Freddie Papazyan

Welcome to my website!

I am an Assistant Professor of Economics at Texas Tech University. My research applies economic theory to study dynamic political economy questions. My recent projects are on inequality, power dynamics, misspecified learning, disinformation, strategic communication, and the design of robust voting mechanisms.

I received a Ph.D. in Economics from UC San Diego in June 2023, where Renee Bowen was my advisor. I also hold a Applied Math Master's from USC.

Curriculum Vitæ

Collusion and Supergames 🔗

with Michael Noel

Elgar Encyclopedia on the Economics of Competition and Regulation, 2024

Strategically Controlling Worldviews 📄PDF (NEW!)

with Cuimin Ba, Danil Dmitriev, and Victoria Hang

How can disinformation work on a sophisticated listener?Show Abstract

This paper studies persuasion when the sender can both control the information the receiver observes and the model through which it is interpreted. 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 strong complementarity between selective information and tailored narratives. Whenever this complementarity is operative, the sender strictly outperforms what she could achieve even with commitment power. We fully characterize the sender-optimal equilibrium for a broad class of information technologies. While softer information weakens credibility, it also expands the scope for manipulative interpretation, sometimes permitting full manipulation when harder information does not. The results offer a plausible explanation for the widespread success of disinformation.

The Economics of Power Consolidation 📄PDF

Why are nations growing more unequal in ways that no longer feel temporary? Show Abstract

Power and resources have been concentrating within major nations around the world, echoing a century-old prediction in political economy that remains a longstanding empirical puzzle with renewed urgency. I develop an economic model of how a society's distribution of power and resources evolves over time. Multiple lineages of players compete by accumulating power, which is modeled as an asset that increases one's probability of winning conflicts over resources. This model provides sharp equilibrium predictions for how a society’s distribution of power evolves and whether it approaches equality, oligarchy, or dictatorship in the long run. My main result shows that power and resources generically fall into the hands of a few when political competition is left unchecked in large societies, suggesting that today’s trends are no anomaly and will not self-correct.

Troll-Proof Mechanism Design 📄PDF

with Danil Dmitriev

Revise & Resubmit at Social Choice and Welfare

How does one keep a voting mechanism from being hijacked?Show Abstract

Online voting mechanisms (e.g. polls) are a potentially powerful, cost-effective means of collecting large amounts of data about preferences, but such large-scale data collection has proven to be vulnerable to sabotage (e.g. by internet trolls) if proper precautions are not taken. To this end, we consider the problem of designing a voting mechanism that is robust to derailment by external groups. We show that plurality voting and other standard mechanisms are often not robust to sabotage; in fact it is sometimes preferable to not run any poll at all. The optimal voting mechanism is found to make saboteurs indifferent between each alternative they can vote for, since this undermines their ability to adversely affect the designer's predictions of other voters' preferences.

Learning Nothing From Everything 📄PDF

Revise & Resubmit at Theory and Decision

How does uncertain relevance affect evidence disclosure?Show Abstract

I study how a sender can use verifiable binary evidence to influence a receiver about a binary state when the relevance of information is ex ante uncertain and asymmetrically known by the sender. The sender has access to two pieces of evidence: one they know to be perfectly informative of the state and one that is completely uninformative. Although full disclosure of evidence is possible in equilibrium, the receiver generically cannot fully unravel which piece of evidence is relevant. Consequently, the Receiver may gain little to no information about the state even when all evidence is disclosed.

Misspecified Fear or Model Choice? Evidence from Financial Markets 📄PDF

with Ayush Jha and Zari Rachev

Under Review

Do traders use the correct model of the market or stick to a misspecified one?Show Abstract

We develop and estimate a dynamic model of financial-market learning in which traders can endogenously switch between correct and misspecified models. Unlike frameworks that impose behavioral biases exogenously, our traders rationally choose to deviate from the correct model when short-term gains outweigh informational accuracy, a mechanism we term greed-driven model choice. This switching behavior generates persistent wedges between subjective and objective beliefs, producing volatility smiles, return predictability, and pricing-kernel distortions as equilibrium outcomes. Using option-price data and a structurally estimated binomial tree model with path dependence and informed traders, we identify belief-switching thresholds that quantify how greed and fear jointly shape learning and risk premia. We document economically significant welfare and performance costs of misspecification, expressed in certainty-equivalent losses and Sharpe-ratio reductions. Our results reveal how heterogeneous information processing and learning frictions jointly shape equilibrium pricing kernels, offering new empirical evidence on misspecified learning in dynamic models and the behavioral foundations of rational asset pricing.

Unknown Rational Expectations: Evidence from Betting Markets 📄PDF (NEW!)

with Alejandro Abarca, Ayush Jha, and James Kemper

How do expectations evolve in sports prediction markets?Show Abstract

Rational expectations are well-supported in financial markets. Evidence that traders are also rationally inattentive, however, runs through a single channel: the business cycle. Whether inattention binds independently of cyclical variation-as a primitive cognitive friction mapping objective events into subjective beliefs-remains open. We answer using NFL prediction markets: binary contracts traded on Polymarket against a cash-like safe asset, benchmarked against ESPN's continuous win probability, in an environment that trends but does not cycle. Using 2025-26 season data and a dynamic program nesting FIRE and cognitive discounting, we reject FIRE three ways: U-shaped pre-game volatility drifting with competitiveness, a persistent state-dependent wedge unaltered by concurrent market load, and precisely zero cross-game spillovers. These collapse to a cognitive discount of 80%, validated by a reinforcement-learning agent reproducing the inaction and panic-liquidation patterns. The result isolates acyclical, purely-cognitive rational inattention, locating the friction at the state-to-probability mapping rather than the attention-across-assets margin.

Communication Inflation

with Christoph Schlom

Strategic Questioning and Answering

with Victoria Hang

Trade Policy and Power Politics

with Philip Economedes and Carlos Góes

The Strategic Interaction Between NGOs and Governments

with Riccardo Di Cato and Vedant Vohra

The Intertwined Dynamics of Power and Wealth

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