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Index Models and Land Allocation Reconsidered

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  • Sergio H. Lence
  • Chad Hart

Abstract

In contrast with previous index model land applications, this article shows that the land allocation problem is a portfolio model with two constraints, namely, investable funds and land. The two-constraint model implies a drastic reinterpretation of what previous studies have quantified as diversifiable and systematic risks in agricultural production. The article also argues that the constant marginal-rate-of-product-substitution (MRPS) technology implicit in financial portfolio models is unlikely to hold in a production context such as the land allocation problem, and that the index model must be modified accordingly. Farm-level data are used to illustrate and test the hypotheses advanced. Empirical results indicate that most of the risk for corn and soybeans is diversifiable, and that corn and soybeans are characterized by decreasing MRPS. The MRPS effect is found to be large from an economic standpoint and implies that crop diversification may be optimal, even for risk-neutral farmers.
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Suggested Citation

  • Sergio H. Lence & Chad Hart, 1997. "Index Models and Land Allocation Reconsidered," Canadian Journal of Agricultural Economics/Revue canadienne d'agroeconomie, Canadian Agricultural Economics Society/Societe canadienne d'agroeconomie, vol. 45(3), pages 267-284, November.
    • Handle: RePEc:bla:canjag:v:45:y:1997:i:3:p:267-284
    DOI: j.1744-7976.1997.tb00208.x
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    Cited by:

    1. Arnberg, Soren & Hansen, Lars Garn, 2007. "The Dynamics of Farm Land Allocation - Short and Long Run Reactions in Long Micro Panel," 2007 Annual Meeting, July 29-August 1, 2007, Portland, Oregon 9978, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    2. Bao-Li Miao & Ying Liu & Yu-Bing Fan & Xue-Jiao Niu & Xiu-Yun Jiang & Zeng Tang, 2023. "Optimization of Agricultural Resource Allocation among Crops: A Portfolio Model Analysis," Land, MDPI, vol. 12(10), pages 1-18, October.

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