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Using Stated Preferences and Beliefs to Identify the Impact of Risk on Poor Households

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  • Ruth Vargas Hill

Abstract

Whilst the importance of uncertainty in shaping economic behaviour of poor households is widely acknowledged, empirically identifying the impact of risk is difficult. By using data on risk preferences and perceptions of risk collected through hypothetical questions in combination with more traditional measures of a household's ability to deal with risk, this article identifies the impact of risk on production decisions. It shows both that data on stated preferences and beliefs can be usefully utilised to explain household behaviour, and that risk has a significant impact on the production decisions of poor households.

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  • Ruth Vargas Hill, 2009. "Using Stated Preferences and Beliefs to Identify the Impact of Risk on Poor Households," Journal of Development Studies, Taylor & Francis Journals, vol. 45(2), pages 151-171.
  • Handle: RePEc:taf:jdevst:v:45:y:2009:i:2:p:151-171 DOI: 10.1080/00220380802553065
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    Cited by:

    1. Ruth Vargas Hill & John Hoddinott & Neha Kumar, 2013. "Adoption of weather-index insurance: learning from willingness to pay among a panel of households in rural Ethiopia," Agricultural Economics, International Association of Agricultural Economists, vol. 44(4-5), pages 385-398, July.
    2. Nielsen, Thea & Zeller, Manfred, 2013. "The Impact of Shocks on Risk Preference Changes between Seasons for Smallholder Farmers in Vietnam," 53rd Annual Conference, Berlin, Germany, September 25-27, 2013 156101, German Association of Agricultural Economists (GEWISOLA).
    3. Sommarat Chantarat & Sirikarn Lertamphainont & Krislert Samphantharak, 2016. "Floods and Farmers: Evidence from the Field in Thailand," PIER Discussion Papers 40., Puey Ungphakorn Institute for Economic Research, revised Aug 2016.
    4. Delavande, Adeline & Giné, Xavier & McKenzie, David, 2011. "Measuring subjective expectations in developing countries: A critical review and new evidence," Journal of Development Economics, Elsevier, vol. 94(2), pages 151-163, March.
    5. Pan He & Marcella Veronesi & Stefanie Engel, 2016. "Consistency of Risk Preference Measures and the Role of Ambiguity: An Artefactual Field Experiment from China," Working Papers 03/2016, University of Verona, Department of Economics.
    6. Alfani, Federica & Dabalen, Andrew & Fisker, Peter & Molini, Vasco, 2015. "Vulnerability to malnutrition in the West African Sahel," Policy Research Working Paper Series 7171, The World Bank.
    7. Hill, Ruth Vargas & Robles, Miguel, 2011. "Flexible insurance for heterogeneous farmers: Results from a small-scale pilot in Ethiopia," IFPRI discussion papers 1092, International Food Policy Research Institute (IFPRI).
    8. de Brauw, Alan & Eozenou, Patrick, 2014. "Measuring risk attitudes among Mozambican farmers," Journal of Development Economics, Elsevier, vol. 111(C), pages 61-74.
    9. Bernd Hardeweg & Lukas Menkhoff & Hermann Waibel, 2013. "Experimentally Validated Survey Evidence on Individual Risk Attitudes in Rural Thailand," Economic Development and Cultural Change, University of Chicago Press, vol. 61(4), pages 859-888.
    10. Verschoor, Arjan & D’Exelle, Ben & Perez-Viana, Borja, 2016. "Lab and life: Does risky choice behaviour observed in experiments reflect that in the real world?," Journal of Economic Behavior & Organization, Elsevier, vol. 128(C), pages 134-148.
    11. Ward, Patrick S. & Singh, Vartika, 2013. "Risk and Ambiguity Preferences and the Adoption of New Agricultural Technologies: Evidence from Field Experiments in Rural India," 2013 Annual Meeting, August 4-6, 2013, Washington, D.C. 150794, Agricultural and Applied Economics Association.
    12. Ruth Hill & Angelino Viceisza, 2012. "A field experiment on the impact of weather shocks and insurance on risky investment," Experimental Economics, Springer;Economic Science Association, vol. 15(2), pages 341-371, June.
    13. Thiagu Ranganathan & Usha Ananthakumar, 2017. "Hedging in Presence of Crop Yield, Crop Revenue and Rainfall Insurance," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), vol. 15(1), pages 151-171, March.
    14. Moser, Stefan & Mußhoff, Oliver, 2015. "Comparing the use of risk-influencing production inputs and experimentally measured risk attitude: Do decisions of Indonesian small-scale rubber farmers match?," EFForTS Discussion Paper Series 14, University of Goettingen, Collaborative Research Centre 990 "EFForTS, Ecological and Socioeconomic Functions of Tropical Lowland Rainforest Transformation Systems (Sumatra, Indonesia)".
    15. Norton, Michael T. & Holthaus, Eric & Madajewicz, Malgosia & Osgood, Daniel E. & Peterson, Nicole & Gebremichael, Mengesha & Mullally, Conner & Teh, TseLing, 2011. "Investigating Demand for Weather Index Insurance: Experimental Evidence from Ethiopia," 2011 Annual Meeting, July 24-26, 2011, Pittsburgh, Pennsylvania 104022, Agricultural and Applied Economics Association.
    16. Hill, Ruth Vargas & Viceisza, Angelino, 2010. "An experiment on the impact of weather shocks and insurance on risky investment," IFPRI discussion papers 974, International Food Policy Research Institute (IFPRI).
    17. Holden , Stein T. & Quiggin, John, 2015. "Climate risk and state-contingent technology adoption: The role of risk preferences and probability weighting," Working Paper Series 15-2015, Norwegian University of Life Sciences, School of Economics and Business.
    18. Clarke, Danielle & Das, Narayan C. & de Nicola, Francesca & Hill, Ruth Vargas & Kumar, Neha & Mehta, Parendi, 2012. "The value of customized insurance for farmers in rural Bangladesh:," IFPRI discussion papers 1202, International Food Policy Research Institute (IFPRI).
    19. Hurley, Terrance M., 2010. "A review of agricultural production risk in the developing world," Working Papers 188476, HarvestChoice.
    20. repec:oup:erevae:v:44:y:2017:i:2:p:285-308. is not listed on IDEAS
    21. Ashour, Maha & Billings, Lucy & Gilligan, Daniel & Hoel, Jessica B. & Karachiwalla, Naureen, 2016. "Do beliefs about agricultural inputs counterfeiting correspond with actual rates of counterfeiting? Evidence from Uganda:," IFPRI discussion papers 1552, International Food Policy Research Institute (IFPRI).

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