Job Market Paper
The Supply Side of Social Media (with Aakaash Rao)
We study an overlooked feature of social media platforms: their distinctive model of content production. Unlike legacy media outlets, platforms do not professionally produce content ex-ante optimized to appeal to viewers; instead, they rely on large numbers of amateur users creating content in pursuit of social status, expressive satisfaction, or creative fulfillment. The resulting scale of their content libraries allows them to ex-post cherry-pick the pieces most appealing to viewers. We develop an equilibrium model of this process. We show that because the scale powering platforms' cherry-picking concentrates where creators are eager to produce, creators' supply-side preferences can influence what viewers consume. Collecting new data on Instagram, TikTok, and X/Twitter, we show that most of the content in viewers' feeds is created by non-professionals who produce envy-provoking “lifestyle” and partisan political content in pursuit of social status and expressive satisfaction. To separate supply- and demand-side preferences, we experimentally manipulate viewers' feeds and pay creators to post different types of content. Piece by piece, lifestyle and partisan political content is less likely to highly engage viewers than more benign entertainment. But the satisfaction creators derive from creating such content leads it to be produced at a scale large enough that platforms can cherry-pick the minority of such pieces viewers find more interesting or entertaining than the marginal piece of entertainment. Estimating our model using the experimental variation, we calculate that supply-side preferences account for one-third to one-half of the prevalence of lifestyle and partisan content in viewers' feeds.
Research
The Business of the Culture War
(with Aakaash Rao); September 2026
We link the contemporary American “culture war” to the entry of 24-hour cable news networks, which we find emphasize cultural issues more than the broadcast networks preceding them and far more than political candidates. Estimating viewer preferences using household-by-second data, we show cable news faces a tradeoff: cultural content attracts non-news entertainment viewers while economic content attracts viewers of rival news outlets. Broadcast news and politicians similarly trade off the cultural content that appeals to the politically disengaged against the economic content that appeals to the politically engaged, but we show why cable has the strongest incentives to emphasize culture. In turn, constituencies quasi-randomly more exposed to cable news networks assign greater importance to cultural issues, and politicians run more cultural campaigns.
The Transmission of Reliable and Unreliable Information
(with Thomas Graeber and Chris Roth); July 2026; accepted, Quarterly Journal of Economics
Information often spreads and influences beliefs regardless of its reliability. We show that this occurs in part because indicators of reliability tend to be lost in the process of word-of-mouth transmission. We conduct controlled experiments where participants listen to economic forecasts and pass them on through voice messages. Other participants listen either to original or transmitted audio recordings and report incentivized beliefs. Across various transmitter incentive schemes, a claim's reliability is lost in transmission much more than the claim itself. Reliable and unreliable information, once filtered through transmission, impact listener beliefs similarly. Mechanism experiments show that reliability is lost not because it is perceived as less relevant or harder to transmit, but because it is less likely to come to mind during transmission. Evidence from our experiments, a large corpus of everyday conversations, and economic TV news shows that contextual cues can bring reliability to mind and induce its transmission, but situations in which people share information seldom contain such cues.
Experimental Evidence on the Productivity Effects of Generative Artificial Intelligence
(with Whitney Zhang); Science, 2023, 381(6654), p.187-192
We examined the productivity effects of a generative artificial intelligence technology—the assistive chatbot ChatGPT—in the context of mid-level professional writing tasks. In a preregistered online experiment, we assigned occupation-specific, incentivized writing tasks to 453 college-educated professionals, and randomly exposed half of them to ChatGPT. Our results show that ChatGPT substantially raised productivity: average time taken decreased by 40% and output quality rose by 18%. Inequality between workers decreased, and concern and excitement about AI temporarily rose. Workers exposed to ChatGPT during the experiment were 2x as likely to report using it in their real job two weeks after the experiment, and 1.6x as likely two months after the experiment.
The German Model of Industrial Relations: Balancing Flexibility and Collective Action
(with Simon Jäger and Benjamin Schoefer); Journal of Economic Perspectives, 2022, 36(4), p.53-80
We give an overview of the two pillars of the “German model” of industrial relations: sectoral collective bargaining and firm-level codetermination. Relative to the United States, Germany outsources collective bargaining to the sectoral level, resulting in higher coverage and the avoidance of firm-level distributional conflict. Relative to other European countries, Germany makes it easy for employers to avoid coverage or use flexibility provisions to deviate downwards from collective agreements. The greater flexibility of the German system may reduce unemployment, but may also erode bargaining coverage and increase inequality. Meanwhile, firm-level codetermination through worker board representation and works councils creates cooperative dialogue between employers and workers. Board representation has few direct impacts owing to worker representatives' minority vote share, but works councils, which hold a range of substantive powers, may be more impactful. Overall, the German model highlights tensions between efficiency-enhancing flexibility and equity-enhancing collective action.
The Effects of Neighborhood and Workplace Income Comparisons on Subjective Wellbeing
(with Isabelle Sin); Journal of Economic Behavior and Organization, 2021, 185, p.918-945
We investigate how a person's happiness is affected by the incomes of her neighbors and coworkers. Using an unprecedentedly rich combination of administrative and survey data, we establish two central results. First, a person's happiness is sensitive to her ordinal rank within her peer income distribution: people are happier the higher their income rank. Second, workplace rank matters much more than neighborhood rank. We confirm that our results reflect a causal effect of peer income by implementing sensitivity analyses, identifying off changes in peer income over time for immobile people, exploiting plausibly exogenous moves between workplaces triggered by mass layoffs, and testing for the effects of unobservable group-level confounders.