Modul I

The Expected Utility theorem suggests that if certain axioms (ordering, continuity, independence) are satisfied, a utility function exists that can represent preferences, leading to a decision rule of maximizing expected utility.

A risk-averse decision maker prefers a certain outcome to a risky lottery with the same expected value. This is represented by a concave utility function.

The certainty equivalent is the amount an individual is willing to accept for a lottery instead of facing the risk, and the risk premium is the difference between the expected value and the certainty equivalent.

They measure risk aversion. The coefficient of absolute risk aversion (r_A) is given by -u"(z) / u'(z), and the coefficient of relative risk aversion (r_R) is z * r_A(z).

Methods include incentivized lotteries (e.g., Holt and Laury, 2002), actual decisions under risk, and self-reported preferences like the DOSPERT scale.