When neighbors tighten belts: Exploring austerity’s spillover effects
Bibliographic record
Abstract
This study investigates the impact of domestic austerity measures and their spillover effects when synchronized among trading partners, focusing on their influence on domestic GDP growth and public debt-to-GDP ratios. Using a novel narrative dataset covering 17 OECD countries from 1978 to 2020 and 14 Latin American and Caribbean countries from 1989 to 2020, the findings reveal that domestic austerity measures significantly depress GDP growth and escalate public debt ratios, while spillover effects from foreign fiscal consolidations can sometimes surpass the impacts of domestic adjustments. Fiscal spillovers affect economic growth in OECD countries and public debt dynamics in the LAC region. Notably, they are particularly pronounced in more trade-open OECD members and during economic downturns in both LAC and OECD countries. Interestingly, OECD countries with lower trade openness and economies going through expansionary phases of the business cycle exhibit positive responses to austerity measures from trade partners. These findings underscore the complex interdependencies in global fiscal policy and highlights the necessity for coordinated approaches to mitigate adverse effects and leverage positive responses during varying economic conditions.
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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 | 0.001 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.020 | 0.001 |
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".