How much do donors care about what their money supports inside a charity? This paper studies preferences over allocating donations to program activity versus organizational overhead. Using a nationwide online experiment with real monetary stakes, I show that donors differ systematically in how they value these allocations. I develop a simple donor utility model that captures this heterogeneity through underlying prosociality and estimate it using a minimum-distance approach. The paper emphasizes transparent experimental design to isolate donor preferences and clarify when aversion to overhead reflects genuine trade-offs rather than misunderstanding or noise.

How do individuals respond when a system is unequal by design and disadvantages others rather than themselves? This paper studies whether people are willing to engage in dishonesty to correct such a system and whether this behavior is viewed as acceptable by others. Using a laboratory bargaining game with exogenously imposed inequality, I combine a clear game-theoretic structure with experimentally identified moral trade-offs.

Donors often express strong aversion to administrative overhead spending. This paper studies how institutional design can incentivize donors to reveal their true tolerance for overhead allocations. I design a donation mechanism that links allocation rules to donor choices under uncertainty, allowing observed behavior to reveal heterogeneous overhead tolerances. The results highlight how charities can account for this heterogeneity in policy design to improve financial sustainability without compromising donor welfare.

Why do people sometimes take risks they privately view as unacceptable? This paper studies how individuals form beliefs about what others do and what others consider socially acceptable in risky driving contexts. Using survey and experimental evidence, I examine systematic gaps between perceived norms and actual norms, and how miscalibrated beliefs are related to risky behavior. The project focuses on separating potential belief errors from preferences to better understand when norm-based interventions are likely to work.