Stochastic Dominance Tests for Decreasing Absolute Risk Aversion. I. Discrete Random Variables

1975 ◽  
Vol 21 (12) ◽  
pp. 1438-1446 ◽  
Author(s):  
R. G. Vickson
2020 ◽  
Vol 66 (10) ◽  
pp. 4630-4647 ◽  
Author(s):  
Rachel J. Huang ◽  
Larry Y. Tzeng ◽  
Lin Zhao

We develop a continuum of stochastic dominance rules for expected utility maximizers. The new rules encompass the traditional integer-degree stochastic dominance; between adjacent integer degrees, they formulate the consensus of individuals whose absolute risk aversion at the corresponding integer degree has a negative lower bound. By extending the concept of “uniform risk aversion” previously proposed in the literature to high-order risk preferences, we interpret the fractionalized degree parameter as a benchmark individual relative to whom all considered individuals are uniformly no less risk averse in the lottery choices. The equivalent distribution conditions for the new rules are provided, and the fractional degree “increase in risk” is defined. We generalize the previously defined notion of “risk apportionment” and demonstrate its usefulness in characterizing comparative statics of risk changes in fractional degrees. This paper was accepted by David Simchi-Levi, decision analysis.


2015 ◽  
Vol 61 (7) ◽  
pp. 1615-1629 ◽  
Author(s):  
Thierry Post ◽  
Yi Fang ◽  
Miloš Kopa

2006 ◽  
Vol 28 (1) ◽  
pp. 89-110 ◽  
Author(s):  
Jordi Caballe ◽  
Joan Esteban

1980 ◽  
Vol 53 (3) ◽  
pp. 285 ◽  
Author(s):  
Steven A. Lippman ◽  
John J. McCall ◽  
Wayne L. Winston

2006 ◽  
Vol 29 (2) ◽  
pp. 155-160 ◽  
Author(s):  
Mario A. Maggi ◽  
Umberto Magnani ◽  
Mario Menegatti

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