Adjustment Costs and the Identification of Cobb Douglas Production Functions
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.
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- 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.
- Olley, G Steven & Pakes, Ariel, 1996. "The Dynamics of Productivity in the Telecommunications Equipment Industry," Econometrica, Econometric Society, vol. 64(6), pages 1263-97, November.
- George S Olley & Ariel Pakes, 1992. "The Dynamics Of Productivity In The Telecommunications Equipment Industry," Working Papers 92-2, Center for Economic Studies, U.S. Census Bureau.
- 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.
- Cabalero, R.J., 1997.
97-20, Massachusetts Institute of Technology (MIT), Department of Economics.
- James Levinsohn & Amil Petrin, 2003.
"Estimating Production Functions Using Inputs to Control for Unobservables,"
Review of Economic Studies,
Wiley Blackwell, vol. 70(2), pages 317-341, 04.
- James Levinsohn & Amil Petrin, 2000. "Estimating Production Functions Using Inputs to Control for Unobservables," NBER Working Papers 7819, National Bureau of Economic Research, Inc.
- Richard Blundell & Steve Bond, 1999.
"GMM estimation with persistent panel data: an application to production functions,"
IFS Working Papers
W99/04, Institute for Fiscal Studies.
- 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.
- 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.
- Ackerberg, Daniel & Caves, Kevin & Frazer, Garth, 2006. "Structural identification of production functions," MPRA Paper 38349, University Library of Munich, Germany.
- 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 180-94, April.
When requesting a correction, please mention this item's handle: RePEc:nuf:econwp:0504. 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: (Maxine Collett)
If references are entirely missing, you can add them using this form.