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Why Are Estimates of Agricultural Supply Response So Variable?

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  • Diebold
  • Lamb

Abstract

Estimates of the response of agricultural supply to movements in expected price display curiously large variation across crops, regions, and time periods. We argue that this anomaly may be traced, at least in part, to the statistical properties of the commonly-used econometric estimator, which has infinite moments of all orders and may have a bimodal distribution. We propose an alternative minimum-expected-loss estimator, establish its improved sampling properties, and argue for its usefulness in the empirical analysis of agricultural supply response.

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Paper provided by University of Pennsylvania in its series Home Pages with number _055.

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Handle: RePEc:wop:pennhp:_055

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  1. Zaman, Asad, 1981. "Estimators without moments : The case of the reciprocal of a normal mean," Journal of Econometrics, Elsevier, vol. 15(2), pages 289-298, February.
  2. Fomby, Thomas B. & Guilkey, David K., 1978. "On choosing the optimal level of significance for the Durbin-Watson test and the Bayesian alternative," Journal of Econometrics, Elsevier, vol. 8(2), pages 203-213, October.
  3. Park, Soo-Bin, 1982. "Some sampling properties of minimum expected loss (MELO) estimators of structural coefficients," Journal of Econometrics, Elsevier, vol. 18(3), pages 295-311, April.
  4. Askari, Hossein & Cummings, John Thomas, 1977. "Estimating Agricultural Supply Response with the Nerlove Model: A Survey," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 18(2), pages 257-92, June.
  5. Zellner, Arnold, 1985. "Bayesian Econometrics," Econometrica, Econometric Society, vol. 53(2), pages 253-69, March.
  6. Just, Richard E., 1993. "Discovering Production and Supply Relationships: Present Status and Future Opportunities," Review of Marketing and Agricultural Economics, Australian Agricultural and Resource Economics Society, vol. 61(01), April.
  7. Zellner, Arnold & Geisel, Martin S, 1970. "Analysis of Distributed Lag Models with Application to Consumption Function Estimation," Econometrica, Econometric Society, vol. 38(6), pages 865-88, November.
  8. Zellner, Arnold, 1998. "The finite sample properties of simultaneous equations' estimates and estimators Bayesian and non-Bayesian approaches," Journal of Econometrics, Elsevier, vol. 83(1-2), pages 185-212.
  9. Bewley, R. & Fiebig, D.G., 1989. "Why Are Long-Run Parameter Estimates So Disparate?," Papers 89-3, New South Wales - School of Economics.
  10. Zellner, Arnold, 1978. "Estimation of functions of population means and regression coefficients including structural coefficients : A minimum expected loss (MELO) approach," Journal of Econometrics, Elsevier, vol. 8(2), pages 127-158, October.
  11. Tomek, William G. & Myers, Robert J., 1993. "Empirical Analysis Of Agricultural Commodity Prices: A Viewpoint," Working Papers 6847, Cornell University, Department of Applied Economics and Management.
  12. Braulke, Michael, 1982. "A Note on the Nerlove Model of Agricultural Supply Response," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 23(1), pages 241-44, February.
  13. Marc Nerlove, 1979. "The Dynamics of Supply: Retrospect and Prospect," Discussion Papers 394, Northwestern University, Center for Mathematical Studies in Economics and Management Science.
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Cited by:
  1. repec:ltr:wpaper:2010.06 is not listed on IDEAS
  2. Psaradakis, Zacharias & Sola, Martin, 1998. "Finite-sample properties of the maximum likelihood estimator in autoregressive models with Markov switching," Journal of Econometrics, Elsevier, vol. 86(2), pages 369-386, June.
  3. Shen, Edward Z. & Perloff, Jeffrey M., 2001. "Maximum entropy and Bayesian approaches to the ratio problem," Journal of Econometrics, Elsevier, vol. 104(2), pages 289-313, September.
  4. Frank Kleibergen & Eric Zivot, 1998. "Bayesian and Classical Approaches to Instrumental Variables Regression," Econometrics 9812002, EconWPA.
  5. Demont, Matty & Tollens, Eric, 2001. "Uncertainties Of Estimating The Welfare Effects Of Agricultural Biotechnology In The European Union," Working Papers 31828, Katholieke Universiteit Leuven, Centre for Agricultural and Food Economics.
  6. Ball, V. Eldon & Moss, Charles B. & Erickson, Kenneth W. & Nehring, Richard F., 2003. "Modeling Supply Response In A Multiproduct Framework Revisited: The Nexus Of Empirics And Economics," 2003 Annual meeting, July 27-30, Montreal, Canada 21981, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
  7. Kim, Jae H. & Fraser, Iain & Hyndman, Rob J., 2011. "Improved interval estimation of long run response from a dynamic linear model: A highest density region approach," Computational Statistics & Data Analysis, Elsevier, vol. 55(8), pages 2477-2489, August.
  8. Arnold Zellner, 2003. "Some Recent Developments in Econometric Inference," Econometric Reviews, Taylor & Francis Journals, vol. 22(2), pages 203-215.
  9. Lamb, Russell L., 2000. "Food crops, exports, and the short-run policy response of agriculture in Africa," Agricultural Economics, Blackwell, vol. 22(3), pages 271-298, April.

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