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Record W2997389370 · doi:10.1080/00036846.2019.1708255

Estimation of the rate of return to capital in the East African Community (EAC) Countries

2020· article· en· W2997389370 on OpenAlexaff
Abdallah Othman, Glenn P. Jenkins

Bibliographic record

VenueApplied Economics · 2020
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicCapital Investment and Risk Analysis
Canadian institutionsQueen's University
Fundersnot available
KeywordsEconomicsRate of returnTanzaniaReturn on capital employedCost of capitalCapital (architecture)Return of capitalInvestment (military)Return on investmentReturn on capitalCapital formationFinancial capitalInvestment performanceMacroeconomicsFinanceEconomic growthSocioeconomicsHuman capitalGeographyProduction (economics)Market economy

Abstract

fetched live from OpenAlex

The real rate of return to capital plays a vital part in the economy in evaluating the contribution of capital investment to the economic growth. As it is also a key variable in estimating the economic opportunity cost of capital for use as the economic discount rate in investment decision-making. The objective of this study is to estimate the economic real rates of return to reproducible and remunerative capital of the EAC economies. The results indicate that the real rates of return to reproducible capital over the period 1999–2016 have averaged 10.70% in Kenya and Rwanda, while it averaged 12.05% and 9.86% in Tanzania and Uganda, respectively. With regard to the marginal rates of return to remunerative capital, the results suggest that EAC countries have averaged 16.28%, 16.21%, 15.07% and 14.49% in Tanzania, Rwanda, Kenya and Uganda, respectively, over the same period.

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: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.392
Threshold uncertainty score0.319

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 communication0.0000.000
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 head0.033
GPT teacher head0.197
Teacher spread0.164 · 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

Citations2
Published2020
Admission routes1
Has abstractyes

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