Assessment of Efficiency and Profitability of Listed Banks in Ghana
Bibliographic record
Abstract
The Ghanaian banking industry has had both good and bad times as far as profit is concerned. However, the industry remains good, as evidened from the rising number of other banks from the continent to either merge with the indigenous banks or take over the operation of some of the local banks. In this view this; the study assessed the efficiency and profitability of banks operating in Ghana by using listed banks between the years 2006 to 2011. This quantitative study employed panel data approach using regression analysis to assess the efficiency of banks operating on the Ghana Stock Exchange. The dependent variable is profitability, comprises of return on assets and the size of the firm. The independent variable efficiency also comprises leverage ratio, liquidity ratio, credit risk ratio and profitability ratio. The main source of data employed for this research is a secondary data. The study revealed that 60.74 percent of the variation or changes in the profitability of the banks are accounted for by the independent variables such as the liquidity level, leverage, productivity, credit risk and size of the banks. This was revealed by the coefficient of determination (R 2 ) which shows the amount of variation in the dependent variable as being explained by the independent variables
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".