## Speaker Name:

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## Description:

Most work in mechanism design assumes that buyers are risk neutral; some

considers risk aversion arising due to a non-linear utility for money. Yet

behavioral studies have established that real agents exhibit risk attitudes

which cannot be captured by any expected utility model. We initiate the study

of revenue-optimal mechanisms under behavioral models beyond expected utility

theory. We adopt a model from prospect theory which arose to explain these

discrepancies and incorporates agents under-weighting uncertain outcomes. In

our model, an event occurring with probability x < 1 is worth strictly less to

the agent than x times the value of the event when it occurs with certainty.

I will present three main results. First, I will characterize optimal mechanisms as

menus of two-outcome lotteries. Second, I will show that under a reasonable

bounded-risk-aversion assumption, posted pricing obtains a constant

approximation to the optimal revenue. Notably, this result is "risk-robust"

in that it does not depend on the details of the buyer's risk attitude. Third,

I will discuss dynamic settings in which the buyer’s uncertainty about his future

value may allow the seller to extract more revenue. In contrast to the positive

result above, here I will show it is not possible to achieve any constant-factor

approximation to revenue using deterministic mechanisms in a risk-robust

manner.

Based on joint work with Shuchi Chawla, Kira Goldner, and Emmanouil Pountourakis.