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Linear Programming versus Positively Estimated Supply Functions: An Empirical and Methodological Critique

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  • C. Richard Shumway
  • Anne A. Chang

Abstract

This paper examines whether supply relations derived from a static profit-maximizing linear programming model can be used as information to explain supply response with at least the same reliability as partial adjustment regression models. Programming estimates of direct supply elasticities of California commodities are compared with estimates from time-series regressions. Differences on individual crops are considerable, but on average the elasticity estimates are comparable. Programming parameters are combined with time-series data to test whether imposing such relative parameters on time-series models need not significantly reduce their predictive ability. This imposition does not reduce predictive ability or significantly improve it.

Suggested Citation

  • C. Richard Shumway & Anne A. Chang, 1977. "Linear Programming versus Positively Estimated Supply Functions: An Empirical and Methodological Critique," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 59(2), pages 344-357.
  • Handle: RePEc:oup:ajagec:v:59:y:1977:i:2:p:344-357.
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    File URL: http://hdl.handle.net/10.2307/1240025
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    Citations

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    Cited by:

    1. Wicks, John A. & Dillon, John L., 1978. "APMAA Estimates of Supply Elasticities for Australian Wool, Beef and Wheat," Review of Marketing and Agricultural Economics, Australian Agricultural and Resource Economics Society, vol. 0(Number 01), pages 1-10, April.
    2. Howitt, Richard E. & Mean, Phillippe, 1983. "A Positive Approach to Microeconomic Programming Models," Working Papers 225710, University of California, Davis, Department of Agricultural and Resource Economics.
    3. A. P. Moxey & B. White & R. A. Sanderson & S. P. Rushton, 1995. "An Approach To Linking An Ecological Vegetation Model To An Agricultural Economic Model," Journal of Agricultural Economics, Wiley Blackwell, vol. 46(3), pages 381-397.
    4. Shumway, C. Richard & Talpaz, Hovav, 1977. "Verification Of Linear Programming Solutions, With Emphasis On Supply Implications," Southern Journal of Agricultural Economics, Southern Agricultural Economics Association, vol. 0(Number 2), pages 1-8, December.
    5. Hall, Nigel H. & Menz, Kenneth M., 1985. "Product Supply Elasticities for the Australian Broadacre Industries, Estimated with a Programming Model," Review of Marketing and Agricultural Economics, Australian Agricultural and Resource Economics Society, vol. 0(Number 01), pages 1-8, April.
    6. Phoebe Koundouri, 2004. "Current Issues in the Economics of Groundwater Resource Management," Journal of Economic Surveys, Wiley Blackwell, vol. 18(5), pages 703-740, December.
    7. Rowse, John, 1980. "1. On User Solution Strategy for Mixed-Integer Linear Programming Models 2. On the Solution of Spatial Price and Allocation Models," Queen's Institute for Economic Research Discussion Papers 275172, Queen's University - Department of Economics.
    8. Shumway, C. Richard & Gebremeskel, Tesfaye, 1978. "Impact Of Risk Averse Behavior On Fertilizer Demand For Tame Forages," Southern Journal of Agricultural Economics, Southern Agricultural Economics Association, vol. 0(Number 1), pages 1-7, July.
    9. K. Jegasothy & C. R. Shumway & H. Lim, 1990. "Production Technology And Input Allocations In Sri Lankan Multicrop Farming," Journal of Agricultural Economics, Wiley Blackwell, vol. 41(1), pages 33-46.
    10. Colman, David R., 1983. "A Review of the Arts of Supply Response Analysis," Review of Marketing and Agricultural Economics, Australian Agricultural and Resource Economics Society, vol. 0(Number 03), pages 1-30, December.
    11. Batterham, Robert L. & MacAulay, T. Gordon, 1994. "Price-Linked Farm And Spatial Equilibrium Models," Australian Journal of Agricultural Economics, Australian Agricultural and Resource Economics Society, vol. 0(Number 2), pages 1-28, August.

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