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Record W2999162856 · doi:10.5539/ibr.v13n2p62

Impact of Currency Redenomination on an Economy: An Evidence of Ghana

2020· article· en· W2999162856 on OpenAlexvenueno aff
Bright Obuobi, Emmanuel Nketiah, Faustina Awuah, Fredrick Oteng Agyeman, Deborah Ofosu, Gibbson Adu‐Gyamfi, Mavis Adjei, Adelaide Gyanwah Amadi

Bibliographic record

VenueInternational Business Research · 2020
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicFiscal Policy and Economic Growth
Canadian institutionsnot available
Fundersnot available
KeywordsCurrencyEconomicsInflation (cosmology)Descriptive statisticsIndex (typography)Government expenditureBalance of paymentsSample (material)Independence (probability theory)GlobalizationMacroeconomicsStatisticsMathematicsPublic finance

Abstract

fetched live from OpenAlex

The main objective of this study is to ascertain the impact of currency redenomination on the Ghanaian economy. Since independence in 1957, Ghana has had series of redenomination exercises but the recent one which became a debatable topic happened in 2007. As a result, the study is conducted to determine the pre and post-performance of the country using 2007 as the benchmark. This research takes into consideration the quantitative research technique based on ex-post factor design. Secondary data of the research variables (GDP, Economic growth, Balance of trade, inflation, FDI and Globalization index) were used over a 20-year period between 1997 and 2017. Analytical techniques of both descriptive statistics and independent sample test were used for the research. The t-test for equality of means adopted was to determine the statistically significant difference on the economic variables. The study also used the Levene’s test of equality of variance assumed. It was concluded that, currency redenomination is beneficial to an economy’s growth. It was therefore recommended that, the government of Ghana initiates policies that will boost local production to support the exercise so as to increase GDP and other associated economic variables.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.410
Threshold uncertainty score0.739

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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)0.0010.000

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 head0.243
GPT teacher head0.413
Teacher spread0.170 · 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 designObservational
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

Citations11
Published2020
Admission routes1
Has abstractyes

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