According to the published data at the country level and overall banking system level, the number of non-performing loans and their factors are increasing significantly in the last few decades. The surge in the credit risk during and after the global crisis took the researchers’ attention and, therefore, factors that negatively impact the bank’s portfolio has been severely investigated. The result of several studies revealed that a surge of irresistible problematic loans along with the banking sector’s fragility and financial vulnerability undermined the banking crisis in’90 s. Due to a negative shock in social welfare and economic growth, González-Hermosillo [32] Barseghyan [12], and Zeng [81] concluded the Non-Performing Loans as ‘financial pollution’.
Keeton [47] studied 50 US banks between 1982 and 1996 and showed that the lax credit standards are one of the pivotal reasons for a sudden surge in NPLs. In line with the previous study, McGoven [58] also found that unsecured loans, low credit standards, and borrowers’ attitudes have a crucial impact on raising loan loss in the US banking system. Moreover, a study on banking system of Argentina between 1993 and 1996 was conducted by Bercoff et al. [14] where he applied an Accelerated Failure Time (AFT) method and that revealed both bank-specificFootnote 1 and macroeconomic determinants had an equal influence on NPLs.
This paper reflects several researchers’ investigative and analytical studies regarding the factors that impact the non-performing loans for both individuals and a panel of countries. Some of the researchers investigated both macroeconomic and bank-specific variables, while others investigated macroeconomic or bank-specific factors separately.
Group country level determinants
The correspondence between NPLs and macroeconomic along with bank-specific determinants was explored by Espinoza and Prasad [26] while considering a panel of 80 banks from the GCC zone. The study highlighted that macroeconomic variables, particularly interest rate and non-oil GDP had a remarkable effect on credit risk. Moreover, the study also depicted that some distinct bank-specific factors (credit growth, capital sizes, and efficiency) had an impact on non-performing loans. The study results suggested a short, yet, strong feedback effect from the banking industry to the economy.
Kastrati [46] analyzed the impact of NPLs ratio during the period of 1994–2009 on 15 transition countries (Azerbaijan, Albania, Armenia, Bosnia and Herzegovina, Belarus, Bulgaria, Moldova, Macedonia, Kosovo, Romania, Serbia, Montenegro, Croatia, Georgia, and Ukraine) by using dynamic panel data method. The report demonstrated the non-performing loans were highly persisting from one year to another and inflation rate, real economic growth rate and competition had a noteworthy impact on the NPL ratio.
Using dynamic GMM and fixed effect model, Ghosh [31] analyzed the bank-specific and economic variables of aggregate NPLs by taking 50 banks in both Columbia and USA between 1984 and 2013. The results implied that increasing GDP, housing price index, and personal income growth rate declines NPLs, while sovereign debt and rate of unemployment increase the NPLs significantly. Afterward, Konstantakis et al. [52] confirmed the impact while conducting a study on the Greek economy from 2001 to 2015.
Boudriga et al. [17] conducted an empirical investigation based on 12 selected MENA countries considering a sample of 46 banks and analyzed the impact of non-performing loans on the bank-specific, institutional, and business environment factors for the 2002–2006 year timespan. Their result revealed foreign participation from developed countries, institutional environment, loan loss provision, and credit growth possess a significant impact on bad debt.
De Bock and Demyanets [15] investigated the macroeconomic variables of NPLs spanning from 1996–2000 by considering a group of 25 emerging markets. Their study highlighted that economic expansion, trade growth (goods), exchange rate, capital flows had a significant impact on NPLs.
Messai and Jouini [60] conducted an empirical study on 85 banks in Spain, Italy, and Greece where they evaluated both macroeconomic and bank-specific variables of non-performing loans on for a period of 2004 to 2008 and found a significant relationship between financial and macroeconomic variables (i.e., rate of unemployment, rate of GDP growth, loan loss reserves, and return on assets), real interest rate and non-performing loans.
Reinhart and Rogoff [69] investigated a group of 70 developed and developing countries consisting of 209 sovereign defaultFootnote 2 and 290 banking crises episodes for a prolonged span from 1800 to 2009. In the seminal paper, they revealed that the sovereign default/ government default affected the quality of bank portfolio, irrespective of commitment size. In line with the findings, a strong linkage between sovereign debt and non-performing loans rate was explored by Makri et al. [56] while investigating 14 EU countries from 2000 to 2008.
The effect of financial crisis 2007–2008 on the financial soundness indicators of banks was investigated by Kasselaki and Tagkalakis [45] on 20 industrialized OECD countries spanning the period from 1997 to 2009. The study demonstrated that the global financial crisis caused a significant increase in non-performing loans, real interest rates (both short and long term). The authors suggested the policymakers to develop a prior warning system so that the stability of the banking sector is fragile/threatened or not will be known beforehand.
Individual empirical analysis of Jakubík and Reininger [41], Škarica [77], Klein [50] confirmed the prior findings that the real economy affects significantly to non-performing loans in the observed countries, while they examined the factors of NPLs for Eastern and South-Eastern, and Central European countries and their findings.
A study by Roman and Bilan [73] on EU28 countries, for the period 2000–2013 demonstrated that budgetary consolidation results in a low budget deficit of high budget surplus and, thereby, deteriorates the bank portfolios showed that non-performing loans have a significant positive relationship with government budget balance and sovereign debt. Afterward, Dimitrios et al. [23] confirmed the impact while conducting a study on euro-area banking system for the period 1990Q1–2015Q2.
The empirical study of Castro [20] demonstrated that macroeconomic environment and non-performing loans have noteworthy correlations in the euro-zone countries. Moreover, the study considered the financial variable’s impact on the NPL ratio.
Bofondi and Ropele [16] explored the macroeconomic variables of NPLs on the banking system of Italy between 1990Q1 and 2010Q2. The study highlighted that aggregate money supply, lending rates, and rate of unemployment are directly associated with NPLs and GDP is negatively interrelated with NPLs. Contrarily, Ahmad [3] conducted a study on NPLs as a proxy of credit risk based on 65 Malaysian deposit-taking institutions, and Kalirai and Scheicher [44] analyzed the NPLs impact on the Austrian banking system, and both of them found a significant negative association between credit risk and money supply. Fofack [28], however, found no impact of money supply on non-performing loans.
Individual country level determinants
Using macroeconomic determinants, Babouček and Jančar [10] explored the NPLs in the Czech Republic for 11 years and used the VAR method to examine the macroeconomic determinants’ (real GDP, unemployment percentage, inflation, exports, imports, interest percentage, exchange rate, and aggregate bank loans) influence. Their findings demonstrated that the GDP growth rate reduces the NPLs ratio while raising inflation and exchange rate deteriorate the bank’s loan portfolio quality.
The factors of non-performing loans in the Greek Bank during 2003Q1-2009Q3 were scrutinized by Louzis et al. [55] where they used dynamic panel data estimation techniques and considered various types of loans (mortgage, consumer, and business). The study findings exhibited that the NPLs ratio of business loans was, primarily, highly sensitive to the unemployment rate change, the NPLs ratio of consumer loans were highly sensitive to real growth rates changes, while NPLs ratio of mortgage was comparatively less sensitive to change in macroeconomic environment. Moreover, they presumed the hypothesis of ‘sovereign debt’ and asserted that higher sovereign debt leads to rising NPLs.
Caporale et al. [18] investigated the impact of financial and macroeconomic determinants on the quality of bank portfolio based on the Italian banking sector spanning from 2008–2012 and they found that economic recession leads to a high volume of NPLs since the banks grant high volume of credits during the economic boom. The findings revealed that the deterioration of economic condition caused a record in NPLs surplus in the recessionary period and, during the pre-crisis years, the Italian banks promoted the lending policy.
Chaibi and Ftiti [21] examined the macroeconomic impact of non-performing loans on the quality of bank’s portfolio where the laisse-faire economy (France) was compared with the credit-based economy (Germany) for the span of 2005–2011. The authors found that, in both of the economic contexts, all the chosen macroeconomic determinants (excluding the rate of inflation) had a noteworthy influence on NPLs. The findings suggested that a laisse-faire economy possesses a greater credit risk than a credit-based economy.
Lastly, Khemraj and Pasha [49] scrutinized the determinants of non-performing loans in Guyana spanning from 1992 to 2004. The findings showed that the real effective exchange rate, the high lending rate had a positive relationship with non-performing loans while GDP had a negative relationship with NPLs. In line with the previous study, Beck et al. [13] explored the NPLs’ determinants for 75 developed and emerging economies for 2000–2010 and found a significant impact on lending rate, share price, nominal effective exchange rate (based on local currency), and GDP growth rate.