Risk loving after the storm: A Bayesian-Network study of Hurricane Katrina evacuees

We investigate risk preferences of a sample of hurricane Katrina evacuees shortly after they were evacuated and transported to Houston, and another sample from the same population taken a year later. We also consider a third sample of resident Houstonians with demographics similar to the Katrina evacuees. Conventional statistical methods fail to explain a strong risk-loving bias in the first Katrina-evacuees sample. We utilize Bayesian Networks to investigate all relevant conditional distributions for gamble choices, demographic variables, and responses to psychometric questionnaires. We uncover surprising results: Contrary to prior experimental evidence, we find that women in our sample were significantly more risk loving in the first Katrina sample and only mildly more risk averse in the other two samples. We find that gamble choices are best predicted by positive-emotion variables. We therefore explain the risk-loving choices of the first Katrina-evacuees sample by the detected primacy of negative-emotion variables in that sample and explain the latter by traumatic and heightened-stress experiences shortly after the hurricane.