Suppose that you have the following one-time scenario. You want to buy a sandwich where the options are a roast beef sandwich or an avocado sandwich. Choosing the sandwich of your preference (say, the avocado sandwich) adds one to your utility, but having your private preference known to the seller, reduces by one your utility. The prior people have on your preferences is fifty-fifty.
If you choose the avocado sandwich your utility is zero, hence you can improve on this by picking each type of sandwich at random with probability 1/2. In this case your private preference remains unknown and you gain in expectation 1/2 for having the sandwich you prefer with probability 1/2.
But given this strategy, you can still improve on it by choosing the avocado sandwich.
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As always, comments will be highly appreciated.
best regards, Gil
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This situation can (should?) be modeled as a psychological game, after Geanakopolos, Pearce and Stachetti 1989. In such a game, players' payoffs directly depend on their (and their opponents') hierarchy of beliefs. In Rann's example, the buyer's payoff can
be defined as the value of the product he ends up buying minus 2*|p-0.5|, where p is the seller's posterior on avocado. Equilibrium in such a game is defined more or less as usual (in general, since payoffs can depend on high order beliefs, the equilibrium
concept has to deal with those, too). When the buyer orders avocado for sure, this is an equilibrium. It does not maximize the buyer's ex ante expected payoffs, but that is not unusual in this class of games because payoffs need not be linear in beliefs.
Here is another example, which Kfir Eliaz and I used to call "the dress game". Bob's girlfriend bought a dress. He observes whether it is nice. His strategy is to tell her whether it is nice, given his observation. His objective is to maximize a convex increasing
function of his girfriend's posterior that the dress is nice. TE only equilibria are babbling equilibria, in which Bob's message is totally uninformative, because otherwise he always has an incentive to deviate from his equilibrium (potentially mixed) strategy
and say the dress is nice. By the convexity assumption, the babbling equilibria do not maximize Bob's ex ante expected payoff. If he could commit, he would want to be fully informative.
Ran Spiegler
School of Economics, Tel Aviv University
&
Department of Economics, University College London
Just saw a new paper, by Ely, Frankel and Kamenica, at a conference that is related to these kind of games. They do assume ex ante commitment:
http://faculty.chicagobooth.edu/emir.kamenica/documents/suspense.pdf
For a “paradox” without commitment, there’s also the Hangman’s paradox by John Geanakoplos.
Best, Attila
My comments on the game focuses on the hypothesized probability distribution from a prospect theory perspective. One of the empirical regularities of prospect theory is that people hate symmetric 50-50 bets. Based on the information given, the introduction of a gain utility (+1) for avocado (“A”), and a loss utility (-1) for roast beef (“RB” phonetic Arby), imply a reference point of 0 against which gain and loss is measured. If so, then let p be the probability associated with selecting A, and q that with selecting RB. The “mixed prospect” is now (A, p; 0, 1-p-q ; RB, q). One of the empirical regularities of probability weighting functions is that they have a fixed point probability of approximately 1/3 that separates loss and gain domains based on ranking. In which case an admissible criterion is that 1-p-q=1/3 So that p+q=2/3. Since the “rank dependent utility” implied by the problem is A > 0 > RB, we have the weighting scheme w(p), w(1/3), w(q). So that the introduction of a prior probability of p=1/2 è q=1/6 In which case w(1/6) > 1/6 due to overweighting in“loss probability” domain; w(1/2) < 1/2 due to underweighting gain probability domain; and w(1/3)=1/3 due to fixed point. Roughly, the decision weights for gain (g) and loss (l) respectively, are pi_g=w^+(1/3 + 1/2) – w^+(1/3) and pi_l =w^-(1/6 + 1/3) – w^-(1/6). For a value function V the nonexpected value of the choices available to our subject is V(.)=V^+(+1)pi_g + V^-1(-1)pi_l. Evidently, the nonexpected utility is also greater than zero even if the seller knows the subject will select avocado. For admissible “strategies” that “dominate” ½ we can impose the constraint 0 < V^+(+1)pi_g + V^-1(-1)pi_l > 1/2. So that any combination of value function and decision weights that support that inequality would be “strategy proof” in so far as whether the seller knows the subject selects avocado or not.