Effects Of Short Term Interest Rates On Liquidity Of Commercial Banks In Kenya

The role of Banks remain central in financing economic activity and its effectiveness could exert \npositive impact on overall economy as a sound and profitable Banking sector is better able \nto withstand negative shocks and contribute to the stability of the financial system. Banks play \nintermediary role in the economy through channeling financial resources from surplus economic \nunits to deficit economic units. In turn, they facilitate the saving and capital formation in \nthe economy. Liquidity is the ability of bank to fund increases in assets and meet obligations as \nthey come due, without incurring unacceptable losses. Hence, liquidity risk arises from the \nfundamental role of banks in the maturity transformation of short -term deposits into longterm \nloans. Objective of the Study was to examine the effects of short term interest rates on \nliquidity of commercial banks in Kenya. The theories used in this study included: Liquidity \nPreference Theory, The Real Theory (Model) of Interest Rate and Fisher’s Theory of Interest. \nThe current study employed the use of both descriptive survey and historical research designs. \nThe target population for this study was all the 44 listed commercial banks in Kenya as at \nDecember 2015. The study employed the use of document analysis of secondary data. The study \nextracted reports on various variables for the last five financial years (2011 to 2015). Secondary \ndata on the short term interest rates data was collected from financial institutions through their \nquarterly reports and CBK and this was the individual weighted lending rates in proportion to the \nmarket share of the firms. The data on Debt to Equity ratio was collected from the firm’s \nquarterly financial reports and emphasis put on total liabilities and total assets. The operating \nexpense ratio was similarly collected from the firms quarterly financial reports of the firms \nspecifically the operating expenses and the revenue. Secondary data on bank liquidity was \ncollected from banks basically through quarterly reports on cash and cash equivalents balances \nand the value of the total assets. The data collected was sorted, organized and captured in SPSS \nanalysis tool. The study used one way ANOVA to test the level of significant of the independent \nvariables on the dependent variable at 95% level of significance, the one way ANOVA was used \nto test whether there exist any significant difference between the study variable. In addition, the \nstudy conducted a multiple regression analysis. Inferential statistics was analyzed using \nregression analysis to establish the relationship among study variables and to test the \nhypothesized relationships. Inferential statistics was carried out using multiple regression \nmodels. The regression model was used to test the strength of the predictor variables. The study \nfound a weak positive correlation between banks liquidity of commercial banks and short term \ninterest rates. The study also found weak positive correlation between banks liquidity of \ncommercial banks and debt to equity ratio. A negative correlation between banks liquidity of \ncommercial banks and Operating Expense / Revenue was established. The study therefore \nconcludes that short term interest rates, debt to equity ratio and Operating Expense / Revenue are \nnot major determinants of bank liquidity in Kenya. Based on the findings on average, \ncommercial banks in Kenya will register liquidity of negative - 0.422 units if the independent \nvariables were excluded in the estimation model. This implies there are other control variables \nthat affect liquidity of banks which were not considered in the study.