Regulation’s influence on EU banking efficiency: An evaluation post crisis

Figures & data

Figure 1. Histograms of net interest margin and logarithm of net interest margin, Source: the authors.

Figure 2. Histograms of overhead costs and logarithm of overhead costs, Source: the authors.

Table 1. Descriptive statistics

Variable	Mean	Std. Dev.	Minimum	Maximum	Observations
LOGNIM LOGOC	−4.24	0.98	−11.10	−1.58	671
	−4.09	1.24	−9.95	−0.42	678
CAPREG ACTRES	6.70	1.56	4	9	678
	6.21	1.70	4	11	678
SPOWER PMONIT	11.29	1.90	5	14	678
	8.32	1.06	6	11	678
LOGTA EQTA MS GOVERN GDPGR	6.53	1.00	3.42	9.51	678
	0.12	0.13	−0.01	1.00	678
	0.03	0.07	0.00	0.58	678
	0.07	0.09	0	0.51	678
	0.01	0.02	−0.06	0.05	678

Note: This table presents the mean, standard deviation, minimum, maximum and number of observations of all variables used in this study for a sample of 21 EU countries for the year 2010. Sources: SNL Financial database, World Bank: Bank Regulation and Supervision Survey, and World Bank: World Development Indicators and own calculations. The bank-level variables include logarithm of net interest margin (LOGNIM), logarithm of overhead costs (LOGOC), bank size (LOGTA), bank equity (EQTA) and bank market share (MS). The country-level variables include capital regulation (CAPREG), activity restrictions (ACTRES), official supervisory power (SPOWER), private monitoring (PMONIT), government-owned banks (GOVERN) and annual growth rate of GDP per capita (GDPGR).

Table 2. Regression results

	(1)	(2)
	LOGNIM	LOGOC
CAPREG	0.0353	0.0399
	(0.0304)	(0.0337)
ACTRES	0.161***	0.175***
	(0.0266)	(0.0313)
SPOWER	0.0177	0.0511**
	(0.0327)	(0.0242)
PMONIT	−0.119*	−0.171***
	(0.0612)	(0.0581)
LOGTA	−0.197***	−0.445***
	(0.0493)	(0.0648)
EQTA	0.158	1.154*
	(0.578)	(0.658)
MS	2.063***	2.247***
	(0.671)	(0.619)
GOVERN	0.224	−1.169***
	(0.313)	(0.381)
GDPGR	−14.89***	−9.589***
	(2.087)	(2.366)
Constant	−3.283***	−1.669**
	(0.858)	(0.684)
Observations R-squared F	671	678
	0.130	0.234
	15.89	20.89

Note: This table exhibits the estimates from OLS regressions of model 1 and 2, explaining the relationship between bank regulation and banking efficiency. The dependent variable of model 1 is logarithm of net interest margin (LOGNIM) and model 2 is logarithm of overhead costs (LOGOC). The independent variables of both models are: capital regulation (CAPREG), activity restrictions (ACTRES), official supervisory power (SPOWER), private monitoring (PMONIT), bank size (LOGTA), bank equity (EQTA), bank market share (MS), government-owned banks (GOVERN) and annual growth rate of GDP per capita (GDPGR). The symbols *, **, *** indicate the statistical significance of the estimated coefficients at the 10, 5 and 1% level, respectively. The robust standard errors are in parentheses below the estimated coefficients. The number of observations, R-squared and F statistic of each regression are also presented in this Table.