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Land Resilience and Tail Dependence among Crop Yield Distributions

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  • Xiaodong Du
  • David A Hennessy
  • Hongli Feng
  • Gaurav Arora
Abstract
We propose and empirically test a simple model to shed light on the nature of interactions between weather, land quality, and yield. The conceptual model posits substitution relations between water stress metrics and soil quality, as well as a soil-conditioned threshold water stress level beyond which soil cannot buffer crop yields. The model implies that yield-yield dependence should vary as growing conditions vary. In comparison with intermediate growing conditions, yield-yield dependence should strengthen when growing conditions are either very good or very poor. County yield data strongly support substitution between soil and benign water availability levels, but complementarity between soil and beneficial heat variables. Our estimated model provides qualified support for the hypothesis that better land is more resilient to water stress. We estimate a pseudo-copula that nests the Gaussian copula, finding strong evidence of left tail dependence among yields. Our formal model and empirical findings corroborate others’ concerns about the appropriateness of current USDA rate-setting methodologies, which posit constant state-conditional rank correlations, implicitly assumed by use of the Gaussian copula. An application to aggregate crop yield rate setting suggests that current methods underprice area yield and whole farm premiums. Applying our empirical model to medium-range weather projections under a climate change scenario for the Northern Great Plains, we infer that systemic yield correlations will increase in future years.

Suggested Citation

  • Xiaodong Du & David A Hennessy & Hongli Feng & Gaurav Arora, 2018. "Land Resilience and Tail Dependence among Crop Yield Distributions," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 100(3), pages 809-828.
    • Handle: RePEc:oup:ajagec:v:100:y:2018:i:3:p:809-828.
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    File URL: http://hdl.handle.net/10.1093/ajae/aax082
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    Cited by:

    1. Negi, Digvijay S., 2018. "Tail-dependent Rainfall Risk and Demand for Index based Crop Insurance," 2018 Annual Meeting, August 5-7, Washington, D.C. 274481, Agricultural and Applied Economics Association.
    2. Xuche Gong & David A. Hennessy & Hongli Feng, 2023. "Systemic risk, relative subsidy rates, and area yield insurance choice," American Journal of Agricultural Economics, John Wiley & Sons, vol. 105(3), pages 888-913, May.
    3. Yaoyao Wu & Hanqi Liao & Lei Fang & Guizhen Guo, 2023. "Quantitative Study on Agricultural Premium Rate and Its Distribution in China," Land, MDPI, vol. 12(1), pages 1-14, January.

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    More about this item

    Keywords

    Climate change; crop insurance; Gaussian copula; pseudo-copula; reinsurance; systemic risk;
    All these keywords.

    JEL classification:

    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
    • Q18 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Agriculture - - - Agricultural Policy; Food Policy; Animal Welfare Policy

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