Publications:
1. "When Does Centralization Undermine Adaptation?," with Dimitri Migrow, Journal of Economic Theory, accepted.
2. "Preference, Confusion and Competition," with Andreas Hefti and Armin Schmutzler, Economic Journal, vol. 132, pp. 1852-81, 2022.
3. "Monotone Equilibria in Signalling Games," with Harry Pei, European Economic Review, vol.124, 103408/pp. 1-16, 2020.
4. "Delegating Performance Evaluation," with Igor Letina and Nick Netzer, Theoretical Economics, vol. 15, pp. 477-509, 2020.
5. "Targeted Information and Limited Attention," with Andreas Hefti, RAND Journal of Economics, vol. 51, pp. 402-420, 2020.
6. "On Linear Transformations of Intersections," with Alexey Kushnir, Set-Valued and Variational Analysis, vol. 28, pp. 475-489, 2020.
7. "Voting with Public Information," Games and Economic Behavior, vol. 113, pp. 694-719, 2019.
8. "On the Equivalence of Bayesian and Dominant Strategy Implementation for Environments with Non-Linear Utilities,"
with Alexey Kushnir, Economic Theory, vol. 67, pp. 617-644, 2019.
Working Papers:
1. "Happy Times: Identification from Ordered Response Data," with Nick Netzer, June 2021.
- Revise & Resubmit at the American Economic Review.
Abstract: Surveys that are designed to measure subjective states (e.g., happiness) typically generate ordinal data. A fundamental problem is that methods used to analyse ordinal data (e.g., ordered probit) rely on strong and often unjustified distributional assumptions. In this paper, we propose using survey response times to solve that problem. The key assumption of our approach is that individual response time is decreasing in the distance between the value of the latent variable and an indecision threshold. This assumption is supported by a large body of evidence on chronometric effects in psychology, neuroscience and economics. We provide conditions under which the expected value of the latent variable (e.g., average happiness) can be compared across groups, even without making distributional assumptions. We apply our method to an online survey experiment and obtain some evidence that happiness follows distributions for which traditional regression analysis is valid.
2. "Talent Poaching and Job Rotation," with Diego Battiston and Miguel Espinosa, July 2022.
Abstract: The value of a firm's service lies both in its workers and its relationship with clients. In this paper, we study the interaction between client-specific experience accumulated by workers, poaching behaviour from clients and strategic rotation of workers by firms. Using detailed personnel data from a security-service firm, we show that an increase in client-specific experience increases both the productivity of workers and their probability of being poached. The firm reacts to this risk by rotating workers across multiple clients, and more frequently so to those workers more likely to be poached. We show that after a policy change that prohibited talent poaching, the firm sharply decreased the frequency of rotation which in turn increased workers' productivity. We propose a theoretical model that guides the empirical patterns and allows us to argue their external validity beyond our specific empirical setting.
3. "Optimal Contest Design: Tuning the Heat," with Igor Letina and Nick Netzer, April 2022.
- Revise & Resubmit at the Journal of Economic Theory.
Abstract: We consider the design of contests when the principal can choose both the prize profile and how the prizes are allocated as a function of a possibly noisy signal about the agents' efforts. We provide sufficient conditions that guarantee the optimality of a contest. Optimal contests have a minimally competitive prize profile and an intermediate degree of competitiveness in the contest success function. Whenever observation is not too noisy, the optimum can be achived by an all-pay auction with a cap. When observation is perfect, the optimum can also be achieved by a nested Tullock contest. We relate our results to a recent literature which has asked similar questions but has typically focused on the design of either the prize profile or the contest success function.
1. "When Does Centralization Undermine Adaptation?," with Dimitri Migrow, Journal of Economic Theory, accepted.
2. "Preference, Confusion and Competition," with Andreas Hefti and Armin Schmutzler, Economic Journal, vol. 132, pp. 1852-81, 2022.
3. "Monotone Equilibria in Signalling Games," with Harry Pei, European Economic Review, vol.124, 103408/pp. 1-16, 2020.
4. "Delegating Performance Evaluation," with Igor Letina and Nick Netzer, Theoretical Economics, vol. 15, pp. 477-509, 2020.
5. "Targeted Information and Limited Attention," with Andreas Hefti, RAND Journal of Economics, vol. 51, pp. 402-420, 2020.
6. "On Linear Transformations of Intersections," with Alexey Kushnir, Set-Valued and Variational Analysis, vol. 28, pp. 475-489, 2020.
7. "Voting with Public Information," Games and Economic Behavior, vol. 113, pp. 694-719, 2019.
8. "On the Equivalence of Bayesian and Dominant Strategy Implementation for Environments with Non-Linear Utilities,"
with Alexey Kushnir, Economic Theory, vol. 67, pp. 617-644, 2019.
Working Papers:
1. "Happy Times: Identification from Ordered Response Data," with Nick Netzer, June 2021.
- Revise & Resubmit at the American Economic Review.
Abstract: Surveys that are designed to measure subjective states (e.g., happiness) typically generate ordinal data. A fundamental problem is that methods used to analyse ordinal data (e.g., ordered probit) rely on strong and often unjustified distributional assumptions. In this paper, we propose using survey response times to solve that problem. The key assumption of our approach is that individual response time is decreasing in the distance between the value of the latent variable and an indecision threshold. This assumption is supported by a large body of evidence on chronometric effects in psychology, neuroscience and economics. We provide conditions under which the expected value of the latent variable (e.g., average happiness) can be compared across groups, even without making distributional assumptions. We apply our method to an online survey experiment and obtain some evidence that happiness follows distributions for which traditional regression analysis is valid.
2. "Talent Poaching and Job Rotation," with Diego Battiston and Miguel Espinosa, July 2022.
Abstract: The value of a firm's service lies both in its workers and its relationship with clients. In this paper, we study the interaction between client-specific experience accumulated by workers, poaching behaviour from clients and strategic rotation of workers by firms. Using detailed personnel data from a security-service firm, we show that an increase in client-specific experience increases both the productivity of workers and their probability of being poached. The firm reacts to this risk by rotating workers across multiple clients, and more frequently so to those workers more likely to be poached. We show that after a policy change that prohibited talent poaching, the firm sharply decreased the frequency of rotation which in turn increased workers' productivity. We propose a theoretical model that guides the empirical patterns and allows us to argue their external validity beyond our specific empirical setting.
3. "Optimal Contest Design: Tuning the Heat," with Igor Letina and Nick Netzer, April 2022.
- Revise & Resubmit at the Journal of Economic Theory.
Abstract: We consider the design of contests when the principal can choose both the prize profile and how the prizes are allocated as a function of a possibly noisy signal about the agents' efforts. We provide sufficient conditions that guarantee the optimality of a contest. Optimal contests have a minimally competitive prize profile and an intermediate degree of competitiveness in the contest success function. Whenever observation is not too noisy, the optimum can be achived by an all-pay auction with a cap. When observation is perfect, the optimum can also be achieved by a nested Tullock contest. We relate our results to a recent literature which has asked similar questions but has typically focused on the design of either the prize profile or the contest success function.
