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Record W4380224684 · doi:10.1016/j.jeca.2023.e00312

Macroeconomic effects of fiscal consolidation on economic activity in SSA countries

2023· article· en· W4380224684 on OpenAlexvenueno aff
Gabriel Temesgen Woldu, Izabella Szakálné Kanó

Bibliographic record

VenueThe Journal of Economic Asymmetries · 2023
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicFiscal Policy and Economic Growth
Canadian institutionsnot available
FundersConsortium pour la recherche économique en AfriqueSzegedi Tudományegyetem
KeywordsEconomicsFiscal policyConsolidation (business)Current accountPrivate consumptionRevenueMonetary economicsBoomUnemploymentMacroeconomicsExchange rateFinance

Abstract

fetched live from OpenAlex

This paper studies the effects of fiscal measures in 40 sub-Saharan countries on economic output, unemployment, consumption, private investment, REER, and current account balance. The study estimates impulse response functions with local projections, based on a yearly dataset covering 40 countries over 2000–2019. The key variable in the dataset is a measure of fiscal stance computed following Blanchard (1993), with a threshold of 1.5%. The study finds that in the short run, fiscal consolidation reduces real GDP and private demand. In addition, the current account balance responds positively to a shock in fiscal consolidation, whereas the real effective exchange rate responds negatively. Moreover, compared with revenue-based consolidations, spending-based consolidations lead to smaller losses in output. Our finding also reveals that fiscal consolidations also depend on economic cycles, with a lower output loss during an economic boom. Finally, this study suggests that fiscal consolidations should be carried out based on spending-based consolidations and have to be preceded by an economic boom.

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.

How this classification was reachedexpand

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.347
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.002

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 head0.021
GPT teacher head0.245
Teacher spread0.224 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designTheoretical or conceptual
Domainnot available
GenreEmpirical

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".

Quick stats

Citations21
Published2023
Admission routes1
Has abstractyes

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