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Using Regression Analysis To Reduce Aggregation Bias In Linear Programming Supply Models

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  • John O.S. Kennedy

Abstract

Because methods of eliminating aggregation bias are impracticable, an alternative method is suggested for reducing aggregation bias which uses regression estimates of farm resonrce availabilities as functions of farm size. The estimates are incorporated in a parametric run of the LP problem in which size is parameterized. The method is applied to a case study problem, and the results compared with other methods of demarcating representative farms.
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  • John O.S. Kennedy, 1975. "Using Regression Analysis To Reduce Aggregation Bias In Linear Programming Supply Models," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 19(1), pages 1-11, April.
    • Handle: RePEc:bla:ajarec:v:19:y:1975:i:1:p:1-11
    DOI: j.1467-8489.1975.tb00141.x
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    1. Quirino Paris & Gordon C. Rausser, 1973. "Sufficient Conditions for Aggregation of Linear Programming Models," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 55(4_Part_1), pages 659-666.
    2. Miller, Thomas A., 1966. "Sufficient Conditions for Exact Aggregation in Linear Programming Models," Journal of Agricultural Economics Research, United States Department of Agriculture, Economic Research Service, vol. 18(2), pages 1-6, April.
    3. Jones, Harold B. & Thompson, Jack C., 1968. "Squared Versus Unsquared Deviations for Lines of Best Fit," Journal of Agricultural Economics Research, United States Department of Agriculture, Economic Research Service, vol. 20(2), pages 1-7, April.
    4. Richard H. Day, 1963. "On Aggregating Linear Programming Models of Production," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 45(4), pages 797-813.
    5. Lee, John E., Jr., 1966. "Exact Aggregation--A Discussion of Miller's Theorem," Journal of Agricultural Economics Research, United States Department of Agriculture, Economic Research Service, vol. 18(2), pages 1-4, April.
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    1. Kingwell, Ross, 1996. "Programming models of farm supply response: The impact of specification errors," Agricultural Systems, Elsevier, vol. 50(3), pages 307-324.
    2. Bathgate, Andrew D. & Kingwell, Ross S. & O'Connell, Michael, 1999. "WOOL’S FUTURE in WESTERN AUSTRALIA and the R&D IMPLICATIONS: A Discussion Paper," 1999 Conference (43th), January 20-22, 1999, Christchurch, New Zealand 123761, Australian Agricultural and Resource Economics Society.
    3. Greiner, Romy, 1996. "On-farm Costs of Soil Salinisation: a Case Study for the Liverpool Plains in New South Wales," Review of Marketing and Agricultural Economics, Australian Agricultural and Resource Economics Society, vol. 64(01), pages 1-15, April.
    4. Onal, Hayri & McCarl, Bruce A., 1991. "Aggregation In Mathematical Programming Sector Models And Model Stability," 1991 Annual Meeting, August 4-7, Manhattan, Kansas 271241, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    5. P. C. Abbott & W. E. Tyner & M. J. Roth & G. T. Rafsnider, 1991. "The Economics Of ‐ Wheat Production In Morocco," Journal of Agricultural Economics, Wiley Blackwell, vol. 42(1), pages 23-32, January.
    6. Ahmed, Anwar & Kennedy, John O.S., 1991. "The Effect of Credit Liberalization on Small-Farm Households: The Case of Bangladesh," 1991 Conference (35th), February 11-14, 1991, Armidale, Australia 145719, Australian Agricultural and Resource Economics Society.

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