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A Two Stage Model of the Demand For Specialty Crop Insurance

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  • Richards, Timothy J.

Abstract

Proposals for reform of the federal multiple-peril crop insurance program for specialty crops seek to change fees for catastrophic (CAT) insurance from a nominal fifty-dollar per contract registration fee to an actuarially sound premium. Growers argue that this would cause a significant reduction in participation rates, thus impeding the program's goals of eventually obviating the need for ad hoc disaster payments and worsening the actuarial soundness of the program. The key policy issue is, therefore, empirical one - whether the demand for specialty crop insurance is elastic or inelastic. Previous studies of this issue using either grower or county-level field crop data typically treat the participation problem as either a discrete insure / don't insure decision or aggregate these decisions to a continuous participation rate problem. However, a grower's problem is more realistically cast as one of simultaneously making a coverage level / insurance participation decision. Because the issue at hand considers a significant price increase for only one coverage level (50%), differentiating between these decisions is necessary both from an analytical and econometric standpoint. To model this decision, the paper develops a two-stage estimation procedure based on Lee's multinomial logit-OLS selection framework. This method is applied to a county-level panel data set consisting of eleven years of the eleven largest grape-growing counties in California. Results show that growers choose among coverage levels based upon expected net premiums and the variance of these returns, as well as the first two moments of expected market returns. At the participation-level, the mean and variance of indemnities are also important, as are several variables measuring the extent of self-insurance, such as farm size, enterprise diversity, or farm income. The results also show that the elasticity of 50% coverage insurance is elastic, suggesting that premium increases may indeed worsen the actuarial soundness of the program. These increases will also cause a significant adjustment of growers among coverage levels.

Suggested Citation

  • Richards, Timothy J., 1998. "A Two Stage Model of the Demand For Specialty Crop Insurance," Working Papers 28546, Arizona State University, Morrison School of Agribusiness and Resource Management.
  • Handle: RePEc:ags:asumwp:28546
    DOI: 10.22004/ag.econ.28546
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    2. Lee, Dong Won & Diersen, Matthew A. & Janssen, Larry & Gustafson, Cole R., 2006. "Premium Subsidy Changes and Demand for Crop Insurance," 2006 Agricultural and Rural Finance Markets in Transition, October 2-3, 2006, Washington, DC 133086, Regional Research Committee NC-1014: Agricultural and Rural Finance Markets in Transition.
    3. Jing Yi & Henry L. Bryant & James W. Richardson, 2020. "How do premium subsidies affect crop insurance demand at different coverage levels: the case of corn," The Geneva Papers on Risk and Insurance - Issues and Practice, Palgrave Macmillan;The Geneva Association, vol. 45(1), pages 5-28, January.
    4. Tsiboe, Francis & Turner, Dylan, 2023. "The crop insurance demand response to premium subsidies: Evidence from U.S. Agriculture," Food Policy, Elsevier, vol. 119(C).
    5. Birthal, Pratap S. & Hazrana, Jaweriah & Negi, Digvijay S. & Mishra, Ashok K., 2022. "Assessing benefits of crop insurance vis-a-vis irrigation in Indian agriculture," Food Policy, Elsevier, vol. 112(C).
    6. Robert Aidoo & James Osei Mensah & Prosper Wie & Dadson Awunyo-vitor, 2014. "Prospects of Crop Insurance as a Risk Management Tool among Arable Crop Farmers in Ghana," Asian Economic and Financial Review, Asian Economic and Social Society, vol. 4(3), pages 341-354, March.
    7. M J Bhende, 2012. "Agricultural Insurance in India: Problems and Prospects," Working Papers id:4840, eSocialSciences.
    8. Yi, Jing & Richardson, James & Bryant, Henry, 2016. "How Do Premium Subsidies Affect Crop Insurance Demand at Different Coverage Levels: the Case of Corn," 2016 Annual Meeting, July 31-August 2, Boston, Massachusetts 236249, Agricultural and Applied Economics Association.
    9. Mbonane, Nobuhle Duduzile, 2018. "An analysis of farmers’ preferences for crop insurance: a case of maize farmers in Swaziland," Research Theses 334771, Collaborative Masters Program in Agricultural and Applied Economics.
    10. Olen, Beau & Wu, Junjie, 2013. "Supply of Insurance for Specialty Crops and its Effect on Yield and Acreage," 2013 Annual Meeting, August 4-6, 2013, Washington, D.C. 150787, Agricultural and Applied Economics Association.
    11. Tsiboe, Francis & Turner, Dylan, 2023. "Econometric identification of crop insurance participation," Agricultural and Resource Economics Review, Cambridge University Press, vol. 52(3), pages 476-497, December.
    12. César Salazar & Marcela Jaime & Cristián Pinto & Andrés Acuña, 2019. "Interaction between crop insurance and technology adoption decisions: The case of wheat farmers in Chile," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 63(3), pages 593-619, July.
    13. Richards, Timothy J. & Manfredo, Mark R., 2003. "Infrequent Shocks and Rating Revenue Insurance: A Contingent Claims Approach," Journal of Agricultural and Resource Economics, Western Agricultural Economics Association, vol. 28(2), pages 1-19, August.
    14. Diao Panpan & Zhang Zhonggen, 2015. "Premium Rate Design and Risk Regionalization for the Policy-Based Wheat Insurance of Henan Province in China," Asia-Pacific Journal of Risk and Insurance, De Gruyter, vol. 9(2), pages 203-229, July.
    15. 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.
    16. Anne Corcos & François Pannequin & Claude Montmarquette, 2017. "Leaving the market or reducing the coverage? A model-based experimental analysis of the demand for insurance," Experimental Economics, Springer;Economic Science Association, vol. 20(4), pages 836-859, December.

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