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Government Insurance Program Design, Incentive Effects, and Technology Adoption: The Case of Skip-Row Crop Insurance

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  • Joshua D. Woodard
  • Alexander D. Pavlista
  • Gary D. Schnitkey
  • Paul A. Burgener
  • Kimberley A. Ward

Abstract

Can the availability of poorly-designed government insurance alter technology adoption decisions? A theoretical model of technology adoption and insurance incentive effects for a high- and low-risk technology is developed and explored empirically using a unique dataset of skip-row agronomic trial data. A multivariate nonparametric resampling technique is developed, which augments the trial data with a larger dataset of conventional yields to improve estimation efficiency. Skip-row adoption is found to increase mean yields and reduce risk in areas prone to drought. RMA insurance rules have incentive-distorting impacts which disincentivize skip-row adoption. Copyright 2012, Oxford University Press.

Suggested Citation

  • Joshua D. Woodard & Alexander D. Pavlista & Gary D. Schnitkey & Paul A. Burgener & Kimberley A. Ward, 2012. "Government Insurance Program Design, Incentive Effects, and Technology Adoption: The Case of Skip-Row Crop Insurance," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 94(4), pages 823-837.
    • Handle: RePEc:oup:ajagec:v:94:y:2012:i:4:p:823-837
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    File URL: http://hdl.handle.net/10.1093/ajae/aas018
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    Cited by:

    1. Agnieszka Kurdyś-Kujawska & Agnieszka Sompolska-Rzechuła & Joanna Pawłowska-Tyszko & Michał Soliwoda, 2021. "Crop Insurance, Land Productivity and the Environment: A Way forward to a Better Understanding," Agriculture, MDPI, vol. 11(11), pages 1-17, November.
    2. Madhu Khanna, 2021. "Digital Transformation of the Agricultural Sector: Pathways, Drivers and Policy Implications," Applied Economic Perspectives and Policy, John Wiley & Sons, vol. 43(4), pages 1221-1242, December.
    3. Maas, Alexander S. & McIntosh, Christopher S. & Fuller, Kate B., 2022. "An Exploration of Preferences for Soil Health Practices in Potato Production," 2022 Annual Meeting, July 31-August 2, Anaheim, California 322072, Agricultural and Applied Economics Association.
    4. Liu, Y. & Ker, A., 2018. "Is There Too Much History in Historical Yield Data," 2018 Conference, July 28-August 2, 2018, Vancouver, British Columbia 277293, International Association of Agricultural Economists.
    5. Miao, Ruiqing, 2020. "Tradeoff between Short-Term and Long-Term Risk Management Tools: New Study Shows that Crop Insurance May Hinder Agricultural Innovations in Drought-Tolerant Technologies," farmdoc daily, University of Illinois at Urbana-Champaign, Department of Agricultural and Consumer Economics, vol. 10(115), June.
    6. Joshua D. Woodard & Leslie J. Verteramo‐Chiu, 2017. "Efficiency Impacts of Utilizing Soil Data in the Pricing of the Federal Crop Insurance Program," American Journal of Agricultural Economics, John Wiley & Sons, vol. 99(3), pages 757-772, April.
    7. Peilu Zhang & Marco A. Palma, 2021. "Compulsory Versus Voluntary Insurance: An Online Experiment," American Journal of Agricultural Economics, John Wiley & Sons, vol. 103(1), pages 106-125, January.
    8. Porth, Lysa & Tan, Ken Seng & Zhu, Wenjun, 2016. "A Relational Model for Predicting Farm-Level Crop Yield Distributions in the Absence of Farm-Level Data," 2016 Annual Meeting, July 31-August 2, Boston, Massachusetts 236278, Agricultural and Applied Economics Association.
    9. Kemény, Gábor & Varga, Tibor & Fogarasi, József & Tóth, Kristóf, 2012. "The development of Hungarian agricultural insurance system," Problems of World Agriculture / Problemy Rolnictwa Światowego, Warsaw University of Life Sciences, vol. 12(27), pages 1-10, September.
    10. Jensen, Nathaniel D. & Barrett, Christopher B. & Mude, Andrew G., 2014. "Basis Risk and the Welfare Gains from Index Insurance: Evidence from Northern Kenya," MPRA Paper 59153, University Library of Munich, Germany.
    11. Sarah C. Sellars & Nathanael M. Thompson & Michael E. Wetzstein & Laura Bowling & Keith Cherkauer & Charlotte Lee & Jane Frankenberger & Ben Reinhart, 2022. "Does crop insurance inhibit climate change technology adoption?," Mitigation and Adaptation Strategies for Global Change, Springer, vol. 27(3), pages 1-20, March.
    12. Miao, Ruiqing & Khanna, Madhu, 2013. "Crop Insurance for Energy Grasses," 2013 AAEA: Crop Insurance and the Farm Bill Symposium 156936, Agricultural and Applied Economics Association.
    13. Dolginow, Joseph & Massey, Raymond E. & Myers, Brent & Kitchen, Newell, 2013. "Adjusting Crop Insurance APH Calculation to Accommodate Biomass Production," 2013 AAEA: Crop Insurance and the Farm Bill Symposium 156945, Agricultural and Applied Economics Association.
    14. Pu Liao & Xianhua Zhou & Qingquan Fan, 2020. "Does agricultural insurance help farmers escape the poverty trap? Research based on multiple equilibrium models," The Geneva Papers on Risk and Insurance - Issues and Practice, Palgrave Macmillan;The Geneva Association, vol. 45(1), pages 203-223, January.
    15. Shi-jie Jiang & Lilin Wang & Feiyun Xiang, 2023. "The Effect of Agriculture Insurance on Agricultural Carbon Emissions in China: The Mediation Role of Low-Carbon Technology Innovation," Sustainability, MDPI, vol. 15(5), pages 1-20, March.
    16. Prasenjit N. Ghosh & Ruiqing Miao & Emir Malikov, 2023. "Crop insurance premium subsidy and irrigation water withdrawals in the western United States," The Geneva Papers on Risk and Insurance - Issues and Practice, Palgrave Macmillan;The Geneva Association, vol. 48(4), pages 968-992, October.
    17. Joshua D. Woodard & Leslie Verteramo Chiu & Gabriel Power & Dmitry Vedenov & Steven Klose, 2017. "Factors Affecting Changes in Managerial Decisions," Agribusiness, John Wiley & Sons, Ltd., vol. 33(3), pages 443-465, June.

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