Warm-glow versus cold-prickle: the effect of positive and negative framing on cooperation in experiments
AbstractExperiments on privately provided public goods generally find that subjects are far more cooperative than predicted, while experiments on oligopolies and the commons almost always obtain the Nash-equilibrium predictions, despite being very similar games. This paper examines whether this difference could be due to the fact that with public goods there is a positive externality, while with the others the externality is negative. The result of the experiments is that subjects are more willing to cooperate when the externality is positive, even though the potential outcomes are the same. This suggests a behavioral asymmetry between the warm-glow of doing something good and cold-prickle of doing something bad. Copyright 1995, the President and Fellows of Harvard College and the Massachusetts Institute of Technology.
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Date of creation: 01 Aug 1997
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Other versions of this item:
- Andreoni, James, 1995. "Warm-Glow versus Cold-Prickle: The Effects of Positive and Negative Framing on Cooperation in Experiments," The Quarterly Journal of Economics, MIT Press, vol. 110(1), pages 1-21, February.
- James Andreoni, 1994. "Warm-Glow versus Cold-Prickle: The Effects of Positive and Negative Framing on Cooperation in Experiments," Experimental 9410002, EconWPA.
- C9 - Mathematical and Quantitative Methods - - Design of Experiments
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- Andreoni, James, 1988. "Why free ride? : Strategies and learning in public goods experiments," Journal of Public Economics, Elsevier, vol. 37(3), pages 291-304, December.
- Walker, James M & Gardner, Roy, 1992. "Probabilistic Destruction of Common-Pool Resources: Experimental Evidence," Economic Journal, Royal Economic Society, vol. 102(414), pages 1149-61, September.
- Walker, James M. & Gardner, Roy & Ostrom, Elinor, 1990. "Rent dissipation in a limited-access common-pool resource: Experimental evidence," Journal of Environmental Economics and Management, Elsevier, vol. 19(3), pages 203-211, November.
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