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Banking sector diversity and socioeconomic structure—criteria for matching pairs

  1. Journals
  2. Economics, Finance, Business & Management
  3. Vierteljahrshefte zur Wirtschaftsforschung
  4. Vol. 87, Issue 4
  5. pp. 39–54

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Gischer, H., Ilchmann, C. Banking sector diversity and socioeconomic structure—criteria for matching pairs. Vierteljahrshefte zur Wirtschaftsforschung, 87(4), 39-54. https://doi.org/10.3790/vjh.87.4.39
Gischer, Horst and Ilchmann, Christian "Banking sector diversity and socioeconomic structure—criteria for matching pairs" Vierteljahrshefte zur Wirtschaftsforschung 87.4, 2018, 39-54. https://doi.org/10.3790/vjh.87.4.39
Gischer, Horst/Ilchmann, Christian (2018): Banking sector diversity and socioeconomic structure—criteria for matching pairs, in: Vierteljahrshefte zur Wirtschaftsforschung, vol. 87, iss. 4, 39-54, [online] https://doi.org/10.3790/vjh.87.4.39
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Banking sector diversity and socioeconomic structure—criteria for matching pairs

Gischer, Horst | Ilchmann, Christian

Vierteljahrshefte zur Wirtschaftsforschung, Vol. 87 (2018), Iss. 4 : pp. 39–54

2 Citations (CrossRef)

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Article Details

Publisher Name
Duncker & Humblot
DOI
https://doi.org/10.3790/vjh.87.4.39
Language
English
Pages
16
Keywords

Author Details

Horst Gischer (corresponding author), Otto-von-Guericke University Magdeburg and Forschungszentrum für Sparkassenentwicklung e. V.

Christian Ilchmann, Otto-von-Guericke University Magdeburg.

Cited By

  1. Systemic Risk in the Banking Sector – The German Model

    Burghof, Hans-Peter | Gischer, Horst

    Vierteljahreshefte zur Arbeits- und Wirtschaftsforschung, Vol. 1 (2024), Iss. 2 P.155

    https://doi.org/10.3790/vaw.2024.1447202 [Citations: 0]

  2. Bankenwettbewerb und die Stabilität von Finanzsektoren

    Richter, Toni

    Zeitschrift für Wirtschaftspolitik, Vol. 70 (2021), Iss. 1 P.1

    https://doi.org/10.1515/zfwp-2021-2044 [Citations: 0]

References

  1. Ayadi, Rim, Willem De Groen, Ibtihel Sassi, Walid Mathlouthi, Harol Rey and Olivier Aubry (2016): Banking Business Models Monitor 2015 Europe. Centre for European Policy Studies, Brussels.  Google Scholar
  2. BIS (2018a): Summary of debt securities outstanding. http://stats.bis.org/statx/srs/table/c1 (accessed December 2018).  Google Scholar
  3. BIS (2018b): Consolidated banking statistics (CBS_PUB). http://stats.bis.org:8089/sta-tx/srs/table/b1?m=S&f=csv (accessed December 2018).  Google Scholar
  4. Behr, Patrick, Lars Norden and Felix Noth (2013): Financial constraints of private firms and bank lending behavior. Journal of Banking & Finance, 37, 3472–3485.  Google Scholar
  5. Brämer, Patrick, Horst Gischer and Toni Richter (2010): Das deutsche Bankensystem im Umfeld der internationalen Finanzkrise, List Forum für Wirtschafts- und Finanzpolitik, 36 (4), 318–334.  Google Scholar
  6. Bureau van Dijk (2018): Orbis BankFocus database. https://banks.bvdinfo.com/version-20181219/home.serv?product=OrbisBanks (accessed December 2018).  Google Scholar
  7. Calinski, Tadeusz, and Jerzy Harabasz (1974): A dendrite method for cluster analysis. Communications in Statistics, 3, No. 1, 1–27.  Google Scholar
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  11. Gischer, Horst, and Christian Ilchmann (2017): CMU—a threat to the German banking sector? Quarterly Journal of Economic Research, 86 (1/2017), 81–94.  Google Scholar
  12. Langfield, Sam, and Marco Pagano (2016): Bank bias in Europe: Effects on systemic risk and growth. Economic Policy, 31 (85), 51–106.  Google Scholar
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  20. Ward, Joe (1963): Hierarchical grouping to optimize objective function. Journal of the American Statistical Association, 58 (301), 236–244.  Google Scholar
  21. Ayadi, Rim, Willem De Groen, Ibtihel Sassi, Walid Mathlouthi, Harol Rey and Olivier Aubry (2016): Banking Business Models Monitor 2015 Europe. Centre for European Policy Studies, Brussels.  Google Scholar
  22. Behr, Patrick, Lars Norden and Felix Noth (2013): Financial constraints of private firms and bank lending behavior. Journal of Banking & Finance, 37, 3472–3485.  Google Scholar
  23. BIS (2018b): Consolidated banking statistics (CBS_PUB). http://stats.bis.org:8089/sta-tx/srs/table/b1?m=S&f=csv (accessed December 2018).  Google Scholar
  24. World Bank (2018b): GDP (current US$). https://data.worldbank.org/indicator/NY.GDP.MKTP.CD (accessed December 2018).  Google Scholar
  25. World Bank (2018a): Market capitalization of listed domestic companies. https://data.worldbank.org/indicator/CM.MKT.LCAP.CD (accessed December 2018).  Google Scholar
  26. Schmidt, Reinhard (2018): Passt das deutsche Dreisäulensystem in eine zunehmend harmonisierte Bankenstruktur für Europa? Zeitschrift für das gesamte Kreditwesen, 71, 34–37.  Google Scholar
  27. Lucas, Robert (2013): Glass-Steagall: A Requiem. American Economic Review, 103 (3),43–47.  Google Scholar
  28. Levine, Ross (2002): Bank-Based or Market-Based Financial Systems: Which Is Better? Journal of Financial Intermediation, 11, 398–428.  Google Scholar
  29. Langfield, Sam, and Marco Pagano (2016): Bank bias in Europe: Effects on systemic risk and growth. Economic Policy, 31 (85), 51–106.  Google Scholar
  30. Gischer, Horst, and Christian Ilchmann (2017): CMU—a threat to the German banking sector? Quarterly Journal of Economic Research, 86 (1/2017), 81–94.  Google Scholar
  31. Gischer, Horst, and Bernhard Herz (2016): Das Geschäftsmodell „Regionalbank“ auf dem amerikanischen Prüfstand. Credit and Capital Markets: Kredit und Kapital, 49 (2), 175–191.  Google Scholar
  32. Eurostat (2018): Eurostat regional yearbook. 2018 edition. European Commission, Brussels.  Google Scholar
  33. ECB (2017): CBD2—Consolidated Banking data. http://sdw.ecb.europa.eu/browse.do-?node=9689685 (accessed December 2018).  Google Scholar
  34. Calinski, Tadeusz, and Jerzy Harabasz (1974): A dendrite method for cluster analysis. Communications in Statistics, 3, No. 1, 1–27.  Google Scholar
  35. Bureau van Dijk (2018): Orbis BankFocus database. https://banks.bvdinfo.com/version-20181219/home.serv?product=OrbisBanks (accessed December 2018).  Google Scholar
  36. Brämer, Patrick, Horst Gischer and Toni Richter (2010): Das deutsche Bankensystem im Umfeld der internationalen Finanzkrise, List Forum für Wirtschafts- und Finanzpolitik, 36 (4), 318–334.  Google Scholar

Abstract

It has been an age-old debate whether the financial structure matters for the real economy’s efficiency and therefore for real outcomes. We suppose that varying socioeconomic conditions require appropriately designed corresponding financial sectors. For providing evidence, we firstly determine the specific (quantitative) size and corporate alignments of banking sectors across Europe, based on a sophisticated cluster analysis. Secondly, we develop a coherent system of geographic, social and economic parameters to identify structural patterns within the real economy’s sector. In a conclusive synthesis, we link both analytical parts and draw tentative conclusions for possible future policy implications in Europe.

Table of Contents

Section Title Page Action Price
Horst Gischer and Christian Ilchmann: Banking sector diversity and socioeconomic structure—criteria for matching pairs 1
Summary 1
Zusammenfassung 1
1 Introduction 2
2 Structural diversity in banking sectors—an approach to identifyspecific features 2
3 Real economies’ requirement specifications 8
3.1 Geographical considerations 8
3.2 Aspects of Economic Infrastructure 1
4 Synthesis 1
References 1

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