics," MIT Press Books, The MIT Press, edition 1, volume 1, number 0262100711, December.
    9. Ackerberg, Daniel & Caves, Kevin & Frazer, Garth, 2006. "Structural identification of production functions," MPRA Paper 38349, University Library of Munich, Germany.
    10. Hayashi, Fumio, 1982. "Tobin's Marginal q and Average q: A Neoclassical Interpretation," Econometrica, Econometric Society, vol. 50(1), pages 213-224, January.
    11. 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, vol. 15(2), pages 180-194, April.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Doraszelski, Ulrich & Jaumandreu, Jordi, 2006. "R&D and productivity: Estimating production functions when productivity is endogenous," MPRA Paper 1246, University Library of Munich, Germany.
    2. Stephen Bond & Måns Söderbom, 2005. "Adjustment Costs and the Identification of Cobb Douglas Production Functions," Economics Series Working Papers 2005-W04, University of Oxford, Department of Economics.
    3. Caggese, Andrea, 2007. "Testing financing constraints on firm investment using variable capital," Journal of Financial Economics, Elsevier, vol. 86(3), pages 683-723, December.
    4. Stucchi, Rodolfo, 2008. "Catching up in total factor productivity through the business cycle : evidence from Spanish manufacturing surveys," UC3M Working papers. Economics we085125, Universidad Carlos III de Madrid. Departamento de Economía.
    5. Benoit Dostie, 2011. "Wages, Productivity and Aging," De Economist, Springer, vol. 159(2), pages 139-158, June.
    6. Amoroso, S., 2013. "Heterogeneity of innovative, collaborative, and productive firm-level processes," Other publications TiSEM f5784a49-7053-401d-855d-1, Tilburg University, School of Economics and Management.
    7. Jan De Loecker & Frederic Warzynski, 2012. "Markups and Firm-Level Export Status," American Economic Review, American Economic Association, vol. 102(6), pages 2437-2471, October.
    8. Enghin Atalay, 2014. "Materials Prices And Productivity," Journal of the European Economic Association, European Economic Association, vol. 12(3), pages 575-611, June.
    9. Jinhyung Lee & Jeffrey S. McCullough & Robert J. Town, 2013. "The impact of health information technology on hospital productivity," RAND Journal of Economics, RAND Corporation, vol. 44(3), pages 545-568, September.
    10. Florin Maican & Matilda Orth, 2017. "Productivity Dynamics and the Role of ‘Big-Box’ Entrants in Retailing," Journal of Industrial Economics, Wiley Blackwell, vol. 65(2), pages 397-438, June.
    11. Shepotylo, Oleksandr & Vakhitov, Volodymyr, 2012. "Services liberalization and productivity of manufacturing firms : evidence from Ukraine," Policy Research Working Paper Series 5944, The World Bank.
    12. Jason G. Cummins & Kevin A. Hassett & Stephen D. Oliner, 2006. "Investment Behavior, Observable Expectations, and Internal Funds," American Economic Review, American Economic Association, vol. 96(3), pages 796-810, June.
    13. Trax, Michaela & Brunow, Stephan & Suedekum, Jens, 2015. "Cultural diversity and plant-level productivity," Regional Science and Urban Economics, Elsevier, vol. 53(C), pages 85-96.
    14. Aguirregabiria, Victor, 2009. "Econometric Issues and Methods in the Estimation of Production Functions," MPRA Paper 15973, University Library of Munich, Germany.
    15. Almeida, Rita & Carneiro, Pedro, 2009. "The return to firm investments in human capital," Labour Economics, Elsevier, vol. 16(1), pages 97-106, January.
    16. Bakhtiari, Sasan, 2017. "Corporate credit ratings: Selection on size or productivity?," International Review of Economics & Finance, Elsevier, vol. 49(C), pages 84-101.
    17. Sergey Lychagin & Joris Pinkse & Margaret E. Slade & John Van Reenen, 2016. "Spillovers in Space: Does Geography Matter?," Journal of Industrial Economics, Wiley Blackwell, vol. 64(2), pages 295-335, June.
    18. Robin S. Lee, 2013. "Vertical Integration and Exclusivity in Platform and Two-Sided Markets," American Economic Review, American Economic Association, vol. 103(7), pages 2960-3000, December.
    19. Benoit Dostie & Pierre Thomas Léger, 2014. "Firm-Sponsored Classroom Training: Is It Worth It for Older Workers?," Canadian Public Policy, University of Toronto Press, vol. 40(4), pages 377-390, December.
    20. Dobbelaere, Sabien & Kiyota, Kozo & Mairesse, Jacques, 2015. "Product and labor market imperfections and scale economies: Micro-evidence on France, Japan and the Netherlands," Journal of Comparative Economics, Elsevier, vol. 43(2), pages 290-322.

    More about this item

    Keywords

    Production functions; adjustment costs; identification;
    All these keywords.

    JEL classification:

    • D20 - Microeconomics - - Production and Organizations - - - General
    • D24 - Microeconomics - - Production and Organizations - - - Production; Cost; Capital; Capital, Total Factor, and Multifactor Productivity; Capacity
    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:ifs:ifsewp:05/04. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Emma Hyman (email available below). General contact details of provider: https://edirc.repec.org/data/ifsssuk.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.