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Demand for weather hedges in India: An empirical exploration of theoretical predictions:

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  • Hill, Ruth Vargas
  • Robles, Miguel
  • Ceballos, Francisco

Abstract

This paper analyzes the demand for rainfall-based weather hedges among farmers in rural India. We explore the predictions of a standard expected utility theory framework on the nature of demand for such products, in particular testing whether demand behaves as predicted with respect to price, the basis of the hedge, and risk aversion using data from a randomized control trial in which price and basis risk was varied for a series of hedging products offered to farmers. We find that demand behaves as predicted, with demand falling with price and basis risk, and appearing hump-shaped in risk aversion. Second, we analyze understanding of and demand for hedging products over time, examining the impact of increased investments in training on hedging products as well as evidence for learning by doing among farmers. We find evidence that suggests that learning by doing is more effective at increasing both understanding and demand.

Suggested Citation

  • Hill, Ruth Vargas & Robles, Miguel & Ceballos, Francisco, 2013. "Demand for weather hedges in India: An empirical exploration of theoretical predictions:," IFPRI discussion papers 1280, International Food Policy Research Institute (IFPRI).
    • Handle: RePEc:fpr:ifprid:1280
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    References listed on IDEAS

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    1. Shawn Cole & Xavier Gine & Jeremy Tobacman & Petia Topalova & Robert Townsend & James Vickery, 2013. "Barriers to Household Risk Management: Evidence from India," American Economic Journal: Applied Economics, American Economic Association, vol. 5(1), pages 104-135, January.
    2. Smith, Richard J & Blundell, Richard W, 1986. "An Exogeneity Test for a Simultaneous Equation Tobit Model with an Application to Labor Supply," Econometrica, Econometric Society, vol. 54(3), pages 679-685, May.
    3. Mobarak, A. Mushfiq & Rosenzweig, Mark, 2012. "Selling Formal Insurance to the Informally Insured," Working Papers 97, Yale University, Department of Economics.
    4. S. Viswanathan & Adriano Rampini, 2013. "Household risk management," 2013 Meeting Papers 647, Society for Economic Dynamics.
    5. Clarke,Daniel Jonathan & Mahul,Olivier & Rao,Kolli Nageswara & Verma,Niraj, 2012. "Weather based crop insurance in India," Policy Research Working Paper Series 5985, The World Bank.
    6. Shawn Cole & Xavier Gine & Jeremy Tobacman & Petia Topalova & Robert Townsend & James Vickery, 2013. "Barriers to Household Risk Management: Evidence from India," American Economic Journal: Applied Economics, American Economic Association, vol. 5(1), pages 104-135, January.
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    Citations

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    Cited by:

    1. Petraud, Jean & Boucher, Stephen & Carter, Michael, 2015. "Competing theories of risk preferences and the demand for crop insurance: Experimental evidence from Peru," 2015 Conference, August 9-14, 2015, Milan, Italy 211383, International Association of Agricultural Economists.
    2. Ceballos, Francisco, 2016. "Estimating spatial basis risk in rainfall index insurance: Methodology and application to excess rainfall insurance in Uruguay," IFPRI discussion papers 1595, International Food Policy Research Institute (IFPRI).
    3. 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.
    4. Ceballos, Francisco & Robles, Miguel, 2014. "Insurance opportunities against weather risks for the rural poor:," IFPRI book chapters, in: Fan, Shenggen & Pandya-Lorch, Rajul & Yosef, Sivan (ed.),2013 Global Food Policy Report, chapter 10, International Food Policy Research Institute (IFPRI).
    5. Jensen, Nathaniel & Stoeffler, Quentin & Fava, Francesco & Vrieling, Anton & Atzberger, Clement & Meroni, Michele & Mude, Andrew & Carter, Michael, 2019. "Does the design matter? Comparing satellite-based indices for insuring pastoralists against drought," Ecological Economics, Elsevier, vol. 162(C), pages 59-73.
    6. Shawn Cole & Daniel Stein & Jeremy Tobacman, 2014. "Dynamics of Demand for Index Insurance: Evidence from a Long-Run Field Experiment," American Economic Review, American Economic Association, vol. 104(5), pages 284-290, May.
    7. Liu, Yanyan & Chen, Kevin Z. & Hill, Ruth Vargas & Xiao, Chengwei, 2013. "Borrowing from the insurer: An empirical analysis of demand and impact of insurance in China:," IFPRI discussion papers 1306, International Food Policy Research Institute (IFPRI).
    8. Delavallade, Clara & Dizon, Felipe & Hill, Ruth Vargas & Petraud, Jean Paul, 2015. "Managing risk with insurance and savings: Experimental evidence for male and female farm managers in West Africa:," IFPRI discussion papers 1426, International Food Policy Research Institute (IFPRI).
    9. Nathaniel Jensen & Christopher Barrett, 2017. "Agricultural Index Insurance for Development," Applied Economic Perspectives and Policy, Agricultural and Applied Economics Association, vol. 39(2), pages 199-219.
    10. Jensen, Nathaniel D. & Mude, Andrew G. & Barrett, Christopher B., 2018. "How basis risk and spatiotemporal adverse selection influence demand for index insurance: Evidence from northern Kenya," Food Policy, Elsevier, vol. 74(C), pages 172-198.
    11. 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.

    More about this item

    Keywords

    index insurance; Economic theory; expected utility; weather index insurance; Risk; randomized experiment;

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