DOMESTIC DEBT, INFLATION AND ECONOMIC CRISES: A PANEL COINTEGRATION APPLICATION TO EMERGING AND DEVELOPED ECONOMIES
Bibliographic record
Abstract
The paper aims to investigate the economic relationship between inflation and domestic debt. In countries that experience high inflation, the inflationary process fed on increasing costs of domestic debt. As a result, the increasing debt to GDP ratios led these countries to borrow at higher interest rates and with lower maturity rates. The paper aims to divide countries into three groups. First group consists of Mexico, Turkey and Brazil; countries with high inflation experiences which result in increasing costs of domestic debt. Second group consists of Belgium, Canada and Japan, low inflation rates, low costs of borrowing. Third group consists of Portugal, Greece and Spain, countries with low inflation, high borrowing with low costs of borrowing and fiscal discipline. It is observed that, increasing costs of borrowing is epidemic to those with Non-Ricardian fiscal policies. As a result, it is not the rate of domestic debt/GDP ratio but the cost of borrowing and active fiscal regimes that lessens the immunity of emerging economies to the economic crises. Another important result that cannot be avoided is the fact that, FMOLS and DOLS methods followed in the study resulted in similar estimates for some countries, whereas we also observe very different estimates for others.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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 source (direct Gemma or distilled Codex), 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".