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Asset Integration and Attitudes to Risk: Theory and Evidence

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  • Steffen Andersen
  • James C. Cox
  • Glenn W. Harrison
  • Morten Lau
  • E. Elisabet Rutström
  • Vjollca Sadiraj

Abstract

Measures of risk attitudes derived from experiments are often questioned because they are based on small stakes bets and do not account for the extent to which the decision-maker integrates the prizes of the experimental tasks with personal wealth. We exploit the existence of detailed information on individual wealth of experimental subjects in Denmark, and directly estimate risk attitudes and the degree of asset integration consistent with observed behavior. The behavior of the adult Danes in our experiment is consistent with partial asset integration: they behave as if some fraction of personal wealth is combined with experimental prizes in a utility function, and that this combination entails less than perfect substitution. Our subjects do not perfectly asset integrate. The implied risk attitudes from estimating these specifications imply risk premia and certainty equivalents that are a priori plausible under expected utility theory or rank dependent utility models. These are reassuring and constructive solutions to payoff calibration paradoxes. In addition, the rigorous, structural modeling of partial asset integration points to a rich array of neglected questions in risk management and policy evaluation in important field settings.

Suggested Citation

  • Steffen Andersen & James C. Cox & Glenn W. Harrison & Morten Lau & E. Elisabet Rutström & Vjollca Sadiraj, 2012. "Asset Integration and Attitudes to Risk: Theory and Evidence," Experimental Economics Center Working Paper Series 2012-12, Experimental Economics Center, Andrew Young School of Policy Studies, Georgia State University, revised Oct 2017.
  • Handle: RePEc:exc:wpaper:2012-12
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    2. Lionel Page & David Savage & Benno Torgler, 2012. "Variation in Risk Seeking Behavior in a Natural Experiment on Large Losses Induced by a Natural Disaster," NCER Working Paper Series 83, National Centre for Econometric Research, revised 09 Jul 2012.
    3. Fafchamps, Marcel & Kebede, Bereket & Zizzo, Daniel John, 2015. "Keep up with the winners: Experimental evidence on risk taking, asset integration, and peer effects," European Economic Review, Elsevier, vol. 79(C), pages 59-79.
    4. Andersen, Steffen & Harrison, Glenn W. & Lau, Morten I. & Rutström, E. Elisabet, 2014. "Discounting behavior: A reconsideration," European Economic Review, Elsevier, vol. 71(C), pages 15-33.
    5. Page, Lionel & Savage, David A. & Torgler, Benno, 2014. "Variation in risk seeking behaviour following large losses: A natural experiment," European Economic Review, Elsevier, vol. 71(C), pages 121-131.
    6. Falco, Paolo, 2014. "Does risk matter for occupational choices? Experimental evidence from an African labour market," Labour Economics, Elsevier, vol. 28(C), pages 96-109.
    7. Page, Lionel & Savage, David A. & Torgler, Benno, 2014. "Variation in risk seeking behaviour following large losses: A natural experiment," European Economic Review, Elsevier, vol. 71(C), pages 121-131.
    8. Nejat Anbarci & Nick Feltovich, 2013. "How responsive are people to changes in their bargaining position? Earned bargaining power and the 50–50 norm," EcoMod2013 5855, EcoMod.
    9. Falco, Paolo, 2014. "Does risk matter for occupational choices? Experimental evidence from an African labour market," Labour Economics, Elsevier, vol. 28(C), pages 96-109.

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    More about this item

    JEL classification:

    • D01 - Microeconomics - - General - - - Microeconomic Behavior: Underlying Principles
    • D81 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Criteria for Decision-Making under Risk and Uncertainty
    • C91 - Mathematical and Quantitative Methods - - Design of Experiments - - - Laboratory, Individual Behavior
    • C93 - Mathematical and Quantitative Methods - - Design of Experiments - - - Field Experiments
    • C55 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Large Data Sets: Modeling and Analysis
    • C81 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Methodology for Collecting, Estimating, and Organizing Microeconomic Data; Data Access

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