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Record W3123768626 · doi:10.1504/ijfsm.2014.062292

Cost structure and financial sustainability of microfinance institutions: the potential effects of interest rate cap in Bangladesh

2014· article· en· W3123768626 on OpenAlexaff
Zahid Islam, Marcela Porporato, Nelson Waweru

Bibliographic record

VenueInternational Journal of Financial Services Management · 2014
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicMicrofinance and Financial Inclusion
Canadian institutionsYork University
Fundersnot available
KeywordsMicrofinanceInterest rateSustainabilityBusinessEconomicsFinancePublic economicsEconomic growth

Abstract

fetched live from OpenAlex

This paper examines the cost structures of 215 MFIs reported by the Microcredit Regulatory Authority of Bangladesh with a view to identify the main determinants of sustainability. MFIs in Bangladesh are an important case to study, as it is the first country to introduce an interest rate cap. Using management accounting ideas and frameworks, principally contingency theory to identify components of MFI’s cost structure, this study measures Operational Self Sufficiency (OSS) as the result of administrative costs, financial costs, interest rate spread and size/complexity. The results suggest that there are two key factors that are significantly related to MFI sustainability: interest rate spread and general administrative costs. We conclude that MFIs that have lower administrative costs and a large interest rate spread are more likely to achieve sustainability prior to the introduction of the interest cap.

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)0.001
metaresearch head score (Gemma)0.011
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.027
Threshold uncertainty score0.055

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.011
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.013
GPT teacher head0.240
Teacher spread0.227 · 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

Citations8
Published2014
Admission routes1
Has abstractyes

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