Abstract
In this paper we examine the relationship between the default risk of banks and sovereigns, i.e. the ‘doom-loop’. Specifically, we try to assess the effectiveness of the implementation of the new recovery and resolution framework in the European Union. We use a panel with daily data on European banks and sovereigns ranging from 2012 to 2016 in order to test the effects of the Bank Recovery and Resolution Directive on the two-way feedback process. We find that there was a pronounced feedback loop between banks and sovereigns from 2012 to 2014. However, after the implementation of the European Banking Union, in 2015/2016, the magnitude of the doom-loop decreased and the spillovers became not statistically significant. Furthermore, our results suggest that the implementation of the new resolution framework is a suitable candidate to explain this finding. Overall, the results are robust across several specifications.
Similar content being viewed by others
Change history
13 June 2018
The original version of this article unfortunately incorrectly captured all tables incorrectly.
Notes
Merler and Pisani-Ferry (2012: 204) argue that if market participants perceive that there is the risk of a bail-out, yields of government bonds are already affected.
Sgherri and Zoli (2009: 17) verify that the deterioration in fiscal positions led to an increase in the risk premiums of government bonds for most European countries. In particular, they argue that increases in debt levels of sovereigns and concerns about the solvency of national banking systems have caused this increase.
The EBA assesses the importance of banks according to several criteria. Important are: size of the balance sheet, the ratio of the size of the balance sheet to the economic activity in the home country and whether the bank has applied for financial support from other European mechanisms.
Specifically, those tools are: sales of business, bridge institutions, asset separation and a bail-in tool (European Parliament 2014, Article 37). Moreover, Denmark, Switzerland and UK decided to opt-in and apply the reforms stated in the new legislation.
See Toader (2015) for a discussion of the relationship between implicit government guarantees and the introduction of the new bank resolution framework.
Lybeck (2016) provides a critical appraisal of the future of bank bail-outs in the European Union under the Single Resolution Mechanism and the Bank Recovery Resolution Directive.
See Fig. A1 in the online appendix for a timeline of the European Banking Union.
Although Switzerland is not a member of the European Union, it has implemented a regime with similar characteristics to the BRRD. Nevertheless, this regime was implemented in different steps between 2012 and 2016, and its bail-in tool entered into force in January 2012. For this reason, UBS and Credit Suisse will not be considered for the analysis.
The MREL is only in the phase-in process, and it will be fully operational in January 2020 (ISDA 2016: 37).
We include foreign exposures of a country’s banks until we have reached 85% of the total foreign exposure, as this eliminates the need to deal with countries for which a time series of CDS premiums is not available for the sovereign or the largest banks. Then the index is normalized to 100%.
The data selection and cleaning procedure is implemented following Acharya et al. (2014: 2712).
This subdivision is useful in presenting the results and makes them comparable before and after the BRRD implementation. This selection does not drive our results; to this respect we provide estimates for a one-year rolling window over the entire period. This results justify to split the sample into yearly intervals.
The alternative approach in the literature is to implement a VAR. In this respect, the identification of a VAR model is problematic and, in order to utilize fully the cross-sectional variation, a fixed effects estimation approach seems more appropriate. Moreover, the advantage of the single equation approach is that results are easier to interpret than in a VAR.
The results of the common residual and time series diagnostics justify our exact estimation specification and can be found in the statistical appendix for the sake of space.
Since we have a large T dimension and a small N, the criticism of Nickell (1981), who points out possible biases, does not pose a problem for our estimation.
Results do not change after the inclusion of two interactions terms between bank fixed effects and the CDS market index as well as between bank fixed effects and the volatility index. This technique should be able to take into account the heterogeneity in bank characteristics. Results are provided in the online appendix, Table A1.
This finding does not change by using recursive and reversed recursive estimation methods. Furthermore, it is robust to changes in the length of the selected rolling window to three and six months.
Clearly, the bond purchase program aims at lowering the sovereign yields, that is, it affects the variable in level not in log-changes.
It is important to remark that the timetable for the implementation is different across countries, although the common deadline is 1st January 2016. To this respect, the dummy variable captures the effect of the heterogeneous implementation across countries within the period January 2015–March 2016. See Fig. 4 for the timetable of the BRRD full-implementation across countries.
As investigated by Toader (2015: 141), the decreasing value of public guarantees might work against our hypothesis. To this end, we want to recall that governments’ interventions are still possible under the BRRD resolution framework, but take place after all bail-in-able instruments are converted into new equity. This strongly reduces the likelihood and the amount of government capital injections. “This finding leads us to the conclusion that investors expect lower public support for banks from countries where efforts to implement a resolution mechanism are made. Moreover, results indicate that potential interactions between the sovereign rating and the introduction of resolution mechanism reduce significantly the expectations of public support” (Toader 2015: 142).
Data on the PSPP by country are available only at monthly frequency from the ECB’s website. Since Sweden and Denmark do not belong to the Euro Area, the inclusion of the PSPP omits them from the sample.
Data on debt to GDP are collected from the ECB’s statistical data warehouse.
For the sake of space and for a better comparison and interpretation of the results at monthly frequency between the two channels, results are placed in the appendix.
Data at monthly frequency for channel 2 is only one third (428) of the data available for channel 1 (1256). This is due to the reduction of the cross-sectional data: N - the number of countries - is 9, while N - the number of banks - is 26.
Moreover, results are not driven by the economic recovery. Table A2 in the online appendix reports the estimates for both channels at daily frequency. This robustness check verifies that those countries experiencing an economic recovery before the BRRD introduction were still prone to the doom loop.
References
Acharya V, Drechsler I, Schnabl P (2014) A Pyrrhic victory? Bank bailouts and sovereign credit risk. J Financ 69:2689–2739. https://doi.org/10.1111/jofi.12206
Alter A, Beyer A (2014) The dynamics of spillover effects during the European sovereign debt turmoil. J Bank Financ 42:134–153. https://doi.org/10.1016/j.jbankfin.2014.01.030
Alter A, Schüler Y (2012) Credit spread interdependencies of European states and banks during the financial crisis. J Bank Financ 36:3444–3468. https://doi.org/10.1016/j.jbankfin.2012.08.002
Breton R, Pinto C, Weber P (2012) Banks, moral hazard, and public debts. Banque de France Financial Stability Review 16
Chen CH (2015) The recovery framework in the BRRD and its effectiveness. International Company and Commercial Law Review 26
Covi G (2017) The emerging regulatory landscape: a new normal. Breaking the link between banks and sovereigns. J Bank Regul 18:233–255. https://doi.org/10.1057/s41261-016-0036-6
Dieckmann S, Plank T (2012) Default risk of advanced economies: an empirical analysis of credit default swaps during the financial crisis. Rev Financ 16:903–934. https://doi.org/10.1093/rof/rfr015
Ejsing J, Lemke W (2011) The Janus-headed salvation: sovereign and bank credit risk premia during 2008-2009. Econ Lett 110:28–31. https://doi.org/10.1016/j.econlet.2010.10.001
European Banking Association (2015) EBA final draft regulatory technical standards. On criteria for determining the Minimum Requirement for Own Funds and Eligible Liabilities under directive 2014/59/EU. Regulatory technical standards, http://www.eba.europa.eu/documents/10180/1132900/EBA-RTS-2015-05+RTS+on+MREL+Criteria.pdf. Accessed 20 July 2016
European Parliament (2010) Regulation no 1093/2010 of the European Parliament and of The Council of 24 November 2010 establishing a European Supervisory Authority. Official Journal of the European Union. http://eur-lex.europa.eu/legal-content/EN/TXT/PDF/?uri=CELEX:32010R1093&from=EN. Accessed 20 July 2016
European Parliament (2013) Directive 2013/36/EU of The European Parliament and of The Council of 26 June 2013 on access to activity of credit institutions and the prudential supervision of credit institutions and investment firms. Official Journal of the European Union. http://eur-lex.europa.eu/legal-content/EN/TXT/PDF/?uri=CELEX:32013L0036& from=EN. Accessed 20 June 2016
European Parliament (2014) Directive 2014/59/EU of the European Parliament and of the council of 15 May 2014 establishing a framework for the recovery and resolution of credit institutions and investment firms. Official Journal of the European Union. http://eur-lex.europa.eu/legal-content/EN/TXT/PDF/?uri=CELEX:32014L0059&from=IT. Accessed on 20 June 2016
Fratzscher M, Rieth M (2015) Monetary policy, bank bailouts and the sovereign-bank risk nexus in the Euro Area. DIW working paper series. Discussion paper 1448. http://www.diw.de/documents/publikationen/73/diw_01.c.496615.de/dp1448.pdf
Guan W (2003) From the help desk: bootstrapped standard errors. Stata J 3:71–80
Haldane A (2009) Banking on the state BIS review 139/2009. http://www.bis.org/review/r091111e.pdf. Accessed 20 July 2016
Haldane A (2012) The dog and the frisbee. BIS central bankers’ speeches. http://www.bis.org/review/r120905a.pdf. Accessed 20 June 2016
International Swap and Derivative Association (2016) BRRD implementation monitor. http://www2.isda.org/isda-brrd-implementation-monitor/. Accessed 20 June 2016
Kallestrup R, Lando D, Murgoci A (2016) Financial sector linkages and the dynamics of bank and sovereign credit spreads. J Empir Financ 37:30–88. https://doi.org/10.1016/j.jempfin.2016.01.004
Lehmann M (2016) Bail-in and private international law: how to make bank resolution measures effective across borders. SSRN: http://ssrn.com/abstract=2759763
Lybeck JA (2016) The future of financial regulation. Who should pay for the failure of American and European banks. Cambridge University Press, Cambridge
Merler S, Pisani-Ferry J (2012) Hazardous tango: sovereign-bank interdependence and financial stability in the euro area. Financial Stab Rev 16:201–210
Mody A, Sandri D (2012) The Eurozone crisis: how banks and sovereigns came to be joined at the hip. Econ Policy 27:199–230. https://doi.org/10.1111/j.1468-0327.2012.00281.x
Nickell S (1981) Biases in dynamic models with fixed effects. Econometrica 49:1417–1426. https://doi.org/10.2307/1911408
Sgherri S, Zoli E (2009) Euro area sovereign risk during the crisis. IMF working paper series. Working paper 09/222. https://www.imf.org/external/pubs/ft/wp/2009/wp09222.pdf
Shambaugh JC (2012) The Euro’s three crises. Brook Pap Econ Act 43:157–231
Singh MK, Gomez-Puig M, Sosvilla-Rivero S (2016) Sovereign-bank linkages: quantifying directional intensity of risk transfers in EMU countries. J Int Money Financ 63:137–164. https://doi.org/10.1016/j.jimonfin.2016.01.003
Stanga I (2011) Sovereign and bank credit risk during the global financial crisis. De Nederlandsche Bank working papers series. Working paper 314. https://www.dnb.nl/binaries/working%20paper%20314_tcm46-257146.pdf
Toader O (2015) Quantifying and explaining implicit public guarantees for European banks. Int Rev Financ Anal 41:135–147. https://doi.org/10.1016/j.irfa.2015.06.003
Acknowledgments
We wish to thank Matthias Raddant, Harmen Lehment, Olivier Godart, Eugenio Caverzasi, Jamel Saadaoui and the participants to the 7th ICEEE (Messina, 2017), DIW Macroeconometric Workshop (Berlin, 2016), 4th Workshop in “Macro Banking and Finance” Sapienza University (Rome, 2016), Economics, Economic Policies and Sustainable Growth in the Wake of the Crisis Conference (Ancona, 2016), and the seminar at Kiel Institute for the World Economy, University of Verona, and University of Potsdam for helpful comments and suggestions. Furthermore, we thank the contributions of two anonymous referees on a previous version of the paper. Finally, we would like to emphasize our gratitude to the Kiel Institute for the World Economy for the opportunity to develop this paper in a highly stimulating environment. None of the above are responsible for errors in the paper.
Author information
Authors and Affiliations
Corresponding author
Additional information
The original version of this article was revised: All tables are corrected.
Electronic supplementary material
Fig. A1
Timeline of the European Banking Union. This figure shows the steps taken for the European Banking Union’s implementation: the European Stability Mechanism (ESM), the Basel III requirements (CRD IV), the Single Supervisory Mechanism (SSM), the European Fiscal Compact (EFC), the Deposit Guarantee Scheme Directive (DGSD), the Bank Recovery and Resolution Directive (BRRD), the Single Resolution Fund (SRF), and ultimately the Single Resolution Mechanism (SRM). (PNG 2.05 mb)
Table A1
Robustness: controlling for interaction terms. This table examines the robustness of the results by reporting the coefficients after having controlled for interaction terms, respectively between bank fixed effects and the CDS index - iTraxx Europe - as well as bank fixed effects and the volatility index - VDAX. Standard errors are clustered at the bank level and bootstrapped by 200 replications. ***, **, and * indicates statistical significance at the 1%, 5%, and 10% level, respectively. The regression specification is given by: Δ log (BANK CDSijt) = αi + ζt + βΔ log (SOV CDSjt) + ωΔ log (BANK CDSit − 1) + γΔ log (FXjt) + φΔ log (SPit) + δΔ log (Xt) + [αi ∗ Δ (Xt)] + εijt. (PNG 2.95 mb)
Table A2
Robustness: time fixed effect specification - economic recovery. This table examines the robustness of the time fixed effects specification by reporting the coefficients after having controlled for those countries that were experiencing an economic recovery during 2012, 2013, 2014. Respectively the countries excluded in the estimation are: Italy, Portugal and Spain; Italy and Spain; Sweden. Standard errors are clustered at the bank level and bootstrapped by 200 replications. ***, **, and * indicates statistical significance at the 1%, 5%, and 10% level, respectively. The regression specification for channel 1 is given by: Δ log (BANK CDSijt) = αi + ζt + β Δ log (SOV CDSjt) + ω Δ log (BANK CDSit − 1) + γΔ log (FXjt) + φΔ log (SPit) + δΔ log (Xt) + εijt. The regression specification for channel 2 is given by: Δ log (SOV CDSit) = αi + ζt + βΔ log (FSDit) + ωΔ log (SOC CDSit − 1) + δΔ log (Xt) + εit (PNG 2.58 mb)
Appendix
Appendix
Rights and permissions
About this article
Cite this article
Covi, G., Eydam, U. End of the sovereign-bank doom loop in the European Union? The Bank Recovery and Resolution Directive. J Evol Econ 30, 5–30 (2020). https://doi.org/10.1007/s00191-018-0576-2
Published:
Issue Date:
DOI: https://doi.org/10.1007/s00191-018-0576-2
Keywords
- Financial stability
- Sovereign bail-out
- Bail-in tool
- Doom loop
- European Banking Union
- Bank Recovery and Resolution Directive