This thesis studies the interaction between changes in the countercyclical capital buffer and the development of bank risk. Recent theoretical advances have highlighted the important role macroprudential policies play in containing systemic risk. This research contributes to the existing literature in two ways. First, it studies the effect of the countercyclical capital buffer in a cross-country framework at a time when the first preliminary results can be analysed. Second, it allows for policy variability through the use of a continuous variable for the countercyclical capital buffer.
To measure the impact of changes in the effective CCyB rate on the growth of leverage and bank lending, a two-step system GMM model is applied. In this thesis’ data sample, 14 out of 28 countries have implemented non-zero CCyB rates somewhere between 2015 and 2020. It allows for sufficient bank observations in CCyB countries, while it also provides counterfactual evidence in countries where this policy instrument has not been put into effect.
The results of this thesis suggest that the countercyclical capital buffer has been successful in containing bank risk. When controlling for macroeconomic indicators, this effect is found to be stronger when fluctuations in the financial cycle are larger. Also, the results indicate that the CCyB’s impact on bank risk is only significant in periods of financial uncertainty.
There are limitations to this research. Most importantly, there exists the possibility that a tightening of macroprudential policies is avoided by channelling financing through less regulated parts of the financial system. As such, properly measuring the development of systemic risk would require the incorporation of these waterbed effects. One way to solve this issue is to study the development of overall credit supply. In addition, spillover effects from policies that arise from reciprocal arrangements can then more easily be accounted for. On the flip side, this introduces other econometric caveats and would require a wider implementation of the CCyB, as well as a longer time period with more policy variability.
39
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46
APPENDICES
Appendix A
Notes: All countries depicted in Appendix A are admitted into the datasample, except for Bulgaria. Canada’s CCyB takes the form of the domestic stability buffer and only applies to 6 of its largest banks.
47
Implementation of Macroprudential policies by country/year
Instruments Main objectives Country Period of
implementation
Countries Frequency of use (%) Countercyclical
capital buffer
Improving banks’
resilience and potentially reducing excessive risk build-up
Belgium 2019 15 17,3
Canada 2018-2019
Czech Republic 2016-2019
Denmark 2019
France 2019
Great Britain 2018-2019
Hong-Kong 2015-2020
Ireland 2019
Iceland 2017-2019
Lithuania 2018-2019
Luxembourg 2019-2020
Norway 2015-2020
Sweden 2015-2019
Slovakia 2017-2020
Dynamic provisioning
Improving banks’
resilience and potentially reducing excessive risk build-up
Australia 2007-2017 3 10,3
Spain 2006-2015
Loan-to-value cap Reducing financial imbalances that are cause highly geared borrowings
Austria 2006-2017 19 47,4
Canada 2008-2017
Czech Republic 2014-2017
Denmark 2006-2017
Estonia 2015-2017
Spain 2006-2017
Finland 2016-2017
Hong-Kong 2006-2017
Hungary 2010-2017
Ireland 2015-2017
Iceland 2017
Italy 2014-2017
Korea 2006-2017
Lithuania 2011-2017
The Netherlands 2013-2017
Norway 2010-2017
New-Zealand 2013-2017
Sweden 2010-2017
Slovakia 2014-2017
Debt-to-income cap
Reducing financial imbalances that are cause highly geared borrowings
Canada 2008-2017 9 25
Estonia 2015-2017
Hong-Kong 2006-2020
Hungary 2010-2017
Korea 2006-2017
Lithuania 2011-2017
The Netherlands 2013-2017
Norway 2010-2017
Slovakia 2017
Notes: Data on effective CCyB rates at year’s end is constructed by combining datasets ERSB and BIS data. For DP, LTV and DTI, the “Macro-Prudential Index” framework by Cerutti, Claessens and Laeven (2017), which observations end in the year 2017.
48 Appendix B
Including macroeconomic variables to baseline regressions: 2006-2020
Explanatory variables Leverage growth Loan growth
(I) (II) (III) (IV) (V) (VI)
Lag dependent var. 0.018 Yes Yes 0.353*** Yes Yes
(0.055) (0.026)
Lag leverage ratio 0.018 Yes Yes 0.243** Yes Yes
(0.055) (0.108)
Lag deposit ratio -0.581*** Yes Yes 0.008 Yes Yes
(0.123) (0.012)
Lag real GDP growth -0.005 0.278***
(0.004) (0.096)
Lag FX system -0.862*** 0.017***
(0.122) (0.003)
Lag IR growth -0.005 -0.490***
(0.004) (0.109)
CCyB 3.539*** 2.360*** -1.047 0.125
(1.062) (0.733) (0.776) (0.722)
CCyB x lag dependent var. 0.238** -0.536***
(0.120) (0.074)
LTV 1.898*** 1.053*** 1.358*** 1.259***
(0.645) (0.405) (0.355) (0.342)
LTV x lag dependent var. 0.190** 0.028
(0.083) (0.046)
DTI 1.697** 0.559 1.368*** 1.181***
(0.792) (0.673) (0.380) (0.350)
DTI x lag dependent var. 0.397*** 0.032
(0.087) (0.046)
DP 1.950*** 2.770*** 0.451 0.029
(0.722) (0.385) (0.541) (0.339)
DP x lag dependent var. -0.343*** 0.023
(0.067) (0.052)
Constant 17.112*** Yes Yes 2.846** Yes Yes
(1.139) (1.178)
AR(2) test 0.935 0.905 0.831 0,242 0.223 0.247
Hansen test of overid. 0.276 0.224 0.290 0.007 0.006 0.006
Observations 1,488 1,488 1,488 1,488 1,488 1,488
Notes: In these GMM regressions, lagged dependent variables, the lagged credit-to-GDP gap, time fixed effects and country fixed effects are used as instrumental variables for the lagged dependent variable. To save space, each macroprudential policy variable is regressed one at a time and results are stacked in one column. In the regressions where macroprudential policies are incorporated, if results are shown for the lagged dependent variable, bank-specific variables and model validity tests, they represent the regression which only uses CCyB as policy instrument variable. GMM robust standard errors are reported in the parentheses. The asterisks *, ** and
*** stand for significance at the 0.1, 0.05 and 0.01 level, respectively.