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.
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- 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.
- Caballero, Ricardo J., 1999.
Handbook of Macroeconomics,
in: J. B. Taylor & M. Woodford (ed.), Handbook of Macroeconomics, edition 1, volume 1, chapter 12, pages 813-862
- 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.
- Richard Blundell & Stephen Bond, 2000.
"GMM Estimation with persistent panel data: an application to production functions,"
Taylor & Francis Journals, vol. 19(3), pages 321-340.
- 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.
- George S Olley & Ariel Pakes, 1992.
"The Dynamics Of Productivity In The Telecommunications Equipment Industry,"
92-2, Center for Economic Studies, U.S. Census Bureau.
- 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.
- 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.
- 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.
- 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.
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