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Record W1996784084 · doi:10.5539/ijef.v6n8p161

Does Foreign Capital Crowd–Out Domestic Saving in Developing Countries? An Empirical Investigation of Ghana

2014· article· en· W1996784084 on OpenAlexvenueno aff
Barnabas Nartey Angmortey, Patrick Tandoh-Offin

Bibliographic record

VenueInternational Journal of Economics and Finance · 2014
Typearticle
Languageen
FieldSocial Sciences
TopicInternational Development and Aid
Canadian institutionsnot available
Fundersnot available
KeywordsForeign direct investmentShort runEconomicsCapital (architecture)Investment (military)Work (physics)Developing countryCapital deepeningCapital Consumption AllowanceCrowding outForeign capitalMonetary economicsCapital formationCapital flightFinancial capitalInternational economicsMacroeconomicsMarket economyHuman capitalEconomic growth

Abstract

fetched live from OpenAlex

Savings in Ghana like most developing countries is very low. This poses problems to investment spending and accelerated economic growth due to lack of capital formation. The trend has been to use foreign capital as the source of development. This work tries to examine the contribution that foreign capital has had on the Ghanaian economy. Precisely, the work examines the effect of foreign capital on domestic savings. More precisely, it examines the effect of foreign direct investment, foreign aids and grants and foreign commercial borrowing on domestic savings. The study uses the co-integration technique for the estimation of the long-run and the Error Correction Model (ECM) to estimate the short-run dynamic savings model in Ghana. The outcome of the study shows that there is a positive and significant effect of foreign capital on real domestic savings in Ghana in the long run, though not steady but volatile. The short-run dynamic model revealed that foreign capital has no significant effect on real domestic savings in Ghana in the short-run. The three components of foreign capital do not therefore displace domestic savings both in the short-run and the long-run. The policy implications are that, Ghana must rely more on foreign direct investment by improving on the locational advantages. Again, the capital market must be strengthened to provide an avenue for investing the profits of firms to prevent capital flight.

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)0.000
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.389
Threshold uncertainty score0.205

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.021
GPT teacher head0.293
Teacher spread0.271 · 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

Citations7
Published2014
Admission routes1
Has abstractyes

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