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Methods of Estimating the Input Coefficients for Linear Programming Models

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  • Subhash C. Ray

Abstract

In order to apply the linear programming method to determine the most profitable product mix of a farm, it is often necessary to estimate the input coefficients from sample data. The estimated coefficients must all be nonnegative. Estimates from regression models of input demand equations are not always nonnegative. The sample average of inputs used per acre of various crops provides nonnegative estimates but may suffer from selectivity bias. In this study the methods of minimizing the mean of absolute deviations and of minimizing the maximum absolute deviation are discussed as alternatives to inequality-constrained least squares.

Suggested Citation

  • Subhash C. Ray, 1985. "Methods of Estimating the Input Coefficients for Linear Programming Models," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 67(3), pages 660-665.
    • Handle: RePEc:oup:ajagec:v:67:y:1985:i:3:p:660-665.
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    File URL: http://hdl.handle.net/10.2307/1241090
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    Cited by:

    1. Hornbaker, Robert H. & Dixon, Bruce L. & Sonka, Steven T., 1987. "Estimating Activity Costs for Multi-Output Firms With a Random Coefficient Regression Model," 1987 Annual Meeting, August 2-5, East Lansing, Michigan 269946, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    2. Louhichi, Kamel & Jacquet, Florence & Butault, Jean Pierre, 2012. "Estimating input allocation from heterogeneous data sources: A comparison of alternative estimation approaches," Agricultural Economics Review, Greek Association of Agricultural Economists, vol. 13(2), pages 1-20.
    3. Dixon, Bruce L. & Hornbaker, Robert H., 1989. "Estimating the Technology Coefficients in Linear Programming Models," 1989 Annual Meeting, July 30-August 2, Baton Rouge, Louisiana 270519, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    4. Peeters, Ludo & Surry, Yves R., 2003. "Farm Cost Allocation Based on the Maximum Entropy Methodology - The Case of Saskatchewan Crop Farms," Economic and Market Information 54461, Agriculture and Agri-Food Canada.

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