Counterpart funding requirements and the foreign aid procyclicality puzzle
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Official development assistance is a key source of external finance in many developing countries. A striking feature of these aid flows is their positive correlation with business cycles in recipient countries. This pattern is puzzling in that it reinforces recipients’ already strong and costly macroeconomic fluctuations. We propose a simple model of investment financing and aid provision under asymmetric information that rationalizes such a pattern. We assume that donor agencies and recipient governments value projects differently, and that donors know less than recipients do about project characteristics. We show that donors can make a recipient government identify high-return projects by requiring that the latter contribute some of its own funds to projects. Providing these matching grants or ‘counterpart funds’ is less affordable for recipients during economic downturns, which leads to aid procyclicality. Our model produces aid contracts consistent with those used by aid agencies, rationalizes observed aid patterns, and yields a rich set of testable empirical predictions.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 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 it