Global Capital Cycles and Market Discipline: Perceptions of Developing-Country Borrowers
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
Abstract Developing countries are often thought to be particularly exposed to the constraints of global markets. Facing scrutiny from foreign investors, why do developing-country governments enter international bond markets, especially when they can access cheaper finance from international financial institutions? I argue that borrowing governments' perception of market constraints depends on global liquidity. When bond markets are highly liquid, investors become more risk acceptant and governments perceive the political costs of borrowing to be lower, especially compared to the conditionality of concessional loans. I use data on the timing of bond issues and three case studies—Ethiopia, Ghana, and Kenya—to demonstrate that choices to issue debt were shaped by global liquidity. These findings nuance debates about how markets constrain governments, emphasizing that market constraints are conditional on systemic factors, including, global liquidity.
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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 | 0.001 |
| 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 | 0.001 |
| 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