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Competition in the Clearing and Settlement Industry

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Abstract

This chapter empirically analyzes the competitive landscape within the clearing and settlement industry. Using the panel data of 46 clearing and settlement institutions from 23 countries we confirm that competition between clearing and settlement institutions is limited. We show that competition increases with the institutional size, with technological development and after horizontal mergers but not after vertical mergers. Additionally, we find that competition in clearing and settlement is higher in the U.S. than in Europe and higher during the global financial crisis compared to normal times.

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Notes

  1. 1.

    Several studies analyze competition in banking industry across countries. De Bandt and Davis (2000) provide evidence that the behavior of large banks in the EMU was less competitive compared to the banks in the U.S. Competition appears to be lower among small banks, especially in France and Germany. Bikker and Haaf (2002) work on a study of 23 industrialized countries and conclude that in local markets competition is weaker than in international markets. Gelos and Roldós (2004) focus on eight emerging markets during the 1990s and argue that lower entry barriers mitigated a decline in competition driven by consolidation. Claessens and Laeven (2004) analyze competition across 50 banking systems and argue that higher competition is associated with lower restrictions to bank entry and to bank activities. Schaeck et al. (2009) provide evidence that more competitive banking systems are less likely to undergo a systemic crisis. Liu et al. (2013) confirm the positive relation between competition and bank stability among regional banks in 11 European countries.

  2. 2.

    Following Schmiedel et al. (2006), we use the operating income as a measure of the clearing and settlement income. We also use total revenue as another measure of revenue for robustness check. Bikker et al. (2012) argue that a scaled revenue function creates a significant upward bias and incorrectly measures the degree of competition. We follow their suggestion and employ the unscaled revenue function.

  3. 3.

    VerticallyMerged it equals one for the whole sample period if the clearing and settlement institution was vertically integrated before our sample period. If the vertical integration occurs during the sample period, VerticallyMerged it equals zero before vertical integration and one after vertical integration.

  4. 4.

    The inclusion of logarithm of total assets as a proxy for the size of a clearing and settlement institution results in an upward bias and incorrect measure of competition (see Bikker et al. 2012). We include Market share it as a proxy for size to control for size effect on dependent variable in regression (operating income or total revenue). Market share it does not unscale the dependent variable and therefore bypasses the main concern of Bikker et al. (2012). We thank the anonymous referee for this suggestion. Our results are robust even if we do not include Market share it as a control variable.

  5. 5.

    The inclusion of year dummy variables and institution dummy variables partially controls for changes in regulation across countries and for changes in accounting standards (see also Sect. 4.7.4).

  6. 6.

    Panzar and Rosse (1987, p. 446) show that for a pure monopoly higher H-statistic is negatively related to market power (in the case of constant returns to scale Cobb-Douglas technology, see also Shaffer 2004). Vesala (1995a, b) confirms the negative relationship between H-statistic and market power in the case of monopolistic competition with free entry (but not for monopolistic competition without the threat of entry, see also Shaffer 1982, 1983a, b).

  7. 7.

    Without de-meaning, the coefficients on the unit input price variables in the regression with the interaction terms correspond to the partial derivative of the dependent variable with respect to the unit input price variables when the factor variable j equals zero. This differs from the interpretation of the unit input price variables in a regression without the interaction terms. By de-meaning, the interpretation of the coefficients on the unit input price variables in the regression with the interaction terms closely corresponds to the ones in regression without the interaction terms (Balli and Sørensen 2013). See also Popov and Udell (2012), Guidara et al. (2013) and Montes (2014).

  8. 8.

    The Lerner index is widely used to estimate competition in the banking sector. Coccorese (2009) points out that Lerner index is a true reflection of the bank’s degree of market power. Angelini and Cetorelli (2003) assess the behavior of Italian regional banks and find that deregulation fostered a reduction in price-costs margins. See also Koetter et al. (2012) and Fu et al. (2014).

  9. 9.

    Several other approaches that mostly build on the Lerner measure of market power have been developed. For example, Bresnahan (1982) and Lau (1982) estimate the conjectural variation coefficient based on the deviation of perceived firm revenues from demand. A high conjectural variation implies that a firm is highly aware of its interdependence with other firms in terms of output and prices (see also Appelbaum 1979; Iwata 1974).

  10. 10.

    Under the Anderson and Rubin (1949) test of the validity of the instruments, the hypothesis that the instruments are not valid is rejected at 5% level for all regression models based on (4.10) and (4.11). Hansen’s J statistic provides a test for the joint validity of instruments. The null hypothesis that the overidentifying restrictions are correct cannot be rejected. In addition to this, the underidentification test (measured by the Kleibergen–Paap rk LM statistic (Kleibergen and Paap 2006) and weak identification test [measured by the Cragg–Donald Wald F statistic (Cragg and Donald 1993), and Kleibergen–Paap Wald rk F statistic (Baum et al. 2007)] also confirm the validity of instrumental variables.

  11. 11.

    We focus on clearing and settlement institutions from the U.S., the EU countries, and countries closely related to the EU, i.e., Switzerland, Iceland, Bosnia & Hercegovina, and Turkey, which are either members of the European Free Trade Association or candidate countries for EU accession. The clearing and settlement institutions from these countries are also members of European Central Securities Depositories Association.

  12. 12.

    The inclusion of scale in estimation of H-statistic results in a significant upward bias and an incorrect measure of the degree of competition (Bikker et al. 2012). The estimated H-statistic in column 2 in Table 4.5 is based on a scaled revenue function and is therefore not considered for evaluation of competitive condition.

  13. 13.

    These findings resemble observations in the banking industry. Bikker and Groeneveld (2000), De Bandt and Davis (2000), Bikker and Haaf (2002), Hempell (2002), and Bikker (2004) find that competition in banking increases with a bank’s size.

  14. 14.

    The finding that competition in clearing and settlement is higher in countries with HHI = 1 compared to countries with HHI < 1 holds also for the subsamples of EU countries and euro area countries.

  15. 15.

    For example, DTCC has offices in 15 countries around the world, Annual report of DTCC (2013), http://www.dtcc.com/annuals/2013/pdfs/DTCC-Annual-Report-2013.pdf.

  16. 16.

    In all our estimations we have included time and institution dummy variables to partially mitigate the concern that the differences in regulation are correlated with factor variables (δ t , ICSD i , Market share it , Horizontal merger it , Vertical merger it , and ICT ratio it ) and are therefore affecting the results.

  17. 17.

    European Markets Infrastructure Regulation (Regulation 153/2013, OJ L52/41, 23.2.2013).

  18. 18.

    Directive 2014/65/EU of the European Parliament and of the Council of 15 May 2014 on markets in financial instruments and amending Directive 2002/92/EC and Directive 2011/61/EU, OJ L173/349, 12.6.2014.

  19. 19.

    Regulation (EU) No 600/2014 of the European Parliament and of the Council of 15 May 2014 on markets in financial instruments and amending Regulation (EU) No 648/2012, OJ L173/84, 12.6.2014.

  20. 20.

    Regulation (EU) 909/2014 on improving securities settlement in the European Union and on central securities depositories, OJ L257/1, 28.8.2014.

  21. 21.

    When considering the effect of the factor variables on H-statistic in the euro area subsample, the results predominantly hold but with lower statistical significance. The results are available upon request.

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Acknowledgements

This chapter is co-authored with Matej Marinč. We would like to thank two anonymous referees, Iftekhar Hasan, Marko Košak, Igor Lončarski, Emmanouil Noikokyris, the participants at the 2nd EBR Conference in Ljubljana, the 9th EBES Conference in Rome, the 13th INFINITI Conference on International Finance in Ljubljana, and the 7th International IFABS Conference in Hangzhou for their valuable comments and suggestions. This chapter was published in Journal of International Financial Markets, Institutions & Money.

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Li, S. (2018). Competition in the Clearing and Settlement Industry. In: Financial Institutions in the Global Financial Crisis. Springer, Singapore. https://doi.org/10.1007/978-981-10-7440-0_4

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