Published Papers:
Julianne Treme, Lee A. Craig & Andrew Copland (2019) Gender and box office performance, Applied Economics Letters, 26:9, 781-785, DOI: 10.1080/13504851.2018.1495818
Working Papers:
Compensation without Distortion: Stochastic Termination and Incentive Compatibility in Preference Elicitation (2021). Job Market Paper [Link to Current Version] (Previous title: Experimenting with Incentives: Restoring Incentive Compatibility in Decision Experiments)
Previous literature has highlighted shortcomings in methods currently used to elicit beliefs. Specifically, compensating individuals based on choices they make increases reliability, however these payments can themselves distort subjects’ preferences, limiting data’s usefulness. I propose using a stochastic mechanism, called the Random Stopping Procedure (RSP) to mechanically induce separation between subject decisions. I conduct an experiment explicitly designed to test the accuracy of data gathered by the RSP against the current best practice for measuring subject preferences. The results show that RSP-elicited preferences more closely match a control group’s responses than the alternative, supporting the paper’s theoretical predictions.
School Choice and Class Size Externalities (2021). [Link to Current Version] (Previous Title: Hidden Dimensions of School Choice; Examining Class Size Externalities and Efficiency)
I extend the standard school choice problem to incorporate student preferences over both school identity and the size of their cohort (a measure of school crowding) I show that, if students do have preferences over schools and cohort sizes, current mechanisms are no longer stable, fair, nor non-wasteful. I propose an original algorithm, deferred acceptance with voluntary withdrawals, that allows students to rescind proposals depending on contemporary cohort size. This new algorithm satisfies many core properties in matching theory and can yield substantial efficiency gains compared to mechanisms that do not consider class size.
Current Works in Progress:
Imperfect Division (with Tina Letsou)
This project bridges cooperative bargaining problems with and without convex bargaining sets. The former approach generally allows for convexification by using lotteries over indivisible goods, while the latter assumes these lotteries are impossible. We suggest that both obscure a practical reality: convexification of the bargaining set via division is possible, but costly. We highlight how often agents first face the question of whether to exert costly effort to divide an asset or use a crude randomization device (which convexifies the bargaining set), and what the necessary conditions are for subjects to prefer one option over the other.
Multiunit Allocation in Small Economies (with Navin Kumar)
In this project, we examine the implications of applying efficiency improvements developed for large-markets to small-market contexts, like course allocation for students. We demonstrate that exogeneity assumptions commonly used in non-atomic settings are often not satisfied, and examine the implications in terms of efficiency costs.
Pre-trends and Policy Trends; Difference-in-Differences Estimation with Unobserved Policy Confounds (with Jean-Francois Gauthier and Vera Sharunova)
We show how two common observations—political boundaries between states can impact population sorting, and policy implementation is often non-random, politically—impacts county-matching DiD regression analysis. First, variation in local population characteristics can lead otherwise similar economic shocks to have disparate impacts across political borders. Second, newly enacted policies of interest can be correlated with unobserved ones. Both problems can lead to bias in DiD estimates.
Distributions of Uncertainty: Ambiguity and Probability Weighting
I examine the necessary conditions for rank dependent utility maximizers to be ambiguity averse or seeking when facing various distributions of possible event probabilities.