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Explaining Satisficing through Risk Aversion

Yudistira Permana


This paper extends the analysis of the data from the experiment of Hey, Permana and Rochanahastin (2017), which was designed to test Proposition 2 of the theory of Manski (2017). I will solely focus on how the subjects select the aspiration levels when they choose to satisfice and try to find a better explanation for that story than that of Manski’s story. I start by assuming that the subjects are of expected utility (EU) agent and that they think of the payoffs as having a uniform risky distribution. I consider two special cases of the EU preferences: CRRA and CARA; and I combine these with two different stories for the stochastic specification of noise distribution: beta and normal. To give a fair comparison in finding a better explanation of the individual behaviour, I also fit the data using Manski’s optimal strategy under both stochastic specifications. I estimate using the maximum log-likelihood method. The estimation is done subject by subject. The results tell us that assuming that the subjects are EU agents and that they see the payoffs as uniformly distributed produces a better statistical explanation than that of Manski’s theory. That is the actual aspiration levels are statistically closer to the optimal aspiration level assuming CRRA and CARA than those of Manski’s prediction. In addition, the subjects in the Hey, Permana and Rochanahastin (2017) experiment appear to be risk loving when selecting their aspiration levels.

Keywords: expected utility, risk aversion, maximum log-likelihood

JEL Classification: C15, D81, D83

Appendix (MS Word , 45kb) for the paper.

The data from experiment (zip , 56kb).

The input data (zip , 42kb) for the parameters of the problems posed to the subjects.

The  Matlab files for Estimation (zip , 9kb). The data from the experiment needs to be put in a sub-folder 'ResultsMain'. There is a Guide to Matlab program (zip , 1kb) here.