Violations of the betweenness axiom and nonlinearity in probability

Models of stochastic choice and decision theories: why both are important for analyzing decisions

“…Notice that when decision theories are embedded in a Fechner model of homoscedastic errors, the best fit to the data is provided by DAT. This confirms the finding of Camerer and Ho (1994) who reexamine the data from 11 laboratory studies and conclude that DAT provides "surprisingly good fit" when decision theories are estimated in a strong utility model, which is equivalent to our Fechner model of homoscedastic random errors.…”

“…Researchers, who use a Fechner model of homoscedastic errors (e.g. Hey and Orme, 1994;Camerer and Ho, 1994) would claim that the most accurate description of the data is given by DAT. Last but not least, researchers who use a Fechner model of heteroscedastic truncated errors would conclude that the best decision theory is either EUT with expo-power utility function or RDEU.…”

Eliciting Environmental Preferences of Ghanaians: An Experimental Approach

“…Note that, however strong, this assumption is supported by a wide empirical and theoretical literature. Using solely choice data, Harless and Camerer (1994), Camerer and Ho (1994), Hey and Orme (1994), Hey (1995), and Harrison (1994) found that expected utility is, at least from a statistical point of view, not dominated by its more general alternatives. Using both price and choice data, a similar finding was obtained by Schmidt and Hey (2004), and by Morone and Schmidt (2003).…”

The internal consistency of the standard gamble: tests after adjusting for prospect theory

“…Transformed probabilities equal one when p = 1 and zero when p = 0, and are non-decreasing with probability. The common empirical finding is that individuals transform probabilities in an inverse S-shaped pattern (e.g., Abdellaoui, 2000;Bleichrodt and Pinto, 2000;Bleichrodt et al, 1999;Camerer and Ho, 1994;Gonzalez and Wu, 1999;Kahneman and Tversky, 1979;Lattimore et al, 1992;Tversky and Fox, 1995;Tversky and Kahneman, 1992;Wu and Gonzalez, 1996;, such that people appear to overweight small probabilities, underweight large probabilities, and perceive w(p) as equal to p at approximately 0.4. This general pattern is observed in the domains of both gains and losses (e.g., see Bleichrodt, 2001;Tversky and Kahneman, 1992).…”