Ex-post and real-time estimations of the output gap: A new assessment of fiscal procyclicality in the eurozone
Bibliographic record
Abstract
The revisions implemented twice a year by the European Commission significantly change not only the forecasts but also the past values of the output gap. Consequently, many possible time series exist. Based on a new approach for estimating a real-time definition of the business cycle, we develop a comparative framework between ex-post and real-time variables using dynamic panel data models with FE, GLS and AB estimators. The real-time version of the output gap solves the important endogeneity issue between the budget balance and the output gap. Considering the period from 1995 to 2021 and the 19 Eurozone countries, our analysis deepens the cyclical nature of fiscal policy, pointing to robust procyclicality. Regardless of the specification, fiscal policy was found to be procyclical, but real-time and ex-post estimates have shown some interesting discrepancies (i.e., on a real-time basis, discretionary budgetary decisions have never been significantly expansionary, and the likely positive effects of automatic stabilisers during economic downturns have been weakened by spending reductions and/or revenue increases). Our findings may help the future reform of the Stability and Growth Pact.
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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 | 0.003 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".