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Banking Competition and Banking Stability in SEM Countries: The Causal Nexus

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Advances in Analytics and Applications

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Abstract

The study tries to evaluate whether banking competition impacts the banking stability in the case of 32 Single European Market countries, and whether a guiding principle focus on banking competition is appropriate as a loom to boost banking stability. This study finds the interactions between banking competition and banking stability in 32 European countries between 1996 and 2014 with a panel vector auto-regressive model. Our observed results show that there is a cointegrating relationship between the two. Moreover, banking competition is a causative factor in banking stability in the long run. Thus, a focus on banking competition will enhance the banking stability of these countries.

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Notes

  1. 1.

    Theories of finance and economic growth nexus suggest that the financial purposes performed by banks (and other nonbanking financial intermediaries) are significant in encouraging economic growth (Levine 2005).

  2. 2.

    Competition has both positive and negative impact on banking stability. There exist two strands of literature which argue that competition in banking industry endangers financial stability. Increased competition in bank deposits wears away the profitability in the banking market and thus lowers the market power of banks, this is due to the increase in bank interest (see, for instance, Matutes and Vives 2000; Schaeck et al. 2009). Second, positive relationship exists between the two; competition created a number of benefits such as reducing liquidity and giving them in the form of bank loans to the public and sells securities to the investors. Less concentration in banking industry leads to good stability by diversifying both interest and noninterest income activities (Amidu and Wolfe 2013; Hellmann et al. 2000; Berger et al. 2009).

  3. 3.

    The SEM is meant for the benefit of all the European Union (EU) countries. Its mainstreams are the “four freedoms”: free movement of people, goods, services, and capital between all the EU member countries. These can be enjoyed, with limited exemptions, by everyone living and working in the EU.

  4. 4.

    Under different conditions of bank reforms in the host country, the degree of relationship between the two (banking stability and banking competition) varies.

  5. 5.

    Competition-fragility view (Marcus 1984; Keeley 1990; Hellmann et al. 2000) and competition-stability view (Boyd and De Nicolo 2005).

  6. 6.

    The panels used in this study are unbalanced due to data unavailability for some of these countries over the complete sample period.

  7. 7.

    European Single Market Countries (see, for instance, Jayakumar et al. 2018). It can be noted that some of these countries are transcontinental.

  8. 8.

    Some of these measures of banking competition have been used previously. (See, for instance, by Hamada et al. (2017), Fernandez et al. (2016), Kasman and Kasman (2015), Hakam et al. (2013), Bikker et al. (2007), Turk-Ariss (2009), and Boone (2008).)

  9. 9.

    Some of these measures of banking stability have been used previously, for example, by Carretta et al. (2015), Creel et al. (2015), Kasman and Kasman (2015), Tabak et al. (2012), Berger et al. (2009), Cihak and Hesse (2010), and Chang et al. (2008).

  10. 10.

    AIC-Akaike information criterion. A suitable statistical technique to fix optimum lag length (Brooks 2014).

  11. 11.

    See Maeso-Fernandez et al. (2006) and Pedroni (2001) for more details on FMOLS.

  12. 12.

    See Kao and Chiang (2000) for detailed description on DOLS.

  13. 13.

    The results are consistent with the findings of Fiordelisi and Mare (2014), Fu et al. (2014), Jeon and Lim (2013), Amidu and Wolfe (2013), Berger et al. (2009), and Allen and Gale (2004).

  14. 14.

    As it is apparent and is true in a most of the cases that we consider.

  15. 15.

    This is line with the study of Jayakumar et al. (2018).

  16. 16.

    To promote the banking stability in the economy, the banking authority should implement better policies and reforms supporting the banking competition in the market in a well-refined form.

  17. 17.

    It is widely regarded that a good banking system is as an important drivers of economic growth; while any failure in the banking system will have direct negative effect on any country’s economy (see, inter alia, Louzis et al. 2012; Dell’ Ariccia et al. 2008; Hogart et al. 2002; Levine and Zervous 1998).

  18. 18.

    See Jayakumar et al. (2018) for more details.

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Acknowledgements

We are thankful to anonymous reviewers and session chair (5th IIMA International Conference of Advanced Data Analysis, Business Analytics, and Intelligence (ICADABAI), April 8–9, 2017) for detailed suggestions that significantly improved the paper. We are also grateful to Professor Arnab K. Laha (the conference convenor, ICADABAI) for his valuable direction and kind support.

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Authors and Affiliations

  1. Vinod Gupta School of Management, Indian Institute of Technology Kharagpur, Kharagpur, 721302, West Bengal, India

    Manju Jayakumar, Rudra P. Pradhan, Debaleena Chatterjee, Ajoy K. Sarangi & Saurav Dash

Authors
  1. Manju Jayakumar
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  2. Rudra P. Pradhan
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  3. Debaleena Chatterjee
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  4. Ajoy K. Sarangi
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  5. Saurav Dash
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Corresponding author

Correspondence to Rudra P. Pradhan .

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Editors and Affiliations

  1. Indian Institute of Management Ahmedabad, Ahmedabad, Gujarat, India

    Arnab Kumar Laha

Appendices

Appendix 1: Description of Variables

Table 6 Definition of variables
Full size table

Appendix 2: Devising of Composite Index of Financial Stability by Using PCA

The study constructs a composite index of financial stability (CBS) using principal component analysis (PCA). We deploy the subsequent steps to obtain the CBS: (a) data are arranged in order to create an input matrix for principal components (PCs), subsequently the matrix is normalized, based on the min-max criteria; (b) expending PCA, eigenvalues, factor loadings, and PCs are derived; and (c) PCs are used to construct the “CBS” for each country and for each year. The detailed discussion of these stepsFootnote 18 is not available here due to conserve space.

To have the “CBS”, combination of few important variables relating to banking stability was utilized. The following four variables are used for CBS: bank capitalization (BCA), private credit by deposit money banks (PCD), performing loan assets (PLA), and return on assets (ROA). These four indicators are selected to calculate CBS, as they have a common unit of measurement, i.e., in percentage. Table 7 offers the statistical analysis of PCA.

Table 7 Instantaneous of PCA-related information for composite index of banking stability
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Jayakumar, M., Pradhan, R.P., Chatterjee, D., Sarangi, A.K., Dash, S. (2019). Banking Competition and Banking Stability in SEM Countries: The Causal Nexus. In: Laha, A. (eds) Advances in Analytics and Applications. Springer Proceedings in Business and Economics. Springer, Singapore. https://doi.org/10.1007/978-981-13-1208-3_21

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