A two-edged sword: the impact of public debt on economic growth—the case of Ethiopia
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
This study investigates the dynamic effects of public debt on economic growth in Ethiopia using annual data from 1980 to 2021. The results from the Autoregressive Distributed Lag (ARDL) modeling approach reveal that while public debt boosts investment and enhances growth in the short term, it hinders long-term growth. Additionally, debt servicing negatively impacts growth in both the short and long term by diverting vital resources from investment. Thus, public debt acts as a two-edged sword for Ethiopia’s economic growth. On one side, it finances infrastructure and other growth-stimulating projects; on the other, high debt levels can impede growth. To mitigate the adverse impacts of public debt, Ethiopia should implement prudent fiscal discipline, mobilize domestic revenue, manage debt efficiently, address its structural trade deficit, and prioritize needs to prevent misuse and corruption. This approach should also prioritize social spending and public investment while strategically transitioning from debt dependence.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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