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Record W1895499342

Microfinance: Debt or Equity? What are the Implications for Profitability and Social Welfare?

2009· article· en· W1895499342 on OpenAlexaff
Ayi Gavriel Ayayi

Bibliographic record

VenueSSRN Electronic Journal · 2009
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicMicrofinance and Financial Inclusion
Canadian institutionsUniversité du Québec
Fundersnot available
KeywordsMicrofinanceBusinessFinanceProfitability indexVenture capitalDebtLoanWelfareEquity (law)Financial systemEconomicsMarket economyEconomic growth
DOInot available

Abstract

fetched live from OpenAlex

We provide a new evidence on a potential best way for a microfinance institution (MFI) to alleviate poverty while remaining financially profitable. Results show that equity contract generate more social welfare and profit than debt contract. By becoming a stakeholder in the micro-venture rather than a lender, the MFI is in a more tightly coupled relationship, providing knowledge and guidance necessary for ensuring success of the venture. A MFI providing micro-equity receives equity in the micro-business in return for his investment, the return on which is entirely dependent the success of the microventure, where as a MFI providing a loan gets paid first whether there is any profit or not. Results also show that microcredit financing places a heavy cash drain on micro-enterprises because the coupon is a precious resource needed to nurture and sustain the growth of micro-enterprises to propel them to the next stage of their development.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.009
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.014
Threshold uncertainty score0.046

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.009
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0010.004
Scholarly communication0.0040.006
Open science0.0010.002
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0140.001

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 head0.285
Teacher spread0.250 · 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 source (direct Gemma or distilled Codex), 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

Citations4
Published2009
Admission routes1
Has abstractyes

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