Macroeconomic Determinants of Credit Risk on the Example of Non-performing Loans

Top 10 of the highest and lowest NPL ratios in 2019

Country	NPL as assets %	Country	NPL as assets %
Ukraine	46.8	Macao	0.2
Greece	39.4	South Korea	0.4
Cyprus	30.5	Micronesia	0.4
Angola	17.7	Hong Kong	0.7
Burundi	17.7	Luxembourg	0.8
Iraq	14.1	Australia	0.9
Moldova	13.1	Norway	1.0
Italy	12.9	United Kingdom	1.0
Albania	12.8	United States	1.1
Vanuatu	12.7	Singapore	1.2

Wu-Hausman test results

	df	df2	statistic	p-value
Wu-Hausman	1	97.00	0.137	0.71

Correlation matrix

	ln NPL	INF	UN	DCTOPS	DEBT	GDP	IR	OECD	CurDep
ln NPL	1
INF	0.30	1
UN	0.25	−0.20	1
DCTOPS	−0.54	−0.35	−0.08	1
DEBT	0.33	0.02	0.14	0.08	1
GDP	−0.11	−0.05	−0.13	0.00	−0.26	1
IR	0.27	0.41	−0.11	−0.47	−0.04	−0.02	1
OECD	−0.28	−0.32	−0.01	0.34	0.13	−0.27	−0.48	1
CurDep	0.28	0.91	−0.07	−0.28	0.08	−0.10	0.27	−0.16	1

Data specification and symbols

Variable	Symbol
Non-performing loan ratio in 2019	NPL
Natural logarithm of non-performing loan ratio in 2019	ln_NPL
Inflation rate is expressed as an index in 2019, where the base year is 2008	INF
Unemployment rate is expressed as the average unemployment rate in 2009–2019	UN
Banking sector development indicator as a relation between total loans granted to the private sector and GDP in 2019	DCTOPS
State debt as a ratio of public debt to GDP in 2019	DEBT
GDP growth rate as a relation of the value of GDP expressed in constant prices to the national currency in 2019 to 2008	GDP
Interest rate as the average interest rate on loans granted in 2009–2019	IR
OECD membership (dummy variable)	OECD
Currency depreciation as a ratio of the value of the currency expressed in SDRs in 2019 in relation to 2008	CurDep

VIF testing results

	INF	UN	DCTOPS	DEBT	GDP	IR	OECD
vif(a)	1.3699	1.1468	1.4102	1.1042	1.2153	1.6610	1.5495
vif(b)	1.3278	1.1215	1.2615	1.1038	1.1885	X	1.3277
vif(c)	1.3531	1.1194	1.4102	1.0576	X	1.6245	1.3884
vif(d)	1.0817	1.3429	1.0971	X	1.2004	1.6100	1.4983
vif(e)	1.0280	1.1399	1.0400	X	X	X	1.1428

Description of the determinants and proxies of NPLs and a representative sample of their use in the literature

Variable	Expected impact on NPL	Basis of the NPL influence sign	Relevant literature
Inflation rate	+	The state of high inflation hinders running a business and reduces the ability of households to settle their liabilities.	Curak et al., 2013; Klein, 2013; Kjosevski & Petkovski, 2021
Unemployment rate	−	Unemployment reduces the ability of households to pay their liabilities.	Klein, 2013; Messai & Jouini, 2013; Wdowiński, 2014; Louzis et al., 2015; Kjosevski & Petkovski, 2021
Banking sector development	−	A large number of loans means greater availability of financing. In addition, the high value of loans means that banks are mature and can properly assess creditworthiness.	Keeton & Morris, 1987;Abid & Zouari, 2014; Petkovski et al., 2021
State debt	+	High state debt limits the availability of financing, which contributes to higher loan-servicing costs.	Louzis et al., 2015; Kjosevski & Petkovski, 2021
GDP growth rate	−	Lower GDP growth means limited ability to settle liabilities.	Messai & Jouini, 2013; Wdowiński, 2014; Beck et al., 2015; Louzis et al., 2015; Kjosevski & Petkovski, 2021
Interest rate	+/−	A high interest rate may limit lending, i.e., only those entities with high creditworthiness receive loans. On the other hand, the high cost of money may make it difficult to settle liabilities.	Curak et al., 2013; Messai & Jouini, 2013; Wdowiński, 2014; Beck et al., 2015
Currency depreciation	+	The depreciation of the domestic currency means an increase in loans in foreign currency. This is important in the case of loans with a significant value in a foreign currency.	Klein, 2013; Wdowiński, 2014; Beck et al., 2015

Regression statistics for the assessment of non-performing loans

Variable	Model (a)	Model (b)	Model (c)	Model (d)	Model (e)
INF	0.1624	0.1499	0.1690	n/a	n/a
	(0.1526)	(0.1783)	(0.1328)
UN	0.0268*	0.0279*	0.0277*	0.0227	0.0243*
	(0.0258)	(0.0187)	(0.0190)	(0.0520)	(0.0318)
DCTOPS	−0.0110***	−0.0106***	−0.0110***	−0.0116***	−0.0114***
	(0.0000)	(0.0000)	(0.0000)	(0.0000)	(0.0000)
DEBT	0.0105***	0.0104***	0.01071***	0.0107***	0.0110***
	(0.0000)	(0.0000)	(0.0000)	(0.0000)	(0.0000)
GDP	−0.1737	−0.1430	n/a	−0.2259	n/a
	(0.5958)	(0.6577)		(0.4903)
IR	−0.0075	n/a	−0.0066	−0.0045	n/a
	(0.5274)		(0.5744)	(0.7007)
OECD	−0.3360	−0.2906	−0.3035	−0.3856*	−0.3268*
	(0.0789)	(0.0992)	(0.0921)	(0.0419)	(0.0468)
p-value:	0.0000***	0.0000***	0.0000***	0.0000***	0.0000***
Residual standard error	0.7050	0.7028	0.7024	0.7088	0.7037
White test p-value:	0.3654	0.3014	0.406	0.3185	0.2484
Goldfeld–Quandt test p-value:	0.9114	0.8307	0.9144	0.8789	0.8730
Multiple R-squared	0.4922	0.4901	0.4907	0.4814	0.4785
Adjusted R-squared	0.4559	0.4592	0.4598	0.45	0.4578
AIC	236.3774	234.8116	234.6833	236.6023	233.1925
BIC	260.3484	256.1191	255.9909	257.9098	249.1731
RESET	1.2344 (0.2956)
Shapiro			0.9841(0.2376)
Jarque Bera	3.0718 (0.2153)
Observations	106	106	106	106	106

Ramsey's RESET test results

RESET	5.3029
df1	2
df2	95
p value	0.0065

Descriptive statistics of variables

	NPL	INF	UN	DCTOPS	DEBT	GDP	IR	CurDep
Mean	6.44	1.60	8.37	61.40	53.60	1.24	10.16	1.31
Maximum	46.82	6.19	31.65	236.75	194.11	2.16	54.48	8.58
Minimum	0.20	1.00	0.71	3.23	2.58	0.79	0.52	0.76
Standard deviation	6.92	0.71	6.21	42.32	31.36	0.23	7.43	0.90
Skewness	3.38	3.92	1.55	1.37	1.40	0.89	2.78	6.20
Kurtosis	15.23	20.04	2.09	2.38	3.28	1.54	12.94	44.56
Jarque-Bera test	1.119.70	1.868	57.70	53.63	75.08	22.27	799.40	8,610.70
JB Probability	0.0000	0.0000	0.0000	0.0000	0.0000	0.0000	0.0000	0.0000
Number of observations	106	106	106	106	106	106	106	106