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Assessing farmers’ risk preferences and their determinants in a marginal upland area of Vietnam: a comparison of multiple elicitation techniques

Authors

  • Thea Nielsen,

    Corresponding author
    • Department of Agricultural Economics and Social Sciences in the Tropics and Subtropics (490a), University of Hohenheim, D-70593 Stuttgart, Germany
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  • Alwin Keil,

    1. Department of Agricultural Economics and Social Sciences in the Tropics and Subtropics (490a), University of Hohenheim, D-70593 Stuttgart, Germany
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  • Manfred Zeller

    1. Department of Agricultural Economics and Social Sciences in the Tropics and Subtropics (490a), University of Hohenheim, D-70593 Stuttgart, Germany
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Corresponding author. Tel.: +49-711-459-23771; fax: +49-711-459-23934. E-mail address: thea.nielsen@uni-hohenheim.de (T. Nielsen).

Abstract

We examine the consistency of risk preference measures based on eight hypothetical elicitation methods and a lottery game applied to smallholder farmers in a marginal upland environment in Vietnam. Using these measures, we identify influencing factors of risk aversion via regression analysis, whereby unlike previous studies, we include several proxies of social capital such as social networks and norms. Data were collected from household heads and spouses separately in a random sample of 300 households. Although correlations between most of the various risk preference measures are all statistically highly significant, most are weak. On average, respondents have a high degree of risk aversion and specific characteristics—gender, age, idiosyncratic shocks, education, social norms, network-reliance with extended family, and connections to local authorities—are significant determinants of risk preferences across most elicitation methods, whereas others—the household's dependency ratio, wealth, and covariate shocks—are significant in a few methods only. The explanatory power of the models is limited, indicating that other factors are likely to be of greater importance in determining risk preferences. The results can help target safety nets, encourage investments, and lead to the development of more applicable methods for assessing risk preferences of smallholders in developing countries.

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