ADRRI JOURNAL OF ARTS AND SOCIAL SCIENCES ADRRI JOURNALS (www.adrri.org) VOL. 14, No.6 (2), November, 2016 The Impact of Changes in Monetary Policy Rates on the Lending and Financial Performance of Banks in Ghana Paul Kwame Awuah 1, Emmanuel Addai Kwaning 2 and Mohammed Sfarjilani 3 1 Lecturer, Faculty of IT business; Ghana Technology University College Email:Pkawuah61@gmail.com 2 Lecturer, Faculty of IT business Ghana Technology University College Email: ekwaning@gtuc.edu 3 Graduate School Ghana Technology University College Email: sfarjilani@live.com Correspondence: Pkawuah61@gmail.com Available Online: 30 th November, 2016 URL: https://www.journals.adrri.org [Cite article as: Awuah K. P., Kwaning A. E., Sfarjilani M. (2016). The Impact of Changes in Monetary Policy Rates on the Lending and Financial Performance of Banks in Ghana. ADRRI Journal of Arts and Social Sciences, Ghana: Vol. 14, No. 6(2), Pp. 1-21, ISSN: 2026-5204, 30 th November, 2016.] Abstract This research examines the impact of Bank of Ghana policy rate on commercial bank lending and their financial performance. It assesses the degree of responsiveness of the Commercial Bank Lending to changes in the central bank policy rate and the overall impact of the policy rate on the financial performance variables of the banks. The study first observes the Central bank of Ghana s policy rate movement over the past five (5) years. It focuses on licensed banks in Ghana as the population and obtained a sample size of 10 banks using a stratified sampling technique. Quantitative research approach was used to assess the relationship and multiple regression techniques were employed for the quantitative analyses. The results of the finding was significant positive relationship between monetary policy rate on banks lending implying that an increase in policy rate generally leads to an increase in commercial bank lending rate. However contrary to our expectation we also observed a positive significant impact of monetary policy rate on bank loans and advances, we therefore reject the hypothesis 1
that increasing policy rate leads to a fall in commercial bank lending (In the case of Ghana) With respect to financial performance the results showed no significant impact on profitability and efficiency as the increase in the rates are generally passed on, however there is a significant adverse impact of an increase in policy rate on the liquidity position of the banks. Keywords: commercial bank lending, monetary policy, Policy rate INTRODUCTION The 2002 bank of Ghana act mandates that the primary role of the central bank s monetary policy is price stability. The act led to the creation of the Monetary Policy Committee (MPC) as a preliminary requisite for the transition to inflation targeting. Before the shift from the traditional monetary policy framework to the inflation targeting framework in 2002 the government had to ensure other essential changes to the financial system including the liberalization of interest and exchange rate controls. (Addison, 2008) Among the monetary policies applied from time to time one of the most significant particularly in Ghana is the policy rate. The general rationale for implementing monetary policy through raising or lowering interest rates is to influence the demand for goods and services in the economy in order to achieve the desired level of inflation and employment. The volatility of inflation in Ghana has necessitated several significant changes in the Central Bank policy rate over the last five (5) years, starting with a decline in the first two years followed by consistent increases in the succeeding three years. In the words of Ologunde et al. (2006), interest rate along with monetary aggregates formed targets of monetary policy in Ghana. Using the direct monetary policy measures, the monetary authorities directly influence items of the balance sheet of commercial banks. In such a system, interest rates are set and credits are allocated by monetary authorities in accordance with the government s economic plan. 2
The shift from free monetary policy implementation to the new framework was intended to minimize over-reaction to temporary shocks. Another advantage of inflation targeting framework is that it is not dependent on the stability of money demand (Mishkin, 1999). Considering that monetary policy transmits through bank lending channels it is assumed that banking industry has been significantly influenced by the fluctuations in policy rate The specific objectives of this research are i. To analyze the trend of Bank of Ghana monetary policy rate over the past five (5) year period. ii. To assess the impact of changes in monetary policy rate on the lending rate and loan portfolio of commercial banks in Ghana iii. To determine the impact of monetary policy rate on the financial performance of commercial banks in Ghana. Research Questions i. What is the trend of Bank of Ghana monetary policy rate in the past five (5) year period? ii. What is the impact of changes in monetary policy rate on the lending rate and loan portfolio of commercial banks in Ghana? iii. What is the impact of changes in monetary policy rate on the financial performance of commercial banks in Ghana? Hypotheses Given the objectives, the following hypotheses were tested. Hypothesis 1 H0: There is no significant impact of changes in monetary policy rate on banks lending rate H1: There is a significant impact of changes in monetary policy rate on banks lending rate 3
Hypothesis 2 H0: There is no significant impact of changes in monetary policy rate on the issue of loans and advances by commercial banks. H1: There is a significant impact of changes in monetary policy rate on the issue of loans and advances by commercial banks. Hypothesis 3 H0: There is no significant impact of changes in monetary policy rate on banks return on Assets H1: There is a significant impact of changes in monetary policy rate on banks return on Assets Hypothesis 4 H0: There is no significant impact of changes in monetary policy rate on banks operating profit margin H1: There is a significant impact of changes in monetary policy rate on banks operating profit margin Hypothesis 5 H0: There is no significant impact of changes in monetary policy rate on banks loans to deposits ratio H1: There is a significant impact of changes in monetary policy rate on banks loans to deposits ratio The role of the financial sector in economic development cannot be overemphasized. They mobilize savings, provide long and short term finance, and facilitate trade among many others. There is therefore the need to ensure that the banking industry; at the heart of the sector performs viably and all possible threats to the sector are well considered. The commercial banks would benefit immensely from this study as a guiding principle to managing their affairs in response to the volatility of central bank monetary policy. This can only be achieved with a comprehensive understanding of the role and extent to which the central bank monetary policy influences their trade and impacts their financial performance. 4
This would also allow them be proactive in dealing with the influences and assessed risk of future changes in policy rates. This research would also be beneficial to Policy makers and the government of Ghana by providing a greater understanding of the impact of their monetary policy rate measures on the commercial banks. An appropriate analysis of monetary shock transmission mechanisms is of crucial importance for central banks. This is to determine the process through which monetary policy influence the entire economy within the financial system framework. This study would also benefit researchers and students as a reference into further studies. LITERATURE REVIEW. Several studies have been conducted in other countries to assess the relationship between monetary policy and bank lending and various stylized facts about bank portfolio behavior have emerged from this line of research (Bernanke and Blinder, 1992; Romer and Romer, 1990). Most of the research on bank lending made use of aggregate time series data. Some studies examined the change in the portfolios of commercial banks during periods of monetary tightening; Keeton, (1979); Stiglitz and Weiss, (1981). There are other studies that have examined changes in the price and non-price terms of lending ; Romer and Romer 1990; Bernanke and Blinder (1992); Gertler and Gilchrist (1993). Their study concluded significant relationship between economic variables such as money supply and policy rate and bank lending.it was observed that the Central Bank prime rate and inflation rate negatively affect bank lending. Policy rate was found to be statistically significant while inflation was insignificant. Based on the firm level characteristics, their study revealed that bank size and liquidity significantly influence bank s ability to extend credit when demanded. In contrast to the study by Gertler and Gilchrist (1993), Kashyap and Stein (1995) in their research in Indonesia find evidence that a tightening of monetary policy does not evenly affect 5
bank lending. They examined the lending behavior of banks; small and large and deduced that when monetary policy is tightened, business loans as well as total loan value at small banks fall significantly, on the other hand loans at large banks were not significantly affected. Friedman, M.(1995) observed that a tightening of policy results in a direct fall in bank transactions deposits or core deposits, total bank loans also decline, but not directly, the effect on total bank loans is usually realized after a time lag of two to three quarters. Generally people choose to be more liquid at lower interest rates hence a negative relationship exists between the bank deposits and the policy interest rate exists. In the case of Ghana very few studies have sought to examine the impact of monetary policy on bank lending. One key research was that of Amidu and Wolfe (2008) between 1998 and 2004. The empirical testing made use of the model of Ehrmann et al. (2003) however it was adapted to consider multiple policy instruments. The result was the regression model below: Lendιτ = β0 + β1gdpg + β2inftι + β3rateτ + β4msupτ + Sizeιτ + Liqq+ e ιτ where: Lendιτ = loan and advances to total assets for firm i in period t; Gdpg = the growth of GDP in period τ; inftι = the inflation rate in period τ; rateτ = the central bank policy rate in period τ; Msupτ = the change in money supply in period τ; Sizeιτ = log of total assets for firm ι in period τ; Liqq = cash and cash equivalent to asset for firm ι in period τ; e ιτ = the error term for firm ι in period τ. The results showed a positive relationship between the GDP growth and bank loans and a negative relationship between inflation and bank loans. This was consistent most previous studies. However with respect to the relationship between policy rate and bank loans the result was an insignificant relationship. This result was quite surprising as it nullifies the role of monetary 6
policy rate in the influence of bank lending channels and downplays its practical usefulness in managing aggregates in the economy. Amidu and Wolfe (2008) approach however focuses solely on total loan value as the only dependent variable and neglects the impact on lending rates and deposits. Also the use of the multiple regression model which was derived from altering Ehrmann et al. (2003) model; originally intended to analyze a single independent variable may have compromised the findings. Khawaja and Din (2007) also examined to what extent macro-economic variables influence the Interest Rate Spread in Pakistan. His study used a panel data of 29 banks. The result of the study was that the share of interest-insensitive deposits in total bank deposits is a key determinant of interest spread. On the other hand the results also concluded that industry concentration has no significant impact on interest spread. This is inconsistent with theories on the subject particularly Goddard et al. (2001). Other earlier studies including Barajas et al. (1996) had shown a significant influence of loan market power on the interest spread. Elkayam (1996) observes that in a competitive banking system. The interest rate spread derives solely from central bank variables while under a monopolistic structure the interest rate spread is in addition affected by elasticity of demand for credit and deposits. He also found that there was more market power in the credit market than the deposit market. There is some evidence of price rigidity in local deposit markets with decrease in deposit interest rates being more likely than increases in these rates in the face of changes in the market interest rate (Hannan and Berger, 1991). One reason for such behavior is market concentration. The market-specific determinants of commercial bank interest rate spreads highlighted in the literature typically include lack of adequate competition in the banking sector and consequent market power of commercial banks, the degree of development of the banking sector, and explicit and implicit taxation such as profit taxes and reserve requirements. 7
Another study by Elkayam (1996) considered monetary policy,its impact on money supply and interest spread of the banking sector found that an increase in money supply under elastic demand reduces the spread more in a monopolistic than in a competitive market. Other studies have also examined the other determinants of commercial bank interest rate spreads to include the efficiency of institutions in the country. It was established that as institutional factors improve interest rate spreads for Banks tend to fall. Such factors include the legal system, contract enforcement, and the levels of corruption, which form part of the critical elements of the basic infrastructure needed to support efficient banking. According to Gambacorta (2004), changes in monetary policy can affect deposit and lending rates through the interest rate, bank lending and bank capital channels. For instance, a monetary tightening that raises policy rate and short term interest rates makes it more costly for banks to get funds and they pass these costs to borrowers through higher lending rates. The bank lending channel works through moral hazard and adverse selection. Following monetary tightening that leads to higher interest rates, banks tend to attract more risky customers and to compensate for the higher risk they increase lending rates. Kashyap and Stein (1995) found evidence that banks lending may respond to a tightening of monetary policy. This finding was confirmed in more recent studies ; Barseghyan (2010) and Caballero et al (2008) in Japan. However their observation was that small and large banks reacted differently to a change in monetary policy. While loans in large banks were not significantly altered the smaller banks witnessed a tremendous fall in business loans and total loans altogether. The varied reaction result was believed to be an indication of different funding channels. Small banks generally have less access to alternative funding sources as compared to large banks and hence are more prone to the effect of the loss of core deposits during periods of policy tightening. 8
Earlier on Gertler and Gilchrist (1994) had found evidence that banks lending does not decline when policy is tightened. They concluded that the entire decline in total lending comes from a reduction in consumer and real estate loans. With respect to the impact on profitability research work by Caballero et al (2008) concluded a significant negative effect of monetary policy rate, reserve requirements and statutory ratio on commercial bank profitability.these findings were consistent with the work of Gambacorta and Lannoti (2005) which sought to investigate the velocity and asymmetry in response of bank interest rates (lending, deposit, and inter-bank) to movements in monetary policy between the years 1985 to 2002. Punita and Somaiya (2006) also carried out a study on the impact of monetary policy on the profitability of Indian banks between the years 1995 to 2000. The study involved a regression analysis using the variables banks rate, lending rates, cash reserve system and statutory ratio, where each was regressed on banks profitability independently. From their study it was observed that a significant direct positive relationship existed between lending rates and commercial bank profitability. METHODOLOGY. The population of a study involves all components with similar characteristics that could be considered for the study. The population for the study is commercial banks in Ghana. As at the end of 2014, the cut-off period being considered for the study, there were twenty-four licensed banks in Ghana (Bank of Ghana, 2015); which therefore constitutes our population. Sampling was based on the market share controlled by banks in terms of deposits as at 2014. The total list of banks were sorted in terms of deposits from the highest to the lowest for 2014, and divided into two equal strata of 12 banks each. The top five banks in the upper stratum were selected together with the top five banks in the lower stratum. A total of 10 banks were therefore selected to make the sample and their financial data was collected and collated for the 5-year period ending 2014. 2014 was used as the cut-off point 9
because as at the time of sampling some of banks had not yet published their financial statements for 2015. The use of 10 banks representing almost half of the total population size increased the reliability of the findings under the research. The source of data for the study was secondary data. This is because all the information required for the analysis are historical in nature and readily available. The data consisted of quarterly and annual reports of the selected banks which included their audited financial statements as well as other information relating to their performance. This was obtained from their official websites and the Ghana stock exchange (In the case of listed banks). Other relevant financial information were obtained from verifiable sources such as the PWC banking surveys, newspapers and official websites to support the analysis. 10
The Research Model The general form of the model employed by this study is given as: DV = f(mpr, DEP, ) Where: DV represents the dependent variables lending rate and financial performance. Financial Performance was analyzed by Operating Profit Margin (OPM), Return on Assets (ROA), Loans to deposits (LTD) and Advances (ADV); MPR and DEP represent Monetary Policy rate and Deposits respectively. The specific forms of the model are given below as: LR = b 0 + b 1 MPR + b 2 DEP + ε (1) ADV = b 0 + b 1 MPR + b 2 DEP + ε (2) ROA = b 0 + b 1 MPR + b 2 DEP + ε (3) OPM = b 0 + b 1 MPR + b 2 DEP + ε (4) LTD = b 0 + b 1 MPR + b 2 DEP + ε (5) ε = represents the error term or residual term of the model. RESULTS AND DISCUSSIONS Descriptive Statistics Table 1 It shows the mean, standard deviation, minimum, and maximum for the period. Average lending rate for the period was 22.9% and monetary policy rate was 15.2%. Average return on assets was 121%, operating profit margin was 12.1%, loan portfolio size was 5.8 [an equivalent of about GH 680,000,000]. 21
Quantitative Statistics The quantitative statistics are done through multiple regression techniques to estimate the models developed in the methodology section above. The results are discussed based on the hypothesis developed for the study. Hypothesis 1 Table 2. Below shows the regression results for impact of monetary policy rate on lending rate with deposits as control variable as expressed in model 1.A positive significant impact of monetary policy rate on banks lending rate was observed. we therefore reject the null hypothesis that there is no significant impact of monetary policy rate on lending rate of banks in Ghana. This results is inconsistence with research of that of Amidu and Wolfe (2008) Hypothesis 2 Table 3 below shows the regression results for impact of monetary policy rate on banks loans and advances generated by banks, with deposits as control variable as expressed in model 2. A positive significant impact of monetary policy rate on banks loan and advances was observed. We therefore reject the null hypothesis that there is no significant impact of monetary policy rate on loan and advances granted by banks. This results is consistent with findings by Gambacorta (2004) Hypothesis 3 Table 4 below shows the regression results for impact of monetary policy rate on return on assets with deposits as control variable as expressed in model 3. A negative insignificant impact of monetary policy rate on banks Return on Assets was observed. we therefore accept the null hypothesis that there is no significant impact of monetary policy rate on banks return on assets in Ghana. This results is consistent with the research by Caballero et al (2008). 21
Hypothesis 4 Table 5 below shows the regression results for impact of monetary policy rate on banks operating profit margin with deposits as control variable as expressed in model 4. A positive insignificant impact of monetary policy rate on banks operating profit margin was observed we therefore accept the null hypothesis that there is no significant of monetary policy rate on banks operating profit margin in Ghana. Hypothesis 5 Table 6 below shows the regression results for impact of monetary policy rate on banks liquidity with deposits as control variable as expressed in model 5 A positive significant impact of monetary policy rate on banks liquidity was observed.. A positive significant impact of monetary policy rate on banks liquidity was observed. We therefore reject the null hypothesis that there is no significant impact of monetary policy rate on banks liquidity. CONCLUSIONS Government s aim of monetary policy regulation is to control money supply, and affect lending especially to the private sector among other objectives. The central bank would therefore have to reconsider its monetary policy stance to spare the policy rate of too frequent manipulations which are not yielding the expected responses in the availability of credit in the economy. Generally although the central bank policy rate can improve the short-run behaviour of inflation through its impact on general lending rates, the achievement of long run stability is dependent on effective management and control of all monetary aggregates in the economy. 21
REFERENCES Amidu, M., & Wolfe, S. (2008) Bank competition, diversification and financial stability, SSRN Electronic Journal,. Friedman, M. (1995). The role of monetary policy. Macmillan Education UK. Gambacorta, L., & Mistrulli, P.E.( 2004)_. Does bank capital affect lending behavior? Journal of Financial intermediation, 13(4), pp.436-457. Gerali, A., Neri, S., Sessa, l., & Signoretti, F.M. (2010) Credit and banking in a DSGE model of the Euro area, Journal of Money, Credit and Banking, 42, pp. 107 141. Gertler, M., & and Gilchrist, S. (1994) Monetary policy, business cycles, and the behavior of small manufacturing firms, The Quarterly Journal of Economics, 109(2), pp. 309 340. Goddard, N., Bonnet, G., Krichevsky, O., & Libchaber, A. (2001) Goddard et al. Reply:, Physical Review Letters, 88(6). Hannan, T.H., & Berger, A.N. (1991). The rigidity of prices: Evidence from the banking industry. The American Economic Review. 81(4), pp.938-945. Kashyap, A.K., & Stein, J.C. (1995) The impact of monetary policy on bank balance sheets, Carnegie-Rochester Conference Series on Public Policy, 42, pp. 151 195. Keeton, W.R. (1979). Equilib Credit Ration. Dissertations-G. Lee, C.C., & Chen, P.F. (2013). How does diversification impact bank stability? The role of globalization, regulations, and governance environments. Asia Pacific Journal of Financial Studies. 42(5), pp.813-844.. Michalski, G. (2008) Representational handling of Poznań-Cracow voicing in government phonology, Poznań Studies in Contemporary Linguistics, 44(3). Mishkin, F.S. (1999) Lessons from the Asian crisis, Journal of International Money and Finance, 18(4), pp. 709 723. Ologunde, A.O., Elumilade, D.O., & Asaolu, T.O. (2006). Capital budgeting and economic development in the third world: The case of Nigeria. International Research Journal of Finance and Economics, 2(2), pp.136-152. Schwaiger, M. S., & Liebig, D. (2008) Determinants of bank interest margin in Central 21
and Eastern Europe. Financial stability report. 14. Pp. 68-87. Romer, C.D., Romer, D.H., Goldfeld, S.M., & Friedman, B.M. (1990). New evidence on the monetary transmission mechanism. Brookings Papers on Economic Activity. 1990 (1). pp.149-213. APPENDIX Variable Obs Mean Std. Dev. Min Max LR 50 12.4361 12.43868.16715 28.69 ROA 49.0444819.0299493 -.0418584.0917764 OPM 49.1211593.1595476 -.1641694.4023343 LTD 49.7149195.1930687.3363701 1.08853 ADV 49 5.870261.2892202 5.341433 6.619668 MPR 50 15.25833 1.874839 12.91667 18.5 DEP 49 6.020141.3487505 5.29321 6.636521 Table 1. Descriptive statiscs.. regress LR MPR DEP Source SS df MS Number of obs = 49 F( 2, 46) = 47.83 Model 5019.38305 2 2509.69153 Prob > F = 0.0000 Residual 2413.91561 46 52.4764262 R-squared = 0.6753 Adj R-squared = 0.6611 Total 7433.29866 48 154.860389 Root MSE = 7.2441 LR Coef. Std. Err. t P> t [95% Conf. Interval] MPR 2.047844.6225857 3.29 0.002.7946438 3.301044 DEP -31.94606 3.274672-9.76 0.000-38.53764-25.35449 _cons 173.3989 18.1432 9.56 0.000 136.8785 209.9193 21
Table 2. Model 1 regression. regress ADV MPR DEP Source SS df MS Number of obs = 49 F( 2, 46) = 129.40 Model 3.4091725 2 1.70458625 Prob > F = 0.0000 Residual.605945917 46.013172737 R-squared = 0.8491 Adj R-squared = 0.8425 Total 4.01511841 48.0836483 Root MSE =.11477 ADV Coef. Std. Err. t P> t [95% Conf. Interval] MPR.0228044.009864 2.31 0.025.0029491.0426597 DEP.7079917.0518828 13.65 0.000.603557.8124264 _cons 1.261603.2874549 4.39 0.000.6829865 1.84022 Table3. model 2 regression. regress ROA MPR DEP Source SS df MS Number of obs = 49 F( 2, 46) = 33.92 Model.025656599 2.0128283 Prob > F = 0.0000 Residual.017397535 46.000378207 R-squared = 0.5959 Adj R-squared = 0.5783 Total.043054134 48.000896961 Root MSE =.01945 ROA Coef. Std. Err. t P> t [95% Conf. Interval] MPR.0021039.0016714 1.26 0.214 -.0012605.0054682 DEP.0610627.0087912 6.95 0.000.0433669.0787586 _cons -.355087.0487076-7.29 0.000 -.4531303 -.2570437 Table 4. Model 3 regression Table Error! No text of specified style in document..1: Model 2 Regression Results 21
. regress OPM MPR DEP Source SS df MS Number of obs = 49 F( 2, 46) = 17.55 Model.528876296 2.264438148 Prob > F = 0.0000 Residual.692984189 46.015064874 R-squared = 0.4328 Adj R-squared = 0.4082 Total 1.22186048 48.025455427 Root MSE =.12274 OPM Coef. Std. Err. t P> t [95% Conf. Interval] MPR.0134066.0105487 1.27 0.210 -.0078269.03464 DEP.2656143.0554841 4.79 0.000.1539307.377298 _cons -1.681551.3074075-5.47 0.000-2.300331-1.062772 21
Table 5. Model 4 regression. regress LTD MPR DEP Source SS df MS Number of obs = 49 F( 2, 46) = 13.26 Model.654443233 2.327221617 Prob > F = 0.0000 Residual 1.13478222 46.024669179 R-squared = 0.3658 Adj R-squared = 0.3382 Total 1.78922546 48.03727553 Root MSE =.15706 LTD Coef. Std. Err. t P> t [95% Conf. Interval] MPR.0365955.0134988 2.71 0.009.0094239.0637671 DEP -.3621007.0710008-5.10 0.000 -.5050178 -.2191836 _cons 2.338851.3933771 5.95 0.000 1.547024 3.130678 Table 6. Model 5 regression. Dependent Independent p> t Model Variable variables Coefficients value Implication Monetary Policy Positive, 1 Lending Rate rate 2.047 0.002 significant Level of Deposits -31.94 0.000 Negative, 21
significant Monetary Policy Positive, 2 Loans and Advances rate 0.022 0.024 significant Positive, Level of Deposits 0.707 0.000 Significant Monetary Policy Positive, 3 Return on Assets rate 0.002 0.214 Level of Deposits 0.206 0.000 Monetary Policy Insignificant Positive, significant Positive, 4 Operating Profit Margin rate 0.013 0.210 Insignificant Positive, Level of Deposits 0.265 0.000 significant 5 Liquidity (Loans to Deposits Ratio) Monetary Policy rate 0.036 0.009 Level of Deposits -0.362 0.000 Positive, significant Negative, significant Table 7: Summary of Findings a n A n a n a n a n m a n a n a n m a n a n a n m a n a n a n m a n a n a n a n a n a n m a n a n a n m a n a n a n a n a n a n a n a n a n A n a n a n a 21