银行盈利能力分析中英文对照外文翻译文献
EQALOFUASSMACPMACGDPCON
COST SIZE INF S ND GDP ASS GDP GR C (9.93(25.9(46.38(73111.3(0.117) 4) (0.69(0.40(4.3606) 507) 84) 215) 09) 61) 61) 75)
All financial and ownership data of individual banks as well as information concerning market concentration were drawn from Bankscope Database of Bureau van Dijk's company. Using BANSCOPE has two advantages. Firstly, it has information for 11,000 banks, accounting for about 90% of total assets in each country. Secondly, the accounting information at the bank level is presented in standardized formats, after adjustments for differences in accounting and reporting standards.
Country and market specific data such as inflation, real GDP growth, market capitalization, etc., were obtained from Euromonitor International Database which collects data from sources such as International Monetary Fund's (IMF), International Financial Statistics (IFS), World Economic Outlook/UN/National Statistics and World Bank.
4.2. Methodology
In order to examine the internal and external factors that affect the profitability of banks in European Union, the following model has been developed: (1)
zit=boit+bmitYmit+bdjtYdit+ε
where i refers to an individual bank; t refers to year; j refers to the country in which bank i operates; zit the dependent variable that refers to the return on average assets (ROAA) and is the observation of a bank i in a particular year t; Ym represents the internal factors/determinants of a bank; Yd represents the external factors/determinants of a bank; ? is an error term.
Model (1) is estimated through a fixed effects regression taking each bank's ROAA as the dependent variable. The opportunity to use a fixed effects rather than a random effects model has been tested with the Hausman test. If the value obtained by the Hausman test is larger than the critical chi-square
or
, then the fixed effects estimator is the appropriate choice.
Therefore, a fixed effects model is a natural choice since our estimating sample is identical to the population of interest (Judge et al., 1988). Moreover, the fixed effects approach is further supported by the absence of significant heteroscedasticity in the residuals from our estimated model.
Based on the Breusch-Pagan test6 (Baltagi, 2001) and in order to investigate whether there is evidence of heteroscedasticity in the residual variance we calculate the Lagrange multiplier (LM) and compare the relevant statistic of each model with the critical chi-square value
. Values below this would reject the null
hypothesis of heteroscedastic residual variance. The model (1) is finally estimated using White's transformation to control the cross-section heteroscedasticity of the
银行盈利能力分析中英文对照外文翻译文献
variables.
Extending Eq. (1) to reflect the variables, as described in Table 1, the model is formulated as follows: (2)
zit=bot+bit(EQASit+COSTit+LOFUNDit+SIZEit)+bjt(INFjt+GDPGRjt+CONCjt+ASSGDPjt+MACPASSjt+MACGDPjt) 5. Empirical results
Table 4 reports the empirical estimations of Eq. (2) for banks’ ROAA. The first column presents the results when all the banks (584) are simultaneously considered. Columns two and three present the results when we split the banks according to the country of origin of their owner. We define a bank to be foreign (domestic) when foreigners own more (less) than 50% of its share capital. The sub-samples include 332 domestic banks and 218 foreign banks. About 34 banks were excluded from the analysis at this stage, as we had not enough information to classify them either as domestic or foreign.
Table 4. Regressions results (dependent variable: ROAA)
Domestic banks in Foreign banks in
All banks in samplea
sampleb samplec 0.238877 0.240276
EQAS 0.228045 (51.44043)***
(30.70840)*** (41.46373)***
?0.198939 ?0.143611 ?0.309044
COST
(?48.87565)*** (?30.10036)*** (?36.14324)***
0.046915 ?0.020300
LOFUND 0.040155 (14.42604)***
(9.738826)*** (?9.405973)***
?0.005713 ?0.004235 ?0.009339
SIZE
(?21.15411)*** (?8.549996)*** (?5.378429)***
0.002199 ?0.004812
INF 0.001506 (6.617562)***
(7.716279)*** (?9.258363)*** 0.010174 ?0.001819
GDPGR 0.000821 (2.667922)***
(23.25582)*** (?2.772711)*** ?0.001712 0.116854
CONC 0.037344 (32.73005)***
(?1.618062) (27.25397)***
?0.021273 ?0.025387 ?0.035854
ASSGDP
(?45.93489)*** (?15.65656)*** (?39.40473)***
0.011691 0.014071
MACPASS 0.015120 (25.77822)***
(16.33099)*** (11.98591)*** 0.051569 0.074522
MACGDP 0.066306 (80.14221)***
(54.31495)*** (28.16418)***
Adjusted R2 0.5609 0.6371 0.3903 F-value 61.3783 78.0738 35.6322 LM 340.667 1.519 × 1052 3.835 × 1050 Hausman test 27.825 34.285 9.649 t-Values in parentheses. ***significant at the 1% level.
银行盈利能力分析中英文对照外文翻译文献
a 584 banks, period 1995–2001, no. of observations = 4088. b 332 banks, period 1995–2001, no. of observations = 2324. c 218 banks, period 1995–2001, no. of observations = 1526.
All the variables are significant, with the exception of concentration in the case of domestic banks ROAA, although their impact and relation with ROAA is not always the same for domestic and foreign banks. The explanatory power of the model is much higher for domestic banks (adjusted R2 equal to 0.6371 for domestic banks compared with 0.3903 for foreign banks) while F-statistic for all models is significant at the 1% level. This implies that additional factors may influence the profitability of foreign banks. As Williams (2003) correctly points out, foreign banks operating in a host market are being affected by both the fact that they are owned by a foreign multinational bank and their participation in the host banking system.
Capital strength and efficiency in expenses management are the main determinants of ROAA in all cases as the relatively high significant coefficients of the equity to assets (EQAS) and cost to income (COST) ratios show. Equity to assets is positive related to ROAA whether we examine domestic or foreign banks and appears to be the most significant determinant of profitability for domestic banks. This finding is consistent with previous studies (e.g., Berger, 1995, Demirguc-Kunt and Huizinga, 1999, Staikouras and Wood, 2003, Goddard et al., 2004, Kosmidou et al., 2005 and Kosmidou, 2006) providing support to the argument that well capitalized banks face lower costs of going bankrupt and reduce, thus, their cost of funding or that they have lower needs for external funding resulting in higher profitability. As expected the coefficient of the cost to income ratio (COST), which appears to be the most significant determinant of profitability for foreign banks, is negative showing that an increase (decrease) in these expenses reduces (increases) the profits of banks operating in the EU to a large extent. Guru et al. (1999), Kosmidou et al. (2005) and Kosmidou (2006) among others also found poor expenses management to be among the main contributors to poor profitability. Thus, commercial banks in the EU should take the necessary actions to achieve a more efficient cost control in order to further increase their profits. The difference in the coefficient between foreign (?0.309) and domestic banks (?0.144) could be the result of diseconomies of operating or monitoring an institution from a distance as Berger et al. (2000) suggested for the foreign banks.
Referring to liquidity, the results are mixed. The ratio net loans to customer and short term funding (LOFUND) is statistically significant and positively related to the profitability of domestic banks, indicating a negative relationship between bank profitability and the level of liquid assets held by the bank, and consistent with our expectations and some earlier studies (e.g., Molyneux and Thorton, 1992 and Guru et al., 1999). In the case of foreign banks, the variable is also significant but has a negative sign, indicating a positive relationship between liquidity and banks profits, contrary to our expectations although consistent with the studies of Bourke (1989) and Kosmidou (2006).
The relation between size (SIZE) and bank's performance is negative whether we examine domestic or foreign banks. The negative coefficient indicates that in both
银行盈利能力分析中英文对照外文翻译文献
cases, larger (smaller) banks tend to earn lower (higher) profits and provides support to the studies that found either economies of scale and scope for smaller banks or diseconomies for larger financial institutions. Vander Vennet (1998) found evidence of economies of scale only for the smallest banks with assets under ECU 10 billion in the EU, with constant returns thereafter and diseconomies of scale for the largest banks exceeding ECU 100 billions, while similar results were obtained in other studies that examined single countries in the EU (e.g., Pallage, 1991, Rodriguez et al., 1993 and Kosmidou et al., 2006b).
The impact of the indicators of macroeconomic conditions on ROAA is significant in all cases but with opposite signs for domestic and foreign banks. Inflation (INF) is positively related to domestic banks, implying that during the period of our study the levels of inflation were anticipated by domestic banks. This gave them the opportunity to adjust the interest rates accordingly and consequently to earn higher profits. On the other hand in the case of foreign banks inflation brought a higher increase in costs than revenues as the negative relationship between inflation and foreign banks profits indicates. These mixed results could be attributed to different levels of knowledge of country macroeconomic conditions and expectations concerning inflation rate between domestic and foreign banks. The results about the impact of GDPGR on domestic banks ROAA are consistent with the results of Kosmidou et al. (2005), Kosmidou (2006), and Hassan and Bashir (2003) among others, and provide further support to the argument of positive association between economic growth and financial sector performance. However, there is a negative association between GDPGR and foreign banks ROAA. There are two possible explanations for this difference. First, banks in countries with higher GDP normally operate in more mature environments resulting in more competitive interest and profit margins (Staikouras and Wood, 2003) and a number of studies have shown that foreign banks are disadvantaged compared to domestic banks in developed countries (e.g., Peek et al., 1999, Berger et al., 2000, Claessens et al., 2001 and Sathye, 2001). Second, since GDP growth is assumed to have an impact on numerous factors related to the supply and demand of loans and deposits, the opposite signs of the coefficient of this variable between the two groups of banks could be related to the fact that (usually) domestic and foreign banks tend to serve different customers who may react different under the same macroeconomic conditions.
MACPASS and MACGDP are statistically significant and positively related to both domestic and foreign banks ROAA. ASSGDP is negatively related to ROAA in both cases, while the impact of concentration on ROAA differs between foreign and domestic banks. The positive and statistically significant relationship between either MACGDP or MACPASS and ROAA indicates that a larger stock market compared to either the economy or the banking sector increase bank profits. This finding confirms the empirical results of Ben Naceur (2003) who examined the Tunisian banking industry and suggested that as stock market enlarges, more information become available. This leads to an increase of potential number of customers to banks making easier the process of identification and monitoring of borrower that increases bank activity and profitability. The results about ASSGDP are consistent with the findings
银行盈利能力分析中英文对照外文翻译文献
of Demirguc-Kunt and Huizinga (1999) who found that in countries where banking assets constitute a large portion of the GDP, banks have smaller margins and are less profitable. The results also indicate a negative but not statistically significant relationship between concentration and domestic banks profits consistent with previous studies that found no evidence to support the structure–conduct–performance (SCP) hypothesis. From the 45 studies reviewed by Gilbert (1984) only 27 provide evidence that the SCP paradigm hold, while Staikouras and Wood (2003) also found no evidence to support the SCP hypothesis in their study of the EU banking sector over the period 1994–1998. Surprisingly, the results indicate that concentration has a positive and statistically significant impact on foreign banks profits. This is inconsistent with the results of Williams (2003) that examined the Australian market and found that concentration reduces profits of the foreign entrants and acts as an effective barrier to entry. We also expected foreign banks profits to be negatively related to concentration since foreign banks are usually smaller than domestic banks. A possible explanation in our case is that the majority of foreign banks in the sample come from few countries in which foreign banks dominate the market (e.g., Luxembourg) or hold a considerable proportion of banking sector's assets (e.g., UK). 6. Concluding remarks
In recent years numerous factors contributed to the increase of competition in the EU banking sector and posed great challenges to banks as the environment in which they operate changed rapidly. It is reasonable to assume that all these changes must have had some impact on banks’ performance. As Golin (2001) points out adequate earnings are required in order for banks to maintain solvency and to survive in a suitable environment. The relation between banks’ efficiency and the growth of the economy is now well documented. At the same time banks’ insolvencies have adverse consequences on the economy. Hence, knowledge of the underlying factors that influence banks’ profitability is essential, not only for the managers of the banks but for numerous stakeholders such as the Central Banks, Bankers Associations, Governments, and other Financial Authorities in the 15 EU countries. The conclusions drawn from this study would also be of particular interest to the new EU countries whose economies and banking systems are experiencing fundamental changes during this period.
For the reasons mentioned above this paper analyzed how financial characteristics and the overall banking environment affected the profitability of banks operating in the 15 EU banking industries. A balanced pooled times series dataset of 584 commercial banks operating during the period 1995–2001 provided the basis for the econometric analysis. Banks were also split according to their ownership resulting in two sub-samples of 332 domestic and 218 foreign banks.
The results indicated that profitability of commercial banks in European Union regardless of their ownership is affected by both internal characteristics and changes in the overall banking environment. The explanatory power (in terms of adjusted R2) of the model for domestic banks was much higher than that for foreign banks while F-statistic was significant at the 1% level for all models.