A country's real effective exchange rate (REER) is an important determinant of the growth of crossborder trading and it serves as a measure of its international competitiveness. Studies that have focused on the relationship between REER volatility and FDI inflow have generated mixed results, thus, there is lack of clear-cut conclusion on the relationship. This study assessed the REER volatility and determined its impact on foreign direct investment in Kenya for the period 1972-2015. The study was guided by the Dornbusch overshooting model and adopted correlation Research Design. It relied on secondary data. To overcome methodological deficiencies that could arise from using measures of unconditional volatility, the study focused on Generalized Autoregressive Conditional Heteroskedasticity (GARCH) technique which is a superior measure of uncertainty. Vector Error Correction Model (VECM) was used to establish the relationship between REER volatility and foreign direct investment. Augmented Dickey-Fuller and Phillip-Perron approaches were used to test for the presence of unit roots. The test for volatility conducted using the GARCH model showed that there is persistent volatility in the Kenyan shilling real effective exchange rate with that of the trading partner currencies for the period under consideration and the results of the VAR and VECM indicate a negative and significant impact of real effective exchange rate volatility Original Research Article
A country's real effective exchange rate (REER) is an important determinant of the growth of crossborder trading and it serves as a measure of its international competitiveness. The REER is an active source of discussions in Kenya where questions have arisen revolving around persistent exchange rate shocks and possible interventions. Kenya's vulnerability to the external shocks has increased and the real effective exchange rate has experienced episodes of appreciations. There is scanty information that has specifically focused on the Kenyan's real effective exchange rate (REER). This study carried out an assessment of the real effective exchange rate (REER) volatility in Kenya. The study was guided by the Dornbusch overshooting model and adopted correlation Research Design. It relied on secondary data for the period 1972-2015. To overcome the methodological deficiencies of using the measures of unconditional volatility, this study focused on the conditional volatility employing the GARCH technique that is a superior measure of uncertainty. The Augmented Dickey-Fuller and Phillip-Perron approaches were used to test for the presence of unit roots. It was found that real effective exchange rate in Kenya has been volatile within the period under consideration. These findings will add value to the Dornbusch overshooting model, production Original Research Article
Purpose: Commercial banks in Kenya have put in place several credit policies and strategies to reduce non-performing loans. The capacity of a bank to grow its loan in the year is largely determined by its asset quality and efficiency. Regrettably, the measures put in place by many banks to improve asset quality and efficiency seem to bear little fruits particularly in tier IV commercial banks have been recording declining performance over the recent past. The aim of the study was to establish the influence of credit risk on financial performance of tier IV commercial banks in Kenya. Methodology: The study was guided by scientific theory of management, Transaction cost theory and Contingency theory. This study employed longitudinal research design. The target population was 13 tier IV commercial banks in Kenya as at 2022 from Central bank of Kenya website. A secondary data collection sheet assisted in tabulating secondary data from audited financial statements which were downloaded from the Central Bank of Kenya website. Panel Data analysis technique was employed to establish the relationships through STATA. Findings: Pearson’s product moment correlation coefficient depicted r = -0.4306, p-value of 0.0000 which is significant for credit risk. The regression model had a p-value of 0.0000, indicating that it was significant and reliable. An R2 of 0.3799 was produced by the random effect model indicating that financial imperative contributes 37.99% to financial performance of tier IV commercial banks. The regression coefficients were -0.13 with a p-value 0.004< 0.05), credit risk (CR) and financial performance (ROE) at 5% level of significance. These results indicate that credit risk had significant influence on financial performance. Recommendation: It was recommended that commercial banks should properly manage credit risk; prompt recovery of loans is also recommended to reduce loan impairment charges.
<p>The main objective of the study was to assess the influence of asset quality on the financial performance of tier IV commercial banks in Kenya. The study was guided by the scientific theory of management, Transaction Cost theory and Contingency theory. This study employed a longitudinal research design. The target population was 13 tier IV commercial banks in Kenya as at 2022 from the Central Bank of Kenya’s website. Panel data was analyzed using STATA. Pearson’s product-moment correlation coefficient depicted r = -0.4306, a p-value of 0.0000 which is significant for asset quality. The regression coefficient was -0.14, a p-value of 0.013, for asset quality (AQ) and financial performance (ROE) at a 5% level of significance. These results indicate that Asset Quality had a significant influence on financial performance. It was recommended that commercial banks should use their assets efficiently and effectively to yield optimum results.</p><p><strong>JEL:</strong> G21; G29; G38</p><p> </p><p><strong> Article visualizations:</strong></p><p><img src="/-counters-/edu_01/0567/a.php" alt="Hit counter" /></p>
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