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Models of Stochastic Choice and Decision Theories: Why Both are Important for Analyzing Decisions

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  • Pavlo Blavatskyy
  • Ganna Pogrebna

Abstract

Economic research offers two traditional ways of analyzing decision making under risk. One option is to compare the goodness of fit of different decision theories using the same model of stochastic choice. An alternative way is to vary models of stochastic choice combining them with only one or two decision theories. This paper proposes to look at the bigger picture by comparing different combinations of decision theories and models of stochastic choice. We select a menu of seven popular decision theories and embed each theory in five models of stochastic choice including tremble, Fechner and random utility model. We find that the estimated parameters of decision theories differ significantly when theories are combined with different models. Depending on the selected model of stochastic choice we obtain different ranking of decision theories with regard to their goodness of fit to the data. The fit of all analyzed decision theories improves significantly when they are embedded in a Fechner model of heteroscedastic truncated errors (or random utility model in a dynamic decision problem).

Suggested Citation

  • Pavlo Blavatskyy & Ganna Pogrebna, 2007. "Models of Stochastic Choice and Decision Theories: Why Both are Important for Analyzing Decisions," IEW - Working Papers 319, Institute for Empirical Research in Economics - University of Zurich.
  • Handle: RePEc:zur:iewwpx:319
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    Keywords

    Fechner model; random utility; tremble; expected utility theory; risk;

    JEL classification:

    • C93 - Mathematical and Quantitative Methods - - Design of Experiments - - - Field Experiments
    • D81 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Criteria for Decision-Making under Risk and Uncertainty

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