THE IMPACT OF MONETARY POLICY ON FINANCIAL PERFORMANCE OF INDONESIA COMMERCIAL BANKS: EVIDENCE FROM MAJOR CHALLENGES DURING THE COVID-19

This study investigates the impact of Bank Indonesia through its monetary policy response on financial performance of commercial banks group of business activities 3 and 4 amid the rising of recent global uncertainty and economic shocks due to COVID-19 outbreak. The sample of this study is in the...

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Bibliographic Details
Main Author: Presticha Hedyaratih, Gelischa
Format: Theses
Language:Indonesia
Subjects:
Online Access:https://digilib.itb.ac.id/gdl/view/55062
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Institution: Institut Teknologi Bandung
Language: Indonesia
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Summary:This study investigates the impact of Bank Indonesia through its monetary policy response on financial performance of commercial banks group of business activities 3 and 4 amid the rising of recent global uncertainty and economic shocks due to COVID-19 outbreak. The sample of this study is in the form of balanced panel data that comprises 33 commercial banks in Indonesia over the period of 2016:1 to 2020:3. To control the effect of the monetary policy responses during the COVID-19 pandemic, this study applied a dummy variable. This study used the lagged dependent variables that may indicate appearance of endogeneity and autocorrelation. Therefore, the two-step system GMM was employed to estimate the model specification. This study developed two specification models. The first estimation is panel A where ROA is the dependent variable and the second model namely panel B, ROE acts as a dependent variable. The results show that the lagged dependent variables, monetary policy interest rate, net interest margin, and reserve requirement statistically have a positive impact on bank profitability. The coefficients of monetary policy interest rate (MPR) are positive and statistically significant for both panels, indicating that a decrease in MPR leads to a decrease in bank profitability or vice versa. According to the coefficient result, it implies that the monetary policy shocks have a greater effect on ROE than ROA. ROA in the previous period and BOPO have the largest impact on bank profitability. The COVID-19 pandemic statistically has an inverse relationship with banks’ performance, it indicates that the occurrence of this virus has disrupted the business cycle of Commercial Banks Group of Business Activities 3 and 4 by eroded its ROA and ROE. Contrary to that, NPL, LDR, BOPO, and COVID-19 have an inverse relationship with bank profitability. To that end, this study suggested that Bank Indonesia should continue implementing the expansionary monetary policy to maintain the effectivity of monetary policy transmission in bank lending channel, it is hoped that this decision could resulting in the increase of profitability of commercial banks while hoped that the credit demand side will be interesting hence the net interest margin will be increasing which means it will increase the return on assets as well. Another proposed solution that this study suggested is commercial banks should improve their business in generating profit by transforming into digitized banks. Involving technology and digitalization could be an alternative for Commercial Banks to pursue to be more efficient and to reduce the operating expense regarding the social distancing policy. This study suggests that strengthening the macroprudential policy is a must especially in recession periods like this. Regarding the results of operating expenses to operating income and dummy variables of COVID-19 on ROA and ROE, this study is also highly recommends that Bank Indonesia should strengthen and expand digital acceptance in all regions of the Indonesian archipelago considering these days people need to have minimum physical contact due to the rapid spread of COVID-19, greater public acceptance of noncash payment, and the faster digitalization trend. In order to avoid a biased empirical result and ensure the efficiency and consistency of the two-step SYS-GMM estimator method, this study conducted a fixed effect model regression, Arellano-Bond (AR) test, Hansen test, and the Variance Inflation Factors test.