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Record W3000015053 · doi:10.5089/9781513523736.001

Do Fiscal Rules Cause Fiscal Discipline Over the Electoral Cycle?

2019· article· en· W3000015053 on OpenAlex
Kodjovi Eklou, Marcelin Joanis

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueIMF Working Paper · 2019
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicFiscal Policy and Economic Growth
Canadian institutionsCenter for Interuniversity Research and Analysis on OrganizationsPolytechnique Montréal
Fundersnot available
KeywordsEconomicsFiscal policyVolatility (finance)Consumption (sociology)Argument (complex analysis)Fiscal unionSample (material)PoliticsExploitPoint (geometry)MacroeconomicsMonetary economicsPublic economicsEconometricsPolitical science

Abstract

fetched live from OpenAlex

This paper estimates the causal effect of fiscal rules on political budget cycles in a sample of 67 developing countries over the period 1985–2007. We exploit the geographical pattern in the adoption of fiscal rules to isolate an exogenous source of variation in the adoption of national fiscal rules. Based on a diffusion argument, we use the number of other countries in a given subregion that have fiscal rules in place to predict the probability of having them at the country level. We find that in election years with fiscal rules in place, public consumption is reduced by 1.6 percentage point of GDP as compared to election years without these rules. This impact is equivalent to a reduction by a third of the volatility of public consumption in our sample. Furthermore, the effectiveness of these rules depends on their type, their institutional design, whether they have been in place for a long time and finally on the degree of competitiveness of elections.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.120
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.005

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.

Opus teacher head0.029
GPT teacher head0.241
Teacher spread0.211 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it