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Returns To Scale And Size In Agricultural Economics

Author

Listed:
  • McClelland, John W.
  • Wetzstein, Michael E.
  • Musser, Wesley N.

Abstract

Differences between the concepts of returns to size and returns to scale are systematically reexamined in this paper. Specifically, the relationship between returns to scale and size are examined through the use of the envelope theorem. A major conclusion of the paper is that the level of abstraction in applying a cost function derived from a homothetic technology within a relevant range of the expansion path may not be severe when compared to the theoretical, estimative, and computational advantages of these technologies.

Suggested Citation

  • McClelland, John W. & Wetzstein, Michael E. & Musser, Wesley N., 1986. "Returns To Scale And Size In Agricultural Economics," Western Journal of Agricultural Economics, Western Agricultural Economics Association, vol. 11(2), pages 1-5, December.
    • Handle: RePEc:ags:wjagec:32252
    DOI: 10.22004/ag.econ.32252
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    References listed on IDEAS

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    1. Lawrence J. Lau & Pan A. Yotopoulos, 1972. "Profit, Supply, and Factor Demand Functions," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 54(1), pages 11-18.
    2. Boggess, William G., 1984. "Discussion: Use of Biophysical Simulation in Production Economics," Journal of Agricultural and Applied Economics, Cambridge University Press, vol. 16(1), pages 87-90, July.
    3. Boggess, William G., 1984. "Discussion: Use Of Biophysical Simulation In Production Economics," Southern Journal of Agricultural Economics, Southern Agricultural Economics Association, vol. 16(1), pages 1-3, July.
    4. B. Delworth Gardner & Rulon D. Pope, 1978. "How is Scale and Structure Determined in Agriculture?," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 60(2), pages 295-302.
    5. Hanoch, Giora, 1975. "The Elasticity of Scale and the Shape of Average Costs," American Economic Review, American Economic Association, vol. 65(3), pages 492-497, June.
    6. Philip M. Raup, 1969. "Economies and Diseconomies of Large-Scale Agriculture," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 51(5), pages 1274-1283.
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    Cited by:

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    2. Yu Sheng & Shiji Zhao & Katarina Nossal & Dandan Zhang, 2015. "Productivity and farm size in Australian agriculture: reinvestigating the returns to scale," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 59(1), pages 16-38, January.
    3. Ker, Alan & Howard, Wayne H., 1993. "Economies of Size in the Ontario Swine Industry," Department of Agricultural Economics and Business 258725, University of Guelph.
    4. Liangyue Cao,, 1997. "Testing predictability of symbolic sequences using time-delay embedding," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 247(1), pages 473-481.
    5. Chater, Nick & Loewenstein, George, 2016. "The under-appreciated drive for sense-making," Journal of Economic Behavior & Organization, Elsevier, vol. 126(PB), pages 137-154.
    6. Sara Amoroso, 2015. "Profits, R&D and labour: Breaking the law of diminishing returns to labour," JRC Working Papers on Corporate R&D and Innovation 2015-10, Joint Research Centre.
    7. Abayateye, F. & Skolrud, T. & Galinato, G., 2018. "Environmental Regulation Stringency and U.S. Agriculture," 2018 Conference, July 28-August 2, 2018, Vancouver, British Columbia 277138, International Association of Agricultural Economists.
    8. Kattan, Michael W. & Cooper, Randolph B., 2000. "A simulation of factors affecting machine learning techniques: an examination of partitioning and class proportions," Omega, Elsevier, vol. 28(5), pages 501-512, October.
    9. Curry, B. & Morgan, P., 1997. "Neural networks: a need for caution," Omega, Elsevier, vol. 25(1), pages 123-133, February.
    10. Gupta, Jatinder N. D. & Sexton, Randall S., 1999. "Comparing backpropagation with a genetic algorithm for neural network training," Omega, Elsevier, vol. 27(6), pages 679-684, December.

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