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. 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.
    2. 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.
    3. 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.
    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. 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," Review of Economic Studies, Oxford University Press, 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. Ackerberg, Daniel & Caves, Kevin & Frazer, Garth, 2006. "Structural identification of production functions," MPRA Paper 38349, University Library of Munich, Germany.
    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. 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.
    2. Doraszelski, Ulrich & Jaumandreu, Jordi, 2006. "R&D and productivity: Estimating production functions when productivity is endogenous," MPRA Paper 1246, University Library of Munich, Germany.
    3. Francesco Devicienti & Elena Grinza & Davide Vannoni, 2015. "The Impact of Part-Time Work on Firm Total Factor Productivity: Evidence from Italy," Carlo Alberto Notebooks 433, Collegio Carlo Alberto.
    4. 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.
    5. 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.
    6. Stucchi, Rodolfo & Escribano, Álvaro, 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.
    7. Benoit Dostie, 2011. "Wages, Productivity and Aging," De Economist, Springer, vol. 159(2), pages 139-158, June.
    8. 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.
    9. 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.
    10. Göbel, Christian & Zwick, Thomas, 2009. "Age and productivity: evidence from linked employer employee data," ZEW Discussion Papers 09-020, ZEW - Leibniz Centre for European Economic Research.
    11. Enghin Atalay, 2014. "Materials Prices And Productivity," Journal of the European Economic Association, European Economic Association, vol. 12(3), pages 575-611, June.
    12. 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.
    13. Shepotylo, Oleksandr & Vakhitov, Volodymyr, 2012. "Services liberalization and productivity of manufacturing firms : evidence from Ukraine," Policy Research Working Paper Series 5944, The World Bank.
    14. repec:ebl:ecbull:v:12:y:2006:i:6:p:1-11 is not listed on IDEAS
    15. Klaas Mulier & Koen Schoors & Bruno Merlevede, 2014. "Investment-Cash Flow Sensitivity and the Cost of External Finance," Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium 14/890, Ghent University, Faculty of Economics and Business Administration.
    16. Sieg, Holger & Zhang, Jipeng, 2012. "The importance of managerial capacity in fundraising: Evidence from land conservation charities," International Journal of Industrial Organization, Elsevier, vol. 30(6), pages 724-734.
    17. 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.
    18. Petrick, Martin & Kloss, Mathias, 2013. "Identifying Factor Productivity from Micro-data: The case of EU agriculture," Working papers 144004, Factor Markets, Centre for European Policy Studies.
    19. Aguirregabiria, Victor, 2009. "Econometric Issues and Methods in the Estimation of Production Functions," MPRA Paper 15973, University Library of Munich, Germany.
    20. Almeida, Rita & Carneiro, Pedro, 2009. "The return to firm investments in human capital," Labour Economics, Elsevier, vol. 16(1), pages 97-106, January.
    21. Dostie Benoit & Jayaraman Rajshri, 2012. "Organizational Redesign, Information Technologies and Workplace Productivity," The B.E. Journal of Economic Analysis & Policy, De Gruyter, vol. 12(1), pages 1-41, February.

    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.

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

    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 hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.