Uncertainty and
Monetary Policy in
the Euro Area
Policy Department for Economic, Scientific and Quality of Life Policies
Directorate-General for Internal Policies
Authors: Christophe BLOT, Paul HUBERT, Fabien LABONDANCE
PE 658.196 - November 2020
EN
IN-DEPTH ANALYSIS
Requested by the ECON committee
Monetary Dialogue Papers, November 2020
Abstract
The outbreak of the COVID-19 crisis has triggered a new wave of
uncertainty, which may amplify the negative effect of the crisis.
Based on several uncertainty measures, we show that inflation in
the euro area is negatively affected by higher uncertainty.
However, uncertainty does not impair the transmission of
monetary policy. Consequently, the ECB should consider
uncertainty in its reaction function in order to fulfil its mandate.
This document was provided by the Policy Department for
Economic, Scientific and Quality of Life Policies at the request of
the Committee on Economic and Monetary Affairs (ECON) ahead
of the Monetary Dialogue with the ECB President on 19
November 2020.
Uncertainty and
Monetary Policy in
the Euro Area
Monetary Dialogue Papers,
November 2020
This document was requested by the European Parliament's committee on Economic and Monetary
Affairs (ECON).
AUTHORS
Christophe BLOT, Sciences Po – OFCE and Université Paris Nanterre
Paul HUBERT, Sciences Po – OFCE
Fabien LABONDANCE, Université de Bourgogne Franche-Comté
ADMINISTRATOR RESPONSIBLE
Drazen RAKIC
EDITORIAL ASSISTANT
Janetta CUJKOVA
LINGUISTIC VERSIONS
Original: EN
ABOUT THE EDITOR
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Manuscript completed: October 2020
Date of publication: November 2020
© European Union, 2020
This document was prepared as part of a series on the “Effects of Pandemic-Induced Uncertainty on
Monetary Policy”, available on the internet at:
https://www.europarl.europa.eu/committees/en/econ/econ-policies/monetary-dialogue
DISCLAIMER AND COPYRIGHT
The opinions expressed in this document are the sole responsibility of the authors and do not
necessarily represent the official position of the European Parliament.
Reproduction and translation for non-commercial purposes are authorised, provided the source is
acknowledged and the European Parliament is given prior notice and sent a copy.
For citation purposes, the publication should be referenced as: Blot, C., Hubert, P., and Labondance, F.,
Uncertainty and Monetary Policy in the Euro Area, Publication for the committee on Economic and
Monetary Affairs, Policy Department for Economic, Scientific and Quality of Life Policies, European
Parliament, Luxembourg, 2020.
Uncertainty and Monetary Policy in the Euro Area
3 PE 658.196
CONTENTS
LIST OF ABBREVIATIONS 4
LIST OF FIGURES 5
LIST OF TABLES 5
EXECUTIVE SUMMARY 6
1. INTRODUCTION 7
2. MEASURING UNCERTAINTY 8
3. THE EFFECT OF UNCERTAINTY ON EURO AREA INFLATION 12
4. DOES UNCERTAINTY IMPAIR THE TRANSMISSION OF MONETARY POLICY? 17
5. CONCLUSION 21
REFERENCES 22
ANNEX 24
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LIST OF ABBREVIATIONS
Composite Indicator of Systemic Stress
Consumer Price Index
European Central Bank
Economic Policy Uncertainty
Gross domestic product
Organisation for Economic Co-operation and Development
Survey of Professional Forecasters
US United States
(Chicago Board Options Exchange) Volatility Index
Euro Stoxx 50 Volatility Index
Uncertainty and Monetary Policy in the Euro Area
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LIST OF FIGURES
Figure 1: The evolution of financial uncertainty: the CISS 9
Figure 2: The evolution of economic policy uncertainty: the EPU 10
Figure 3: The evolution of macroeconomic news uncertainty: the Scotti (2016) index 11
Figure 4: The effect of CISS uncertainty on inflation 13
Figure 5: The effect of EPU uncertainty on inflation 14
Figure 6: The effect of Scotti (2016) uncertainty on inflation 15
Figure 7: The state-dependent effect of monetary policy to the CISS 18
Figure 8: The state-dependent effect of monetary policy to the EPU 19
Figure 9: The state-dependent effect of monetary policy to the Scotti (2016) index 20
Figure 10: The linear effect of monetary policy on inflation 24
LIST OF TABLES
Table 1: Correlation between uncertainty measures 11
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EXECUTIVE SUMMARY
• Academic literature emphasises that uncertainty shocks work as negative demand shocks
suggesting that they would amplify the deflationary pressures already at work.
• Uncertainty is a multidimensional concept that can encompass
several dimensions – financial,
macroeconomic, economic policy. The different types of uncertainty do not have similar dynamics
and effects on the economy.
• We show that uncertainty has negative effects on inflation overall. Although financial
uncertainty does not transmit to non-energy industrial goods and uncertainty about
macroeconomic news is positively correlated with energy prices, the overall effect of all uncertainty
metrics on the various components of inflation in the euro area is negative and persistent.
• However, we find no evidence that uncertainty affects the transmission mechanism of
monetary policy to inflation. The effectiveness of the European Central Bank (ECB)’s monetary
policy on euro area inflation is the same regardless whether uncertainty is high or not.
• The policy implications of such results are that the effectiveness of the policy instruments is not
impaired and that monetary policymakers should consider uncertainty in their reaction
function in order to fulfil their mandate.
Uncertainty and Monetary Policy in the Euro Area
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1. INTRODUCTION
The outbreak of the COVID-19 crisis has triggered an unprecedented worldwide recession. In the first
semester of 2020, gross domestic product (GDP) plummeted by 15 % in the euro area and even if a
rebound is expected during the second half of the year, the economic outlook remains gloom y. This
situation has been accompanied by a new wave of uncertainty as it was the first time in the modern
era that the world was confronted with such a pandemic. Not only were the spread of the coronavirus
and its health effects unknown but so were the economic consequences of the lockdown measures
implemented by most governments. Now that we have the first statistical information released by
national institutes, the depth of the recession is confirmed but uncertainty remains as the pandemic is
still not under control. The path for the ongoing recovery is still unchartered and several scenarios are
likely: will it be a V-shaped recession, a W-shaped or "inverted square root sign"-shaped recession?
The volatility of financial markets has testified to this uncertainty. After a sharp decline of stock price
indices, prices have rapidly gone up and even fully recovered in the United States (US). The difficulty to
understand the evolution of the pandemic has led the Organisation for Economic Co-operation and
Development (OECD) to provide two scenarios in its spring forecast for assessing the economic effect
of the crisis. Statistical information for the second quarter has exhibited a wider heterogeneity than
usual across industrialised countries. In the euro area for instance, GDP fell by 18.5 % in Spain but only
by 4.4 % in Finland. According to the September Consensus forecasts, there is a high dispersion of GDP
forecasts for 2020 ranging from -8.9 % to -6.3 % for the euro area as a whole and the probability of
higher forecast errors provide additional signs of how the current economic outlook is uncertain.
This uncertainty is an important feature that central banks need to take into account when setting their
monetary policy. The ECB indeed faces major supply and demand shocks but also an uncertainty shock.
Theoretical and empirical literature has generally emphasised that uncertainty may reinforce negative
demand shocks, suggesting that it would amplify the reduction of inflation in the current situation.
Consequently, monetary policy is expected to be expansionary but the question arises of whether
uncertainty may affect the transmission of monetary policy. In this paper, we deal with these issues and
document the effect of uncertainty on several components of inflation in the euro area. Then, we focus
on the effect of monetary policy on inflation and assess, by disentangling between periods of low and
high uncertainty, whether this transmission mechanism is influenced by uncertainty. The main
challenge of the analysis is to proxy uncertainty, which is unobservable. To that end, we first survey the
different measures proposed in the literature. We notably point to the fact that uncertainty
encompasses several dimensions – financial, macroeconomic, economic policy – and that available
indicators generally capture only one of these dimensions. Given that the current situation is
characterised by a large degree of uncertainty, our analysis is not restricted to one dimension but
strives to account for all potential sources of uncertainty.
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2. MEASURING UNCERTAINTY
While the role of uncertainty for individual choice has been assessed for several decades, its role in the
macroeconomic business cycle has been emphasised more recently.
1
Yet, uncertainty is an
unobservable variable and can only be proxied. A growing literature has therefore been devoted to
provide various measures encompassing the different dimensions of uncertainty. In this section we
notably focus on four measures of uncertainty.
2
First, uncertainty can be observed on financial markets through indices of volatility. For example, as
stock prices encompass all kinds of information that are useful to anticipate future dividends, t heir
volatility captures uncertainty related to stock markets but also about the economic outlook that
affects current stock prices. A widely used measure of uncertainty is the VIX index, an indicator based
on the US option prices for the S&P 500 index.
3
The VIX – or alternatively VSTOXX for the euro area –
have been interpreted as indicators of risk appetite. The more investors are ready to take risky positions,
the lower is the VIX. Conversely when investors are reluctant to take risks, they express “fear” about the
future. Implicit volatility then increases, thus indicating higher uncertainty. As the US stock market is
highly internationalised, the VIX index has often been used as a proxy for global uncertainty. Yet, an
equivalent indicator can be obtained from options related to European stock market indices. As stock
markets are often synchronised, those indicators based on implied volatility are usually highly
correlated.
The ECB proposed an aggregate measure called the composite indicator of systemic stress (CISS). The
CISS is computed for the euro area but also does not only focus on stock price volatility. This index
encompasses 15 market-based financial stress measures that are split equally into five categories,
namely the financial intermediaries sector, money markets, equity markets, bond markets and foreign
exchange markets. High levels of CISS are associated with systemic risk. It has therefore reached record
levels during the subprime and the sovereign debt crisis in the euro area (see Figure 1). By comparison,
the CISS has slightly increased since the COVID-19 pandemic. The peak reached during this period is
notably below the levels reached during the previous crises.
1
See Bloom (2009) for a first attempt to quantify the macroeconomic effect of uncertainty.
2
See Ferrara et al. (2018) for a survey of those measures.
3
A stock option gives an investor the right, but not the obligation, to buy or sell a stock at an agreed upon price and date. The price of
option is related to the volatility of stock prices.
Uncertainty and Monetary Policy in the Euro Area
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Figure 1: The evolution of financial uncertainty: the CISS
Source: ECB. Shaded areas represent euro area slowdowns and recessions as defined by the Eurostat Business Cycle Clock.
Sample period: January 1999 – September 2020.
Second, uncertainty can also be captured by analysing daily news. Newspapers indeed report events
and policy decisions and they provide indications on how those are perceived, and hence how they are
subject to uncertainty. Based on a textual analysis, Baker et al. (2016) build an indicator of Economic
Policy Uncertainty (EPU), which is another dimension through which aggregate dynamics can be
affected drastically. The indicator relates to the uncertainty surrounding elections, referenda and
political decisions that affect the implementation of economic and social programs. Baker et al. (2016)
construct an EPU index for different economies based on a textual analysis that consists in counting
the occurrence of a sequence of words that together refer to the economy, policy and uncertainty. This
method has been developed for several countries: e.g. the United States, China, the euro area as a
whole, France and Germany. Uncertainty can also stem from different economic policies: fiscal policy,
monetary policy and trade policy for instance. Husted et al. (2020) develop an indicator of monetary
policy uncertainty for the US. In Europe, the EPU index has been high during the subprime crisis and
the sovereign debt crisis but is higher since 2018, probably pushed by the uncertainty surrounding
Brexit and the political decisions during the COVID-19 pandemic (Figure 2).
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Figure 2: The evolution of economic policy uncertainty: the EPU
Source: Baker et al. (2016). Shaded areas represent euro area slowdowns and recessions as defined by the Eurostat Business
Cycle Clock. Sample period: January 1999 – September 2020.
Third, uncertainty can also be reflected through macroeconomic forecasting errors or, said differently,
through macroeconomic news surprises. The idea being that when uncertainty about the state of the
economy is rising, macroeconomic forecasts are less and less accurate. On this subject, Scotti (2016)
identifies macroeconomic surprises as differences between professional forecasts and real data. Then,
based on these surprises, she develops an uncertainty index. This indicator clearly captures the
uncertainty since the COVID-19 pandemic as all forecasts have been dramatically revised (Figure 3).
Macroeconomic uncertainty can also be measured when observing the disagreement between
professional forecasters: forecasts about the future state of the economy should be more dispersed
when uncertainty is high and vice versa. The ECB’s Survey of Professional Forecasters (SPF) provides,
for example, the variance of forecasts for the real GDP growth rate. The shape of this measure of
dispersion is very similar to the shape of Figure 3 and indicates that uncertainty about future real GDP
growth dynamics in the euro area has never been that high.
Uncertainty and Monetary Policy in the Euro Area
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Figure 3: The evolution of macroeconomic news uncertainty: the Scotti (2016) index
Source: Scotti (2016). Shaded areas represent EA slowdowns and recessions of the Eurostat Business Cycle Clock. Sample
period: March 2005 – September 2020.
The correlation coefficients between these measures of uncertainty suggest that a common
component between these indicators exists (Table 1) but they also show that the correlation is not
perfect. It suggests that the choice of the uncertainty estimator is crucial as all measures are not fo cused
on the same kind of uncertainty. Moreover, Figure 1 illustrates that during the subprime crisis and the
sovereign debt crisis, uncertainty observed on the financial markets was a key factor. But since the
COVID-19 pandemic, the euro area is dealing with a new kind of uncertainty that seems to be a
combination of macroeconomic and economic policy uncertainty, reflecting how the economy will be
affected by the shock and what will be the economic policy responses to deal with the crisis. The CISS
indicator does indeed not show a drastic rise.
Table 1: Correlation between uncertainty measures
VIX CISS Scotti (2016) EPU
VIX 1
CISS 0.69 1
Scotti (2016) 0.27 0.21 1
EPU 0.18 0.12 0.19 1
Source: Authors’ own computation.
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3. THE EFFECT OF UNCERTAINTY ON EURO AREA INFLATION
We assess the effect of uncertainty on euro area inflation by estimating its dynamic response to
uncertainty shocks at several horizons. To that end, we use local projections to infer how different
measures of inflation are affected by a rise in different indicators of uncertainty. The estimations are
realised for several indicators of inflation: headline inflation, core inflation, the inflation of prices of
services and the inflation of prices of industrial non-energy goods. All data are taken from Eurostat. We
assume that uncertainty is not influenced by current inflation so that it can be treated as exogenous
(i.e. orthogonal to inflation). Thus, we are able to quantify whether subcomponents of the price index
react differently to uncertainty. Besides, we control for three lags of the inflation indicator, oil prices
and the unemployment rate in the euro area to circumvent reverse causality or omitted variable biases.
Thus, we are able to estimate the effect of uncertainty beyond the effect of change in demand –
captured by the unemployment rate – and the effect of oil prices, which play an important role in the
dynamic of the consumer price index (CPI). The sample period goes from January 1999 to September
2020.
When we consider the effect of uncertainty on inflation either measured by the CISS – reflecting
uncertainty on financial markets – or by the EPU index computed by Baker et al. (2016), our estimates
show that a rise in uncertainty has a negative impact on inflation and its components. The evidence is
however more nuanced with the Scotti (2016) measure of uncertainty related to macroeconomic news
surprises.
The response of headline inflation is negative but weakly significant to a rise in the CISS. More precisely,
a one-standard deviation increase in the CISS index reduces headline inflation on impact by less than
0.1 percentage point. The effect of uncertainty on core CPI is less pronounced on impact but more
significant at longer horizons. The effect of CISS uncertainty on CPI services is more pronounced: a one-
standard deviation increase in uncertainty yields a 0.2 percentage point decrease in prices after 18
months (Figure 4). However, the response of non-energy industrial goods to uncertainty is s lightly
positive. This might be related to the fact that financial uncertainty does not transmit much to industrial
firms (which by definition are non-financial). This might explain why the overall effect of CISS
uncertainty on core CPI is negative.
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Figure 4: The effect of CISS uncertainty on inflation
Source: Authors’ estimates. Shaded areas represent 68 and 90% confidence intervals.
When uncertainty is measured with the EPU index, all responses are significantly negative, suggesting
no discrepancies across services and non-energy industrial goods (Figure 5). The effect of economic
policy uncertainty appears strong and homogeneous across markets.
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Figure 5: The effect of EPU uncertainty on inflation
Source: Authors’ estimates. Shaded areas represent 68 and 90% confidence intervals.
These results, across the CISS and the EPU indices, are consistent with macroeconomic evidence
indicating that an increase in uncertainty is associated with a reduction in demand, as can be inferred
from the decrease in core CPI. Uncertainty shocks can be indeed interpreted as negative demand
shocks as it would deter firms from investing and households from consuming. Following Bernanke
(1983), we may consider that investment – or hiring – decisions entail “sunk” costs representing fixed
expenses needed to implement those decisions, that cannot be recovered even if the investment or
the hiring decision is reversed. Those decisions are seen as irreversible and when firms face higher
uncertainty, they prefer to postpone decisions to avoid paying the sunk costs. The same argument may
hold for consumers. When uncertainty regarding their future revenues is higher, they increase
precautionary saving to avoid a more substantial fall of consumption if their revenues decrease. Finally,
uncertainty may also affect the financial sector. Uncertainty is intrinsically related to the ability to take
risks. The financial system – financial intermediaries and markets – will request a risk premium when
uncertainty rises. It increases the cost of financing for firms and reduces aggregate demand. These
different transmission channels all point to a negative demand shock explaining why the rise of
uncertainty is followed by a reduction of inflation as illustrated by Figures 4 and 5. Caldara et al. (2016)
and Mumtaz and Surico (2018) confirm the negative effect of uncertainty – measured by different
indicators – on output, consumption and investment. The negative effect of uncertainty on output,
prices, interest rates and exports has also been confirmed by Cuaresma et al. (2019).
Uncertainty and Monetary Policy in the Euro Area
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The effect of uncertainty measured by Scotti (2016)’s indicator that focuses on macroeconomic news
surprises provides a slightly different picture since the response of the headline CPI after an uncertainty
shock is positive (Figure 6). The response of core CPI and CPI services is however slightly negative. The
contrast between these latter responses and the response of the headline CPI suggests an effect of
uncertainty on the most volatile components of CPI. Figure 6 plots a positive effect of the uncertainty
about macroeconomic news on the overall price index. However, this positive effect disappears when
we focus on the effect of uncertainty on core CPI and on more structural prices: services or non-energy
industrial goods. Our estimates show a negative response of core CPI and prices of services after an
increase of uncertainty. One interpretation of this positive effect is that the uncertainty related to
macroeconomic news in general and potentially from energy prices more specifically – like volatile oil
price news – have a positive effect on energy prices. This is related to the finding of Piffer and
Podstawski (2018) who show that uncertainty shocks can be confounded with news shocks th at would
generate positive responses of prices.
Figure 6: The effect of Scotti (2016) uncertainty on inflation
Source: Authors’ estimates. Shaded areas represent 68 and 90% confidence intervals.
This result is somehow at odds with the results found by Scotti (2016) for the United States s ince she
shows that a rise in her indicator on uncertainty is followed by a decline in employment. To that extent,
her results are consistent with the evidence from other indicators. Our analysis would suggest a
different impact of this uncertainty indicator on the components of euro area inflation: the most
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volatile part – energy prices – reacts positively whereas more structural parts – like services – react
negatively. This latter being consistent with the result of Scotti (2016).
Finally, for the sake of completeness, some other uncertainty indices have been proposed in the
literature. Regarding the relationship between uncertainty and inflation, one could also refer to the
uncertainty about the inflation target or about future inflation. In this strand of the literature, Cogley
(2005) establishes a link between uncertainty about the inflation target and risk premia on long-term
US bonds, while Wright (2011) relates the fall in inflation uncertainty and the fall in term premia in a
cross-country analysis. Istrefi and Mouabbi (2018) construct a measure of monetary policy uncertainty
and show that this uncertainty about future interest rates has large, negative and persistent effects on
the economy. Jurado et al. (2015) compute econometric estimates of macroeconomic uncertainty.
They show that large and significant uncertainty episodes appear far less than suggested by popular
uncertainty proxies. When they do happen, they are larger, more persistent, and have more negative
effects on real activity. Bachmann et al. (2013) provide business-level uncertainty measures. This type
of uncertainty leads to significant reductions in production that are, however, offset quickly. O verall,
these different contributions point out that uncertainty shocks are akin to demand shocks in their
macroeconomic effects.
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4. DOES UNCERTAINTY IMPAIR THE TRANSMISSION OF
MONETARY POLICY?
If uncertainty reduces aggregate demand and core inflation, it will eventually appear in the reaction
function of monetary policymakers. When such a negative shock occurs, central banks are expected to
implement more expansionary monetary measures in accordance with their final objective. Yet, the
effect of monetary policy may itself be affected by uncertainty as illustrated by Tillmann (2020) who
shows that a policy tightening decision is less effective – leading to a weaker reaction of long-term
interest rates – if uncertainty is high. However, those results do not focus on the transmission of
monetary policy to inflation and the uncertainty considered by Tillman (2020) relates to monetary
policy itself. Aastveit et al. (2017) show that policy uncertainty reduces the transmission of Fed
monetary policy on investment and consumption. This dampening of the effects of monetary policy in
situations of uncertainty is confirmed by Castelnuovo and Pellegrino (2018). Andrade et al. (2019) show
that ambiguity reduces the effectiveness of forward guidance. Empirical analysis has also emphasised
that the effects of uncertainty shocks are state-dependent. As for standard demand shocks, the
consequences of negative uncertainty increase when the economy is at the zero lower bound
(Caggiano et al., 2017) or during recessions (Caggiano et al., 2014). There is consequently evidence
suggesting several non-linearities when assessing the role of uncertainty.
Here we notably assess whether the transmission of monetary policy is affected by the size of
uncertainty. To that end, we estimate the effect of monetary shocks identified by Altavilla et al. (2019)
on our different measures of euro area inflation. As for the effect of uncertainty, we consider monthly
data over the sample 2002-2020.
4
We disentangle the effectiveness of monetary policy during periods
of low and high uncertainty.
5
More precisely, for each indicator, we label a “low” (respectively “high”)
uncertainty regime for uncertainty values in the first third (respectively the last third) of the distribution
of uncertainty outcomes. Monetary policy shocks capture the conventional and unconventional
measures implemented by the ECB. As for our previous estimations, we use the local projections
approach since we can consider that the monetary shocks identified by Altavilla et al. (2019) –
stemming from an event-study approach – are exogenous. The equations include three lags of the
dependent variable.
The linear effect of monetary policy on the inflation indicators is exhibited in the Annex (Figure 10). As
expected, we find that a restrictive monetary policy has a negative effect on inflation. The effect is short-
lived for the headline index but is significant at longer horizons when we consider the core inflation or
inflation in services. The effect is negative but not significant for non-energy industrial goods.
When we disentangle periods of “low” and “high” uncertainty, we do not find any significant difference
in the response function of inflation to monetary policy whatever the uncertainty indicator. Our focus
is not on the effect of monetary policy per se (see Figure 10 in the Annex) but whether there are
differences in price responses according to the level of uncertainty. The only small difference that may
be captured is for the CPI response to monetary policy when uncertainty is measured by the CISS
(Figure 7).
4
The measures of monetary policy shocks in the euro area provided by Altavilla et al. (2019) is based on overnight indexed swap (OIS) data,
which were very noisy until the end of 2001.
5
Altavilla et al. (2019) provide a distinction between surprises related to the policy decisions, which are estimated on a window following
the policy announcement and surprises related to information released by the ECB during the press conference held 45 minutes a f ter the
press release.
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Figure 7: The state-dependent effect of monetary policy to the CISS
Source: Authors’ estimates. Shaded areas represent 68 and 90% confidence intervals.
It seems here that the short-term effect of monetary policy is stronger when uncertainty is high. The
other results are shown in Figure 8 and Figure 9. The state-dependent effect of monetary policy
estimated conditional on the EPU or the Scotti (2016) index does not suggest any difference. The level
of uncertainty does not change the transmission of monetary policy.
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Figure 8: The state-dependent effect of monetary policy to the EPU
Source: Authors’ estimates. Shaded areas represent 68 and 90% confidence intervals.
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Figure 9: The state-dependent effect of monetary policy to the Scotti (2016) index
Source: Authors’ estimates. Shaded areas represent 68 and 90% confidence intervals.
Those results suggest that the transmission of monetary policy is not affected by uncertainty.
Consequently, the expansionary measures taken by the ECB during the crisis may help to mitigate the
recessionary shock and its negative effect on inflation.
Beyond the transmission channel of monetary policy, there is also a role for policy makers to influence
expectations and potentially mitigate uncertainty. Central banks and governments may strive to
implement measures that will restore confidence. By making sure that monetary policy will act when
economic outlook is at risk, central banks may help to mitigate the risk of negative self-sustaining
expectations. Central bank communication may help to provide information on the future path of
monetary policy and signal their intentions when the economic outlook becomes more uncertain.
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5. CONCLUSION
The academic literature emphasises that uncertainty shocks work as negative demand shocks
suggesting that they would amplify the deflationary pressures already at work. The analysis carried out
in this paper for the euro area generally confirms these results. Uncertainty is a multidimensional
concept that can encompass several dimensions – financial, macroeconomic, economic policy – and
we aimed to investigate the role of each of them. The different types of uncertainty do not have similar
dynamics and effects on the economy. We show that uncertainty has negative effects on inflation
overall. Although financial uncertainty does not transmit to non-energy industrial goods and
uncertainty about macroeconomic news is positively correlated with energy prices, the overall effect
of all uncertainty metrics on the various components of inflation is negative and persistent. However,
we find no evidence that uncertainty affects the transmission mechanism of monetary policy to
inflation. The effect of ECB monetary policy on euro area inflation is the same regardless whether
uncertainty is high or not. The policy implications of such results are that the effectiveness of the policy
instruments is not impaired and that monetary policymakers should consider uncertainty in their
reaction function in order to fulfil their mandate.
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ANNEX
Figure 10: The linear effect of monetary policy on inflation
Source: Authors’ estimates. Shaded areas represent 68 and 90% confidence intervals.
PE 658.196
IP/A/ECON/2020-51
PDF ISBN 978-92-846-7448-0 | doi:10.2861/95843 | QA-03-20-744-EN-N
The outbreak of the COVID-19 crisis has triggered a new wave of uncertainty, which may amplify the
negative effect of the crisis. Based on several uncertainty measures, we show that inflation in the
euro area is negatively affected by higher uncertainty. However, uncertainty does not impair the
transmission of monetary policy. Consequently, the ECB should consider uncertainty in its reaction
function in order to fulfil its mandate.
This document was provided by the Policy Department for Economic, Scientific and Quality of Life
Policies at the request of the Committee on Economic and Monetary Affairs (ECON) ahead of the
Monetary Dialogue with the ECB President on 19 November 2020.