Unconventional Monetary Policy and Wealth Inequalities in Great Britain*
| Author | Apostolos Fasianos,Anastasios Evgenidis |
| Date | 01 February 2021 |
| Published date | 01 February 2021 |
| DOI | http://doi.org/10.1111/obes.12397 |
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©2020 The Department of Economics, University of Oxford and JohnWiley & Sons Ltd.
OXFORD BULLETIN OF ECONOMICSAND STATISTICS, 83, 1 (2021) 0305–9049
doi: 10.1111/obes.12397
Unconventional Monetary Policy and Wealth
Inequalities in Great Britain*
Anastasios Evgenidis† and Apostolos Fasianos‡
†Newcastle University Business School, Newcastle upon Tyne NE1 4SE, UK
(e-mail: anastasios.evgenidis@newcastle.ac.uk)
‡Council of Economic Advisors, Hellenic Ministry of Finance, Athens 10180, Greece
(e-mail: a.fasianos@minfin.gr)
Abstract
This paper explores whether unconventionalmonetary policy operations have redistributive
effects on household wealth. Drawingon household balance sheet data from the Wealth and
Asset Survey, we construct monthly time series indicators on the distribution of different
asset types held by British households for the period that the monetary policy switched, as
the policy rate reached the zero-lower bound. Using this series, we estimate the response
of wealth inequalities on monetary policy, taking into account the effect of unconventional
policies conducted by the Bank of England in response to the Global Financial Crisis. Our
evidence reveals that unconventional monetary policy shocks have significant and linger-
ing effects on wealth inequality: the shock raises wealth inequality across households, as
measured by their Gini coefficients, percentile shares and other standard inequality indica-
tors. Additionally, weexplore the effects of different transmission channels simultaneously.
We find that the portfolio rebalancing channel and house price effects widen the wealth
gap, outweighing the counterbalancing impact of the savings redistribution and inflation
channels. The findings of our analysis help to raise awareness of central bankers about the
redistributive effects of their monetary policy decisions.
I. Introduction
The Global Financial Crisis (GFC) led to a profound shift in monetary policy. As policy
rates reached the zero-lower bound (ZLB), central banks employed unconventional mon-
etary policy measures (UMP) aimed at boosting nominal spending, increasing liquidity
JEL Classification numbers: D31, E21, E52, H31.
*The authors would like to thank George Chortareas, David Kaplan, Leo Krippner, Apostolis Pavlou, Markus
Schneider, Andreas Thiemann, and Andreas Zervas for their useful advice, as well as the editor Brian Bell, and
three anonymous referees for their thoughtful and constructive comments.Additionally, we thank participants in the
Applied Macroeconomic and Empirical Finance Conference in Thessaloniki, 2019, for their helpful comments. We
are thankful to the UK Data Service for updating the WASdata with relevant information that allowed us to construct
the inequality series employed in this study. Without their help, our analysis would not be feasible.All remaining
errors are ours. The views expressed in the paper are those of the authors and do not necessarily reflect those of the
Council of Economic Advisors, Hellenic Ministry of Finance.
116 Bulletin
and reaching their inflation targets. UMP played a significant role in alleviating the im-
pact of the crisis but also triggered policy concerns that such measures can have large
effects on economic inequalities (Casiraghi et al., 2018; Colciago, Samarina and de Haan,
2019). Over the last 15 years, the UK has witnessed increasing levels of wealth inequality
(Alvaredo, Atkinson and Morelli, 2018). This study’s estimations suggest that the share
of net wealth held by the richest 10% of the population accounts for almost 50% of the
country’s total net wealth, while overall wealth inequality increased by more than 4%
from 2006 to 2016.1Although there is by now a growing interest in exploring the rela-
tionship between monetary policy and income inequality,2the impact of monetary policy
on wealth inequalities has received much less attention in the literature.3Yet, monetary
policy, and particularly UMP, can influence household wealth shares by re-valuating and
rebalancing their portfolios through different transmission channels (O’Farrell and Raw-
danowicz, 2017; Colciago et al., 2019). Understanding the impact of monetary policy on
wealth inequalities is of major policy importance because wealth is associated with house-
holds’ financial health; it reflects future well-being; it is associated with political power
(Cowell and Van Kerm, 2015); also, wealth disparities imply heterogeneous consumption
elasticities which can function as a transmission mechanism of monetary policy them-
selves (Kaplan, Moll andViolante, 2018; Auclert, 2019; Arrondel, Lamarche and Savignac,
2019).4
This paper studies whether and how the UMP measures implemented by the BoE
affected financial and housing wealth inequalities in Great Britain (GB) for the period
2006–16. It contributes to the relevant empirical literature in the following ways:
This is the first study investigating the distributional effects of monetary policy on
wealth inequality, for the UK, using low-level household balance sheet data at a relatively
high frequency. The gap in the literature is not due to lack of research interest or policy
relevance but mainly due to serious data limitations. Reliable data on the short-term dy-
namics of household portfolios are scarce in most countries, but are a requisite for the
investigation of the redistributive impact of monetary policy. Against this background, we
draw on the Wealth andAsset Survey (WAS), a large sample survey on household finances,
in which individual responses are balanced proportionately over time and geography, to
construct monthly indices of net wealth inequalities for the period 2006–16. In this way,
our paper contributes to the broader wealth inequalities literature by providing a range
of unique time series of financial and housing wealth inequality estimates for the period
preceding and following the Global Financial Crisis. We additionally assess whether our
monthly sample distributions suffer from non-response bias, by comparing them to the
representative WAS biennial sample across different points of the Cumulative Distribu-
tion Function (CDF) (Goldman and Kaplan, 2018). The application of this methodology
strengthens the credibility of our results.
1Authors’ estimations usingWealth and Asset Survey data ONS (2019).
2See for example, Mumtaz and Theophilopoulou (2017); Coibion et al. (2017); Guerello (2018) and Colciago
et al. (2019) for a literature review on the subject.
3Notable exceptions include Adam andTzamourani (2016); Casiraghi et al. (2018); Lenza and Slacalek (2018);
Hohberger, Priftis and Vogel (2019)
4Relatedly, de Roiste et al. (2020) provide a literature review on heterogeneouswealth effects and consumption
elasticities.
©2020 The Department of Economics, University of Oxford and JohnWiley & Sons Ltd
Monetary policy and wealth inequalities 117
Second, most of the existing empirical literature applies static micro-simulation exer-
cises (Doepke and Schneider, 2006;Adam and Tzamourani, 2016; Bunn, Pugh and Yeates,
2018) that typically provide information on household wealthor income distribution under
policy scenarios which deterministically affect one or more of the distribution’s com-
ponents. These techniques fail to capture the underlying economic mechanisms at play,
especially when the policy effects are indirect or take time to realize. They are also nar-
rowed to the use of only a few time points, that prevents a deep and dynamic exploration
of the relationship (Colciago et al., 2019). To the best of our knowledge, this is the first
paper that applies vector autoregressive (VAR) models to investigate the impact of UMP
shocks on wealth inequality.5Furthermore, we adopt Bayesian methods to estimate our
VAR and use a Gibbs sampling algorithm to approximate the posterior distribution of the
model parameters. Recently, Bayesian VAR (BVAR) methodology has become a relevant
tool for evaluation of the effects of monetary policy shocks (see, for instance, Ba´nbura, Gi-
annone and Reichlin (2010); Gal´
i and Gambetti (2015); Mumtaz and Theodoridis (2019)).
As discussed in Koop and Korobilis (2010), this approach offers a convenient method to
estimate precise error bands for impulse responses. The latter is an important tool of our
analysis since it allows us to measure the impact of monetary policy on wealth inequality.
Third, our approach explores the effects of different transmission channels simultane-
ously.In contrast to most empirical literature on wealth inequality, which either focuses on
the role of financial assets or investigates the transmission channels in isolation (see, e.g.
Adam and Zhu (2015); Inui et al. (2017); O’Farrell and Rawdanowicz (2017); Hohberger
et al. (2019)), we specify the broader portfolio rebalancing mechanism functioning under
periods of UMP. In particular, we measure the impact of the portfolio rebalancing channel
by controlling for the effects of financial asset prices and corporate bond yields. In addition,
we explore secondary effects by examining the impact of UMP on inequality via changes
in housing asset prices (Joyce, McLaren andYoung,2012). Further more, weinvestigate the
savings redistribution and the inflation channel from savers to borrowers. In comparison to
the portfolio rebalancing channel, the last two channels function in the opposite direction,
via lower borrowing rates and drops in the real value of nominal assets and liabilities.
Fourth, we further explore the effects of UMP shocks on wealth inequality corre-
spondingly by carrying out counterfactual policy analysis. These experiments allow us to
explicitly measure what would have happened to inequality had the BoE reversed its QE
(Quantitative Easing) policy earlier.Wealso offer some evidence on the asymmetric impact
of monetary policy on inequality across different policy regimes. To assess this, we use a
Bayesian threshold VAR that allows us to endogenously identify ZLB vs. non-ZLB states.
Two sets of results emergefrom our analysis that shed light on theories linking monetary
policy and wealth inequality. First, impulse response analysis suggests that unconventional
monetary policy shocks elicit significant and persistent effects on wealth inequality: the
shock raises wealth inequality across households, as measured by their Gini coefficients
of total, housing and financial net wealth, as well as across wealth percentile shares. In
numbers, the shock is estimated to increase the Gini coefficient of total wealthby about 0.06
5The available evidence on the use of multivariate time series models to examine monetary policy impacts on
inequality is limited. Notable exceptions include Saiki and Frost (2014), Guerello (2018) and Inui, Sudou and
Yamada(2017), who focus on income inequality, and Curran and Fagerstrom (2019), who focus on financial sector
wages.
©2020 The Department of Economics, University of Oxford and JohnWiley & Sons Ltd
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