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on Contract Theory and Applications |
| By: | Biais, Bruno; Gersbach, Hans; Rochet, Jean-Charles; von Thadden, Ernst-Ludwig; Villeneuve, Stéphane |
| Abstract: | We analyze dynamic capital allocation and risk sharing between a principal and many agents, who privately observe their output. The state variables of the mechanism design problem are aggregate capital and the distribution of continuation utilities across agents. This gives rise to a Bellman equation in an infinite dimensional space, which we solve with mean-field techniques. We fully characterize the optimal mechanism and show that the level of risk agents must be exposed to for incentive reasons is decreasing in their initial outside utility. We extend classical welfare theorems by showing that any incentive- constrained optimal allocation can be implemented as an equilibrium allocation, with appropriate money issuance and wealth taxation by the principal. |
| Date: | 2025–05–22 |
| URL: | https://d.repec.org/n?u=RePEc:tse:wpaper:130553 |
| By: | Kyohei Okumura |
| Abstract: | This paper investigates the robustness of online learning algorithms when learners possess private information. No-external-regret algorithms, prevalent in machine learning, are vulnerable to strategic manipulation, allowing an adaptive opponent to extract full surplus. Even standard no-weak-external-regret algorithms, designed for optimal learning in stationary environments, exhibit similar vulnerabilities. This raises a fundamental question: can a learner simultaneously prevent full surplus extraction by adaptive opponents while maintaining optimal performance in well-behaved environments? To address this, we model the problem as a two-player repeated game, where the learner with private information plays against the environment, facing ambiguity about the environment's types: stationary or adaptive. We introduce \emph{partial safety} as a key design criterion for online learning algorithms to prevent full surplus extraction. We then propose the \emph{Explore-Exploit-Punish} (\textsf{EEP}) algorithm and prove that it satisfies partial safety while achieving optimal learning in stationary environments, and has a variant that delivers improved welfare performance. Our findings highlight the risks of applying standard online learning algorithms in strategic settings with adverse selection. We advocate for a shift toward online learning algorithms that explicitly incorporate safeguards against strategic manipulation while ensuring strong learning performance. |
| Date: | 2025–05 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2505.05341 |
| By: | Enache, Andreea; Rhodes, Andrew |
| Abstract: | We consider a setting in which a platform matches buyers and sellers, who then wish to transact with each other multiple times. The platform charges fees for hosting transactions, but also offers convenience benefits. We consider two scenarios. In one scenario, all transactions must occur on the platform; in the other scenario, buyers and sellers can disintermediate the platform after the first transaction, and do subsequent transactions offline. We find that the platform reacts to disintermediation by using a “front-loaded” pricing scheme, whereby it charges more for earlier transactions. We also show that sometimes the platform is better off when disintermediation is possible—because it can use disintermediation to screen users’ private information about their convenience benefits. Buyers are not necessarily better off when they can disintermediate, due to the way in which the platform adjusts its fees. |
| Keywords: | Platforms; disintermediation; convenience benefits; repeat transactions |
| Date: | 2025–05 |
| URL: | https://d.repec.org/n?u=RePEc:tse:wpaper:130557 |
| By: | Auriol, Emmanuelle; Bonneton, Nicolas; Polborn, Mattias |
| Abstract: | We present a moral hazard model of electoral accountability that challenges the common view of the populist vote as mere frustration with the elite. Rational voters use the threat of electing outsiders to incentivize more competent insiders whose policy preferences diverge from those of voters. Their optimal retention strategy involves differentiated punishment for failing incumbents, replacing them either with other elite politicians or with outsiders. The latter only occurs when the incumbent’s policy is both perceived as a failure and as benefiting the elite. This strategic voting behavior explains why outsider electoral success is often volatile: rational voters may back an outsider in one election and an establishment candidate in another, without changing their fundamental preferences. |
| Date: | 2025–05–26 |
| URL: | https://d.repec.org/n?u=RePEc:tse:wpaper:130565 |