Nonprofit Organizations’ Financial Obligations and the Paycheck Protection Program
Bibliographic record
Abstract
We examine nonprofit organizations’ involvement in the Paycheck Protection Program (PPP). The PPP provided participants with forgivable loans to pay employee salaries, increasing participants’ financial flexibility during the pandemic. We examine the associations between nonprofits’ prepandemic financial obligations (e.g., long-term debt and donor-restricted net assets) and PPP participation and participants’ loan characteristics. First, we find nonprofit organizations participated at a lower rate than other small business industries and that nonprofits with greater financial obligations were more likely to participate in the program. Second, we find financial obligations were positively associated with the loan amount received as a percentage of total payroll costs. Last, although approximately 11% of nonprofits failed to obtain loan forgiveness, we find nonprofits with restricted net assets were more likely to have their loans forgiven. Our results suggest nonprofits with greater debt and donor obligations used the PPP to increase their financial flexibility. This paper was accepted by Ranjani Krishnan, accounting. Supplemental Material: The data files and online appendix are available at https://doi.org/10.1287/mnsc.2023.4804 .
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| 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".