Universität Bonn

Department of Economics

Micro Theory Seminar

Botond Közsegi (briq) 12.10.2022
Oct 12, 2022 from 04:30 to 05:45

We model an agent who stubbornly underestimates how much his behavior is driven by undesirable motives, and, attributing his behavior to other considerations, updates his view about those considerations. We study general properties of the model, and then apply the framework to identify novel implications of partially naive present bias. In many stable situations, a partially naive present-biased agent appears realistic in that he eventually predicts his behavior well. His unrealistic self-view does, however, manifest itself in several other ways. First, in basic settings he always comes to act in a more present-biased manner than a realistic agent. Second, he systematically mispredicts how he will react when circumstances change, such as when incentives for forward-looking behavior increase or he is placed in a new, ex-ante identical environment. Third, he follows empirically realistic addiction-like consumption dynamics that he does not anticipate. Fourth, he holds beliefs that — when

Andrea Wilson (Princeton) - 19.10.2022
Oct 19, 2022 from 04:30 to 05:45

We explore a novel model where authors of heterogeneous papers submit to ranked journals with admission standards on noisy referee evaluations. Journal caliber reflects paper quality in a rational expectations equilibrium. In our main finding, journal rejection rates first rise and then fall in caliber, and so cannot be used to rank journals. The logic by extension applies to college rankings. This paper therefore invalidates using selectivity to rank journals and colleges. Our theory holds for all signals obeying a novel log-concavity condition that is typically met.

Harry Pei (Northwestern) 26.10.2022
Oct 26, 2022 from 04:30 to 05:45

A patient seller decides whether to build a reputation for exerting high effort in front of a sequence of consumers. Each consumer decides whether to trust the seller after she observes the number of times that the seller took each of his actions in the last K periods, but not the order with which these actions were taken. I show that (i) the seller’s payoff from building a reputation is at least his commitment payoff for all K and in all equilibria, and (ii) the seller sustains his reputation for exert high effort in all equilibria if and only if K is below some cutoff. Although a larger K allows more consumers to observe the seller’s opportunistic behavior, it weakens their incentives to punish the seller after they observe opportunistic behavior. This effect undermines the seller’s reputational incentives and lowers consumers’ welfare.

Manuel Müller-Frank (IESE) 02.11.2022
Nov 02, 2022 from 04:30 to 05:45

The classic wisdom-of-the-crowd problem asks how a principal can “aggregate” information about the unknown state of the world from agents without understanding the information structure among them. We propose a new simple procedure called Population-Mean-Based Aggregation to achieve this goal. The procedure only requires eliciting agents’ beliefs about the state, and also eliciting some agents’ expectations of the average belief in the population. We show that this procedure fully aggregates information: in an infinite population, it always infers the true state of the world. The procedure can accommodate correlations in agents’ information, misspecified beliefs, any finite number of possible states of the world, and only requires very weak assumptions on the information structure.

Eva Tardos (Cornell University) 07.11.2022
Nov 07, 2022 from 04:30 to 05:45

Over the last two decades we have developed good understanding how to quantify the impact of strategic user behavior on outcomes in many games (including traffic routing and online auctions) and showed that the resulting bounds extend to repeated games assuming players use a form of no-regret learning to adapt to the environment. Unfortunately, these results do not apply when outcomes in one round effect the game in the future, as is the case in many applications. In this talk, we study this phenomenon in the context of a game modeling queuing systems: routers compete for servers, where packets that do not get served need to be resent, resulting in a system where the number of packets at each round depends on the success of the routers in the previous rounds. In joint work with Jason Gaitonde, we analyze the resulting highly dependent random process. [...]

Ran Spiegler (Tel Aviv University, UCL) 16.11.2022
Nov 16, 2022 from 04:30 to 05:45

We present an equilibrium model of politics in which political platforms compete over public opinion. A platform consists of a policy, a coalition of social groups with diverse intrinsic attitudes to policies, and a narrative. We conceptualize narratives as subjective models that attribute a commonly valued outcome to (potentially spurious) postulated causes. When quantifi…ed against empirical observations, these models generate a shared belief among coalition members over the outcome as a function of its postulated causes. The intensity of this belief and the members’intrinsic attitudes to the policy determine the strength of the coalition’s mobilization. Only platforms that generate maximal mobilization prevail in equilibrium. Our equilibrium characterization demonstrates how false narratives can be detrimental for the common good, and how political fragmentation leads to their proliferation.

Philipp Strack (Yale) 23.11.2022
Nov 23, 2022 from 04:30 to 05:45

We study how long-lived, rational, exponentially discounting agents learn in a social network. In every period, each agent observes the past actions of his neighbors, receives a private signal, and chooses an action with the objective of matching the state. Since agents behave strategically, and since their actions depend on higher order beliefs, it is difficult to characterize equilibrium behavior. Nevertheless, we show that regardless of the size and shape of the network, and the patience of the agents, the speed of learning in any equilibrium is bounded from above by a constant that only depends on the private signal distribution.

Axel Niemeyer (BGSE) 30.11.2022
Nov 30, 2022 from 04:30 to 05:45

Posterior implementation is a solution concept for mechanism design with interdependent values. It requires that each agent’s strategy is optimal against the strategies of other agents for every possible message profile. Green and Laffont (1987) give a geometric characterization of posterior implementable social choice functions for binary collective decision problems with two agents and non-transferable utility. This paper generalizes the analysis to any finite number n of agents, with three main insights. First, posterior implementable social choice functions are posterior implementable by score voting: each agent submits a number from a set of consecutive integers; the collective decision is determined by whether or not the sum exceeds a given quota. Second, the possibility for posterior implementation depends crucially on the number of agents: in generic environments with n ≥ 3 agents, a (responsive) social choice function is posterior implementable [...]

Patrick Lahr (BGSE) 07.12.2022
Dec 07, 2022 from 04:30 to 05:45


Alp Atakan (Queen Mary) 11.01.2023
Jan 11, 2023 from 04:30 to 05:45


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