MétaCan
Menu
Back to cohort
Record W3126004025 · doi:10.5539/ijef.v5n3p90

Consequential Effects of Budget Deficit on Economic Growth: Empirical Evidence from Ghana

2013· article· en· W3126004025 on OpenAlexvenueno aff
Samuel Antwi, Xicang Zhao, Ebenezer Fiifi Emire Atta Mills

Bibliographic record

VenueInternational Journal of Economics and Finance · 2013
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicFiscal Policy and Economic Growth
Canadian institutionsnot available
Fundersnot available
KeywordsEconomicsCointegrationDeficit spendingNull hypothesisGranger causalityRevenueUnit rootStructural breakBudget constraintSustainabilityGovernment (linguistics)Order (exchange)MacroeconomicsGovernment budgetGovernment revenueCausality (physics)EconometricsEmpirical evidencePublic financeFinanceMicroeconomics

Abstract

fetched live from OpenAlex

The study evaluates budget deficit sustainability of Ghana between 1960 and 2010 using the present value budget constraint approach. By applying annual time series data, the ADF and PP tests for unit root rejected the null hypothesis at 1 percent significance level after first difference. Hence, both government expenditure and revenue of Ghana are stationary and integrated of order one. The Granger causality test supported a bi-directional causation such that both expenditure and revenue of Ghana have temporal precedence over each other. This means past and present values of government revenue provide important information to forecast future values of expenditure. The test for cointegration favored the sustainability of budget deficit of Ghana at 10 percent significance level in the strong sense. In this case, government can continue to service its past accumulated deficits without large future correction to the balance of income and expenditure. Again, the study achieved the conventional negative sign of the speed of adjustment to long run equilibrium following shocks to the system at 5 percent significance level.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.059
Threshold uncertainty score0.872

Codex and Gemma teacher scores by category

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

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.

Opus teacher head0.039
GPT teacher head0.250
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

Classification

machine, unvalidated

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

The models applied no category: nothing in the taxonomy fit this work.
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

Citations19
Published2013
Admission routes1
Has abstractyes

Explore more

Same venueInternational Journal of Economics and FinanceSame topicFiscal Policy and Economic GrowthFrench-language works237,207