Strategies in dynamic decision making - An experimental investigation of the rationality of decision behaviour
This paper is concerned with the question of how people tackle dynamic decision problems. It is on the interface between economics and psychology. Economic theory has a well-defined theory of how people should tackle such problems, but experimental evidence suggests that these are not empirically valid, and particularly that people find dynamic decision problems complex and cognitively demanding. Psychologists have long been aware of such issues and have developed a suite of theories to explain behaviour in such contexts, but these have been largely developed in a static context. This paper attempts to build a bridge between the two disciplines by exploring decision processes in a dynamic problem for which economic theory provides clear predictions. To aid us in this quest we use an experimental design which enables us to infer the decision rules that people are using. We identify a number of distinct decision heuristics, which could usefully be embodied into economic models of dynamic decision making.
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- Johnson, Eric J. & Camerer, Colin & Sen, Sankar & Rymon, Talia, 2002. "Detecting Failures of Backward Induction: Monitoring Information Search in Sequential Bargaining," Journal of Economic Theory, Elsevier, vol. 104(1), pages 16-47, May.
- Müller, Wieland, 1999.
"Strategies, heuristics and the relevance of risk aversion in a dynamic decision problem,"
SFB 373 Discussion Papers
1999,61, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.
- Muller, Wieland, 2001. "Strategies, heuristics, and the relevance of risk-aversion in a dynamic decision problem," Journal of Economic Psychology, Elsevier, vol. 22(4), pages 493-522, August.
- Bettman, James R. & Johnson, Eric J. & Payne, John W., 1990. "A componential analysis of cognitive effort in choice," Organizational Behavior and Human Decision Processes, Elsevier, vol. 45(1), pages 111-139, February.
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