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Demand For Herbicide In Corn: An Entropy Approach Using Micro-Level Data

  • Arndt, Channing

Price responsiveness of herbicide demand in corn for farmers in Indiana'Â’s White River Basin using cross-section data from individual farms is estimated. Particular attention is paid to appropriate treatment of binding nonnegativity constraints. Estimation was first attempted using an approach to demand systems estimation suggested by Lee and Pitt. However, analytical and computational difficulties effectively preclude estimation by the Lee and Pitt approach. As an alternative, a maximum entropy (ME) approach is presented and discussed. Results from the ME estimator tentatively indicate limited response of herbicide demand to changes in own prices. The maximum entropy approach to demand systems estimation appears to have merit and warrants further attention.

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File URL: http://purl.umn.edu/30866
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Article provided by Western Agricultural Economics Association in its journal Journal of Agricultural and Resource Economics.

Volume (Year): 24 (1999)
Issue (Month): 01 (July)
Pages:

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Handle: RePEc:ags:jlaare:30866
Contact details of provider: Web page: http://waeaonline.org/
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  1. Heien, Dale & Wessells, Cathy Roheim, 1990. "Demand Systems Estimation with Microdata: A Censored Regression Approach," Journal of Business & Economic Statistics, American Statistical Association, vol. 8(3), pages 365-71, July.
  2. Neary, J.P & Roberts, K.W.S, 1978. "The Theory of Household Behaviour under Rationing," The Warwick Economics Research Paper Series (TWERPS) 132, University of Warwick, Department of Economics.
  3. Golan, Amos & Judge, George & Karp, Larry, 1996. "A maximum entropy approach to estimation and inference in dynamic models or Counting fish in the sea using maximum entropy," Journal of Economic Dynamics and Control, Elsevier, vol. 20(4), pages 559-582, April.
  4. Heien, Dale & Durham, Cathy, 1991. "A Test of the Habit Formation Hypothesis Using Household Data," The Review of Economics and Statistics, MIT Press, vol. 73(2), pages 189-99, May.
  5. Lee, Lung-Fei & Pitt, Mark M., 1987. "Microeconometric models of rationing, imperfect markets, and non-negativity constraints," Journal of Econometrics, Elsevier, vol. 36(1-2), pages 89-110.
  6. Van Soest, Arthur & Kooreman, Peter, 1990. "Coherency of the indirect translog demand system with binding nonnegativity constraints," Journal of Econometrics, Elsevier, vol. 44(3), pages 391-400, June.
  7. Lee, Lung-Fei & Pitt, Mark M, 1986. "Microeconometric Demand Systems with Binding Nonnegativity Constraints: The Dual Approach," Econometrica, Econometric Society, vol. 54(5), pages 1237-42, September.
  8. Wales, T. J. & Woodland, A. D., 1983. "Estimation of consumer demand systems with binding non-negativity constraints," Journal of Econometrics, Elsevier, vol. 21(3), pages 263-285, April.
  9. Golan, Amos & Judge, George & Robinson, Sherman, 1994. "Recovering Information from Incomplete or Partial Multisectoral Economic Data," The Review of Economics and Statistics, MIT Press, vol. 76(3), pages 541-49, August.
  10. Soest, Arthur van & Kapteyn, Arie & Kooreman, Peter, 1993. "Coherency and regularity of demand systems with equality and inequality constraints," Journal of Econometrics, Elsevier, vol. 57(1-3), pages 161-188.
  11. Golan, Amos & Judge, George G. & Miller, Douglas, 1996. "Maximum Entropy Econometrics," Staff General Research Papers 1488, Iowa State University, Department of Economics.
  12. Quirino Paris & Richard E. Howitt, 1998. "An Analysis of Ill-Posed Production Problems Using Maximum Entropy," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 80(1), pages 124-138.
  13. J. Scott Shonkwiler & Steven T. Yen, 1999. "Two-Step Estimation of a Censored System of Equations," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 81(4), pages 972-982.
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