Definición de los centros de actividad

A first overview of the average bank-level balance sheet shows distinct larger deposit funding and loans levels than reflected in the country-level balance sheet (cf. Figure 2.1.2, p. 10 and Figure 5.2.5). This highlights the differences in definitions between our country-level and bank-level data sources. On average the deposit funding levels in sample shows an increase which is in line with the country-level data. The majority of all country-year observations (6,863) originate from France (1,050) and Germany (4,009). In terms of total asset and deposit funding distributions, the country-level and bank-level data set show great similarities (see Table 5.2.2), and again France, Germany Italy, Luxembourg and the Netherlands account for 80 per cent of total assets. The similarities in bank-level and country-level data are manifested especially from 2005 and onwards (see Appendix B, Figures B.1-B.3).

Changes in the relative deposit funding levels (Measure C) since the crisis are minor with approximately 2 per cent and the relative Measures for other balance sheet classes remain stable as well. The stability of bank balance sheet classes over total assets (Measure C) is also found in the other balance sheet classes – with the exception of advances to banks. An overview of the bank balance sheet classes over total assets is included in Appendix E.1.

Assignment to clusters – In order to examine deposit funding levels across the bank orientation cross-

section, we assign banks with similar characteristics to the same bank business orientation cluster.

6_{See the discussion of the impact of the financial crisis on the Euro Area deposit funding levels.}

0.00 0.20 0.40 0.60 0.80 1.00 Assets (measure C) 1995 2000 2005 2010 2015 Year Loans Securities

Advances to banks Other assets

0.00 0.20 0.40 0.60 0.80 1.00 Liabilities (measure C) 1995 2000 2005 2010 2015 Year

Capital Deposit funding Wholesale funding Other liabilities

Figure 5.2.5: Average bank-level bank balance sheet between 1999-2013.

In line with Ayadi et al. (2011), we employ Ward’s (1963) hierarchical cluster analysis technique to

differentiate between banks on the continuum of investment and retail orientations (see Table 2.2.2). We base the analysis on deposit funding, wholesale funding and capital as the main variables of the funding structure, loans, securities and advances to banks as the main variables of the asset mix and interest income, fee and commission income and trading income. We normalize these variables over total assets and gross income (Measure C) and include the natural logarithm of total assets (Measure B)

to moderate size differences. The clustering procedures shows a maximum in the pseudo F −index and

pseudo T 2−index at the two cluster configuration,7 _{indicating the most distinct combination of maximum}

between-cluster variance and minimum within-cluster variance with two clusters (see Table 5.2.3). This distinction is supported by the cluster-tree in Figure E.8 which schematically shows the dissimilarities between different cluster configurations.

Robustness of clustering – In order to determine the robustness of this result, we examined the

cluster analysis for for different time windows and found also a distinct two cluster configuration in the period 2008-2013. The use of non-normalized measures (Measure A) also had no influence on the dominant cluster configuration. In line with Demirgüç-Kunt and Huizinga (2010), Köhler (2014) and others, we consider the exclusion of the income items and drop a number of asset and liability classes which results in a five distinct cluster configuration. A closer examination reveals that the difference with our earlier findings results from sub-categorization on total assets while other characteristics remain identical. Hence, the different configuration is due to a number of large outliers in terms of total assets and due to differences in bank business orientation. This examination of robustness shows that the two cluster configuration indeed reflects the most likely dominant configuration of bank business models.

7 _{Two major outliers were removed. In 2011 Delta Lloyd NV-Delta Lloyd Group and in 2012 Banque Internationale à Luxembourg}

Loans

Securities

Advances

Deposit funding

Capital

Wholesale funding

Figure 5.2.6: Spider diagram of the different bank business orientations.

Bank business orientation typologies – The descriptive details of the two clusters are reported in Ta­

ble B.1. With the reservations mentioned earlier, we describe the two business orientations as a retail orientation (Cluster 1) and an investment orientation (Cluster 2). This differentiation is primarily based on the difference in reliance on deposit funding, wholesale funding, securities and trading income; how­

ever, simple t−tests show that the two clusters differ on all selected variables at the 99% significance

level. The retail oriented bank sample comprises roughly 75 per cent of the sample and relies pri­ marily on deposit funding which is nearly one sample standard deviation greater than the investment orientation. Furthermore, the retail oriented bank sample relies significantly less on wholesale funding, securities and trading income. Differences on the other variables are in line with our expectations, with the exception of the income profile variables and advances to banks. The advances to banks are most likely due to the large number of German banks included in the sample and the German bank sector structure.8

Over the complete period from 1999 to 2013, the sample contains more banks with a retail orientation than with an investment orientation. However, the number of banks for each bank business orienta­ tion was not constant (see Figure 5.2.8). Between 1999 and 2009 more banks showed an investment orientation while since 2010 the retail orientation was the most dominant orientation again. Although investment-oriented banks were less reliant on deposits for funding and just 17 per cent of the banks were assigned to the investment orientation, in absolute levels 82 per cent of the total deposit fund-

specific banks. We assigned these banks to the cluster in the previous year.

8_{Germany has a number of large co-operative and government-owned regional banks which are interconnected through interbank}

deposits and advances to banks.

Pseudo Pseudo Pseudo Pseudo

# Je(1)/Je(2) # Je(1)/Je(2)

F −index T 2−index F −index T 2−index

1 − 0.395 10482 9 6313 0.838 453 2 10482 0.493 5805 10 5921 0.800 495 3 9728 0.484 1279 11 5580 0.631 342 4 9503 0.677 1234 12 5314 0.754 260 5 8418 0.475 622 13 5091 0.761 580 6 7763 0.785 836 14 4895 0.599 135 7 7115 0.562 495 15 4711 0.752 209 8 6742 0.796 354

Table 5.2.3: Results of the cluster analysis on the complete sample 1999-2013.

ing level in the sample were concentrated within investment-oriented banks (see for more descriptives Table B.1 in Appendix B.4).

Cross-bank business orientation variations (H1d; accepted) – Banks vary in size across their bank

orientation. Retail oriented banks are larger in number and their relative deposit funding level is signif­ icantly higher than those of the investment oriented banks. However, retail banks are on average also

approximately 40 times smaller in size (see Appendix B.1, Table B.2). Paired t−tests indicate significant

differences in deposit funding levels between the two identified business orientations, both on Measure A and Measure C. Furthermore, the box plot of deposit funding levels (Measure B) show consistent differences across business orientations (see Figure 5.2.9). Hence, we accept Hypothesis 1d.

The finding of variation in bank business orientations is not new (see e.g., Cavelaars & Passenier,

2012; Köhler, 2014; Ayadi et al., 2011). However, most researchers differentiate business orientations

distinctively by the proportion deposit funding in their funding profile. Furthermore, implications of on

the concentration of deposit funding levels are rarely discussed. Due to differences in sheer size,

investment-oriented banks accumulate the majority of deposit funding in the Euro Area: roughly 75-85 per cent of the yearly total deposit funding volume in the Euro is allocated to investment-oriented banks while retail-oriented banks are twice as reliant on deposits for funding.