An Empirical Analysis of Productivity Changes in the Ethiopian Commercial Banks: Using DEA- Based Malmquist Productivity Index Approach
Bibliographic record
Abstract
The rationale of this paper is to measure the productivity change of commercial banks in Ethiopia based on DEA-based Malmquist productivity index approach. For this purpose, this study employed a balanced panel data of eight commercial banks operating from 2006 to 2017. The result shows that the banks under study were found to have reported a slight productivity progress of 0.4% over the whole study period. The productivity improvement is accredited to the technological progress (0.9%) rather than the efficiency loss (0.5%). Meanwhile, the finding suggests that the decline in the technical efficiency of the banks was caused both by pure technical efficiency and scale efficiency. Alternatively, the finding of the study indicates that the productivity performance of all the banks under study, with the exception of AIB and CBE, remain almost constant in spite of their size during the period. AIB and CBE have exhibit an average productivity progress of 2% and 1.4% respectively during the study period. In the study period, AIB was found to be the most inefficient (2.4%) and the most productive one (2%) comparing to other banks in the study due to retrogress in scale efficiency change (2.1%) as well as technical progress (4.5%) in that order. Further, the paper suggests that the productivity performance of the banks under study was not significantly different in the period. So, the banks have to move forwards their technology to increase productivity more and more, while improving the resource utilization efficiency by up grading their managerial practices and scale operations (optimum size)
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How this classification was reachedexpand
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 | 0.006 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.006 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".