Almost Stochastic Dominance for Risk-Averse and Risk-Seeking Investors

In this paper we first develop a theory of almost stochastic dominance for risk-seeking investors to the first three orders. Thereafter, we study the relationship between the preferences of almost stochastic dominance for risk-seekers with that for risk averters

Almost Stochastic Dominance for Risk-Averse and Risk-Seeking Investors

In this paper we first develop a theory of almost stochastic dominance for risk-seeking investors to the first three orders. Thereafter, we study the relationship between the preferences of almost stochastic dominance for risk-seekers with that for risk averters

Almost Stochastic Dominance and Moments

This paper establishes some equivalent relationships for the first three orders of the almost stochastic dominance (ASD). Using these results, we first prove formally that the ASD definition modified by Tzeng et al. (2012) does not possess any hierarchy property. Thereafter, we conclude that when the first three orders of ASD are used in the prospects comparison, investors prefer the one with positive gain, smaller variance and positive skewness. This information, in turn, enables decision makers to determine the ASD relationship among prospects when they know the moments of the prospects

Almost Stochastic Dominance and Moments

This paper first extends the theory of almost stochastic dominance (ASD) to the first four orders. We then establish some equivalent relationships for the first four orders of the ASD. Using these results, we prove formally that the ASD definition modified by Tzeng et al.\ (2012) does not possess any hierarchy property. Thereafter, we conclude that when the first four orders of ASD are used in the prospects comparison, risk-averse investors prefer the one with positive gain, smaller variance, positive skewness, and smaller kurtosis. This information, in turn, enables decision makers to determine the ASD relationship among prospects when they know the moments of the prospects. At last, we discuss the necessary and sufficient conditions for different orders the ASD and the moments of the prospects

A Note on Almost Stochastic Dominance

To satisfy the property of expected-utility maximization, Tzeng et al. (2012) modify the almost second-degree stochastic dominance proposed by Leshno and Levy (2002) and define almost higher-degree stochastic dominance. In this note, we further investigate the relevant properties. We define an almost third-degree stochastic dominance in the same way that Leshno and Levy (2002) define second-degree stochastic dominance and show that Leshno and Levy's (2002) almost stochastic dominance has the hierarchy property but not expected-utility maximization. In contrast, Tzeng et al.'s (2012) definition has the property of expected-utility maximization but not the hierarchy property. This phenomenon also holds for higher-degree stochastic dominance for these two concepts. Thus, the findings in this paper suggest that Leshno and Levy's (2002) definitions of ASSD and ATSD might be better than those defined by Tzeng et al. (2012) if the hierarchy property is considered to be an important issue

A Note on Almost Stochastic Dominance

To satisfy the property of expected-utility maximization, Tzeng et al. (2012) modify the almost second-degree stochastic dominance proposed by Leshno and Levy (2002) and define almost higher-degree stochastic dominance. In this note, we further investigate the relevant properties. We define an almost third-degree stochastic dominance in the same way that Leshno and Levy (2002) define second-degree stochastic dominance and show that Leshno and Levy's (2002) almost stochastic dominance has the hierarchy property but not expected-utility maximization. In contrast, Tzeng et al.'s (2012) definition has the property of expected-utility maximization but not the hierarchy property. This phenomenon also holds for higher-degree stochastic dominance for these two concepts. Thus, the findings in this paper suggest that Leshno and Levy's (2002) definitions of ASSD and ATSD might be better than those defined by Tzeng et al. (2012) if the hierarchy property is considered to be an important issue

Almost Stochastic Dominance and Moments

This paper first extends the theory of almost stochastic dominance (ASD) to the first four orders. We then establish some equivalent relationships for the first four orders of the ASD. Using these results, we prove formally that the ASD definition modified by Tzeng et al.\ (2012) does not possess any hierarchy property. Thereafter, we conclude that when the first four orders of ASD are used in the prospects comparison, risk-averse investors prefer the one with positive gain, smaller variance, positive skewness, and smaller kurtosis. This information, in turn, enables decision makers to determine the ASD relationship among prospects when they know the moments of the prospects. At last, we discuss the necessary and sufficient conditions for different orders the ASD and the moments of the prospects

Four Contributions to Experimental Economics

Over the last thirty years findings from economic experiments substantially contributed to a better understanding of a wide variety of phenomena in different branches of economics. In areas like industrial organization, game theory, public choice or labor economics controlled laboratory experiments became commonplace (Plott and Smith 2008). In contrast, in health economics the use of laboratory experimentation is rather in its infant stages. This is somewhat surprising as prominent proponents, like the US health economist Victor R. Fuchs, have already argued that incorporating methods of experimental economics into health economic research might lead to great benefits for the latter (Fuchs 2000). Similarly, very little experimental research has focussed on individual risk attitudes of higher orders, like prudence and temperance, so far. Various experimental methods have been developed to investigate risk aversion (e.g., Holt and Laury 2002) and to test theories of decision-making under risk (e.g., Camerer 1989, Hey and Orme 1994). It is, thus, surprising that an appropriate method to test for higher-order risks is still lacking. The four experimental studies presented in the dissertation at hand aim to fill this gap in the two respective research areas. The first two chapters present novel experimental methods to explore individual attitudes towards higher-order risks. In the third chapter, a laboratory experiment is introduced in order to study the influence of payment incentives on physician behavior. The final chapter analyzes the link between other-regarding motivations and physician payment incentives for two different subject pools