p–ISSN: 2723 - 6609 e-ISSN: 2745-5254
Vol. 5, No. 10, October 2024 http://jist.publikasiindonesia.id/
Indonesian Journal of Social Technology, Vol. 5, No. 10, October 2024 4238
Analysis of the Effectiveness of the Interest Rate Path
Monetary Policy Transmission Mechanism on Non-
Performing Loans of Conventional Commercial Banks in
Indonesia in 2018–2022
Yustika Arga Puspita
1*
, Karsinah
2
Universitas Negeri Semarang, Indonesia
Email: [email protected]
1*
2
*Correspondence
ABSTRACT
Keywords: public open
spaces; visitor attraction;
lifestyle center.
Monetary policy is a policy set by the central bank to
influence the circulation of money in the economy, which is
reflected in the development of the money supply, interest
rates, credit, exchange rates, and various other economic and
financial variables. This study aims to analyze the influence
of the implementation of women's rights in the Manpower
Law on the level of welfare of women workers in the
industrial sector. In the context of gender inequality that still
occurs, it is important to explore how existing regulations
can improve women's living and working conditions. This
study uses a quantitative method with a sample consisting of
female workers in several industrial companies. Data was
collected through surveys that assessed the understanding
and implementation of women's rights in the workplace, as
well as their impact on their well-being. Data analysis was
carried out using statistical techniques to test the hypothesis
proposed. The results of the study are expected to provide a
clear picture of the effectiveness of existing policies and
their contribution to improving the welfare of women
workers. The findings are also expected to serve as a
reference for policymakers and companies in formulating
better strategies to support women's rights in the industrial
sector.
Introduction
Monetary policy is a policy set by the central bank to influence the circulation of
money in the economy, which is reflected in the development of the money supply,
interest rates, credit, exchange rates, and various other economic and financial variables
(Anwar et al., 2023). Meanwhile, the monetary policy transmission mechanism is a
process that describes how the monetary policy pursued by the central bank affects
various economic and financial activities so that it can ultimately achieve the final goal
set (Tanjung, 2021). This mechanism is based on the authority of Bank Indonesia which
Analysis of the Effectiveness of the Interest Rate Path Monetary Policy Transmission
Mechanism on Non-Performing Loans of Conventional Commercial Banks in Indonesia in
2018–2022
Indonesian Journal of Social Technology, Vol. 5, No. 10, October 2024 4239
initially determines the BI Rate so that it affects economic variables and the financial
sector before achieving the final goal, namely macroeconomic stability (Asiama &
Amoah, 2019).
The effectiveness of the monetary policy transmission mechanism is a measure of
the extent to which the monetary policy pursued by the central bank can affect the final
goal of monetary policy, namely macroeconomic stability. According to Law Number 4
of 2023 concerning the development and strengthening of the financial sector, the purpose
of effectiveness in the monetary policy transmission mechanism is to achieve
macroeconomic stability, including sustainable or equitable economic growth, low and
stable inflation, and healthy and strong financial stability. According to (Fitriyani et al.,
2023) In Indonesia, monetary policy is transmitted into six paths, namely the direct
monetary channel or money channel, the interest rate channel, the credit channel, the
exchange rate channel, the asset price path, and the expectation path (Zuffar & Rahadian,
2020).
In setting the ultimate target of monetary policy, namely macroeconomic stability,
Bank Indonesia sets the BI Rate policy rate with the policy taken in the form of setting
the BI Rate through the financial sector and influencing short-term and long-term interest
rates. (Shokr, 2020). In this process, effectiveness in influencing policy objectives is very
necessary, considering that there are different influences from each variable that the
monetary policy mechanism goes through. In this case, to measure the effectiveness using
two methods, the first is by financial institutions and non-bank financial institutions. Non-
bank financial institutions include capital markets, insurance, venture capital, pawnshops,
factoring, leasing, and so on. Meanwhile, bank financial institutions consist of central
banks, commercial banks, and people's credit banks, both government-owned and
privately owned. (Bakti & Putri, 2019). According to Faizal, et al. (2020), Indonesia as a
developing country has a financial system that is still dominated by banks. Banks are
financial institutions that are widely known by the public and can encourage economic
activities through the services provided.
Sharia banks are not included in the monetary policy transmission mechanism of
the interest rate path because of Sharia principles that prohibit usury, namely taking
profits from capital without any returns. (Rizal et al., 2019). Riba is haram by law, Islamic
banks consider that interest rates or riba are very influential on the economic crisis and
prone to instability. Therefore, Islamic banking does not use interest rates in calculating
profit-sharing (Duruechi, Chigbu, & Ukpong, 2020). In the monetary policy transmission
mechanism, this interest rate path only uses conventional commercial banks in Indonesia.
Conventional commercial banks, according to the Financial Services Authority (OJK),
are banks that carry out business activities conventionally, refer to national and
international agreements and use the interest rate system in carrying out their activities.
Table 1
Previous Research
It
Author, Year,
Title
Variable
Analysis Tools
Result
Yustika Arga Puspita, Karsinah
Indonesian Journal of Social Technology, Vol. 5, No. 10, October 2024 4240
1
(Koskei & Samoei,
2023) Does
Monetary Policy
Influence Non-
performing Loans
of Listed
Commercial Banks
in Kenya?
-Depend on:
NPL
-Independent:
Benchmark
interest rate,
bill rate,
central bank
interest rate,
and interbank
interest rate
Multiple
Regression
Indicates that the
benchmark interest rate
and bill rate do not
affect non-performing
loans in commercial
banks registered in
Kenya. The results of
this study also show that
central bank interest
rates and interbank
interest rates affect non-
performing loans in
commercial banks
registered in Kenya.
2
(Sari & Septiano,
2024) The impact
of monetary policy
and credit risk on
bank credit
behavior: An
analysis of banks
listed on the
Indonesian stock
exchange
-Depend on:
Investment
Loans,
Working
Capital Loans,
and
Consumption
Loans
-Independent:
Interest Rate,
NPL,
Inflation,
Exchange
Rate, CAR,
and LDR
Generalized
Method of
Moment
(GMM) dan
estimasi
Dynamic-
GMM
Central bank interest
rates hurt these three
types of credit.
Meanwhile, non-
performing loans have a
positive impact on
investment credit and
working capital but hurt
consumer credit. The
interaction between
central bank interest
rates and non-
performing loans
negatively impacts
investment credit and
working capital, but
positively impacts
consumer credit.
Based on the above background, the objectives of this research are:
1. To find out the effect of Bank Indonesia interest rates on Bank Non-Performing Loans
(NPLs) in Indonesia in the short and long term.
2. To find out the effect of Bank Indonesia certificate interest rates on Bank Non-
Performing Loans (NPLs) in Indonesia in the short and long term.
3. To find out the effect of commercial bank lending rates on Non-Performing Loans
(NPL) of Banks in Indonesia in the short and long term.
4. To find out the effect of commercial bank deposit interest rates on Non-Performing
Loans (NPLs) of Banks in Indonesia in the short and long term.
5. To find out the effect of interbank money market interest rates on Non-Performing
Loans (NPL) of Banks in Indonesia in the short and long term.
Analysis of the Effectiveness of the Interest Rate Path Monetary Policy Transmission
Mechanism on Non-Performing Loans of Conventional Commercial Banks in Indonesia in
2018–2022
Indonesian Journal of Social Technology, Vol. 5, No. 10, October 2024 4241
Method
This type of research is a quantitative approach method using descriptive analysis.
The type of quantitative research using the processing of numeric data (numbers) with
statistical methods is the basis of quantitative research. Quantitative research is a type of
research to examines a sample or population with an instrument in the form of data that
has a quantitative nature by testing conjectures or hypotheses. This descriptive analysis
is used to provide an overview of the research results with data in the form of numbers.
The purpose of this study is to find out and analyze the short-term and long-term effects
of the monetary policy transmission of interest rate pathways on the non-performing loans
of conventional commercial banks in Indonesia. This study uses the Error Correction
Model (ECM) method.
Types and Data Sources
The type of data in this study uses data in the form of secondary data with a time
series in the period of January 2018 - December 2022 or as many as 60 months. Secondary
data is data obtained not from the first source in obtaining data or information but using
library studies. This library study comes from various types of sources such as scientific
articles, books, journals, ebooks, and so on that are related to the research written.
Data Collection Methods
This variable research requires techniques in data collection to obtain information
and facts in answering research questions. The data collection used in the form of
secondary data is the technique used in this study. Data is obtained from government
agency sources that have been published or provided. The data type used in this study is
monthly time series data taken in the period 2018M1-2022M12.
The official data used in this study are data collected from the official websites of
government agencies, such as the Financial Services Authority (OJK), Bank Indonesia
(BI), the Central Statistics Agency (BPS), as well as library studies through journals,
articles, and other official agencies. (Campos, 2019).
Data Analysis Methods
The observation years used in this study include 2018M01 to 2022M012. The basis
for the use of the initial year is to meet the basic assumption of 60 observations in
quantitative studies. The analysis method used in this study uses quantitative analysis
using time series data. The model used in this study is the Error Correction Model (ECM)
and as a tool in data processing, namely using the Eviews 12 program. The time series
approach was chosen in processing the variables to be tested using the Error Correction
Model (ECM) analysis technique, namely to find out or obtain an overview related to the
interaction of Bank Indonesia interest rates, interbank money market interest rates, BI
certificate interest rates, general deposit interest rates of commercial banks, and
commercial bank lending rates.
The Error Correction Model (ECM) method restricts the long-term and short-term
relationships between research variables and their cointegration relationships but still
provides the existence of dynamism in the short term. The following are the general
equations of the ECM model:
Yustika Arga Puspita, Karsinah
Indonesian Journal of Social Technology, Vol. 5, No. 10, October 2024 4242
So that the long-term econometric model with the variables that have been
determined in this study is written in the following formal form:
The long-term econometric model with the variables that have been determined in
this study is written in the following formal form:
Several stages of testing need to be passed so that we can determine the use of the
right model for data in conducting this research, namely:
Data Stationary Test
The first stage in estimating the model using time series data is first carried out the
stationarity of the data. The purpose of this test is to obtain a stable mean value and
random error equal to zero so that the regression model obtained has reliable prediction
capabilities and avoids the emergence of spurious regression. Random regression is a
situation where the regression results show a high value of the determination coefficient
(R2) but the relationship between variables in the model has no meaning (Gujarati, 2004).
Stationary data testing is usually used as a unit root test developed by David Dickey
and Wayne Fuller by looking at the probability of Augmented Dickey-Fuller (ADF) by
comparing its critical values (Basuki, 2015). To be able to find out whether the data tested
has a unit root or not, namely by comparing the ADF t-statistic with the Mc Kinnon
critical value.
Hypothesis:
H0 = there is a root of the unit (data is not stationary)
H1 = no unit root (stationary data)
If the t-statistic ADF is greater than the Mc Kinnon critical value (1, 5, 10 percent)
then H0 is accepted or in other words, the data is not stationary. However, when the ADF
value of t-statistic is smaller than the critical value of Mc Kinnon (1, 5, 10 percent) then
H0 is rejected or in other words, the data is stationary (Basuki, 2015). If the results of the
data test are not stationary at the level level, differentiation can be made at the First
Difference level or the next level to overcome this situation.
Cointegration Test
The Cointegration Test is carried out to detect the stability of long-term
relationships between two or more variables. If there is a cointegration between related
variables, it means that there is a long-term relationship between these variables.
Confrontation tests of two or more time series data show that there is a long-term
relationship. Time series data is said to be co-integrated if the residue of the stationary
regression rate, then the regression rate will provide an accurate estimate for the long-
term relationship.
Analysis of the Effectiveness of the Interest Rate Path Monetary Policy Transmission
Mechanism on Non-Performing Loans of Conventional Commercial Banks in Indonesia in
2018–2022
Indonesian Journal of Social Technology, Vol. 5, No. 10, October 2024 4243
Uji Error Correction Model (ECM)
The Error Correction Model (ECM) is a model used to correct regression equations
between variables that are individually not stationary to return to their equilibrium values
in the long term, with the main condition being the existence of a cointegration
relationship between the constituent variables (S.R. Ajija, 2011).
The Error Correction Model is a technique used to correct short-term equilibrium
towards long-term equilibrium, introduced by Sargan and popularized by Engle and
Granger. To use the ECM model, there must be a cointegration relationship between
variables. After that, the ECM model is formed using the residuals of its long-term
equations or cointegrated equations. The residuals of long-term equations are used as
error correction Term (ECT) errors in models that affect short-term equations.
Results and Discussion
Unit Root Test (Stationarity)
In this study, the detection of stationary data was carried out using the Augmented
Dickey-Fuller (ADF) test with a real level of 5%. The purpose of this stationery test is to
find out whether the variables used are stationary/stable or not. This is done to minimize
the occurrence of spurious/false results and lead to wrong conclusions. Data that is not
stationary at the level can be tested again at the first-difference level and so on. If the
prob.* value is less than α = 5%, then the data is stationary. Conversely, if the value of
prob.* is greater than α = 5%, the data is non-stationary.
Table 2
Results of Unit Root Test at Level Level
Variable
Probability
Conclusion
NPL
0.6421
Not stationary
CHOOSE
0.6492
Not stationary
RSBI
0.6258
Not stationary
RKRDT
0.8300
Not stationary
RDEPO
0.0692
Not stationary
RPUAB
0.8161
Not stationary
Source: Secondary data processing results in Eviews 12, 2024
Based on table 2 of conventional commercial banks based on the results of the unit
root test at the level level, shows that all variables have data conditions that are not
stationary at the level level. This can be seen from the value of the prob.* all variables
are greater than α = 5% with a probability value of 0.6421 for the NPL variable, 0.6492
for the BIRATE variable, 0.6258 for the RSBI variable, 0.8300 for the RKRDT variable,
0.0692 for the RDEPO variable, and 0.8161 for the RPUAB variable. So the decision is
to reject Ha and accept H0 which means that all variables are not stationary at the level
level, so the integration degree test is continued.
Cointegration Test
After knowing that the data is stationary at the second difference level, the next
step is to conduct a cointegration test. The cointegration test is used to provide an initial
Yustika Arga Puspita, Karsinah
Indonesian Journal of Social Technology, Vol. 5, No. 10, October 2024 4244
indication that the model used has a long-term relationship (cointegration relation). The
long-term relationship can be detected by knowing the stationarity of the linear
combination between the independent variable and the dependent variable even though
the tested variables are not stationary. The results of the cointegration test were obtained
by forming a residual obtained by regressing independent variables to dependent
variables using the Ordinary Least Square (OLS) method. The residual must be stationary
at the level level to be said to have cointegration. The regression results of independent
variables to their dependent variables are presented in the table.
Table 3
Results of OLS Cointegration Regression Estimation
Variable
Coefficient
Std. Error
t-Statistic
Prob.
C
4.237415
0.344345
12.30573
0.0000
CHOOSE
-0.158241
0.105789
-1.495814
0.1450
RSBI
0.077631
0.052500
1.478686
0.1450
RKRDT
-0.099994
0.048477
-2.062713
0.0440
RDEPO
0.104264
0.024178
4.132271
0.0001
RPUAB
-0.157586
0.077437
-2.035025
0.0468
R-squared
0.854051
F-statistic
63.19853
Prob(F-statistic)
0.000000
Source: Secondary data processing results in Eviews 12, 2024
The table shows the results of long-term estimates for non-performing loans
(NPLs) of conventional commercial banks in Indonesia. From the results of the
estimation, it can be seen that the variables of the lending interest rate (rKRDT), deposit
interest rate (rDEPO), and interbank money market interest rate (rPUAB) have a
significant effect on non-performing loans (NPLs). The results of the analysis of the
influence equation on non-performing loans (NPLs) of conventional commercial banks
are:
1. Effect of the benchmark interest rate (BIRate) on non-performing loans (NPLs)
Based on the table above, shows that the probability value of the variable of the
benchmark interest rate is 0.1450. This indicates that the value of the prob. The
benchmark interest rate > a significant level (α = 0.05% or 5%), namely 0.1450 >
0.05, so it can be concluded that H0 is accepted and H1 is rejected, which means that
the variable of the benchmark interest rate does not have a significant effect on non-
performing loans in the long term.
2. Effect of Bank Indonesia Certificate Interest Rate (rSBI) on Non-Performing Loans
(NPL)
Based on the table above, shows that the variable probability value of the interest
rate of Bank Indonesia certificates is 0.1450. This indicates that the value of the prob. The
interest rate on bank Indonesia certificates > a significant level (α = 0.05% or 5%), which
is 0.1450 > 0.05, so it can be concluded that H0 is accepted and H1 is rejected, which
Analysis of the Effectiveness of the Interest Rate Path Monetary Policy Transmission
Mechanism on Non-Performing Loans of Conventional Commercial Banks in Indonesia in
2018–2022
Indonesian Journal of Social Technology, Vol. 5, No. 10, October 2024 4245
means that the variable interest rate on bank Indonesia certificates does not have a
significant effect on non-performing loans in the long term.
3. Effect of lending interest rate (rKRDT) on non-performing loans (NPL)
Based on the table above, shows that the probability value of the credit interest rate
variable is 0.0440. This indicates that the value of the prob. The lending rate < a
significant level (α = 0.05% or 5%), which is 0.0440 < 0.05, so it can be concluded that
H0 is rejected and H1 is accepted, which means that the lending rate variable has a
significant effect on non-performing loans in the long term. The higher the lending rate,
the greater the risk of non-performing loans in Indonesian banks.
4. The effect of the deposit rate (rDEPO) on non-performing loans (NPLs)
Based on the table above, shows that the probability value of the credit interest rate
variable is 0.0001. This indicates that the value of the prob. The deposit interest rate < a
significant level (α = 0.05% or 5%), namely 0.0001 < 0.05, so it can be concluded that
H0 is rejected and H1 is accepted, which means that the deposit rate variable has a
significant effect on non-performing loans in the long term. The higher the deposit interest
rate, the greater the risk of non-performing loans in Indonesian banks.
5. The effect of the interbank money market interest rate (rPUAB) on non-performing
loans (NPLs)
Based on the table above, shows that the value of the variable probability of the
interbank money market interest rate variable is 0.0468. This indicates that the value of
the prob. The interbank money market interest rate < a significant level (α = 0.05% or
5%), namely 0.0468 < 0.05, so it can be concluded that H0 is rejected and H1 is accepted,
which means that the interbank money market interest rate variable has a significant effect
on non-performing loans in the long term. The higher the interbank money market interest
rate, the greater the risk of non-performing loans in Indonesian banks.
The Kostanta value (C) in modeling has a probability value of 0.0000 which means
that C has a significant influence on modeling. The results of the estimation of the long-
term equation show that R-squared has a value of 0.854051 which means that 85.4051
percent of the non-performing loan (NPL) model can be explained by independent
variables, namely the benchmark interest rate (BIRate), the bank Indonesia certificate
interest rate (CBI), the lending rate (rKRDT), the deposit interest rate (repo), and the
interbank money market interest rate (epub). While the remaining 14.5954 percent is
explained by other variables outside the equation.
The estimation results of the long-term equation show that the F-statistic has a value
of 63.19853 with a probability of 0.000000. This value is smaller than the real level of 1
percent, so it can be concluded that together all independent variables consisting of the
benchmark interest rate (BIRate), the Indonesian bank certificate interest rate (CBI), the
lending rate (rKRDT), the deposit interest rate (repo), and the interbank money market
interest rate (rPUAB) have a significant influence on the dependent variable, namely non-
performing loans (NPL).
Yustika Arga Puspita, Karsinah
Indonesian Journal of Social Technology, Vol. 5, No. 10, October 2024 4246
Model Error Correction Model (ECM)
The Error Correction Model (ECM) model test was carried out to determine the
short-term equation. The formation of the Error Correction Model (ECM) model is
intended to determine the changes in variables between the benchmark interest rate
(BIRate), the Indonesian bank certificate interest rate (CBI), the lending rate (rKRDT),
the deposit interest rate (rDEPO), and the interbank money market interest rate (rPUAB)
which have a significant influence (in the short term) on non-performing loans (NPLs).
A commonly used form of description of the Error Correction Model (ECM) equation is
shown in the formula:
D(NPL) = C (1) + C (2) *D (BIRATE) + C (3)*D(RSBI) + C (4)*D (RKRDT) +
C(5)*D(RDEPO) + C(6)*D(RPUAB) + C (7)*ECT(-1)
Information:
NPL = Non-Performing Loans
C (1) = Constant
C (2) to C(7) = Coefficient of each variable
BIRATE = Benchmark Interest Rate
RSBI = Bank Indonesia Certificate Interest Rate
RKRDT = Lending Interest Rate
RDEPO = Deposit Interest Rate
RPUAB = Interbank Money Market Interest Rate
ECT = Error Correction Model
The output results of the Error Correction Model (ECM) method in this study are
presented in the table:
Table 4
Hasil Error Correction Model (ECM)
Variable
Coefficient
Std. Error
t-Statistic
Prob.
C
0.019659
0.013950
1.409255
0.1647
D(SELECT)
-0.190858
0.084393
-2.261547
0.0279
D(RSBI)
0.004913
0.060995
0.080550
0.9361
D(RKRDT)
0.595974
0.199137
2.992777
0.0042
D(RDEPO)
-0.033464
0.095700
-0.349679
0.7280
D(RPUAB)
-0.069232
0.053271
-1.299614
0.1995
ECT (-1)
-0.469265
0.131328
-3.573230
0.0008
R-squared
0.472141
Adjusted R-
squared
0.411234
F-statistic
7.751846
Prob(F-
statistic)
0.000006
Source: Eviews Output Results 12, 2024 (processed)
Based on the regression results in the table above, it can be known that the model
equation is as follows:
Analysis of the Effectiveness of the Interest Rate Path Monetary Policy Transmission
Mechanism on Non-Performing Loans of Conventional Commercial Banks in Indonesia in
2018–2022
Indonesian Journal of Social Technology, Vol. 5, No. 10, October 2024 4247
D(NPL) = 0.019659 - 0.190858*D(BIRATE) + 0.004913*D(RSBI) +
0.595974*D(RKRDT) - 0.033464*D(RDEPO) - 0.069232*D(RPUAB) - 0.469265*ECT
(-1)
Information:
NPL = Non-Performing Loans
BIRATE = Benchmark Interest Rate
RSBI = Bank Indonesia Certificate Interest Rate
RKRDT = Lending Interest Rate
RDEPO = Deposit Interest Rate
RPUAB = Interbank Money Market Interest Rate
The equation above is a model of non-performing loans (NPL) dynamics for the
short term, where the NPL variable is not only influenced by D(BIRATE), D(RSBI),
D(RKRDT), D(RDEPO), and D (RPUAB) but can also be influenced by the variable error
term et. The value of the coefficient is significant to be placed into a model that serves as
a short-term correction to achieve a long-term equilibrium. The smaller the value of it,
the faster the correction process will be toward long-term equilibrium. Therefore, in the
ECM model, the variable it is often said to be an inertia factor, which is less than zero et
< 0. In this model, the nikai coefficient et is -0.469265 which indicates that the NPL value
is above the long-term value, this value must indeed be negative and significant. This
shows that the error correction term is 46.92%.
Effect of the Benchmark Interest Rate on Non-Performing Loans
In the short term, the benchmark interest rate (BI Rate) has a significant effect on
non-performing loans. If in the short term the benchmark interest rate increases, it will
reduce the risk of non-performing loans so that it will decrease, and vice versa. If in the
short term, the benchmark interest rate decreases, it can increase the risk of non-
performing loans in Indonesian banks. This is in line with the interest rate theory
expressed by Keynes, namely that a high benchmark interest rate will reduce the money
supply (JUB) and credit demand will decrease, as a result of which the demand for money
for speculative purposes will decrease, which will indirectly control the condition of non-
performing loans.
In the long term, the benchmark interest rate (BI Rate) partially has an insignificant
effect. The probability value of the BI Rate variable is 0.1450 because the probability
value must be less than the real level of 5 percent. This shows that an increase or decrease
in the BI Rate in the long term does not affect non-performing loans. The higher or lower
the BI Rate will not have an impact on the increase or decrease in non-performing loans
(NPLs) in the long term. This may also be because credit in the long term is less affected
by interest rate fluctuations, fixed interest rates or long-term agreements with debtors can
stabilize credit payments even if the BI Rate changes. The results of this study support
research conducted by (Ambawani & Wahyudi, 2024) which states that the benchmark
interest rate (BI Rate) does not have a significant effect on non-performing loans. Also,
Yustika Arga Puspita, Karsinah
Indonesian Journal of Social Technology, Vol. 5, No. 10, October 2024 4248
research (Taiwo & Mike, 2021) states that the benchmark interest rate has no significant
effect on non-performing loans.
Effect of Bank Indonesia Certificate Interest Rate on Non-Performing Loans
In the short and long term, the variable interest rate on Indonesian bank certificates
(CBI) does not have a significant effect on non-performing loans. From the results of the
short-term and long-term tests, it is known that the hypothesis was rejected with a
probability value greater than the real level of 5 percent. Although the SBI interest rate is
an important instrument in monetary policy, its effect on non-performing loans in the long
and short term is not significant due to various structural and policy factors that exist in
the banking system and the economy as a whole. This is in line with the Commercial
Loan theory related to bank liquidity, which states that if banks place their funds in Bank
Indonesia Certificates (SBI), it will disrupt bank liquidity and will have an impact on
reducing credit distribution so that it can minimize the existence of non-performing loans.
The results of this study are supported by research conducted (Fajriati et al, 2022)
which states that the interest rate on Indonesian bank certificates does not significantly
affect non-performing loans or NPLs, this is because the interest rate on Indonesian bank
certificates is not responsive in affecting non-performing loans.
Effect of Lending Interest Rates on Non-Performing Loans
In the short and long term, the lending rate variable (rKRDT) has a significant effect
on non-performing loans (NPLs). From the results of the short-term and long-term tests,
it is known that the hypothesis is accepted with a probability value smaller than the real
level of 5 percent. Lending rates are an important variable in analyzing the occurrence of
non-performing loans because high or unstable lending rates can contribute to the
occurrence of non-performing loans. This is in line with the theory expressed by Joseph
Stiglitz, namely that an inappropriate credit rate policy or an imbalance in determining
credit interest rates can affect credit quality and cause non-performing credit risks.
The results of this study are supported by research conducted by (Bahruddin &
Masih, 2018) Which states that lending interest rates have a significant influence on non-
performing loans in the long term and the short term. The results of this study are also in
line with research conducted by (Mahrous et al., 2020) Which states that lending interest
rates have a significant effect on non-performing loans. If the lending rate increases, then
the risk of non-performing loans will also increase.
Effect of Deposit Interest Rates on Non-Performing Loans
In the long term, the deposit interest rate (rDEPO) variable has a significant effect
on non-performing loans (NPLs). Deposit rates can affect non-performing loans in
Indonesian banks in the long term through increased cost of funds, changes in borrower
behavior, and their impact on macroeconomic stability. Banks must balance the interest
rates they offer on deposits to maintain probability and minimize credit risk. High deposit
interest rates are often related to rising credit rates, which will make it difficult for debtors
to pay installments and increase the risk of non-performing loans.
The results of the study are in line with Keynes' theory, namely the theory of
liquidity preference which explains that interest rates are the result of liquidity preference.
Analysis of the Effectiveness of the Interest Rate Path Monetary Policy Transmission
Mechanism on Non-Performing Loans of Conventional Commercial Banks in Indonesia in
2018–2022
Indonesian Journal of Social Technology, Vol. 5, No. 10, October 2024 4249
High deposit rates can increase the cost of funds for banks, which in turn leads to an
increase in lending rates. Higher lending rates can increase the repayment burden for
borrowers, increasing the risk of non-performing loans. Additionally, high interest rates
can reduce investment and consumption, which can negatively impact the economy as a
whole, contributing to an increase in the risk of non-performing loans (NPLs) in the
banking sector.
In the short term, the deposit interest rate does not affect non-performing loans.
This is because banks tend to focus on long-term performance and manage their credit
risk. Borrowers also need time to respond to changes in interest rates. They may not
immediately feel the impact of the increase in deposit rates on their lending rates, so the
risk of default does not increase immediately. This is in line with research conducted by
(Puspita, 2019) stating that deposit interest rates do not have a significant effect in the
short term on non-performing loans (NPLs).
The Effect of Interbank Money Market Interest Rates on Non-Performing Loans
In the long term, the variable interbank market interest rate (rPUAB) affects non-
performing loans (NPLs). Interbank money market interest rates have a significant effect
on non-performing loans in Indonesian banks in the long term due to the higher cost of
funds, challenges in liquidity management, and the impact of unstable macroeconomic
conditions. In the long term, these factors can cumulatively increase the risk of non-
performing loans in the banking sector. High PUAB interest rates are often associated
with unstable economic conditions, in the long run, less stable economic conditions can
affect income and ability to repay loans and increase the risk of non-performing loans.
The results of the study are in line with Joseph Schumpeter's theory, namely
regarding the business cycle theory, the PUAB interest rate often reflects macroeconomic
conditions and business cycles. For example, in deteriorating economic conditions or a
recession, central banks may raise the PUAB interest rate to control inflation or address
economic instability. In these times, many debtors (both individuals and companies) can
experience financial difficulties that make them unable to meet loan repayment
obligations, which in turn contributes to an increase in non-performing loans. It is also in
line with research conducted by (Koskei et al, 2023) which states that interbank market
interest rates have a significant effect on non-performing loans in banks. And also in line
with research (Kasana et al, 2023) which states that interbank money market interest rate
variables have a significant influence on non-performing loans.
In the short term, the interbank money market interest rate (rPUAB) does not have
a significant effect. The probability value of the rPUAB variable is 0.1995, and the
probability value must be less than the real level of 5 percent. Interbank money market
interest rates are more oriented towards funding costs for banks and financial institutions.
While this may affect the bank's operating costs and funding strategies, its impact on non-
performing loans may not be immediately apparent. Banks may adjust their borrowing
costs to customers, but this does not happen quickly or on a large scale that directly affects
the risk of non-performing loans. The results of this study are also in line with research
conducted by (Fajri et al., 2021) which stated that interbank money market interest rate
Yustika Arga Puspita, Karsinah
Indonesian Journal of Social Technology, Vol. 5, No. 10, October 2024 4250
variables do not significantly affect non-performing loans in banks. And it is also
supported by research by (Iqbal et al., 2023) which explains that interbank money market
interest rates do not have a significant effect on non-performing loans (NPLs) in
Indonesian commercial banks.
Conclusion
Based on the analysis of data on the influence of independent variables, namely the
benchmark interest rate (BI Rate), Bank Indonesia certificate interest rate (rSBI), lending
rate (rKRDT), deposit interest rate (rDEPO), and interbank money market interest rate
(rPUAB) on non-performing loans (NPLs) at conventional commercial banks in
Indonesia during 2018 to 2022, it can be concluded that the benchmark interest rate (BI
Rate) does not have a significant influence on non-performing loans in the long term.
Even though it has an effect in the short term. On the other hand, the Bank Indonesia
certificate rate (rSBI) also did not show a significant influence on non-performing loans
in both the long and short term. On the other hand, lending interest rates (rKRDT) have a
significant influence on non-performing loans both in the long and short term.
Furthermore, the deposit rate (rDEPO) shows a significant effect in the long term but has
no effect in the short term. Interbank money market interest rates also have a significant
influence in the long term but have no effect in the short term. Finally, together, the
variables BI Rate, rSBI, rKRDT, rDEPO, and rPUAB have an influence on non-
performing loans both in the long and short term.
Analysis of the Effectiveness of the Interest Rate Path Monetary Policy Transmission
Mechanism on Non-Performing Loans of Conventional Commercial Banks in Indonesia in
2018–2022
Indonesian Journal of Social Technology, Vol. 5, No. 10, October 2024 4251
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