IDEAS home Printed from
   My bibliography  Save this paper

A Two Stage Model of the Demand For Specialty Crop Insurance


  • Richards, Timothy J.


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

    Download full text from publisher

    File URL:
    Download Restriction: no

    File URL:
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item

    Other versions of this item:

    References listed on IDEAS

    1. Ralph R. Botts & James N. Boles, 1958. "Use of Normal-Curve Theory in Crop Insurance Ratemaking," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 40(3), pages 733-740.
    2. Hanemann, W Michael, 1984. "Discrete-Continuous Models of Consumer Demand," Econometrica, Econometric Society, vol. 52(3), pages 541-561, May.
    3. Dubin, Jeffrey A & McFadden, Daniel L, 1984. "An Econometric Analysis of Residential Electric Appliance Holdings and Consumption," Econometrica, Econometric Society, vol. 52(2), pages 345-362, March.
    4. Richard E. Just & Linda Calvin & John Quiggin, 1999. "Adverse Selection in Crop Insurance: Actuarial and Asymmetric Information Incentives," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 81(4), pages 834-849.
    5. 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.
    6. Lee, Lung-Fei, 1983. "Generalized Econometric Models with Selectivity," Econometrica, Econometric Society, vol. 51(2), pages 507-512, March.
    7. Heckman, James, 2013. "Sample selection bias as a specification error," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 31(3), pages 129-137.
    8. Barnett, Barry J. & Skees, Jerry R. & Hourigan, James D., 1990. "Explaining Participation in Federal Crop Insurance," 1990 Annual meeting, August 5-8, Vancouver, Canada 270875, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    9. Niewuwoudt, W.L. & Bullock, J. Bruce, 1985. "The Demand for Crop Insurance," 1985 Conference, August 26-September 4, 1985, Malaga, Spain 183028, International Association of Agricultural Economists.
    10. Cragg, John G, 1971. "Some Statistical Models for Limited Dependent Variables with Application to the Demand for Durable Goods," Econometrica, Econometric Society, vol. 39(5), pages 829-844, September.
    11. Thomas O. Knight & Keith H. Coble, 1997. "Survey of U.S. Multiple Peril Crop Insurance Literature Since 1980," Review of Agricultural Economics, Agricultural and Applied Economics Association, vol. 19(1), pages 128-156.
    12. Goodwin, Barry K., 1994. "Premium Rate Determination In The Federal Crop Insurance Program: What Do Averages Have To Say About Risk?," Journal of Agricultural and Resource Economics, Western Agricultural Economics Association, vol. 19(2), pages 1-14, December.
    13. Vincent H. Smith & Alan E. Baquet, 1996. "The Demand for Multiple Peril Crop Insurance: Evidence from Montana Wheat Farms," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 78(1), pages 189-201.
    14. Barry K. Goodwin & Alan P. Ker, 1998. "Nonparametric Estimation of Crop Yield Distributions: Implications for Rating Group-Risk Crop Insurance Contracts," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 80(1), pages 139-153.
    15. Pradeep K. Chintagunta, 1993. "Investigating Purchase Incidence, Brand Choice and Purchase Quantity Decisions of Households," Marketing Science, INFORMS, vol. 12(2), pages 184-208.
    Full references (including those not matched with items on IDEAS)


    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.

    Cited by:

    1. 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.
    2. 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.
    3. Salazar, Cesar & Jaime, Marcela & Pinto, Cristian & Acuna, Andres, 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), July.
    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. 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.
    12. 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.
    13. 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.
    14. 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.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Rogna, Marco & Schamel, Günter & Weissensteiner, Alex, 2019. "Choosing Between Hail Insurance and Anti-Hail Nets: A Simple Model and a Simulation among Apples Producers in South Tyrol," 2019: Trading for Good - Agricultural Trade in the Context of Climate Change Adaptation and Mitigation... Symposium, June 23-25, 2019, Seville, Spain 312593, International Agricultural Trade Research Consortium.
    2. Chen, Shu-Ling & Miranda, Mario J., 2006. "Modeling Yield Distribution In High Risk Counties: Application To Texas Upland Cotton," 2006 Annual meeting, July 23-26, Long Beach, CA 21392, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    3. Damette, Olivier & Delacote, Philippe & Lo, Gaye Del, 2018. "Households energy consumption and transition toward cleaner energy sources," Energy Policy, Elsevier, vol. 113(C), pages 751-764.
    4. Myyra, Sami & Pietola, Kyosti, 2011. "Testing for Moral Hazard and Ranking Farms by Their Inclination to Collect Crop Damage Compensations," 2011 International Congress, August 30-September 2, 2011, Zurich, Switzerland 114632, European Association of Agricultural Economists.
    5. Juan He & Roderick Rejesus & Xiaoyong Zheng & Jose Yorobe, 2018. "Advantageous Selection in Crop Insurance: Theory and Evidence," Journal of Agricultural Economics, Wiley Blackwell, vol. 69(3), pages 646-668, September.
    6. Shaik, Saleem & Coble, Keith H. & Knight, Thomas O., 2005. "Revenue Crop Insurance Demand," 2005 Annual meeting, July 24-27, Providence, RI 19319, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    7. Mansur, Erin T. & Mendelsohn, Robert & Morrison, Wendy, 2008. "Climate change adaptation: A study of fuel choice and consumption in the US energy sector," Journal of Environmental Economics and Management, Elsevier, vol. 55(2), pages 175-193, March.
    8. Yuehua Zhang & Ying Cao & H. Holly Wang, 2018. "Cheating? The Case of Producers’ Under‐Reporting Behavior in Hog Insurance in China," Canadian Journal of Agricultural Economics/Revue canadienne d'agroeconomie, Canadian Agricultural Economics Society/Societe canadienne d'agroeconomie, vol. 66(3), pages 489-510, September.
    9. Andrea Pellegrini & Stefano Scagnolari, 2021. "The relationship between length of stay and land transportation mode in the tourism sector: A discrete–continuous framework applied to Swiss data," Tourism Economics, , vol. 27(1), pages 243-259, February.
    10. David R. Bell & Jeongwen Chiang & V. Padmanabhan, 1999. "The Decomposition of Promotional Response: An Empirical Generalization," Marketing Science, INFORMS, vol. 18(4), pages 504-526.
    11. Evan J. Miller-Tait & Sandeep Mohapatra & M. K. (Marty) Luckert & Brent M. Swallow, 2019. "Processing technologies for undervalued grains in rural India: on target to help the poor?," Food Security: The Science, Sociology and Economics of Food Production and Access to Food, Springer;The International Society for Plant Pathology, vol. 11(1), pages 151-166, February.
    12. Paul Ellickson & Sanjog Misra, 2012. "Enriching interactions: Incorporating outcome data into static discrete games," Quantitative Marketing and Economics (QME), Springer, vol. 10(1), pages 1-26, March.
    13. Breustedt, Gunnar & Schulz, Norbert & Latacz-Lohmann, Uwe, 2013. "Kalibrierung von Vertragsnaturschutzprogrammen mittels eines zweistufigen Discrete-Choice-Experimentes," German Journal of Agricultural Economics, Humboldt-Universitaet zu Berlin, Department for Agricultural Economics, vol. 62(04), pages 1-17, November.
    14. Torres, Marcelo de O. & Felthoven, Ronald G., 2014. "Productivity growth and product choice in catch share fisheries: The case of Alaska pollock," Marine Policy, Elsevier, vol. 50(PA), pages 280-289.
    15. Ashok Mishra & Barry Goodwin, 2006. "Revenue insurance purchase decisions of farmers," Applied Economics, Taylor & Francis Journals, vol. 38(2), pages 149-159.
    16. Guaracyane Lima Campelo & João Mário Santos De França & Emerson Luís Lemos Marinho, 2016. "Impacts Of Malnutrition On Labor Productivity: Empirical Evidences In Rural Brazil," Anais do XLII Encontro Nacional de Economia [Proceedings of the 42nd Brazilian Economics Meeting] 236, ANPEC - Associação Nacional dos Centros de Pós-Graduação em Economia [Brazilian Association of Graduate Programs in Economics].
    17. Sergi Jiménez-Martín & Cristina Prieto, 2012. "The trade-off between formal and informal care in Spain," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 13(4), pages 461-490, August.
    18. Bhat, Chandra R., 2005. "A multiple discrete-continuous extreme value model: formulation and application to discretionary time-use decisions," Transportation Research Part B: Methodological, Elsevier, vol. 39(8), pages 679-707, September.
    19. Aleksandra Anić & Gorana Krstić, 2019. "What Lies Behind The Gender Wage Gap In Serbia?," Economic Annals, Faculty of Economics and Business, University of Belgrade, vol. 64(223), pages 137-170, October –.
    20. Stéphane Couture & Serge Garcia & Arnaud Reynaud, 2009. "Household Energy Choices and Fuelwood Consumption: An Econometric Approach to the French Data," LERNA Working Papers 09.08.284, LERNA, University of Toulouse.

    More about this item


    Risk and Uncertainty;


    Access and download statistics


    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:ags:asumwp:28546. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: AgEcon Search (email available below). General contact details of provider: .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.