Monetary Policy Implications on Financial Performance of Commercial Banks Listed in the Nairobi Securities Exchange, Kenya
Bibliographic record
Abstract
Commercial banks are regarded as very important players in the financial sector and the economy of a country at large. The study utilized causal research design and utilized panel data for Eleven (11) years from 2007 to 2017 using panel regression analysis. The target population constituted of all the eleven (11) listed commercial banks in Kenya and therefore this implied that a census was adopted. Data was sourced from the audited financial statements of commercial banks from the respective commercial bank’s official websites and CBK statistical bulletins from the CBK’s official website. Data obtained was regressed using the random effect model and the results of the analysis tabulated the results of the study established that that Central Bank Rate and inflation are insignificant to performance while money supply was significant. The study also indicated that capital adequacy had an insignificant moderating effect on the relationship between Central Bank Rate and money supply but significant moderating effect on the relationship between Inflation. Moreover, the study concluded that in absence of prudential regulation, Central Bank Rate and Inflation have insignificant effect on financial performance while Money Supply significantly affects performance. In presence of prudential regulations that dictates the capital buffer, Central Bank Rate, Money Supply have an insignificant moderating effect on the relationship with performance of listed banks while inflation has a significant effect. The results indicated that the CBK should ensure Money Supply is regulated as it affects performance of commercial banks. In the case of capital adequacy banks should engage other profitable ventures as opposed to putting so much capital buffer. This is because in periods of inflation such buffers become depleted and as such lowers the financial performance of commercial banks.
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 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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".