Interest rate and commercial banks’ lending operations in Nigeria: A structural break analysis using chow test

Abstract

This study used the classical least squares method to empirically examine interest rate deregulation effect on the lending operations of Nigerian commercial banks for the period 1970 to 2013. The period was divided into two policy regime periods; the regulated interest rate era spanning 1970-1986 and the deregulated period 1987-2013. The Chow test was applied to examine if there was any significant difference in the relationship between interest rate and commercial banks' lending for the two periods. The empirical result obtained for the interest rate regulation era showed that interest rate spread and statutory liquidity ratio had negative and significant effect on the volume of commercial banks' loans, while fixed exchange rate had negative and insignificant impact on banks' loans and advances. It was found that Monetary Policy Rate (MPR) and inflation rate exert a positive and significant impact on banks' loans for the period. For the deregulation era, the result showed that MPR and the exchange rate had significant impact on banks' loans and advances. While the former exerted a negative impact, the later had a positive influence on loans and advances. Interest rate spread, statutory liquidity ratio and inflation rate were found not to have significantly impacted on commercial banks' loans and advances for the period. The chow test result confirms the impact of deregulation on volume of commercial banks loans and advances due to the deregulation of interest rate. The study submits that, there exist a relatively inelastic relationship between interest rate spread and banks' loans at the deregulated interest rate era. This was largely attributed to imperfections as well as the underdeveloped nature of the financial market. The study suggests that the monetary authority should evolve a guided interest rate deregulation regime with MPR increasingly used to regulate the activities of commercial banks in the area of loans and advances. In order to deepen the financial sector, there is the need to improve financial infrastructure which will enhance commercial bank operations resulting in a more competitive financial market and an improved investment climate in the country.

Determinants of Commercial Banks' Lending Behavior in Nepal

“…Similar results were recorded during the study conducted by Bhattarai (2016) where he found that liquidity ratio correlated negatively with the capital reserve and bank size, somehow collaborating indicators to exchange rates and interest rate spread. In contrast, Eke (2015) reported from his study in Nigeria that there seems to be higher IRS only when there are trends of increasing exchange rate and interest rate spread but with decreasing inflation. This phenomenon could better be conceptualized with the affinity of the borrowers towards low risk of inflation as the major investment these days have, in one way or the other, related to international trade and market.…”

The Influence of Interest Rates Dynamics on Financial Deepening in Nigeria

“…It continued to increase, reaching 4.25 percent between 2000 and 2006, before the banking consolidation reform, and reached 7.39 percent after the reform until the review period of 2020. The financial liberalization theory's theoretical tenet that "high level of interest rates enhances the level of financial deepening" is supported by a considerable interest rate, according to Eke and Inyang (2015). Interest rates are not a reliable indicator of financial repression, according to De Gregorio and Guidotti (1995).…”

The Effect of ROE on the PBV of Toll Road, Airport, Port, and Sub-Sector Companies in the Indonesia Stock Exchange

“…In addition, there are three methods of estimating the regression model using panel data, namely: random effects model based on data characteristics. To select the Panel data regression model, we used the Chow test (Eke, Eke, & Inyang, 2016;Nielsen & Whitby, 2015), Hausman test (Ahn & Moon, 2014;Aït-Sahalia & Xiu, 2019), and Lagrange multiplier test (Chen et al, 2021;Li & Yao, 2021). The regression model (Bernasconi et al, 2021;Sparapani et al, 2021): Hypothesis testing is using the coefficient of determination (adjusted R2), F test, and T test with each probability less than 0.05 (Ongan et al, 2020).…”