Empirical Evidence on the Dynamics of Investment Under Uncertainty in the U.S.*
| Published date | 01 October 2021 |
| Author | Qazi Haque,Leandro M. Magnusson,Kazuki Tomioka |
| Date | 01 October 2021 |
| DOI | http://doi.org/10.1111/obes.12420 |
Empirical Evidence on the Dynamics of Investment
Under Uncertainty in the U.S.*
QAZI HAQUE,†LEANDRO M. MAGNUSSON‡and KAZUKI TOMIOKA§
†
CAMA and Department of Economics, Business School, The University of Western Australia,
Crawley, Western Australia 6009, Australia (e-mail: qazi.haque@uwa.edu.au)
‡
Department of Economics, Business School, The University of Western Australia, Crawley,
Western Australia 6009, Australia (e-mail: leandro.magnusson@uwa.edu.au)
§
Research School of Economics, Australian National University, Canberra, Australian Capital
Territory, Australia (e-mail: Kazuki.Tomioka@anu.edu.au
Abstract
We study the time-varying effects of financial uncertainty shocks in the United States
using a vector autoregression with drifting parameters and stochastic volatilities. We
find negative effects of financial uncertainty shocks on real activity with both
consumption and investment growth declining significantly and comoving along the
entire sample. These effects remained fairly stable in the post-WWII period but the
negative response of investment growth became more pronounced during the Zero
Lower Bound episode. Our findings lend empirical support to theoretical frameworks
that can successfully capture this macroeconomic comovement following an
uncertainty shock. Remarkably, we find a limited role for financial uncertainty shocks
during the Great Recession.
I. Introduction
The recent global economic and financial crisis has led to a renewed interest in the
relationship between uncertainty and the macroeconomy.
1
Following Bloom (2009)’s
influential work, the role played by uncertainty shocks in driving macroeconomic
JEL Classification numbers:C11, C32, E22, E32, E44,
*We thank the Editor and three anonymous referees for their suggestions which improved the quality of the
manuscript. We also thank Guido Ascari, Ivan Alfaro, Giovanni Caggiano, Efrem Castelnuovo, Ken Clements,
Michael Funke, Richard Heaney, Robert King, Sophocles Mavroeidis, Farhad Mohammad, Adrian Pagan,
Aubrey Poon, Tom Simpson, Rod Tyers, Mark Weder, Francesco Zanetti and the seminar participants at The
University of Western Australia, the Australian Conference for Economists 2017 (Sydney), the 26th Annual
Society for Nonlinear Dynamics and Econometrics Symposium (Tokyo, 2018), the Australasian Meeting
(Auckland, 2018) and the North American Summer Meeting (Seattle, 2019) of The Econometric Society. The
authors acknowledge generous support from the Australian Research Council (DP170100697). Tomioka
acknowledges financial support funded by the Commonwealth Government of Australia via the Research
Training Program at The University of Western Australia.
1
See Castelnuovo (2019) for an extensive survey covering the recent literature on uncertainty.
1193
©2021 The Department of Economics, University of Oxford and John Wiley & Sons Ltd.
OXFORD BULLETIN OF ECONOMICS AND STATISTICS, 83, 5 (2021) 0305-9049
doi: 10.1111/obes.12420
fluctuations has been a key topic of research and discussion among both academics
and policymakers. Part of the literature uses vector autoregression (VAR)-based
analysis to identify the impact of uncertainty shocks. Recent contributions include
Bloom (2009), Alexopoulos and Cohen (2009), Bachmann, Elstner and Sims (2013),
Mumtaz and Zanetti (2013), Caggiano, Castelnuovo and Groshenny (2014), Gilchrist,
Sim and Zakrajˇ
sek (2014), Baker, Bloom and Davis (2016), Leduc and Liu (2016),
Basu and Bundick (2017), Mumtaz and Theodoridis (2018), among others. In addition,
a related literature study the transmission mechanism of uncertainty shocks from a
theoretical standpoint.
2
One consensus that has emerged on this topic is that (i)
uncertainty shocks result in adverse effects on the economy (Bloom, 2009; Jurado,
Ludvigson and Ng, 2015; Basu and Bundick, 2017), and (ii) its effects are nonlinear
and time-varying (Caggiano et al., 2014; Caggiano, Castelnuovo and Pellegrino, 2017;
Mumtaz and Theodoridis, 2018).
Regarding (i), recent empirical studies support the notion that investment growth is
retarded upon prevalence of uncertain environment, which produces a rapid drop in output
and employment (Bloom, 2009). Part of the literature tends to attribute such observations to
the ‘wait-and-see’behaviour of firms arising from the real-option value to waiting, that is,
firms become more cautious in responding to business conditions and scale back their plans.
Although this mechanism gained overwhelming support since the seminal contribution of
Bloom (2009), the channel through which uncertainty influences investment is not limited to
it. As pointed out by Basu and Bundick (2017) a New Keynesian (NK) model with
countercyclical markups through sticky prices can generate a drop in investment after an
uncertainty shock, whose real effects are present in the system due to precautionary savings.
Despite the absence of the wait-and-see channel, investment (as well as output and hours
worked) still decline because of the negative effect on aggregate demand arising dueto
reduced consumption. Interestingly, this is notwhatmostrealbusiness cycle (RBC) models
would predict as such models have troubles in replicating the macroeconomic comovement
after an uncertainty shock. For instance, precautionary savings due to higher uncertainty
cause households to reduce consumption and increase labour supply. With flexible prices,
labour demand remains unchanged and so a higher labour supply translates to a rise in
output. Higher output with lower consumption implies that investment must rise. Thus,
higher uncertainty under flexible prices lowers consumption but causes an expansion in
output, investment and hours worked due to precautionary savings (Basu and Bundick,
2017).
Regarding (ii), employing a variety of different approaches, numerous empirical
studies have attempted to answer whether the effects of uncertainty on the economy
have changed over time. For instance, Caggiano et al. (2014) and Angelini et al.
(2019) document that the effects of uncertainty shocks are greater in magnitude during
recessions and in periods of economic and financial turmoil respectively.
3
Caggiano
2
See Fern´
andez-Villaverde et al. (2011), Christiano, Motto and Rostagno (2014), Leduc and Liu (2016), Basu
and Bundick (2017), Bloom et al. (2018) for a non-exhaustive list.
3
Similarly, Caldara et al. (2016) show that the negative effects of uncertainty shock on real variables intensify
when the sample period spans over the 2008–09 financial crisis, relative to when the sample period ends prior to
the onset of the financial crisis.
©2021 The Department of Economics, University of Oxford and John Wiley & Sons Ltd
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