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Record W4390753799 · doi:10.5430/ijba.v14n4p52

The Effect of Availability of Foreign Exchange and Devaluation of Birr on the Performance of Companies in Ethiopia (Instance of Sample Company)

2024· article· en· W4390753799 on OpenAlexvenueno aff
K. Kebede

Bibliographic record

VenueInternational Journal of Business Administration · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicAfrican history and culture studies
Canadian institutionsnot available
Fundersnot available
KeywordsDevaluationCurrencyBusinessEconomic shortageSample (material)PopulationForeign exchange marketMonetary economicsProfit (economics)EconomicsDescriptive statisticsGovernment (linguistics)

Abstract

fetched live from OpenAlex

When a country devalues its currency, some firms and countries generally benefit from any resulting changes in relative prices, while other firms and countries are relatively unaffected or suffer a loss in competitiveness. By taking a sample of import and export firms, this study assessed the effect availability of foreign currency and devaluation of birr on performance of firms in Ethiopia in general. More specifically it intended to assess the main challenges to access foreign currencies, assess the effects of foreign currency shortage on import/export firms, assess the effects of devaluation of Birr on import/export firms and assess company-specific factors. The study used both primary (collected through questionnaire) and secondary data collected from financial statements of the companies. This study applies both the descriptive and inferential analysis. After detail analysis, the increase in private driven business, Informal channels of inflow of foreign currency, increased population and Corruption will worsen appropriate use of forex and aggravate challenges of shortage of forex. And also it is found that the foreign currency shortage has affected the firms in many ways such as profit loss, lay off employees and discourages new investment. On the other hand devaluation of birr against the foreign currencies makes Ethiopian commodities to be competitive in international markets. And it can also attract new investments and export.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.437
Threshold uncertainty score0.208

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.035
GPT teacher head0.322
Teacher spread0.287 · 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

Citations1
Published2024
Admission routes1
Has abstractyes

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