Interconnectedness of the banking sector as a vulnerability to crises

• Author: Michela Rancan,Peter Sarlin,Tuomas Antero Peltonen
• Published date: 01 April 2019
• DOI: http://doi.org/10.1002/ijfe.1701
• Date: 01 April 2019

Received: 14 October 2016 Revised: 20 July 2018 Accepted: 10 September 2018

DOI: 10.1002/ijfe.1701

RESEARCH ARTICLE

Interconnectedness of the banking sector as a vulnerability

to crises

Tuomas Antero Peltonen1Michela Rancan2Peter Sarlin3

1European Systemic Risk Board, Frankfurt

am Main, Germany

2European Commission, Joint Research

Centre (JRC), Ispra, Italy

3Silo.AI, RiskLab at Arcada and Hanken

School of Economics, Helsinki, Finland

Correspondence

Michela Rancan, European Commission,

Joint Research Centre (JRC), Via E. Fermi

2749, Ispra 21027, Italy.

Email: michela.rancan@ec.europa.eu

JEL Classification: F36; G20

Abstract

This paper uses macro-network to measure the interconnectedness of the bank-

ing sector and relates it to banking crises in Europe. Beyond cross-border

financial linkages of the banking sector, the macronetwork also accounts for

financial linkages to the other main financial and nonfinancial sectors within

the economy. We find that a more central position of the banking sector in

the macronetwork significantly increases the probability of a banking crisis. By

analysing the different types of risk exposures, our evidence shows that credit

is an important source of vulnerability. Finally, our early-warning models aug-

mented with interconnectedness measures outperform traditional models in

terms of out-of-sample predictions.

KEYWORDS

banking crises, early-warning model, financial interconnectedness, macronetworks

1INTRODUCTION

The recent global financial crisis has stimulated a wave of

research to better understand sources of systemic risk and

potential determinants of financial crises. Two strands of

literature have emerged: one stressing the identification

of risks that build-up over time and another investigat-

ing the cross-sectional dimension of vulnerabilities. This

paper combines the two approaches to explore whether

complementing macrofinancial indicators with measures

of financial interconnectedness aid in explaining and

predicting recent banking crises in Europe. By includ-

ing measures of centrality of the banking system in the

early-warning model, we are able to account for the poten-

tial shock transmissions and exposures to vulnerabilities

that a banking sector could face through its domestic and

cross-border interconnections. European countries seem

an ideal laboratory for our empirical investigation given

the central role that the banking sector plays in Euro-

pean economies in intermediating funds for the real econ-

omy, and as the introduction of the single currency has

substantially increased the financial integration, poten-

tially increasing cross-border spillover effects.

The early-warning literature has focused on the time

dimension of systemic risk, by identifying vulnerable

states preceding financial crises using a wide range of

country-level macro, financial, and banking sector indica-

tors.1The literature has focused on the determinants of

banking crises through the analysis of univariate indica-

tors (Kaminsky & Reinhart, 1998, i.e., signalling approach)

and multivariate models (see, e.g., Demirgüç-Kunt &

Detragiache, 1998, Eichengreen & Rose, 1998). In general,

periods prior to systemic banking crises have been shown

to be explained by traditional vulnerabilities and risks that

represent imbalances such as lending booms and asset

price misalignments. By an analysis of univariate indica-

tors, Borio and Lowe (2002, 2004) show that banking crises

tend to be preceded by strong deviations of credit and asset

prices from their trend. Alessi and Detken(2011) show that

best-performing indications of boom/bust cycles are given

by liquidity in general and the global private credit gap in

particular. Likewise, in a multivariate regression setting,

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© 2018 The Authors. International Journal of Finance & Economics Published by John Wiley & Sons Ltd.

Int J Fin Econ. 2019;24:963–990. wileyonlinelibrary.com/journal/ijfe 963

964 PELTONENET A L.

vulnerabilities and risks have, overall, been shown to pre-

cede country-level crises on a large sample of developed

and developing countries in Demirgüç-Kunt and Detra-

giache (2000) and for the United States, Colombia, and

Mexico in Gonzalez-Hermosillo (1999), as well as on a

bank level in Eastern European transition economies in

Männasoo and Mayes (2009). Lo Duca and Peltonen(2013)

show that modern financial crises have been preceded

by a range of domestic macrofinancial vulnerabilities and

risks, particularly credit growth, equity valuations, and

leverage. Their analysis also emphasizes the importance

of global financial developments, such as global liquidity

and asset price developments, impacting a domestic vul-

nerability to financial crisis (for a further discussion on

global liquidity, see alsoCerutti et al., 2014). This only pro-

vides a snapshot of the broad literature that aims to detect

and proxy imbalances, risks, and vulnerabilities that func-

tion as determinants of crises, with the ultimate goal of

identifying vulnerable states preceding crises.

Another strand of a rapidly expanding literature analy-

ses the cross-sectional dimension of systemic risk. Beyond

country-level vulnerabilities, the recent crisis propa-

gated across markets and borders, and the banking sys-

tem played a major role in this phenomenon. Adverse

shocks have been exacerbated via balance sheet effects,

causing insolvencies and substantial losses.2Recently,

cross-border linkages and interdependencies of the inter-

national financial system have been modelled using net-

work techniques. Starting with the analysis of the inter-

national trade flows as a network (Fagiolo et al., 2009;

2010), these techniques have been applied to other con-

texts. Kubelec and Sá (2010) and Sa (2010) representa large

dataset of bilateral cross-border exposures by asset class

(FDI, portfolio equity,debt, and foreign exchange reserves)

for 18 advanced and emerging market economies as a net-

work. Minoiu and Reyes (2013) study the features of the

global banking network.3More generally, both theoreti-

cal and empirical works show that network techniques

provide useful insights with respect to financial stability.

Previous literature finds that network structure matters in

the generation of systemic risk (Allen et al., 2011). Net-

work topology influences contagion (e.g., Gai & Kapadia,

2010; Georg, 2013). Also, network measures have been

related to changes of the global banking system (Minoiu &

Reyes, 2013), as well as to economic growth and financial

contagion (Kali & Reyes, 2010).

In this paper, building on these two strands of litera-

ture, we study the intricate web of financial linkages with

the aim to detect vulnerability to banking crises. We con-

sider the cross-border banking linkages in a network archi-

tecture to measure the extent of the direct and indirect

exposures of each country's banking sector to the inter-

national banking system. On top of that, using the Euro

Area Accounts (EAA), each banking system is linkedto the

other institutional sectors of the economy.To include both

aspects in our analysis, that is, country- and sector-level

linkages, we build on the framework proposed by Castrén

and Rancan (2014). They introduce the idea of a macronet-

work, a network representing the financial positions that

links the institutional sectors of the economy, includ-

ing both financial sectors (banks, insurance companies,

pension funds, and other financial intermediaries) and

nonfinancial sectors (nonfinancial corporations [NFC],

government, households, and the rest of the world). Thus,

the macronetwork provides a mapping of the balance sheet

exposures and the associated financial risks in a com-

prehensive framework. As a large part of the financing

is intermediated through banks, particularly in Europe,

our focus is on the banking sector. While in studying

macroeconomic fluctuations through input–output anal-

ysis, firm-level shocks seem to spread along relatively

predictable patterns,4when looking at the banking sec-

tor, there are additional challenges. Banks' balance sheet

are exposed to multiple sources of risks, and the various

exposures can act as a transmission channel of shocks.

With the aim to understand the relationship of the bank-

ing sector with different types of risks and the different

role played by the banking sector—either as a direct holder

or as an intermediary—the macronetwork is constructed

using the different financial instruments: loans, deposits,

securities, and shares. There are several important dif-

ferences across the financial instruments that should be

noted, such as the banking sector having a dominant posi-

tion in loans and deposits. Whereas the banking sector

can hold securities and shares directly in its portfolio,

it can also act as an intermediary of these instruments

to other institutional sectors. The instruments also cap-

ture exposures to different types of risk, such as loans

to credit risk, deposits to funding and liquidity risk, and

also securities and shares to market risk. To identify the

position of the banking sector of each country, we make

use of network centrality measures. Combining the top-

ics of macrofinancial imbalances and networks, this paper

explores whether complementing standard macrofinan-

cial vulnerabilities with network centralities computed on

the macronetwork aids in explaining and predicting the

occurrence of banking crises. As we control for more stan-

dard early-warning indicators, we can test whether and to

what extent the computed network metrics are significant

explanatory variables of precrisis periods and improve the

predictive capabilities of standard models. Moreover, the

macronetwork allows us to display the patterns of asset

and liability positions over time and to monitor imbalances

or fragilities in the domestic and foreign portfolios.

Our findings suggest that a more central position of

the banking sector in the macronetwork increases the