Sequencing the COVID‐19 Recession in the USA: What Were the Macroeconomic Drivers?

Published date01 February 2024
AuthorMax Breitenlechner,Martin Geiger,Daniel Gründler,Johann Scharler
Date01 February 2024
DOIhttp://doi.org/10.1111/obes.12573
OXFORD BULLETIN OF ECONOMICS AND STATISTICS, 86, 1 (2024) 0305-9049
doi: 10.1111/obes.12573
Sequencing the COVID-19 Recession in the USA:
What Were the Macroeconomic Drivers?
MAX BREITENLECHNER,† MARTIN GEIGER,†,‡ DANIEL GR¨
UNDLER† and
JOHANN SCHARLER
Department of Economics, University of Innsbruck, Universitaetsstrasse 15, A-6020 Innsbruck,
Austria (e-mail: max.breitenlechner@uibk.ac.at)
Liechtenstein Institute, St. Luziweg 2, 9487 Bendern, Liechtenstein
(e-mail: martin.geiger@liechtenstein-institut.li)
Abstract
We apply a structural vectorautoregressive analysis to decompose fluctuations in the
growth rate of industrial production and inflation precipitated by the COVID-19 pandemic
in the USA into aggregate demand, aggregate supply, and uncertainty shocks. While all
three types of shocks contributed to output and inflation dynamics, the surge in economic
uncertainty contributed to the decline in output more strongly than aggregate demand or
aggregate supply disruptions. In 2021, the decline in uncertainty and adverse aggregate
supply shocks emerged to be similarly important in spurring inflation.
I. Introduction
The COVID-19 pandemic caused a particularly severe, swift, and globally synchronized
recession. Widespread lockdowns and disruptions in supply chains gave rise to adverse
aggregate supply effects (Bonadio et al.,2021). At the same time, lockdowns resulted in
income shortfalls and limited consumption opportunities, dampening aggregate demand
(Eichenbaum, Rebelo, and Trabandt, 2021; Kapetanios et al.,2022). Moreover, due to
its unprecedented nature, the pandemic increased uncertainty, which potentially induced
consumers and firms to postpone spending and investment (Altig et al.,2020). Thus,
output and inflation dynamics are likely to be the result of a combination of shocks that
contributed simultaneously during the pandemic.
In this paper, we study the macroeconomic implications of the COVID-19 pandemic for
the US economy by decomposing output growth and inflation dynamics into contributions
of standard macroeconomic shocks. This approach allows us to quantify and compare
the relative contributions of the individual shocks. In addition, we contribute to the
existing literature by studying how the relative importance of the different shocks evolved
over time as different forces may have been at play during the pandemic-induced
JEL Classification numbers: C32, E32, E44.
119
©2023 The Authors. Oxford Bulletin of Economics and Statistics published by Oxford University and John Wiley & Sons Ltd.
This is an open access article under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs License, which permits use and
distribution in any medium, provided the original work is properly cited, the use is non-commercial and no modifications or adaptations are made.
120 Bulletin
recession and the subsequent recovery.1From a policy perspective, identifying the
main drivers of output and inflation dynamics and characterising their potentially time-
varying contributions is relevant since the effects of policy measures depend on the
type of shock that hits the economy. For instance, policies that support aggregate
demand are presumably less effective if the economy primarily faces adverse supply-side
developments.
Our analysis is based on structural vectorautoregressive (VAR) models. To identify
orthogonal structural shocks, we rely on sign restrictions on impulse response functions
(Faust, 1998; Canova and Nicol´
o, 2002; Uhlig, 2005), and narrative sign restrictions
(Antol´
ın-D´
ıaz and Rubio-Ram´
ırez, 2018; Ludvigson, Ma, and Ng, 2021) that exploit
information about the timing and the magnitude of structural shocks. The combination
of these two identification approaches allows us to disentangle the shocks that we
are interested in and to narrow down the set of admissible models.2Specifically, we
identify aggregate supply and aggregate demand shocks by imposing discriminating
sign restrictions on the response of the inflation rate, as is standard (see e.g. Fry and
Pagan, 2011; Furlanetto, Ravazzolo, and Sarferaz, 2017; Calvert Jump and Kohler, 2022),
and impose additional narrative restrictions, which are based on Ludvigson et al. (2021),
to identify uncertainty shocks. Since we impose the narrative restrictions only in months
well before the pandemic, we leave the realisations and the effects of uncertainty shocks
unrestricted during the pandemic itself.
We find that the dynamics of industrial production growth during the COVID-19
pandemic were dominated by adverse uncertainty shocks. While aggregate supply and
aggregate demand shocks contributed to the decline in industrial production growth as
well, uncertainty shocks exerted by far the largest effects. The negative contributions
of aggregate demand shocks faded soon after the initial downturn, while aggregate
supply shocks slowed down economic activity more persistently. The most pronounced
contribution to the acceleration of industrial production growth during the subsequent
recovery can be attributed to a decline in uncertainty.
For inflation dynamics, we find that aggregate demand and especially uncertainty
shocks contributed to the downward pressure on inflation during the downturn. Aggregate
supply shocks counteracted the decline in inflation during the early phase and, together
with expansionary uncertainty shocks, contributed to inflationary pressure towards the end
of the sample. At the end of 2021, the contributions of aggregate supply shocks to inflation
dynamics were of a similar order of magnitude as those associated with uncertainty
shocks, while the contributions of aggregate demand shocks were substantially smaller.
The paper is structured as follows: The following section II provides a review of the
related literature. Section III describes our empirical approach. Section IV presents the
results and section Vsupports our findings with a number of robustness checks. Section VI
concludes the paper.
1Our analysis complements papers that analyse the first few months of the COVID-19 period (e.g. Bekaert,
Engstrom, and Ermolov, 2020), or use pre-crisis data to obtain model-implied predictions for the decline in output
and prices during the pandemic itself (e.g. Baker et al.,2020a).
2Similar in spirit, Ludvigson et al. (2021) use narrative restrictions to separate real activity shocks from financial
and macroeconomic uncertainty shocks. Antol´
ın-D´
ıaz, Petrella, and Rubio-Ram´
ırez (2021) consider narrative
restrictions to render anticipated and unanticipated shocks orthogonal.
©2023 The Authors. Oxford Bulletin of Economics and Statistics published by Oxford University and John Wiley & Sons Ltd.

To continue reading

Request your trial

VLEX uses login cookies to provide you with a better browsing experience. If you click on 'Accept' or continue browsing this site we consider that you accept our cookie policy. ACCEPT