1. "Time is Knowledge: What Response Times Reveal," with Jean-Michel Benkert and Nick Netzer, February 2026.
Abstract: Response times contain information about economically relevant but unobserved variables like willingness to pay, preference intensity, quality, or happiness. We provide a general characterization of the properties of latent variables that can be detected using response time data. Our characterization unifies and generalizes results in the literature and gives rise to many new applications. We illustrate the rich insights that the method can deliver through several empirical applications: revealed preference analysis, identifying an optimal nudge, testing decreasing marginal happiness of income, and predicting treatment heterogeneity.
2. "Persuasion versus Presentation," with Carl Heese, December 2023.
Abstract: In many economic situations, people communicate strategically not only to influence the decision-making of their audience but also to shape the perception of certain unobserved characteristics of themselves (e.g. morality, loyalty, or capability). To study such situations, we propose a model of Bayesian persuasion in which a sender endowed with a private type designs the communication about a payoff-relevant state to a receiver. The sender, concerned with both the impacts on the receiver's action and how her type is perceived, aims to strike a balance between persuasion and self-presentation under optimal communication. Whether the receiver fares better or worse compared to the pure persuasion setting may depend on the selected equilibrium, and the welfare effects can be non-monotone with respect to the relative strength of the sender's different motives. We illustrate our findings within various classic payoff environments, for instance with quadratic losses or state-independent sender preferences. Finally, we use the model to shed new light on a wide range of applications.
3. "Managing Burnout: The Critical Role of Middle Managers in Worker Retention and Performance," with Yuyu Chen, Miguel Espinosa, and Jingchen Zhu, July 2025.
Abstract: Burnout is a growing concern in modern workplaces, with serious consequences for employee well-being, talent retention, and organizational performance. While middle managers are known to play a key role in shaping employee experiences, little is understood about how their day-to-day decisions affect burnout and productivity. This paper opens the black box of middle management by showing that the way managers allocate tasks drives both worker performance and turnover. We find that even with better information systems, outcomes depend heavily on managerial quality: good managers improve productivity and retain top talent, while other managers overburden high-performing workers, leading to burnout and attrition. These results highlight that technology alone is not enough; effective people management is critical to unlocking productivity and sustaining healthy organizations.
4. "Engineering Privacy Concerns: A Cross-Country Survey Experiment," with Yu Gao, Ying Lei, Juanjuan Meng, Xi Weng, and Ruoyan Zhang, July 2025.
Abstract: We conduct a large-scale survey experiment across six culturally diverse countries (China, Germany, Japan, Saudi Arabia, Singapore, and the United States) to test whether information about privacy-enhancing technologies (PETs), such as encryption and federated learning, reduces concerns about personal data collection and increases acceptance of facial recognition, We also examine heterogeneity by digital literacy and privacy motivation. We find that PETs information lowers privacy concerns in Germany, the United States, and China, particularly among individuals with lower digital literacy and those motivated by instrumental considerations. However, it has no effect on the acceptance of facial recognition. These findings highlight both the reach and limits of technical assurances, and underscore the relevance of distinguishing between instrumental and intrinsic privacy motivations in shaping public attitude toward emerging technologies.
Abstract: Response times contain information about economically relevant but unobserved variables like willingness to pay, preference intensity, quality, or happiness. We provide a general characterization of the properties of latent variables that can be detected using response time data. Our characterization unifies and generalizes results in the literature and gives rise to many new applications. We illustrate the rich insights that the method can deliver through several empirical applications: revealed preference analysis, identifying an optimal nudge, testing decreasing marginal happiness of income, and predicting treatment heterogeneity.
2. "Persuasion versus Presentation," with Carl Heese, December 2023.
Abstract: In many economic situations, people communicate strategically not only to influence the decision-making of their audience but also to shape the perception of certain unobserved characteristics of themselves (e.g. morality, loyalty, or capability). To study such situations, we propose a model of Bayesian persuasion in which a sender endowed with a private type designs the communication about a payoff-relevant state to a receiver. The sender, concerned with both the impacts on the receiver's action and how her type is perceived, aims to strike a balance between persuasion and self-presentation under optimal communication. Whether the receiver fares better or worse compared to the pure persuasion setting may depend on the selected equilibrium, and the welfare effects can be non-monotone with respect to the relative strength of the sender's different motives. We illustrate our findings within various classic payoff environments, for instance with quadratic losses or state-independent sender preferences. Finally, we use the model to shed new light on a wide range of applications.
3. "Managing Burnout: The Critical Role of Middle Managers in Worker Retention and Performance," with Yuyu Chen, Miguel Espinosa, and Jingchen Zhu, July 2025.
Abstract: Burnout is a growing concern in modern workplaces, with serious consequences for employee well-being, talent retention, and organizational performance. While middle managers are known to play a key role in shaping employee experiences, little is understood about how their day-to-day decisions affect burnout and productivity. This paper opens the black box of middle management by showing that the way managers allocate tasks drives both worker performance and turnover. We find that even with better information systems, outcomes depend heavily on managerial quality: good managers improve productivity and retain top talent, while other managers overburden high-performing workers, leading to burnout and attrition. These results highlight that technology alone is not enough; effective people management is critical to unlocking productivity and sustaining healthy organizations.
4. "Engineering Privacy Concerns: A Cross-Country Survey Experiment," with Yu Gao, Ying Lei, Juanjuan Meng, Xi Weng, and Ruoyan Zhang, July 2025.
Abstract: We conduct a large-scale survey experiment across six culturally diverse countries (China, Germany, Japan, Saudi Arabia, Singapore, and the United States) to test whether information about privacy-enhancing technologies (PETs), such as encryption and federated learning, reduces concerns about personal data collection and increases acceptance of facial recognition, We also examine heterogeneity by digital literacy and privacy motivation. We find that PETs information lowers privacy concerns in Germany, the United States, and China, particularly among individuals with lower digital literacy and those motivated by instrumental considerations. However, it has no effect on the acceptance of facial recognition. These findings highlight both the reach and limits of technical assurances, and underscore the relevance of distinguishing between instrumental and intrinsic privacy motivations in shaping public attitude toward emerging technologies.
