Banks’ capital buffers, risk, and efficiency in emerging economies: are they counter-cyclical?

Abstract

This paper examines the relationship of banks’ capital buffers, risk and efficiency adjustments with cyclical movements. Empirically, we have used dynamic panel data from 461 banks of the BRICS countries (i.e., Brazil, Russia, India, China, and South Africa) for the period 2007–2015 and we also have empirically included Stochastic Frontier Analysis (SFA) to measure the efficiency. In contrast to the consequence of past investigations, this examination additionally affirms the noteworthy effect of macroeconomic fluctuations on the determination of capital buffers, risk and efficiency. The key results of five big emerging countries are as follows: (1) capital buffers of Russia, India, China, and South Africa behave counter-cyclically while it is pro-cyclical for Brazilian banks over the business cycle; (2) there is an anti-cyclical (pro-cyclical) and significant relation between risk (stability) and business cycle for four countries and no significant relation for South Africa; (3) it shows pro-cyclicality of bank’s efficiency except for South African banks; and (4) notably, the adjustment speed of capital buffers is higher for Chinese and Indian banks than Brazilian, Russian and South African banks. Finally, it provides some policy implications for the emerging economies regarding capital buffers, risk, and efficiency adjustment decisions.

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Fig. 1
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Notes

  1. 1.

    These studies focused on the US bank holding company and banking sectors of 13 Latin American and Caribbean countries whereas; in our case, it is BRICS countries.

  2. 2.

    See more among others Shrieves and Dahl (1992), Jacques and Nigro (1997), Rime (2001), and Shim (2013).

  3. 3.

    The weak instruments’ problem appears in models with endogenous regressors in which too many instruments may result in biased estimates of the parameters of interest.

  4. 4.

    See more at http://data.worldbank.org/indicator.

  5. 5.

    Each bank in the sample has a minimum number of consecutive observations of 4 years.

  6. 6.

    Where, Under Basel-II, banks are followed to maintain the Minimum Capital Requirement (MCR) at 8.0 percent of total Risk Weighted Assets (RWA). But practically, the minimum level of required capital is not homogenous in countries. Therefore, we consider 8 percent as the threshold for the minimum capital requirement.

  7. 7.

    By using software package-Frontier 4.1 versions, we estimate cost efficiency in considering a three output (loans, securities and deposits, and short-term funding), three input (price of the fund, the price of physical capital and price of diversification). By considering these, we have developed the multiproduct translog cost function as follows: \(\ln \,{\text{TC}} = \alpha_{0} + \mathop \sum \nolimits_{i} \alpha_{i} \ln Q_{i} + \mathop \sum \nolimits_{j} \beta_{j} \ln P_{j} + \frac{1}{2}\mathop \sum \nolimits_{i} \mathop \sum \nolimits_{k} \gamma_{ik} \ln Q_{i} \ln Q_{k} + \frac{1}{2}\mathop \sum \nolimits_{j} \mathop \sum \nolimits_{h} \delta_{jh} \ln P_{j} \ln P_{h} + \mathop \sum \nolimits_{i} \mathop \sum \nolimits_{j} \lambda_{ij} \ln Q_{i} \ln P_{j} + \, \varepsilon ,\) where, ln TC the natural logarithm of total costs (operating and interest expenses); ln Qi the natural logarithm of outputs, (gross loans, total securities and deposit and, short-term funding); ln Ph the natural logarithm of ith input prices (i.e. price of funds, price of physical capital and price of diversification).

  8. 8.

    For details, see Altunbas et al. (2007), and Miah and Sharmeen (2015).

  9. 9.

    This study shows a negative relationship between bank concentration ratio and capital adequacy but not significant.

  10. 10.

    For brevity, we only report the highest coefficient between two independent variables.

  11. 11.

    Kennedy (2008) indicates that multicollinearity is a serious problem if the correlation coefficient between the two independent variables is above 0.70, which is not the case here.

  12. 12.

    García-Suaza et al. (2012) find that only large banks behave counter-cyclically with capital buffers.

  13. 13.

    But it considered only the US bank holding company data.

  14. 14.

    This result is similar to Shim (2013) and different from Guidara et al. (2013) who used US and Canadian banks consecutively.

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Moudud-Ul-Huq, S. Banks’ capital buffers, risk, and efficiency in emerging economies: are they counter-cyclical?. Eurasian Econ Rev 9, 467–492 (2019). https://doi.org/10.1007/s40822-018-0121-5

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Keywords

  • Capital buffers
  • Risk
  • Efficiency
  • Business cycle
  • BRICS
  • Stochastic frontier analysis (SFA)