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Record W4367681219 · doi:10.1108/cg-03-2022-0136

The influence of external governance mechanisms on the performance of microfinance institutions in Togo

2023· article· en· W4367681219 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueCorporate Governance · 2023
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicMicrofinance and Financial Inclusion
Canadian institutionsUniversité du Québec à Montréal
Fundersnot available
KeywordsMicrofinanceCorporate governanceBusinessAccountingPortfolioSample (material)AuditPanel dataQuality (philosophy)Agency (philosophy)External auditorFinanceFinancial systemEconomicsEconometricsEconomic growthInternal audit

Abstract

fetched live from OpenAlex

Purpose This paper aims to assess the effects of external governance mechanisms on the performance of microfinance institutions (MFIs) in Togo. Design/methodology/approach Using annual time series data from a sample of 30 MFIs during the period 2011–2015, the authors apply panel data econometrics in their estimations. Findings The results indicate that the notation by a rating agency positively and significantly affects the financial return of MFIs. The quality and the regularity of the audits negatively and significantly influence the financial performance (measured by return on assets and operating self-sufficiency) but favorably and significantly influence social performance (increased number of active borrowers (NAB) and reduced size of loans). Furthermore, supervision increases the amount of individual loans but decreases the NAB, which means deterioration in social performance. Overall, this paper shows that external governance mechanisms significantly affect the performance of Togolese MFIs, but with varying effects depending on the mechanism considered. Research limitations/implications The sample size of 30 MFIs is small, and the geographic coverage of the study is restricted to MFIs operating in the city of Lomé, Togo. The authors did not have access to the information regarding the portfolio at risk at 30 days, even though it is a measure of financial performance. Likewise, we did not have access to the appendices to the financial statements for the calculation of prudential ratios. This method, which consists of asking the institutions using a questionnaire if they comply with prudential standards, may be biased because this study cannot verify the authenticity of the responses given that the standards are quantitative. Practical implications The study findings advocate that improving the financial and social performance of MFIs requires improving the quality of external governance mechanisms. MFIs should then pay close attention to well-functioning external governance mechanisms. Social implications As MFIs are key social actors in a society, all mechanisms that contribute to their efficiency benefit society. Originality/value This study contributes to the corporate governance literature by showing that external governance mechanisms influence performance. These external mechanisms are complementary disciplinary measures to internal governance mechanisms and other tools.

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.

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 score0.904
Threshold uncertainty score0.759

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.049
GPT teacher head0.220
Teacher spread0.171 · 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