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Concentration of Banking Relationships in Switzerland: The Result of Firm Structure or Banking Market Structure?

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Abstract

Switzerland is one of the countries with the highest concentration of bank–customer relationships. The present paper seeks to find out whether this can be explained by the structure of Swiss firms or by the organization of the Swiss banking market. Using survey data from small and medium-sized enterprises in 1996 and 2002, we examine the influence of firm-, loan-, and bank-specific variables on the number of banking relationships. We find that firm and industry structure have the largest explanatory power, while banking market structure and conduct play a minor role. Relationship lending by state-owned cantonal banks and small regional banks tends to enhance the concentration of banking relationships.

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Notes

  1. For surveys on relationship banking see Boot (2000), Ongena and Smith (2000a), and Elyasiani and Goldberg (2004).

  2. For a discussion of different measurements of banking relationships and their use in previous studies see Neuberger et al. (2006). In contrast to the present study, the latter focuses on the changes in lending relationships of Swiss SMEs between 1996 and 2002.

  3. This does not necessarily imply that large banks are disadvantaged in providing credit to opaque SMEs since they may use transaction lending technologies well-suited to these enterprises, such as small business credit scoring, asset-based lending, factoring, fixed-asset lending, and leasing (Berger and Udell 2006).

  4. Since technological change has eased the ability to lend to small firms at a distance (Petersen and Rajan 2002), out-of-market lending to small firms in local markets increased substantially in recent years (Hannan 2003).

  5. See Elsas and Krahnen (2000), Lehmann and Neuberger (2001), Machauer and Weber (1998), and Menkhoff et al. (2006).

  6. See e.g. Petersen and Rajan (1994), Cole (1998), Harhoff and Körting (1998a, b), Machauer and Weber (1998), D’Auria et al. (1999), Ongena and Smith (2001), Ferri et al. (2001), Menkhoff et al. (2006); for an overview see Lehmann et al. (2004).

  7. Due to limited space, Table 1 does not report the results of Ogawa et al. (2007) regarding the number of long-term lending relationships in Japan or the results of Fok et al. (2004), which are similar to those of Yu and Hsieh (2006) for Taiwan.

  8. Among others, the USA (Petersen and Rajan 1994; Berger and Udell 1995), Germany (Harhoff and Körting 1998a, b; Elsas and Krahnen 1998; Neuberger and Räthke 2008), Norway (Ongena and Smith 2001), Sweden (Berglöf and Sjögren 1998), and France (Ziane 2003); an exception is Italy (Detragiache et al. 2000; Guiso 2003; Cosci and Meliciani 2002). For overviews see Ongena and Smith (2000a, pp.243) and Neuberger and Räthke (2008).

  9. For an overview see Berger and Udell (2006), Akhavein et al. (2004) and Carter et al. (2004).

  10. In 1995, the ratio of outstanding credits to outstanding bonds was above 140% in Switzerland, compared to 94% in Germany, 83% in the USA, and 75% in the UK (Schmid and Varnholt 1997, p. 310; see Hertig 1998, p. 812). The volume of leasing and factoring is low in Switzerland (Pedergnana et al. 2004, p. 23). In 2002, the ratio of the volume of factoring to GDP was 0.9% compared to 11.9% in Italy (Berger and Udell 2006, p. 6).

  11. In 1997, the big banks and cantonal banks had a combined market share of the credit volume above 80% (Schacht 2005, p. 53), with the big banks providing most of the international banking services. In 2002, 16% of the SMEs used international bank services, 70% of which were provided by the big banks (Source: own calculations with the data described below).

  12. The cantonal banks introduced risk-adjusted pricing to a lesser extent. From 1997 to 1998, the average interest rate on SME loans was raised by 3% at the big banks, but by only 1.2% at the cantonal banks (Task Force KMU 1999, p. 7; Pedergnana et al. 2004, p.102). With the introduction of risk-adjusted pricing by the big banks in 1997, the Basel II capital adequacy rules have been largely anticipated in Switzerland (Credit Suisse 2004).

  13. Excluding the two city cantons of Basle City and Geneva, the correlation coefficient between population density and branch density was −0.53 in 2002.

  14. The HHI is calculated by summing the squared market shares of all banks competing in the market. We are grateful to Daniel Piazza for providing us with this data.

  15. According to the US Merger Guidelines, markets in which the HHI exceeds 1,800 points are considered to be concentrated.

  16. Since our dependent variable takes integer values, the Poisson model may be more suitable than OLS. The negative binomial model is a generalization of the Poisson model, which is appropriate in the case of over/underdispersion in the latter (Cameron and Trivedi 1990). Using a regression-based test, we can reject the null hypothesis of no over/underdispersion in the Poisson regression model.

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Authors and Affiliations

  1. Department of Economics, University of Rostock, Ulmenstr. 69, 18057, Rostock, Germany

    Doris Neuberger & Solvig Räthke-Döppner

  2. IFZ Institute for Financial Services Zug, University of Applied Sciences Central Switzerland, Grafenauweg 10, Postfach 4332, CH-6304, Zug, Switzerland

    Maurice Pedergnana

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  1. Doris Neuberger
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  2. Maurice Pedergnana
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  3. Solvig Räthke-Döppner
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Correspondence to Doris Neuberger.

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This article is based on the research project no. 6476.1 FHS-ET “Lending Relationships Between Banks and SMEs”, conducted at the IFZ Institute for Financial Services Zug, University of Applied Sciences Central Switzerland. It was supported by the CTI: The Innovation Promotion Agency in Switzerland and the Association of Swiss Cantonal Banks, Bern, Switzerland. We are grateful to Christoph Schacht for valuable research assistance and contributions and to two referees for helpful suggestions. The usual disclaimers apply.

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Neuberger, D., Pedergnana, M. & Räthke-Döppner, S. Concentration of Banking Relationships in Switzerland: The Result of Firm Structure or Banking Market Structure?. J Finan Serv Res 33, 101–126 (2008). https://doi.org/10.1007/s10693-008-0026-7

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