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Martine Beijing October 2008
 

Martine Beijing October 2008

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    Martine Beijing October 2008 Martine Beijing October 2008 Presentation Transcript

    • Risk Aversion: Experimental Evidence from South African Fishing Communities
      • Kerri Brick, Justine Burns and Martine Visser*
      • *Environmental Policy Research Unit, University of Cape Town
    • Objectives and relevance
      • Estimate the risk attitudes of a large sample of individuals from nine rural fishing communities along the west coast of South Africa
      • ML estimation allows us to consider the effects of observable demographic characteristics in the estimation model
      • Relate derived risk attitudes to subjects’ admitted risk attitudes, inclination to poach and overfish and attitudes to fishing rights such as quotas or permits
      • Analyse the dynamic between the allocation of fishing rights, propensity to overfish or poach and risk preferences; this is relevant given that since 2005 certain fishing rights are allocated for periods of up to 15 years
      • Analyse the implication of granting long term fishing rights to females given their risk profile (assume a priori that females are more risk averse than males as per forthcoming slides)
    • Elicitation procedure
      • Employ a multiple price list (MPL) experimental measure for risk aversion
      • Each subject was presented with eight pairs of lotteries (lottery A and lottery B)
      • For each pair, respondents had to choose lottery A or lottery B
      • Subjects also completed a detailed questionnaire that elicited information on their socio-economic background, employment activities, fishing experience and also included a range of attitudinal questions
    • Sample description
      • 569 individuals, of whom 337 have consistent preferences (a unique switch point)
      • Of the whole sample:
        • Just over 60% were male
        • On average, participants were 41 years old and had lived in their respective communities for most of their lives
        • Majority reported Afrikaans as their home language
        • Educational attainments were low, with 14% of the sample having completed their primary schooling, 8% having completed high school and 6% having some form of tertiary qualification
        • 66% of participants classified themselves as Coloured, while the remaining majority classified themselves as Black or “Other”
        • 48% were employed at the time of the survey: of those employed, just over 50% reported fishing activities to be their primary source of income
        • Mean wage income for employed individuals (after tax) was R920 per month
        • Mean monthly household per capita income for the entire sample was R330.48 compared with mean monthly household per capita expenditures of R379.93
      • Source: Visser, M., and J. Burns (2007): “Bridging the Great Divide in South Africa: Inequality and Punishment in the Provision of Public Goods,” in Fairness, Reciprocity and Inequality: Experimental Evidence from South Africa , PhD Dissertation 162, Department of Economics, School of Business, Economics and Law, Goteborg University.
    • Preliminary Risk Profiles
    • Preliminary Risk Profiles
    • Preliminary Risk Profiles * All respondents: not only those involved in the fishing industry
    • Preliminary Risk Profiles
    • Preliminary Risk Profiles Do you think that commercial and small-scale commercial quotas are allocated fairly?
    • Preliminary Risk Profiles
    • Estimating Risk Attitudes
      • Estimate a CRRA Utility Function using Maximum Likelihood
      • Dependent variable:
        • Subjects’ choices
      • Independent variables:
        • Age; Age squared
        • Gender
        • Education
        • Income per capita
        • Subject’s perceived financial status
        • Whether fishing is a primary source of household income; whether subject is involved in the fishing industry
        • Employment status
        • Whether the subject is a quota holder
        • Whether the subject is a permit holder
    • Estimating Risk Attitudes
      • Independent variables continued:
        • Number of times the subject has been charged or arrested for violating fishing regulations
        • Whether the subject thinks that commercial and small-scale commercial quotas are allocated fairly
        • Whether the subject thinks that officials who allocate the quotas are corrupt
        • Whether the subject belong to a social group such as a Fishers Association
    •