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


Blavatskyy, Pavlo R; Pogrebna, Ganna (2007). Models of Stochastic Choice and Decision Theories: Why Both are Important for Analyzing Decisions. Working paper series / Institute for Empirical Research in Economics No. 319, University of Zurich.

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 samenmodel of stochastic choice. An alternative way is to vary models of stochastic choicencombining 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 modelsnof stochastic choice. We select a menu of seven popular decision theories and embedneach theory in five models of stochastic choice including tremble, Fechner and randomnutility model. We find that the estimated parameters of decision theories differnsignificantly 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).

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 samenmodel of stochastic choice. An alternative way is to vary models of stochastic choicencombining 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 modelsnof stochastic choice. We select a menu of seven popular decision theories and embedneach theory in five models of stochastic choice including tremble, Fechner and randomnutility model. We find that the estimated parameters of decision theories differnsignificantly 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).

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Additional indexing

Item Type:Working Paper
Communities & Collections:03 Faculty of Economics > Department of Economics
Working Paper Series > Institute for Empirical Research in Economics (former)
Dewey Decimal Classification:330 Economics
Language:English
Date:April 2007
Deposited On:29 Nov 2011 22:47
Last Modified:12 Aug 2017 13:03
Series Name:Working paper series / Institute for Empirical Research in Economics
ISSN:1424-0459
Official URL:http://www.econ.uzh.ch/wp.html

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