HLEG thematic workshop on Measuring economic, social and environmental resilience, 25-26 November 2015, Rome, Italy, More information at: http://oe.cd/StrategicForum2015

1. Resilience of
Economic and
Financial Systems
Strategic Forum of the International Economic
Association, International Statistical Institute and
the High-level Group on the Measurement of
Economic Performance and Social Progress on
“Measuring Economic, Social and Environmental
Resilience”
Philipp Hartmann
European Central Bank
Rome
25 November 2015
Disclaimer: Any views expressed are only the speaker’s own and should not be
regarded as views of the ECB or the Eurosystem

2. Rubric
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On the concept of resilience in economics
Governing Council
• Ability of an economy to retain function, employment and prosperity
in the face of potential perturbations caused by
• shocks (see Forum agenda)
• endogenous cycles or
• large and strategically interacting economies/entities
• Practical macroeconomic perspectives
• Conjunctural: Recessions are not deeper than necessary
• Structural: Recessions do not lead to a reduction in the growth path
• Economic theory perspectives
• Economy settles in a stable versus unstable equilibrium
• Shocks cannot push economy towards an area of diverging dynamics
• Financial stability perspective
• ECB Financial Stability Review: Condition in which the financial system can
withstand shocks without major disruptions in financial intermediation or in the
general supply of financial services 1

3. Rubric
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Two major approaches for assessing resilience
Governing Council
• Early warning systems/vulnerability indicators
• What do current data (or ratios) tell us about future adverse outcomes (e.g.
crises)?
• Estimate the historical relationship between explanatory variables and
adverse outcome, then search for threshold levels of explanatory variables
that predict adverse outcome minimising type 1 and type 2 errors
• If threshold levels (not) exceeded, then vulnerable (resilient) → policy
• Academic criticism: (i) Lucas critique/Goodhart’s law; (ii) miss future crises
• Practical use: (i) identify vulnerable states; (ii) not looked at in isolation
• (Counterfactual) simulations
• Assume adverse conditions (shock/scenario) and assess with an economic
model whether adverse outcome is generated
• If (not) generated, then vulnerable (resilient) → policy
• Stress tests well-known example, can be actively managed
• Also many challenges, perhaps trusted too much at present
2

4. Rubric
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Example of simulation approach: assessing
macroeconomic resilience with a structural model
Governing Council
• 3D model developed under the ESCB Macroprudential Research
Network (MaRs, Clerc et al. 2015)
• Medium-scale macroeconomic model with heterogeneous bank sector
• Banks have incentives for excessive risk taking
• Possibility of default in household, corporate and bank sector
• Based on “first principles” (dynamic, stochastic, general equilibrium…)
• Calibrated to euro area data
• Can assess welfare benefits (reduces risk taking and default rates) and costs
(increases cost of capital reducing lending) of bank regulation
• Currently implemented as analytical tool for regulatory policy assessments
• One illustration of the resilience effects of capital
• Assume persistent and generalised asset price shock (firms and houses)
• Does the release of the countercyclical capital buffer (CCB) attenuate adverse
growth effects?
• Answer: Depends on the level of bank capital before the shock hits
3

5. Rubric
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Release of the CCB in the 3D model
Governing Council
4
• Higher capital requirements (10.5%)
• With high starting capital position the
buffer release attenuates shock
propagation to growth for most of time the
time
• Limited defaults
• Lower capital requirements (8%)
• With low starting capital position the buffer
release attenuates shock propagation only
early on and mostly destabilises growth
• Increasing default rates
Source: Clerc, Derviz, Mendicino, Nikolov, Moyen, Stracca, Suarez and Vardoulakis (2015), Capital regulation in a macroeconomic model
with three layers of default, International Journal of Central Banking, 11(3), pp. 9-63.
Impulse response functions of a persistent reduction in home prices and firm valuations

6. Rubric
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Example of early warning approach: assessing
macroeconomic resilience with an empirical model
Governing Council
• Markov-switching Vectorautoregression (MSVAR) model developed
under MaRs (Hartmann et al. 2012)
• 5 variables: output growth, inflation, interest rate, credit growth and CISS
• Composite Indicator of Systemic Stress (CISS) incorporated measuring the
level of systemic financial instability
• Feedback effects between all variables possible (also lagged)
• Independent regime changes in model coefficients and error variances
possible
• Bayesian estimation for the euro area (monthly data, 1987-2010)
• Around times of financial crises the macroeconomy fundamentally
changes its functioning
• Not only error variances but also coefficients (structure of the economy) switch
• Systemic fragility regime: Financial shocks have much increased real effects
5

7. Rubric
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State dependency of macroeconomic dynamics
Governing Council
6
• CISS shocks have large and
protracted real effects in the
systemic fragility regime, but
hardly any effects in normal
times (resilient)
• Not only large shocks, also
changed transmission
mechanism
Source: Hartmann, Hubrich, Kremer and Tetlow (2012), Melting down: Systemic financial instability and the macroeconomy, mimeo.,
ECB.
Impulse response function of a CISS shock on output growth
Output growth
Normal times
Constant parameter
Systemic fragility

8. Rubric
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Nowcasting of systemic fragility
7
Source: Hartmann, Hubrich, Kremer and Tetlow (2012), Melting down: Systemic financial instability and the macroeconomy, mimeo.,
ECB.
Comparing state probabilities (red and blue) with real time state probabilities (grey)
• Real-time probabilities
estimated for each point on red
line with sub-sample from start of
sample to one month after initial
point
• Comparing red line with grey
arks suggests limited type 1 and
type 2 errors
• Model nowcasts state of
systemic fragility in May 2008
Sep 2001 May 2008

9. Rubric
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Concluding remarks: the bufferless economy/
society
Governing Council
• Resilience is a useful concept we should perhaps mind more often
about in economic research, policy and private sector activities
• Policies enhancing system resilience versus finetuning of macro or
regulatory interventions
• Capitalism may lead to highly efficient economic and financial
systems most of the time, but without public intervention also to an
increasingly bufferless economy/society
• Erosion of bank capital before the crisis
• High public debt levels around the world
• Vulnerability of an incomplete monetary union with structural rigidities
• Complex international supply chains in production
• Power supply networks
8

10. Rubric
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Annex

11. Rubric
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Example of early warning approach: decision tree
as part of a random forest
Governing Council
10
Precrisis
crisis pr.= 0. 51
Bank credit/GDP
Bank credit/GDP gap
Tranquil
crisis pr.= 0.02
< 107
> 93
Precrisis
crisis pr.= 0.45
HH credit/GDP
Precrisis
crisis pr.= 1
< 79
Tranquil
crisis pr.= 0
< -0.8
< 0.14 >0.14
Debt service ratio
> -0.8
< 56
Precrisis
crisis pr.= 0.87
Tranquil
crisis pr.= 0
> 56
Tranquil
crisis pr.= 0.01
Bank credit growth
< 8 > 8
Tranquil
crisis pr.= 0.01
Current account/GDP
< 1
> 107
> 1
Tot. credit/GDP
< 93
Basel gap
< 3.3 > 3.3
Tranquil
crisis pr.= 0.09
Precrisis
crisis pr.= 0.34
Inflation
< 2
> 79
> 2
Bank credit/GDP
< 45
Bank credit growth
Tranquil
crisis pr.= 0
> 45
AUROC (forest): 0.93
[0.5 = useless;
1 = perfect]
Correct predictions (tree): 84%
False alarms (tree): 18%
Source: Alessi and Detken (2014), Identifying excessive credit growth and leverage, ECB Working Paper, no. 1723, August.
Signals of systemic banking crisis 1-5 years ahead

12. Rubric
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Example of simulation approach: Counterfactual
scenario with MSVAR model
Governing Council
11
Source: Hartmann, Hubrich, Kremer and Tetlow (2012), Melting down: Systemic financial instability and the macroeconomy, mimeo.,
ECB.
Scenario in January 2007:
What would have been the growth
outlook for the euro area if systemic
instability had hit?
•Large increase of CISS (to 0.7)
•Fundamental regime change in the
macroeconomy
Output growth

13. Rubric
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Example of simulation approach: indicator of
marginal bank contagion risk
Governing Council
12
Effect of bank failure on euro interbank network (Dec. 08)
Simulation of the overall loss of equity (in % of total) among all banks active in TARGET2 caused by individual bank
failures (“debt rank” methodology based on a further development of Battiston et al. (2012)) and bank size.
Source: di Iasio, Rainone, Rocco and Vacirca (2013).
0%
2%
4%
6%
8%
10%
12%
14%
1 10 100 1,000 10,000 100,000 1,000,000 10,000,000
Debtrank(%)
Total assets (million euros, log scale)
• Transmission not only through
defaults but also proportional
to Furfine interbank
exposures, relative losses
and relative capitalisation of
banks
• Contagion risk larger than
found in traditional default
simulations
• Largest banks have systemic
effect (non-linear) but wide
dispersion
• Helps, inter alia, to under-
stand the systemic impor-
tance of individual banks and
how it evolves over time