The Economic Consequences of Financial Audit Regulation in the Charitable Sector
Bibliographic record
Abstract
ABSTRACT I provide evidence on the effects of financial audit mandates in the charitable sector, in particular their influence on donor behavior. My empirical strategy relies on variation in size‐based exemption thresholds across states and differences in size driven by the nature of charities’ activities. Consistent with audit mandates reducing donors’ reliance on charity reputation, I find audit mandates are associated with a lower concentration of donations on the largest, most well‐known charities. I show this reallocation of resources allows the charitable sector to serve more diverse geographic areas and social needs. In terms of the effect on willingness to give, I document that audit mandates are associated with a higher proportion of taxpayers who donate. However, I only observe a sizable impact on total contributions in dollars for charities with high inherent information asymmetry. Collectively, these results suggest financial audit regulation reduces information frictions and thereby affects resource allocation in the market for charitable giving.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.013 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".