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Spatial producer heterogeneity in crop insurance product decisions within major corn producing states

Author

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  • Shyam Adhikari
  • Eric J. Belasco
  • Thomas O. Knight

Abstract

Purpose - The purpose of this paper is to examine the spatial components of producer heterogeneity in crop insurance product selection among US corn producers and identifies neighborhood spillover or agent marketing effects in these decisions. Design/methodology/approach - County‐level insurance and yield data are used to demonstrate that a gradual shift from yield‐based insurance to revenue‐based insurance has spatial patterns. Conventional risk variables such as yield variability, price variability, prevalence of irrigation, other crops, and yield‐price relationships play an important role in this shift and are consistently estimated only when spatial components are included. A spatial random effects model is used to also identify the impact of spatial lag effects, which include neighborhood spillover and agent marketing effects, on the share of corn acres insured with revenue‐based plans vs yield‐based plans. Findings - Theoretically consistent variables associated with risk are found to significantly influence the choice between crop revenue and yield insurance. Non‐linear parameters identify the region‐specific effects from changes in irrigation, yield price correlation, and the prevalence of corn production on insurance decisions. In addition, spatial components such as the decisions made by nearby producers and marketing drives are also found to influence decisions. These results may demonstrate the relative influence of trusted sources, such as nearby producers and insurance agents, on insurance decisions. Originality/value - Traditional risk variables are consistently estimated by controlling for spatial heterogeneity. This study also reveals the propensity of producers to rely on the opinions of other producers or agents that they know.

Suggested Citation

  • Shyam Adhikari & Eric J. Belasco & Thomas O. Knight, 2010. "Spatial producer heterogeneity in crop insurance product decisions within major corn producing states," Agricultural Finance Review, Emerald Group Publishing Limited, vol. 70(1), pages 66-78, May.
  • Handle: RePEc:eme:afrpps:v:70:y:2010:i:1:p:66-78
    DOI: 10.1108/00021461011042648
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    References listed on IDEAS

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    1. Keith H. Coble & Thomas O. Knight & Rulon D. Pope & Jeffery R. Williams, 1996. "Modeling Farm-Level Crop Insurance Demand with Panel Data," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 78(2), pages 439-447.
    2. T. S. Breusch & A. R. Pagan, 1980. "The Lagrange Multiplier Test and its Applications to Model Specification in Econometrics," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 47(1), pages 239-253.
    3. Barry K. Goodwin & Monte L. Vandeveer & John L. Deal, 2004. "An Empirical Analysis of Acreage Effects of Participation in the Federal Crop Insurance Program," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 86(4), pages 1058-1077.
    4. Barry J. Barnett & Jerry R. Skees, 1995. "Region and Crop Specific Models of the Demand for Federal Crop Insurance," Journal of Insurance Issues, Western Risk and Insurance Association, vol. 18(2), pages 47-65.
    5. Shaik, Saleem & Coble, Keith H. & Knight, Thomas O. & Baquet, Alan E. & Patrick, George F., 2008. "Crop Revenue and Yield Insurance Demand: A Subjective Probability Approach," Journal of Agricultural and Applied Economics, Southern Agricultural Economics Association, vol. 40(3), pages 1-10, December.
    6. Harwood, Joy L. & Heifner, Richard G. & Coble, Keith H. & Perry, Janet E. & Somwaru, Agapi, 1999. "Managing Risk in Farming: Concepts, Research, and Analysis," Agricultural Economic Reports 34081, United States Department of Agriculture, Economic Research Service.
    7. Mueller, Julie M. & Loomis, John B., 2008. "Spatial Dependence in Hedonic Property Models: Do Different Corrections For Spatial Dependence Result in Economically Significant Differences in Estimated Implicit Prices?," Journal of Agricultural and Resource Economics, Western Agricultural Economics Association, vol. 33(2), pages 1-20.
    8. Brian Wansink, 2003. "Farmers' Preferences for Crop Insurance Attributes," Review of Agricultural Economics, Agricultural and Applied Economics Association, vol. 25(2), pages 415-429.
    9. Vedenov, Dmitry V. & Power, Gabriel J., 2008. "Risk-Reducing Effectiveness of Revenue versus Yield Insurance in the Presence of Government Payments," Journal of Agricultural and Applied Economics, Southern Agricultural Economics Association, vol. 40(2), pages 1-17, August.
    10. Swamy, P A V B & Arora, S S, 1972. "The Exact Finite Sample Properties of the Estimators of Coefficients in the Error Components Regression Models," Econometrica, Econometric Society, vol. 40(2), pages 261-275, March.
    11. Shiva S. Makki & Agapi Somwaru, 2001. "Farmers' Participation in Crop Insurance Markets: Creating the Right Incentives," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 83(3), pages 662-667.
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    Cited by:

    1. Adhikari, Shyam, 2015. "Optimal Coverage Level and Producer Participation in Supplemental Coverage Option in Yield and Revenue Protection Crop Insurance," 2015 AAEA & WAEA Joint Annual Meeting, July 26-28, San Francisco, California 205053, Agricultural and Applied Economics Association.
    2. Motamed, Mesbah J., 2021. "Price-Yield Covariance Effects on Producers’ Risk Profile and Risk Response," 2021 Annual Meeting, August 1-3, Austin, Texas 314082, Agricultural and Applied Economics Association.
    3. Daniel KOMADEL & Ludovit PINDA & Katarina SAKALOVA, 2018. "Securitization in crop insurance with soil classification," Agricultural Economics, Czech Academy of Agricultural Sciences, vol. 64(3), pages 131-140.
    4. Eric J Belasco & Joseph Cooper & Vincent H Smith, 2020. "The Development of a Weather‐based Crop Disaster Program," American Journal of Agricultural Economics, John Wiley & Sons, vol. 102(1), pages 240-258, January.
    5. Lajos Barath & Raushan Bokusheva & Imre Ferto, 2016. "Studying Farm Insurance Demand under Financial Constraints," CERS-IE WORKING PAPERS 1625, Institute of Economics, Centre for Economic and Regional Studies.
    6. Woodard, Joshua, 2016. "Estimation of Insurance Deductible Demand under Endogenous Premium Rates," 2016 Annual Meeting, July 31-August 2, Boston, Massachusetts 236151, Agricultural and Applied Economics Association.

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