BANK SPECIFIC DETERMINANTS OF INTEREST RATE MARGINS IN AN ENVIRONMENT OF INTEREST RATE CAPPING AMONG COMMERCIAL BANKS IN KENYA (2016-2019)

Abstract

Among other common forms of government financial control, caps on interest rates have been
declining over the past several decades as most industrialized countries and a rising number of
developing countries continue liberalizing their financial policies. However, in several countries
the last financial crisis reopened the debate on interest rate controls as a tool for consumer
protection. Interest rate margin is one of the critical components in the lending decision process
of commercial banks. Commercial banks are independent business entities that set their own
interest rate margin based on the central bank base rates. The aim of this study was to analyze
bank specific determinants influencing bank margins interest rates in the midst of capping among
commercial banks in Kenya using secondary data for the period 2013 to 2018, a period
characterized by unrestricted and interest rate cap. The specific objectives were to analyze the
influence of: credit risk, capital adequacy, operation efficiency, and liquidity risk and bank size
on interest rate margins. The study adopted exploratory research design. Panel data was
employed using annual data over the period before interest rate, covering 2013-2015, and after
capping of interest rate, covering 2016 to 2018. Thirty-eight commercial banks in Kenya which
were in normal operation as at 31st December 2018 were used giving 228 firm observations.
Interest rate margins was informed by Dealership Model and its extensions while analyzing the
influence of bank specific determinants, that is, credit risk, capital adequacy, operation efficiency
and liquidity risk on interest rate margins. Applying STATA 13.0 employing Dynamic
Stochastic General Equilibrium modeling, Generalized Method of Moments approach was used
in the analysis. Descriptive statistics in form of pie charts, graphs, and summary statistics were
presented. Inferential statistics was analyzed using regression analysis to establish the influence
of bank specific economic determinants on the interest rate margin. The findings would be useful
to policy makers, shareholders, customers in the respective commercial banks in Kenya. The
government could also utilize the findings in making policies affecting commercial banks in
Kenya which could have an impact on interest rate margin.