IDEAS home Printed from https://ideas.repec.org/p/ags/aaeaci/156958.html
   My bibliography  Save this paper

Challenging Belief in the Law of Small Numbers

Author

Listed:
  • Coble, Keith H.
  • Barnett, Barry J.
  • Riley, John Michael

Abstract

Introduction : The context of row crop risk management continues to grow more complex. While the magnitude of price and yield risk changes over time, the development of sophisticated risk management tools and complex government policies may improve growers’ ability to manage risk -- if these instruments are used correctly. Conversely, these instruments may actually increase risk exposure if used incorrectly. Gone are the days when growers had access only to individual yield insurance and national triggered price programs. In 1996, revenue insurance became available for many crop growers. For most major crops, the acreage covered by revenue insurance now far exceeds that covered by yield insurance. The 2008 farm bill created the complex risk policies of ACRE and SURE (Ubilava et al.). Mitchell et al. argue that ACRE, which subsumed multiple revenue risks and integrated with other risk instruments, was difficult for growers to understand and difficult for county USDA officials to implement. Current farm bill proposals are now focused on various shallow loss programs such as Agricultural Risk Coverage (ARC), Stacked Income Protection Plan (STAX) and Supplemental Coverage Option (SCO) which layer risk protection on top of crop insurance. Thus, producers are likely to continue to be confronted with complex risk management tools which may overlap or leave gaps in risk protection. Further, the decision becomes even more complex when one considers the possibility of also using futures or forward contracts.

Suggested Citation

  • Coble, Keith H. & Barnett, Barry J. & Riley, John Michael, 2013. "Challenging Belief in the Law of Small Numbers," 2013 AAEA: Crop Insurance and the Farm Bill Symposium 156958, Agricultural and Applied Economics Association.
  • Handle: RePEc:ags:aaeaci:156958
    DOI: 10.22004/ag.econ.156958
    as

    Download full text from publisher

    File URL: https://ageconsearch.umn.edu/record/156958/files/CobleEtAl2013.pdf
    Download Restriction: no

    File URL: https://libkey.io/10.22004/ag.econ.156958?utm_source=ideas
    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
    ---><---

    References listed on IDEAS

    as
    1. Mitchell, Paul D. & Rejesus, Roderick M. & Coble, Keith H. & Knight, Thomas O., 2011. "Analyzing Farmer Participation Intentions and Enrollment Rates for the Average Crop Revenue Election (ACRE) Program," Staff Paper Series 560, University of Wisconsin, Agricultural and Applied Economics.
    2. Shapira, Zur & Venezia, Itzhak, 2008. "On the preference for full-coverage policies: Why do people buy too much insurance?," Journal of Economic Psychology, Elsevier, vol. 29(5), pages 747-761, November.
    3. Keith H. Coble & Barry J. Barnett, 2013. "Why Do We Subsidize Crop Insurance?," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 95(2), pages 498-504.
    4. Galarza, Francisco B. & Carter, Michael R., 2010. "Risk Preferences and Demand for Insurance in Peru: A Field Experiment," 2010 Annual Meeting, July 25-27, 2010, Denver, Colorado 61871, Agricultural and Applied Economics Association.
    5. Paul D. Mitchell & Roderick M. Rejesus & Keith H. Coble & Thomas O. Knight, 2012. "Analyzing Farmer Participation Intentions and County Enrollment Rates for the Average Crop Revenue Election Program," Applied Economic Perspectives and Policy, Agricultural and Applied Economics Association, vol. 34(4), pages 615-636.
    6. Anderson, John D. & Harri, Ardian & Coble, Keith H., 2009. "Techniques for Multivariate Simulation from Mixed Marginal Distributions with Application to Whole-Farm Revenue Simulation," Journal of Agricultural and Resource Economics, Western Agricultural Economics Association, vol. 34(1), pages 1-15, April.
    7. Ubilava, David & Barnett, Barry J. & Coble, Keith H. & Harri, Ardian, 2011. "The SURE Program and Its Interaction with Other Federal Farm Programs," Journal of Agricultural and Resource Economics, Western Agricultural Economics Association, vol. 36(3), pages 1-19.
    8. Matthew Rabin, 2002. "Inference by Believers in the Law of Small Numbers," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 117(3), pages 775-816.
    9. Peterson, Hikaru Hanawa & Tomek, William G., 2007. "Grain Marketing Strategies Within and Across Lifetimes," Journal of Agricultural and Resource Economics, Western Agricultural Economics Association, vol. 32(1), pages 1-20, April.
    Full references (including those not matched with items on IDEAS)

    Citations

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


    Cited by:

    1. Johan Swinnen & Alessandro Olper & Senne Vandevelde, 2021. "From unfair prices to unfair trading practices: Political economy, value chains and 21st century agri‐food policy," Agricultural Economics, International Association of Agricultural Economists, vol. 52(5), pages 771-788, September.
    2. Luckstead, Jeff & Devadoss, Stephen, 2016. "Implication of 2014 Farm Policies for Wheat Production," 2016 Annual Meeting, July 31-August 2, Boston, Massachusetts 235362, Agricultural and Applied Economics Association.
    3. Preston, Richard & Walters, Cory G., 2015. "Risk Management Properties of the 2014 Farm Bill," 2015 AAEA & WAEA Joint Annual Meeting, July 26-28, San Francisco, California 206435, Agricultural and Applied Economics Association.

    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. Wang, Yang & Barnett, Barry J. & Coble, Keith H. & Harri, Ardian, 2012. "Yield Aggregation Impacts on a “Deep Loss” Systemic Risk Protection Program," 2012 Annual Meeting, August 12-14, 2012, Seattle, Washington 124875, Agricultural and Applied Economics Association.
    2. Barnett, Barry J., 2014. "The Last Farm Bill?," Journal of Agricultural and Applied Economics, Southern Agricultural Economics Association, vol. 46(3), pages 1-9, August.
    3. David M. Ritzwoller & Joseph P. Romano, 2019. "Uncertainty in the Hot Hand Fallacy: Detecting Streaky Alternatives to Random Bernoulli Sequences," Papers 1908.01406, arXiv.org, revised Apr 2021.
    4. , G. & , & ,, 2008. "Non-Bayesian updating: A theoretical framework," Theoretical Economics, Econometric Society, vol. 3(2), June.
    5. Miao, Ruiqing & Hennessy, David A. & Feng, Hongli, 2016. "The Effects of Crop Insurance Subsidies and Sodsaver on Land-Use Change," Journal of Agricultural and Resource Economics, Western Agricultural Economics Association, vol. 41(2), May.
    6. 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.
    7. Mohrschladt, Hannes, 2021. "The ordering of historical returns and the cross-section of subsequent returns," Journal of Banking & Finance, Elsevier, vol. 125(C).
    8. Dohmen, Thomas & Falk, Armin & Huffman, David & Marklein, Felix & Sunde, Uwe, 2009. "Biased probability judgment: Evidence of incidence and relationship to economic outcomes from a representative sample," Journal of Economic Behavior & Organization, Elsevier, vol. 72(3), pages 903-915, December.
    9. Rachel Croson & James Sundali, 2005. "The Gambler’s Fallacy and the Hot Hand: Empirical Data from Casinos," Journal of Risk and Uncertainty, Springer, vol. 30(3), pages 195-209, May.
    10. Sigrid Suetens & Claus B. Galbo-Jørgensen & Jean-Robert Tyran, 2016. "Predicting Lotto Numbers: A Natural Experiment on the Gambler's Fallacy and the Hot-Hand Fallacy," Journal of the European Economic Association, European Economic Association, vol. 14(3), pages 584-607.
    11. Stefano DellaVigna, 2009. "Psychology and Economics: Evidence from the Field," Journal of Economic Literature, American Economic Association, vol. 47(2), pages 315-372, June.
    12. Catia Batista & Janis Umblijs, 2016. "Do migrants send remittances as a way of self-insurance?," Oxford Economic Papers, Oxford University Press, vol. 68(1), pages 108-130.
    13. Evan M. Calford & Anujit Charkraborty, 2022. "The Value of and Demand for Diverse News Sources," ANU Working Papers in Economics and Econometrics 2022-688, Australian National University, College of Business and Economics, School of Economics.
    14. Wu, Chen-Hui & Wu, Chin-Shun & Liu, Victor W., 2009. "The conservatism bias in an emerging stock market: Evidence from Taiwan," Pacific-Basin Finance Journal, Elsevier, vol. 17(4), pages 494-505, September.
    15. Ayako Matsuda & Takashi Kurosaki, 2017. "Temperature and Rainfall Index Insurance in India," OSIPP Discussion Paper 17E002, Osaka School of International Public Policy, Osaka University.
    16. Corgnet, Brice & DeSantis, Mark & Porter, David, 2020. "The distribution of information and the price efficiency of markets," Journal of Economic Dynamics and Control, Elsevier, vol. 110(C).
    17. Stöckl, Thomas & Huber, Jürgen & Kirchler, Michael & Lindner, Florian, 2015. "Hot hand and gambler's fallacy in teams: Evidence from investment experiments," Journal of Economic Behavior & Organization, Elsevier, vol. 117(C), pages 327-339.
    18. Lex Borghans & Bas ter Weel, 2008. "Understanding the Technology of Computer Technology Diffusion: Explaining Computer Adoption Patterns and Implications for the Wage Structure," Journal of Income Distribution, Ad libros publications inc., vol. 17(3-4), pages 37-70, September.
    19. Tiziana Assenza & Te Bao & Cars Hommes & Domenico Massaro, 2014. "Experiments on Expectations in Macroeconomics and Finance," Research in Experimental Economics, in: Experiments in Macroeconomics, volume 17, pages 11-70, Emerald Group Publishing Limited.
    20. Emara, Noha & Owens, David & Smith, John & Wilmer, Lisa, 2017. "Serial correlation in National Football League play calling and its effects on outcomes," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 69(C), pages 125-132.

    More about this item

    Keywords

    Agricultural and Food Policy; Risk and Uncertainty;

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    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:aaeaci:156958. 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: https://edirc.repec.org/data/aaeaaea.html .

    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.