Does higher competition lead to lower probability of license withdrawal in Russian banking sector?

Conclusion

To summarize, several conclusions can be made from the conducted analysis:

Russian banking sector has become more concentrated, therefore, less competitive since 2013. This tendency existed before 2013 according to the literature. All competition measures applied in the research show this trend. This dynamic is also true for competition in various groups (non-state-controlled banks; small banks, etc.), except for the group of state-owned commercial banks.

Dependence between competition and probability of license withdrawal is non-linear and inversely U-shaped. It implies, firstly, that whereas banking system is close to monopoly, no more banks' licenses should be withdrawn (explanation for that might be that monopoly in banking will lead to distress in financial system), secondly, that high competition in banking results in qualitative financial products that provide banks with low default probability.

Results of the research may be of interest to the regulator and banks' management. In the study various graphs and tables with state of competition in Russian banking sector are presented. That helps to realize the dynamics and, therefore, correct future goals of the Central Bank if it is needed. Also, these results can help banks' management to understand better when they should lower accepted risks to avoid license withdrawal.

There are several suggestions for further researches in this field. It would be reasonable to consider effects of different countries and compare developed and emerging countries. Impact of competition in developed and developing states might differ dramatically. Also, more competition measures can be examined, including non-structural parameters as individual market power. And markets in financial system might be divided more accurate and precise. Thus, for example, mortgages, personal crediting, etc. can be defined on loan market.

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Appendix

Table A.1

This table represents time series of competition measurements. There are three blocks: competition with respect to assets, loans and deposits. Five indices are calculated for each block: the concentration ratios for top 5; 10 and 20 commercial banks (CRk_i, where k = 5; 10; 20); Herfindahl - Hirschman index (HHI_i) and the Hall - Tideman index (HT_i), where i = a (assets), l (loans), d (deposits).

Table A.1 continued

Figure A.1. Figure A.1 presents concentration ratio CR10 of assets (green line), loans (orange line) and deposits (blue line). The share of the largest 10 commercial banks has been increasing since 2014. Markets have become more concentrated according to this graph.

Figure A.2. Figure A.2 presents concentration ratio CR20 of assets (green line), loans (orange line) and deposits (blue line). The share of the largest 20 banks has been gradually increasing since 2014 as well, markets have become more concentrated and less competitive. Top 20 banks own over 80% of the markets since 01.04.2018.

Table A.2

This table represents time series of competition measurements in the group of state-owned commercial banks: competition with respect to assets, loans and deposits. Five indices are calculated for each market: the concentration ratios for top 5; 10 and 20 commercial banks (CRk_i, where k = 5; 10; 20); Herfindahl - Hirschman index (HHI_i) and the Hall - Tideman index (HT_i), where i = a (assets), l (loans), d (deposits).

Table A.3

This table presents time series of competition measurements in the group of commercial banks that are not state-owned: competition in assets, loans and deposits. Five indices are calculated for each market: the CRs for top 5; 10 and 20 banks (CRk_i, where k = 5; 10; 20); Herfindahl - Hirschman index (HHI_i) and the Hall - Tideman index (HT_i), where i = a (assets), l (loans), d (deposits).

Table A.4

This table presents time series of competition measurements in the group of the largest banks in Russia: competition in assets, loans and deposits. Five indices are calculated for each market: the CRs for top 5; 10 and 20 banks (CRk_i, where k = 5; 10; 20); Herfindahl - Hirschman index (HHI_i) and the Hall - Tideman index (HT_i), where i = a (assets), l (loans), d (deposits).

Figure A.3. This figure illustrates HHI of assets (green line), loans (orange line) and deposits (blue line) in the group of the biggest banks of Russia.

Table A.5

This table presents time series of competition measurements in the group of the medium banks in Russia: competition in assets, loans and deposits. Five indices are calculated for each market: the CRs for top 5; 10 and 20 banks (CRk_i, where k = 5; 10; 20); Herfindahl - Hirschman index (HHI_i) and the Hall - Tideman index (HT_i), where i = a (assets), l (loans), d (deposits).

Figure A.4. This figure shows HHI of assets (green line), loans (orange line) and deposits (blue line) in the medium cluster of banks.

Table A.6

This table presents time series of competition measurements in the group of the smallest banks in Russia: competition in assets, loans and deposits. Five indices are calculated for each market: the CRs for top 5; 10 and 20 banks (CRk_i, where k = 5; 10; 20); Herfindahl - Hirschman index (HHI_i) and the Hall - Tideman index (HT_i), where i = a (assets), l (loans), d (deposits).

Figure A.5. This figure shows HHI of assets (green line), loans (orange line) and deposits (blue line) in the cluster of the smallest banks.

Table A.7

This table presents comparison of several models: logit model with fixed effects and with first, second and third lags of some variables; pooled probit model with lags; probit model with random effects with lags. Pseudo-R2, AIC and BIC prove that logit specification is better on this sample.

Table A.8

This table presents results of models with different competition measures. All the models here are logit specifications with fixed effects.

Table A.8 continued

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