Bibliographic record
Abstract
Do discretionary spending cuts and tax increases hurt social well-being? To answer this question, we combine subjective well-being data covering over half a million of individuals across 13 European countries, with macroeconomic data on fiscal consolidations. We find that fiscal consolidations reduce individual well-being in the short run, especially when they are based on spending cuts. In addition, we show that accompanying monetary and exchange rate policies (disinflation, depreciations and the liberalization of capital flows) mitigate the well-being cost of fiscal consolidations. Finally, we investigate the well-being consequences of the two well-knowns expansionary fiscal consolidations episodes taking place in the 80s (in Denmark and Ireland). We find that even expansionary fiscal consolidations can have well-being costs. Our results may therefore shed some light on why some governments may choose to consolidate through taxes even at the cost of economic growth. Indeed, if spending cuts are to generate a large well-being loss, they can trigger an opposition and protest against a fiscal consolidation plan and hence making it politically costly.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".