Systemic Financial Stress and Macroeconomic Amplifications in the United Kingdom*
| Published date | 01 April 2022 |
| Author | Somnath Chatterjee,Ching‐Wai (Jeremy) Chiu,Thibaut Duprey,Sinem Hacıoğlu‐Hoke |
| Date | 01 April 2022 |
| DOI | http://doi.org/10.1111/obes.12466 |
Systemic Financial Stress and Macroeconomic
Amplifications in the United Kingdom*
SOMNATH CHATTERJEE,†CHING-WAI (JEREMY)CHIU,†
THIBAUT DUPREY‡and SINEM HACIO
˘
GLU-HOKE§
†Bank of England, London, UK (e-mails: somnath.chatterjee@bankofengland.co.uk;
jeremycwchiu01@gmail.com)
‡Bank of Canada, Ottawa, Ontario, Canada (e-mail: tduprey@bankofcanada.ca)
§Bank of England and CEPR, London, UK (e-mail: sinem.hacioglu@bankofengland.co.uk)
Abstract
We develop a daily composite index of financial stress for the United Kingdom over
50 years, the UKFSI. The index includes market stress indicators based on their
incremental information to capture financial crises. During the COVID-19 crisis,
financial stress peaks but remains less severe than during the Global Financial Crisis.
The UKFSI is used in a threshold vector autoregression to differentiate the economic
dynamics between tranquil and stressful periods. We highlight the importance of
nonlinearities that amplify shocks. But we find no evidence of financial shocks
contributing to the COVID-19 crisis, possibly reflecting effective policy interventions.
I. Introduction
Over the past five decades, the UK financial sector has been buffeted by a few major
shocks, which have highlighted the importance of macro-financial linkages. On the one
hand, the severe economic and financial meltdown during the global financial crisis
(GFC) was amplified within the banking sector. On the other hand, the spread of the
COVID-19 pandemic unleashed profound economic and financial stress, but the shock
was partly absorbed by a more resilient banking sector and unprecedented policy support.
Against this backdrop, we develop a daily systemic financial stress index for the
United Kingdom, the UK Financial Stress Index (UKFSI). We demonstrate its
importance for assessing the transmission of financial shocks and the amplification of
small shocks during stressful periods.
The UKFSI is a daily—from 1971 onwards—composite index of systemic financial
stress, that is, it tracks periods characterized by higher volatilities, valuation losses and a
JEL Classification numbers:C31, C54, G01, G15.
*The authors thank Andy Blake, David Aikman, Lee Foulger and colleagues who participated in Bank of
England seminars on the subject. The views expressed are those of the authors and do not necessarily reflect
those of the Bank of England (its Monetary Policy Committee, Financial Policy Committee or Prudential
Regulatory Committee) nor those of the Bank of Canada. All errors remain our own.
380
©2021 Bank of England. Oxford Bulletin of Economics and Statistics © 2021 Oxford University and John Wiley & Sons Ltd.
OXFORD BULLETIN OF ECONOMICS AND STATISTICS, 84, 2 (2022) 0305-9049
doi: 10.1111/obes.12466
widening of risk spreads that occur simultaneously across a widerange of asset markets
(the equity, government bond, foreign exchange, corporate bond and money markets).
Each market is weighted by its cross-correlation with the othersto reflect the increased
co-movement of tail risks.
We use a novel selection, aggregation and optimization method when combining
the various data inputs into the UKFSI to strike a balance between parsimony and
efficacy. The usual starting place is to first pool together several time series deemed
relevant, and then assess how they match with known crisis events (Illing and Liu,
2006; Oet, Dooley and Ong, 2015; Jing et al., 2015; Duprey, Klaus and Peltonen,
2017). Instead, we reverse the process by considering known crisis events identified by
Lo Duca et al. (2017) as a starting point to determine which type of time series add
incremental information. Specifically, our criterion to optimize the informational
content of the UKFSI is the ‘partial area under the receiver operating characteristic
curve’(partial AUROC). It measures the ability of each potential data input to
contemporaneously identify the known UK financial crises.
1
Our selection algorithm
implies that, if two indicators capture the same aspect of the financial crisis, one is
redundant and is not selected. It also means that an indicator that may individually
appear as less useful may nonetheless be selected if its combination with other
variables provides more information, for instance, if it captures a different aspect of the
crisis. Our procedure is robust to changing the definition of crises or even excluding
the most severe crisis, that is, the GFC, when optimizing the construction of the index.
Once equipped with the UKFSI, we assess the importance of systemic financial
stress for the transmission and amplification of macro-financial shocks. We estimate a
monthly Bayesian threshold vector autoregression (TVAR) model to distinguish
economic dynamics during tranquil vs. stressful times. The benefit of TVARs is that
stressful times are explicitly defined as periods where the UKFSI is above an estimated
threshold value, while alternative Markov chain VARs (Hubrich and Tetlow, 2015; Liu
et al., 2019) do not tie the change in regime to an observed variable. The identification
of financial shocks relies on the assumption that financial markets are fast-moving and
that financial shocks have no contemporaneous impact on the real economy within a
month. This allows us to avoid priors on financial shocks as supply shocks (if the
marginal cost channel dominates) or demand shocks (if the impact of spreads on
demand dominates). Our financial stress index is a composite, such that financial
shocks are broadly defined and related to studies on uncertainty shocks (Caldara et al.,
2016), policy uncertainty (Mumtaz and Zanetti, 2013; Mumtaz and Surico, 2018),
housing price shocks (Furlanetto, Ravazzolo and Sarferaz, 2019), mortgage spread
shocks (Walentin, 2014), corporate spread shocks (Gilchrist and Zakrajsek, 2012) or
news shocks (Baker, Bloom and Davis, 2016; G¨
ortz, Tsoukalas and Zanetti, 2016),
among others. We show that the transmission of shocks in financially stressful periods
is significantly different from what occurs during normal times. All shocks are
amplified during stressful times, which provides empirical evidence to Brunnermeier
1
The AUROC metric was introduced in economics to assess the ability to predict crises (Schularick and
Taylor, 2012; Drehmann and Juselius, 2014). Instead, we use it to assess the ability of a timeseries to
contemporaneously identify a crisis.
©2021 Bank of England. Oxford Bulletin of Economics and Statistics © 2021 Oxford University and John Wiley & Sons Ltd.
Financial stress and UK macro amplifications 381
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