Estimating State-Contingent Production Frontiers
AbstractChambers and Quiggin (2000) use state-contingent representations of risky production technologies to establish important theoretical results concerning producer behavior under uncertainty. Unfortunately, perceived problems in the estimation of state-contingent models have limited the usefulness of the approach in policy formulation. We show that fixed and random effects state-contingent production frontiers can be conveniently estimated in a finite mixtures framework. An empirical example is provided. Compared to conventional estimation approaches, we find that estimating production frontiers in a state-contingent framework produces significantly different estimates of elasticities, firm technical efficiencies, and other quantities of economic interest. Copyright 2006, Oxford University Press.
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Bibliographic InfoArticle provided by Agricultural and Applied Economics Association in its journal American Journal of Agricultural Economics.
Volume (Year): 88 (2006)
Issue (Month): 1 ()
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Other versions of this item:
- Chris O'Donnell & W.E. Griffiths, 2004. "Estimating State-Contingent Production Frontiers," CEPA Working Papers Series WP022004, School of Economics, University of Queensland, Australia.
- C.J. O'Donnell & W.E. Griffiths, 2004. "Estimating State-Contingent Production Frontiers," Department of Economics - Working Papers Series 911, The University of Melbourne.
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- Robert G. Chambers & John Quiggin, 2002. "The State-Contingent Properties of Stochastic Production Functions," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 84(2), pages 513-526.
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- Chambers, Robert G. & Quiggin, John C., 2004. "Technological and financial approaches to risk management in agriculture: an integrate approach," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 48(2), June.
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- Battese, G E & Coelli, T J, 1995. "A Model for Technical Inefficiency Effects in a Stochastic Frontier Production Function for Panel Data," Empirical Economics, Springer, vol. 20(2), pages 325-32.
- Chambers, Robert G. & Quiggin, John, 1996. "Non-point-source pollution regulation as a multi-task principal-agent problem," Journal of Public Economics, Elsevier, vol. 59(1), pages 95-116, January.
- Rasmussen, Svend, 2004. "Optimizing Production under Uncertainty: Generalisation of the State-Contingent Approach and Comparison of Methods for Empirical Application," Unit of Economics Working papers 24184, Royal Veterinary and Agricultural University, Food and Resource Economic Institute.
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