Profit-orientation and efficiency in microfinance industry: an application of stochastic frontier approach
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.
Bibliographic record
Abstract
The aim of this study is to ascertain the effect of the current wave of commercialization of microfinance institutions (MFIs) on their financial and social efficiency. We hypothesize that during the period of analysis, while the for-profit institutions achieve higher levels of financial efficiency, the non-profit MFIs achieve better social efficiency levels. In order to realize the underlined objective of this study, we use a sample of 162 MFIs gathered from Microfinance Information eXchange (MIX) market database, for the period 2007–2013 from 30 countries located in four regions Africa, MENA, Asia and Latin America. The analysis is based on a two-stage model. The first stage consists on classifying MFIs into two groups according to their main orientations (for-profit and non-profit). We design afterward two models to obtain both social and financial estimates for each particular type of MFIs, using the stochastic frontier analysis model. In the second stage, a regression analysis is carried out to determine which variables have an effect on financial and social efficiency.
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Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.003 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it