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Risk, Agricultural Production, and Weather Index Insurance in Village South Asia

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  • Michler, Jeffrey D.
  • Viens, Frederi G.
  • Shively, Gerald E.

Abstract

We investigate the sources of variance in crop output and measure their relative importance in the context of weather index insurance for smallholder farmers. We use parcel-level panel data from South Asia and a multilevel modeling approach to isolate the different sources of variance. We then measure how large a role weather plays in explaining variance in yields. Using Bayesian methods, we draw the underlying distribution of the random error term responsible for weather uncertainty, which is highly skewed and non-normal. We find that variance in weather accounts for a small but important fraction of total variance in crop output. We also derive pricing and payout schedules for actuarially fair weather index insurance. Our results shed light on the low uptake rates of index insurance in South Asia and provide direction for designing index insurance with less basis risk for farmers.

Suggested Citation

  • Michler, Jeffrey D. & Viens, Frederi G. & Shively, Gerald E., 2015. "Risk, Agricultural Production, and Weather Index Insurance in Village South Asia," 2015 AAEA & WAEA Joint Annual Meeting, July 26-28, San Francisco, California 205297, Agricultural and Applied Economics Association.
  • Handle: RePEc:ags:aaea15:205297
    DOI: 10.22004/ag.econ.205297
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    Cited by:

    1. Michler, Jeffrey & Shively, Gerald, 2016. "Agricultural Production, Weather Variability, and Technical Change: 40 Years of Evidence from Indi," 2016 Annual Meeting, July 31-August 2, Boston, Massachusetts 236342, Agricultural and Applied Economics Association.
    2. Ward, Patrick S. & Makhija, Simrin, 2018. "New modalities for managing drought risk in rainfed agriculture: Evidence from a discrete choice experiment in Odisha, India," World Development, Elsevier, vol. 107(C), pages 163-175.
    3. Mekonnen, Dawit & Hira, Channa & Claudia, Ringler, "undated". "Where to invest in the Indus Basin Irrigation System in Pakistan to improve land and water productivity? Insights from a hierarchical model," 2016 Annual Meeting, July 31-August 2, Boston, Massachusetts 235977, Agricultural and Applied Economics Association.
    4. Han Wang & Sieglinde S Snapp & Monica Fisher & Frederi Viens, 2019. "A Bayesian analysis of longitudinal farm surveys in Central Malawi reveals yield determinants and site-specific management strategies," PLOS ONE, Public Library of Science, vol. 14(8), pages 1-17, August.

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    More about this item

    Keywords

    Environmental Economics and Policy; Food Security and Poverty; International Development; Production Economics; Research Methods/ Statistical Methods; Risk and Uncertainty;
    All these keywords.

    JEL classification:

    • C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
    • D81 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Criteria for Decision-Making under Risk and Uncertainty
    • G22 - Financial Economics - - Financial Institutions and Services - - - Insurance; Insurance Companies; Actuarial Studies
    • O12 - Economic Development, Innovation, Technological Change, and Growth - - Economic Development - - - Microeconomic Analyses of Economic Development
    • O13 - Economic Development, Innovation, Technological Change, and Growth - - Economic Development - - - Agriculture; Natural Resources; Environment; Other Primary Products
    • Q16 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Agriculture - - - R&D; Agricultural Technology; Biofuels; Agricultural Extension Services
    • Q12 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Agriculture - - - Micro Analysis of Farm Firms, Farm Households, and Farm Input Markets

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