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Designing Index-Based Livestock Insurance for Managing Asset Risk in Northern Kenya

Authors

  • Sommarat Chantarat,

    1. Sommarat Chantarat is at the Crawford School of Economics and Government, Australian National University. Andrew G. Mude is at International Livestock Research Institute, Nairobi, Kenya. Christopher B. Barrett is at Charles H. Dyson School of Applied Economics and Management, Cornell University. Michael R. Carter is at Department of Agricultural and Resource Economics, University of California-Davis. The authors can be contacted via e-mail: Sommarat.Chantarat@anu.edu.au, a.mude@cgiar.org, cbb2@cornell.edu, and mrcarter@ucdavis.edu, respectively. This research was funded through a USAID Norman E. Borlaug Leadership Enhancement in Agriculture Program Doctoral Dissertation Improvement Grant, the World Bank Commodity Risk Management Program, the Global Livestock Collaborative Research Support Program, funded by the Office of Agriculture and Food Security, Global Bureau, USAID, under grant number DAN-1328-G-00--0046-00, the Assets and Market Access Collaborative Research Support Program, and the Graduate School of Cornell University. We thank Munenobu Ikegarmi, David Levine, John McPeak, Sharon Tennyson, Calum Turvey, seminar participants at Cornell University and the International Livestock Research Institute, Nairobi, Kenya, and two anonymous reviewers for their helpful comments. The opinions expressed do not necessarily reflect the views of U.S. Agency for International Development. Any remaining errors are the authors' sole responsibility.
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  • Andrew G. Mude,

    1. Sommarat Chantarat is at the Crawford School of Economics and Government, Australian National University. Andrew G. Mude is at International Livestock Research Institute, Nairobi, Kenya. Christopher B. Barrett is at Charles H. Dyson School of Applied Economics and Management, Cornell University. Michael R. Carter is at Department of Agricultural and Resource Economics, University of California-Davis. The authors can be contacted via e-mail: Sommarat.Chantarat@anu.edu.au, a.mude@cgiar.org, cbb2@cornell.edu, and mrcarter@ucdavis.edu, respectively. This research was funded through a USAID Norman E. Borlaug Leadership Enhancement in Agriculture Program Doctoral Dissertation Improvement Grant, the World Bank Commodity Risk Management Program, the Global Livestock Collaborative Research Support Program, funded by the Office of Agriculture and Food Security, Global Bureau, USAID, under grant number DAN-1328-G-00--0046-00, the Assets and Market Access Collaborative Research Support Program, and the Graduate School of Cornell University. We thank Munenobu Ikegarmi, David Levine, John McPeak, Sharon Tennyson, Calum Turvey, seminar participants at Cornell University and the International Livestock Research Institute, Nairobi, Kenya, and two anonymous reviewers for their helpful comments. The opinions expressed do not necessarily reflect the views of U.S. Agency for International Development. Any remaining errors are the authors' sole responsibility.
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  • Christopher B. Barrett,

    1. Sommarat Chantarat is at the Crawford School of Economics and Government, Australian National University. Andrew G. Mude is at International Livestock Research Institute, Nairobi, Kenya. Christopher B. Barrett is at Charles H. Dyson School of Applied Economics and Management, Cornell University. Michael R. Carter is at Department of Agricultural and Resource Economics, University of California-Davis. The authors can be contacted via e-mail: Sommarat.Chantarat@anu.edu.au, a.mude@cgiar.org, cbb2@cornell.edu, and mrcarter@ucdavis.edu, respectively. This research was funded through a USAID Norman E. Borlaug Leadership Enhancement in Agriculture Program Doctoral Dissertation Improvement Grant, the World Bank Commodity Risk Management Program, the Global Livestock Collaborative Research Support Program, funded by the Office of Agriculture and Food Security, Global Bureau, USAID, under grant number DAN-1328-G-00--0046-00, the Assets and Market Access Collaborative Research Support Program, and the Graduate School of Cornell University. We thank Munenobu Ikegarmi, David Levine, John McPeak, Sharon Tennyson, Calum Turvey, seminar participants at Cornell University and the International Livestock Research Institute, Nairobi, Kenya, and two anonymous reviewers for their helpful comments. The opinions expressed do not necessarily reflect the views of U.S. Agency for International Development. Any remaining errors are the authors' sole responsibility.
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  • Michael R. Carter

    1. Sommarat Chantarat is at the Crawford School of Economics and Government, Australian National University. Andrew G. Mude is at International Livestock Research Institute, Nairobi, Kenya. Christopher B. Barrett is at Charles H. Dyson School of Applied Economics and Management, Cornell University. Michael R. Carter is at Department of Agricultural and Resource Economics, University of California-Davis. The authors can be contacted via e-mail: Sommarat.Chantarat@anu.edu.au, a.mude@cgiar.org, cbb2@cornell.edu, and mrcarter@ucdavis.edu, respectively. This research was funded through a USAID Norman E. Borlaug Leadership Enhancement in Agriculture Program Doctoral Dissertation Improvement Grant, the World Bank Commodity Risk Management Program, the Global Livestock Collaborative Research Support Program, funded by the Office of Agriculture and Food Security, Global Bureau, USAID, under grant number DAN-1328-G-00--0046-00, the Assets and Market Access Collaborative Research Support Program, and the Graduate School of Cornell University. We thank Munenobu Ikegarmi, David Levine, John McPeak, Sharon Tennyson, Calum Turvey, seminar participants at Cornell University and the International Livestock Research Institute, Nairobi, Kenya, and two anonymous reviewers for their helpful comments. The opinions expressed do not necessarily reflect the views of U.S. Agency for International Development. Any remaining errors are the authors' sole responsibility.
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Abstract

This article describes a novel index-based livestock insurance (IBLI) product piloted among pastoralists in Northern Kenya, where insurance markets are effectively absent and uninsured risk exposure is a main cause of poverty. We describe the methodology used to design the contract and its underlying index of predicted area-average livestock mortality, established statistically using longitudinal observations of household-level herd mortality fit to remotely sensed vegetation data. Household-level performance analysis based on simulations finds that IBLI removes 25–40 percent of total livestock mortality risk. We describe the contract pricing and the risk exposures of the underwriter to establish IBLI's reinsurability on international markets.

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