ÒøÐÐÓ¯ÀûÄÜÁ¦·ÖÎöÖÐÓ¢ÎĶÔÕÕÍâÎÄ·­ÒëÎÄÏ× ÏÂÔر¾ÎÄ

ÒøÐÐÓ¯ÀûÄÜÁ¦·ÖÎöÖÐÓ¢ÎĶÔÕÕÍâÎÄ·­ÒëÎÄÏ×

Finally, in a more recent study, Fries and Taci (2005) examine the cost efficiency in 15 post-communist countries. The results indicate that privatized banks with majority foreign ownership are the most cost efficient ones and those with domestic ownership are the least, though both being more efficient than state-owned banks. 3. Determinants and variable selection 3.1. Dependent variable

This study uses return on average assets (ROAA) to evaluate bank's performance. ROAA is the net profits expressed as a percentage of average total assets. It shows the profits earned per euro of assets and indicates how effectively the bank's assets are being managed to generate revenues. Average assets are being used in order to capture any differences that occurred in assets during the fiscal year. As Golin (2001) points out, return on average assets is the key measure of profitability. 3.2. Determinants and independent variables

Four bank characteristics are used as internal determinants of performance. These are the bank's total assets, the cost to income ratio, the ratio of equity to assets and the ratio of bank's loans divided by customers and short term funding. In addition, six external determinants are used to examine the impact of environment on bank's performance (Table 1).

Table 1. Variables description Variables Description Dependent ROAA The return on average total assets of the bank

Independent

Banks characteristics (internals factors)

This is a measure of capital adequacy, calculated as equity to total

EQAS assets. High capital-asset ratios are assumed to be indicators of low

leverage and therefore lower risk

This is the cost to income ratio. It provides information on the

COST efficiency of the management regarding expenses relative to the

revenues it generates. Higher ratios imply a less efficient management This is a measure of liquidity calculated as loans to customers and

LOFUND

short term funding. Higher figures denote lower liquidity

SIZE The accounting value of the bank's total assets (in €)

Macroeconomic and financial structure (external factors) INF The annual inflation rate

GDPGGR The real gross domestic product (GDP) growth

The C5 concentration measure calculated by dividing the assets of the

CONC

five largest banks with the assets of all banks operating in the country

ÒøÐÐÓ¯ÀûÄÜÁ¦·ÖÎöÖÐÓ¢ÎĶÔÕÕÍâÎÄ·­ÒëÎÄÏ×

Description

The ratio total assets of the deposit money banks divided by the GDP (ASSGDP). It reflects the overall level of development of the banking

ASSGDP

sector and measures the importance of bank financing in the economy (in constant US$ 1995)

The ratio stock market capitalization to total assets of the deposit money banks.a This variable serves as a proxy of financial

MACPASS development as well as a measure of the size of financial market and

the relationship between bank and market financing (in constant US$ 1995)

The ratio stock market capitalization to GDP. It measures the overall

MACGDP level of development of the market and its importance in financing the

economy (in constant US$ 1995)

Notes: the data for the calculation of internal factors and CONC were obtained from Bankscope Database. The data for the external factors were obtained from Euromonitor International Database which uses sources such as International Monetary Fund's (IMF) International Financial Statistics (IFS), World Economic Outlook/UN/National Statistics and World Bank.

The ratio of equity to assets (EQAS) is used as a measure of capital strength. Generally speaking, banks with high capital-asset ratios are considered relatively safer in the event of loss or liquidation. Therefore, the conventional risk¨Creturn hypothesis would imply a negative relationship between equity to assets ratio and bank performance. However, the lower risk increases banks creditworthiness and consequently reduces the cost of funding. At the same time, banks with higher equity to assets ratio will normally have lower needs of external funding and therefore higher profitability.

Another basic policy of commercial banks refers to their liquidity management and specifically the process of managing assets and cash flow to maintain the ability to meet current liabilities as they come due. Without the required liquidity and funding to meet obligations, a bank may quickly fail, or at least be technically insolvent. The ratio of net loans to customers and short term funding (LOFUND) is used to measure the relationship between liquidity management and performance. This ratio shows the relationship between comparatively illiquid assets (i.e. loans) and comparatively stable funding sources (i.e. deposits and other short term funding). Therefore, the lower the value of this ratio, the more liquid the bank is. Since liquid assets are associated with lower rates of return a positive relationship is expected between this variable and performance.

The cost to income ratio (COST) is used to measure the impact of efficiency in expenses management on banks performance. This ratio shows the costs of running the bank, the major element of which is staff salaries and benefits, and is expected to have a negative relationship with bank's performance.

Bank's size (SIZE) is considered an important determinant of its performance. The reason is that large size may result in economies of scale that will reduce the cost of gathering and processing information (Boyd and Runkle, 1993). As in most studies in

Variables

ÒøÐÐÓ¯ÀûÄÜÁ¦·ÖÎöÖÐÓ¢ÎĶÔÕÕÍâÎÄ·­ÒëÎÄÏ×

banking, we use total assets of the bank as a proxy for its size to account for size related economies or diseconomies of scale.

Turning to the external determinants, two sets of variables have been considered in this study, indicating macroeconomic conditions and financial structure characteristics. The two macroeconomic variables used are gross domestic product growth (GDPGR) and inflation (INF).

GDP is among the most commonly used macroeconomic indicators and it is a measure of total economic activity within an economy. The real GDP growth, used in this study, is expected to have a positive impact on bank's performance according to the well-documented literature on the association between economic growth and financial sector performance.

The relationship between inflation and banks performance depends on whether the inflation is anticipated or unanticipated (Perry, 1992). In the first case (i.e. anticipated inflation) banks can timely adjust interest rates, which consequently results in revenues that increase faster than costs, with a positive impact on profitability. In the second case (i.e. unanticipated inflation) banks may be slow in adjusting their interest rates resulting in a faster increase of bank costs than banks revenues. This will consequently have a negative impact on bank profitability.

We finally examine how the performance of banks is related to the relative development of the banking industry and the stock market using the ratios stock market capitalization to GDP (MACGDP), stock market capitalization to total assets of deposit money banks (MACPASS), total assets of deposit money banks to GDP (ASSGDP) and banking industry concentration (CONC). MACPASS reflects the complementarity or substitutability between bank and stock market financing, while ASSGDP and MACGDP measure the overall level of development of the banking sector and the stock market, respectively as well as their importance in financing the economy. Concentration is the proportion of an industry's total assets controlled by its largest firms. According to the structure-conduct performance (SCP) hypothesis, banks in highly concentrated markets tend to collude and therefore earn monopoly profits (Short, 1979, Gilbert, 1984 and Molyneux et al., 1996). Collusion may result in higher rates being charged on loans, less interest rates being paid on deposits and so on (Goddard et al., 2001). CONC is calculated as the total assets held by the five largest commercial banks in the country divided by the total assets of all commercial banks in the country.

4. Data and methodology 4.1. Data

Our sample is a balanced panel dataset of 584 commercial banks operating in the 15 EU countries over the period 1995¨C2001 consisting of 4088 observations.5Table 2 and Table 3 present the number of banks by country and ownership and the sample characteristics, respectively.

Table 2. Banks in sample by country and ownership

ÒøÐÐÓ¯ÀûÄÜÁ¦·ÖÎöÖÐÓ¢ÎĶÔÕÕÍâÎÄ·­ÒëÎÄÏ×

Country

Domestic banks Foreign banksa

Austria 13 7 Belgium 5 15 Denmark 31 2 Finland 2 0 France 90 40 Germany 57 26 Greece 6 0 Ireland 3 8 Italy 49 4 Luxembourg 3 54 The Netherlands 10 13 Portugal 7 4 Spain 28 11 Sweden 5 0 UK 23 34

Total 15 EU 332 218 34 584

a We define a bank to be foreign when foreigners own more than 50% of its share capital.

Table 3. Sample characteristics: independent variables means (and S.D.)

EQALOFUASSMACPMACGDPCON

COST SIZE INF

S ND GDP ASS GDP GR C 8.56463.9656.2402174.0290.3691.692.2888.7

0.4173 0.1524

9 75 2 3 0 86 57 943

Austria (0.060(0.013

(6.15(16.0(27.67(4697.87(0.03(0.73(1.05(1.65

7) 0)

01) 473) 08) 90) 00) 12) 48) 49) 8.49065.9740.4447102.8650.7561.752.4091.5

0.1040 0.0661

1 92 6 0 3 00 00 886

Belgium (0.053(0.019

(12.4(31.2(28.81(23011.8(0.24(0.58(1.18(3.81

0) 5)

237) 047) 99) 401) 60) 36) 32) 20) 10.9869.0168.6063647.0280.3872.282.5286.8

1.3548 0.5309

35 87 4 2 4 71 86 100

Denmark (0.203(0.120

(4.05(16.4(21.91(18890.2(0.04(0.31(0.49(2.18

2) 7)

47) 308) 84) 384) 58) 77) 49) 05) 5.24365.2863.19611079.570.1881.484.2599.1

8.1501 1.3410

8 71 7 62 9 86 71 886

Finland (7.036(0.887

(1.12(11.96(13.03(8659.08(0.04(0.82(1.69(0.20

7) 1)

79) 74) 29) 61) 85) 62) 10) 73)

France 9.56770.0570.78012622.710.3961.9497 0.6991 1.362.5560.5

Not available or complete Total

information for ownership in number of Bankscope banks 0 20 0 20 9 42 1 3 14 144 5 88 0 6 0 11 1 54 0 57 1 24 0 11 3 42 0 5 0 57

ÒøÐÐÓ¯ÀûÄÜÁ¦·ÖÎöÖÐÓ¢ÎĶÔÕÕÍâÎÄ·­ÒëÎÄÏ×

Germany

Greece

Ireland

Italy

Luxembourg

The Netherlands Portugal

Spain

Sweden

UK

EQALOFUASS

MACPMACS COST ND SIZE GDP ASS GDP INF

GDPCON

GR C 4 57 2 31 9 (1.091(0.28900 71 285 (11.05(45.3(69.80(59381.6(0.079) 9) (0.53(1.03(2.84

28) 486) 05) 366) 43) 16) 77) 59) 9.08865.7264.2732734.8170.2976 06 0 2 4

1.6206 0.4788

1.561.6577.2

(10.8(23.7(41.01(5428.54(0.05(0.603(0.168

86 71 729

851) 526) 26) 43) 22) 9) 0)

(0.59(0.68(5.45

95) 84) 76) 8.76466.0248.50015401.600.1140 69 0 24 6

5.6998 0.6713

5.223.3487.3

(6.80(16.1(13.12(13779.4(0.02(4.363(0.510

57 29 471

35) 258) 78) 125) 01) 3) 4)

(2.31(0.74(5.48

41) 42) 60) 8.30933.1058.49112959.751.2164 19 7 45 0

0.5604 0.6529

2.889.3277.9

(5.26(23.6(27.43(21601.9(0.36(0.140(0.156

00 86 629

82) 464) 79) 533) 63) 7) 7)

(1.53(1.68(3.59

54) 07) 21) 8.73276.5178.50810373.100.1188 04 4 82 4

4.5216 0.4266

2.882.0555.5

(6.40(30.1(53.09(23514.5(0.03(3.091(0.187

57 71 066

68) 354) 46) 038) 84) 0) 1)

(1.19(0.65(3.98

05) 22) 18) 5.41049.6224.6535077.40318.347 99 6 5 69

0.1161 1.7163

1.785.4734.0

(5.81(24.3(19.65(7990.22(8.34(0.054(0.223

00 14 235

41) 863) 74) 27) 14) 9) 3)

(0.78(2.62(8.36

28) 23) 10) 7.77157.1187.66235287.940.535

1 74 5 46 7 2.6122 1.3146

2.473.2590.6

(4.74(19.9(88.11(103203.(0.09

(1.089(0.339

71 71 986

30) 921) 55) 8604) 11) 7) 7)

(0.85(0.95(2.69

81) 30) 30) 8.63561.8462.3006979.4110.3426 27 6 7 2

1.3624 0.4191

3.093.4471.11

(5.17(22.0(21.70(9089.01(0.10(0.734(0.159

43 29 57

57) 134) 88) 45) 15) 0) 3)

(0.79(0.88(8.08

60) 94) 93) 12.4670.3767.26915220.040.18220 21 6 59 4

3.8529 0.6206

2.933.5180.6

(11.90(57.6(39.25(52251.6(0.04(1.945(0.195

86 43 065

28) 361) 86) 256) 43) 8) 8)

(0.94(0.77(2.68

16) 54) 02) 6.33463.87151.9713032.100.2023 43 56 29 1

5.5151 1.1095

1.023.0597.2

(5.23(20.9(187.0(21321.0(0.04(0.759(0.240

43 71 900

22) 667) 575) 600) 11) 3) 1)

(0.95(1.34(1.86

16) 79) 91)

11.6859.5056.33426666.031.312

1.2270 1.6039 2.672.7757.085 15 7 63 1 (0.185(0.22943 14 943