Session 11: Political Economic Theory

District-based elections must reconcile two objectives: representing each district’s electorate and matching the statewide delegation to overall political support. We study  the design of seat allocation rules when these objectives conflict. The optimal rule is characterized by an endogenous cutoff that compares the district-level and statewide representational effects of awarding a party an additional seat. In a linear benchmark, the optimal rules form a family ranging from first-past-the-post to proportional representation as the weight on statewide representation increases. Along this path, it becomes increasingly difficult for an already overrepresented party to gain further seats through gerrymandering. The characterization yields a measure of first-past-the-post robustness to statewide representation concerns and provides a unified framework for comparing it with established electoral diagnostics. Applying these measures to U.S. House elections from 2002 to 2024, we find that maps drawn by single-party legislatures generally perform worse across our measures than those produced by other institutions, and Republican-legislature maps fare worse on average than Democratic-legislature maps. The efficiency gap, a widely used wasted-vote measure of partisan gerrymandering, is more strongly associated with struck or litigated maps than the other measures, yet it considerably amplifies the Republican--Democratic asymmetry.

This paper studies how the organization of production shapes democratic accountability. I propose a model in which learning economies make specialization productively efficient: most workers perform one-domain tasks, while a small set of integrators with cross-domain knowledge keep the system coherent. When policy consequences run across domains, integrators understand them better than specialists. Electoral competition then tilts government policies toward integrators’ interests, while low aggregate system knowledge weakens governance and reduces the fraction of public resources converted into citizen-valued services. Labor markets leave these civic margins unpriced, failing to internalize the political returns to system knowledge. Broadening specialists can therefore raise welfare relative to the market allocation. The model speaks to debates on liberal arts education and the effects of AI.

A committee chooses a profile of actions via a sequence of binary votes. Actions are complements and committee members can be ranked according to their preference for high action profiles. We show that, for a rich family of voting procedures, the committee chooses the action profile favoured by an agent who enjoys a central position in the ranking. Moreover, the chosen profile remains the same if agents are privately informed about their preferences. We obtain analogous results for committees facing dynamic stochastic decision problems. We derive applications to problems of multi-input investment, resource allocation, information gathering, optimal bankruptcy, and production with adjustment costs.

We analyze a game-theoretic model of crime and crime reporting to study the quality of crime statistics. A citizen potentially engages in illicit behavior; an enforcement agency chooses effort and how to report outcomes. Because of signaling concerns, the agency may misreport. We show that multiple equilibria can exist and characterize when crime is under- or overreported. Increasing the agency’s costs of data manipulation can backfire, increasing misreporting in crime statistics. When calculating treatment effects of parameter changes, the effect on reported statistics will not equal the effect on true statistics, and the true effect can be under- or overestimated.

We study a novel dynamic game in which a principal can purge a group of agents, sequentially targeting its members for elimination. Agents can organize a protest that, if sufficiently large, may end the purge permanently. When targeting is predictable, next-period targets coordinate with current targets, limiting the purge to a few agents and at most one period. When targeting is unpredictable, currently untargeted agents face diffuse risk of near-term elimination, weakening their incentive to protest. Unpredictability typically benefits the principal by allowing multi-period purges that eliminate a larger share of agents. We illustrate these results with historical elite purges.

Motivated by the growing interest in geoeconomics, we develop a formal framework in which multiple superpowers-such as the United States and China-compete to shape the behavior of less powerful countries or firms. We model superpowers as competing principals who influence an agent's policy choice by threatening costly punishments. We characterize the set of equilibrium policy choices as a system of incentive-compatibility constraints on each actor. Equilibrium policy choices tend to favor more powerful principals, and larger policy concessions can be extracted when principals are more aligned. When all parties additionally have access to frictionless transfers, Coasian surplus-maximizing equilibria always exist regardless of the distribution of punishment power, with power impacting only the division of surplus. However, this result no longer holds if frictions are introduced.

Debates about when and whether (partisan) directional motives influence information processing are hard to resolve because rational and motivated learning often look similar. We develop an experimental design to distinguish between these possibilities which focuses on the order in which information is presented. A core tenet of Bayesian updating is that order should not impact final beliefs, but if some information changes the motivation to process other information, order effects may emerge. In our first study, we randomize the partisanship of real endorsements for ballot propositions, as well as whether participants learn about these endorsements before observing other information about the propositions. We find no evidence of motivated information processing across several tests. In a second study, we randomize whether participants themselves argue for or against a proposition, and whether they know this position before observing other information. This produces a strong order effect: being randomized to argue for versus against a position affects beliefs more when it is learned before information about the proposition is provided. We also find suggestive evidence that this order effect is driven by selective attention to information. Overall, our results suggest that motivated reasoning about politics is less prevalent than commonly believed, but may arise primarily when people are in an argumentative mindset.

We propose a model of whataboutism - a rhetorical strategy that deflects criticism by invoking analogous, yet internally uncriticized, misconduct on the critic's side - and study its implications for social norms governing offensive speech. In an infinite-horizon psychological game with two rival camps, agents weigh the intrinsic benefit of offensive speech against the risk of effective condemnation. External criticism can be rendered ineffective via an equilibrium-based whataboutism rebuttal. We characterize the unique dynamically stable Psychological Subgame Perfect Equilibrium and show that the availability of whataboutism exacerbates o§ensive speech, such that civility norms can break down entirely, especially in polarized societies.

This paper studies persuasive behavior when the sender can control both the information the receiver observes and the model through which it is interpreted (the narrative). Even when the receiver begins with a correctly specified model and understands the sender’s strategic incentives, the sender can manipulate him and often secure her preferred action with probability one. The key mechanism highlights a strong complementarity between strategic communication of information and narratives, allowing the sender to strictly outperform a Bayesian persuader with commitment power. We fully characterize the sender-optimal equilibrium for a broad class of information technologies. Softer information lowers the bar for full manipulation, while harder information expands the set of environments where any manipulation is possible. The results provide a formal foundation for understanding the widespread success of disinformation.

This paper develops a political-economy model studying the interaction between cultural conflict in society and electoral competition. Conservatives and progressives choose, ex ante, their level of tolerance in social relations in response to two sources of threat: the probability of interacting with the cultural outgroup and the risk of unfavorable cultural policy. Political parties compete on both economic and cultural dimensions. The model shows that as societies gradually shift toward more progressive values, this can, beyond a threshold, trigger endogenous backlash and increased societal intolerance. This backlash shifts political competition from economic to cultural issues, further reinforcing cultural conflict. This two-way interaction can generate multiple equilibria and self-fulfilling “culture wars.”

Why do some protest movements escalate from peaceful demonstrations to violent confrontation while others never change tactics? I develop a dynamic model in which an organizer chooses between tactics that differ in how they convert participation into political power. Failed protests reveal information about regime strength, reducing subsequent mobilization. Optimal tactical sequencing reflects not only how powerful each tactic is today, but how valuable it may be in a lower-mobilization environment tomorrow. I show that movements preserve tactics that remain effective after demobilization, generating pathdependent patterns of tactical persistence or learning-motivating switching. Extending the model to repression, I show that state intervention can redirect movements across tactics and, by changing the informational content of failures, partly or even fully undermine the benefits of repression. As a technical contribution, I introduce a cost-signals structure which resolves equilibrium multiplicity in a dynamic global game with public learning.

We consider an alternating-offers redistributive bargaining model where an affected third party can protest against proposals under review. Protests are costly and only stochastically successful. When successful, they secure the status quo. Stationary equilibria feature either inefficient protests or excessive accommodation to the third party. In both cases, the bar- gainers do not extract the full surplus. Strategic delay is necessary and sufficient to curb this issue: By delaying a harmful agreement with positive probability only after acquiescence, the bargainers create an endogenous punishment device that allows them to extract more surplus from the third party without triggering protests. The bargainers’ misaligned interests are key for this result: If they internalized each other’s payoff, strategic delay would not be credible.