Page 140 - FREN-C2021 PROCEEDINGS

the Indian banking sector from 1997 to 2009. The empirical finding revealed that the real GDP growth
rate had an insignificant effect on NPLs.

Inflation and Non-Performing Financing
Shingjergji (2013) considered interest rate in the total loan, credit growth, inflation rate, real exchange
rate and GDP growth rate as the factors NPLs in the Albanian banking system. The study used the
OLS regression model for panel data throughout 2002 and 2012. It was found that the inflation rate
has insignificant effects on the NPLs in the Albanian banking system. Similarly, Swamy (2012) also
found that inflation had insignificant effects on NPLs based on his study of the macroeconomic and
indigenous determinants of NPLs in the Indian banking sector by using panel data analysis from 1997
to 2009.

The correlation and regression analysis method was carried out by Muhammad, Ammara, Abrar, and
Fareeha (2012) in their study entitled Economic Determinants of Non-Performing Loans: Perception
of Pakistani Bankers. They used primary and secondary data in the year 2006 from 201 bankers. The
independent variables used were interest rate, energy crisis, unemployment, inflation, GDP growth,
and exchange rate. They pointed out that the inflation rate has a significant positive relationship with
non-performing loans. Nurnaningtyas and Purwohandoko (2018) studied the effect of gross domestic
product, inflation, interest rate, profitability and capital adequacy ratio on non- performing loans in a
variety of banks covering the period of 2012 to 2015. The analytical method used in their study is
linear multiple regression analysis. The research results showed that inflation does not affect NPLs
and that any changes in this variable do not affect the value of the NPLs.

Balance of payment and Non-Performing Financing
Ouhibi and Hammami (2015) studied the factors influencing non-performing loans in the Southern
Mediterranean countries over the period from 2000 to 2012. By applying the ordinary least square
(OLS) regression model as their method of analysis, the empirical result revealed that government
deficit/surplus has an insignificant relationship with the non-performing loan. On the other hand,
Makri, Tsagkanos and Bellas (2014) identified the factors that influenced non – performing loans in
the Eurozone banking system over the period from 2000 to 2008. Macroeconomic variables are used
in this study to explain NPL is GDP growth rate, public debt as % of gross domestic product,
unemployment rate and the government budget deficit/surplus. By using the GMM estimator, the
result showed that there is a negative relationship between government budget deficit/surplus with
NPL. Kozlow (2003) in his work entitles Selected Issues on the Treatment of Nonperforming Loans in
Macroeconomic Statistics pointed that government deficit/surplus has a significant impact on non-
performing loans.

Money Supply and Non-Performing Financing
Nursechafia and Muhamad Abduh (2014) examined the key macroeconomic variables that influence
the credit risk rate in the Indonesian Islamic banking sector from October 2005 until May 2012. They
used NPF as a proxy for credit risk. The result showed that in the long run, the money supply has a
positive effect on the non-performing financing (NPF) in the Indonesian Islamic banking sector. The
same result with Leka, Bajrami and Duci (2019) found a similar result i.e. M2 has a positive
connection with the level of NPLs, meaning that although the money in the economy is increased, its
efficiency has been weakened, or although the level of loans has increased, a part of them are turned
into non-performing loans because of the wrong credit judgment, or as problems in any sector of the
economy can be displayed. Rulyasri, Achsani and Mulyati (2017) studied the effects of
macroeconomic conditions on non-performing loans in Indonesia’s retail segments. Their result
showed that amount of Money Supply (M2) has a positive and significant influence on the NPL of the
retail segment during the research period.

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