Matthieu Darracq Pariès*
D-Monetary Policy
Discussion of
“Risk-Taking Dynamics and
Financial Stability”
by Anton Korinek and Martin
Nowak
First annual ECB macroprudential policy and research conference,
26 April 2016
*The views expressed are my own and do not necessarily represent the ones of the ECB or the Eurosystem of
Central Banks
Overview
Rubric
•
The paper intends to bring a new perspective on risk taking and financial
sector composition
Inspired from evolutionary economics
Focus on dynamic compositional effects
Complementary approach to more “static” risk-taking frictions related to fire sales, demand
externalities or bounded rationality
•
The insights from the paper could be applied to a variety of extensions
The paper may well open a full research programme
But some flagship applications should be conducted
•
Which policy lessons to draw from the paper?
The composition of the financial sector and its dynamic evolution should be monitored and
at times, counteracted
Difficult to earmark the paper findings to specific policy frameworks
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Heterogeneity
in the euro area financial system
Rubric
Euro area total financial system assets
Euro area shadow banking assets
(Q1 1999 to Q3 2015; EUR trillions)
(Q1 1999 to Q3 2015; EUR trillions)
Credit institutions
80
MMFs
ICPFs
money market funds
non-money market investment funds
financial vehicle corporations
shadow banking sector for which no breakdown available
OFIs
70
September 2015
€ 26 trillion
60
25
IFs, OFIs (incl.
FVCs): 38%
50
20
40
ICPFs: 14%
30
MMFs: 1%
20
Credit
institutions: 47%
March 1999
€ 9 trillion
September 2007
€ 17 trillion
15
10
5
10
0
1999
March 2003
€ 10 trillion
2002
2005
2008
2011
0
1999
2014
2001
2003
Data availability
timeline
Sources: ECB and ECB calculations. See Doyle, Hermans, Molitor and Weistroffer
(2016), ECB Occasional paper forthcoming.
2005
2007
2009
Mar. 2006: Dec. 2008:
MMFs Other funds
2011
2013
2015
Dec. 2009:
FVCs
Sources: ECB and ECB calculations. See Doyle, Hermans, Molitor and Weistroffer
(2016), ECB Occasional paper forthcoming.
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Global
Rubric expansion of the shadow banking sector
FSB global OFI assets by region
2007: USD 67tr
other advanced
China 10%
other emerging
4%
FSB shadow banking assets by region
2010: USD 31tr
2014: USD 80tr
other advanced
11%
other emerging
5%
other advance
d 14%
1%
UK
10%
euro area
38%
US
37%
China
4%
US
32%
UK
12%
2014: USD 36tr
other emerging 6%
China 2%
Italy 1%
other advanced 12%
Italy 1%
Netherla
nds 2%
Germany 7% France 6%
Sources: FSB and ECB calculations. See Doyle, Hermans, Molitor and Weistroffer
(2016), ECB Occasional paper forthcoming.
Note: “OFIs” by the FSB definition include all financial institutions that are not classified
as banks, insurance companies, pension funds, public financial institutions, central
banks, or financial auxiliaries. According to FSB definitions, OFIs include money-market
funds, finance companies, structured finance vehicles, hedge funds, other funds, brokerdealers, real-estate investment trusts and funds, and additional sectors.
US 40%
China 8%
US 41%
Spain 1%
euro area
36%
other emerging 6%
Spain 1%
UK 13%
Ireland 7%
Netherlan
ds 2%
Germany 7%
France 4%
UK 11%
Ireland 8%
Sources: FSB and ECB calculations. See Doyle, Hermans, Molitor and Weistroffer
(2016), ECB Occasional paper forthcoming.
Note: The FSB shadow banking measure cannot be calculated for the euro area as a
whole as only six euro area jurisdictions participate in the data gathering exercise. These
six euro area countries represent 22.5% (USD 8.1tr) of global shadow banking assets,
covering the five FSB members France, Germany, Italy, the Netherlands and Spain, plus
Ireland.
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Heterogeneity
in the euro area financial system
Rubric
Total assets, liquidity mismatch and leverage
multiplier by type of fund
Balance sheet structure of different
business models (2014; ratios and shares in %)
(data as of Q4-2015)
6.0
Real estate
funds
€0.5 trillion
Shares issued to liquid assets
5.0
Bond funds
€3.2 trillion
4.0
MMFs
€1.1 trillion
3.0
Hedge funds
€0.3 trillion
Mixed funds
€2.8 trillion
2.0
1.0
0.0
Other funds
€0.7 trillion
Equity funds
€2.8 trillion
1.0
1.1
1.2
1.3
1.4
Leverage
Sources: Bankscope, Bloomberg, SNL and ECB calculations. See Franch and
Żochowski (2016), ECB mimeo.
Note: The chart shows the median of variables used for the identification of clusters for
each of the seven clusters identified for the year 2014.
Sources: ECB and ECB calculations. See Doyle, Hermans, Molitor and Weistroffer
(2016), ECB Occasional paper forthcoming.
Bubble size: total assets in EUR tr
x-axis: Leverage (total assets / shares and units issued)
y-axis: Liquidity mismatch (shares and units issued / liquid assets )
Note: Liquid assets include equity shares, EA government bonds, and other debt
securities with an original maturity smaller than 1 year.
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ARubric
model of heterogeneous “bankers”
•
“Bankers” types allocate capital to different investment strategies
(independent across time)
Core assumption: imperfect risk sharing across “bankers”
“bankers” maximise the log of their terminal wealth, i.e. the expected geometric mean
return
Evolutionary dynamics: only bankers with maximum expected geometric mean return
survive, but they differ w.r.t the variance of their investment strategy
All investment strategies are perfectly correlated with the aggregate shock
•
Optimal capital allocation implies constant capital shares across types
∗
The planner solves a static portfolio problem and delivers the maximum growth in the
aggregate capital stock
•
Conversely, the decentralised equilibrium displays pro-cyclicality and higher
volatility
“Boom-bust” feature of the model: successive good aggregate shocks reallocate capital
towards the riskier “bankers”, leaving the overall economy more exposed to adverse
shocks when they finally come.
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Transition
matrix across risk types
Rubric
•
Economic interpretation:
1. Idiosyncratic shocks to the set of investment opportunities of “bankers”
2. Changes in the set of financial institutions that are operative
3. Reallocations of funds by external investors
•
Optimal transition matrix is time-invariant and implements the optimal static
capital allocation ∗ .
Policy should lean against inefficient boom-bust dynamics
•
Symmetric and non-state dependent transition matrix.
Compared to the allocation without idiosyncratic shocks, a symmetric matrix brings some
improvements when the distribution of capital across types is “distant enough” from the
optimal one
•
State-dependent transition matrix: momentum versus contrarian.
1. Starting from
∗
, a contrarian matrix exists which preserves the optimal allocation.
2. For capital allocation “not extremely far from the optimal one”, contrarian reallocations
lower volatility
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Adding
Rubric a real economy block to the model
•
“Bankers” aggregate capital is rented out to producers
Cobb-Douglas production function out of capital and labour; producers operate under
perfect competition; their output serves consumption and future capital (which fully
depreciates)
•
Degenerated household sector
Households provide inelastic labour supply; do not have access to financial market; extract
some utility from log wage income
•
Optimal capital allocation still implies constant capital shares across types
∗
This is true whether the planner maximises “bankers”, workers or aggregate welfare.
•
In the decentralised equilibrium, aggregate capital dynamics is now bounded
but the allocation of capital across types is unchanged
Decreasing returns and perfect substitution across capital types in the production function
are key assumptions
•
The social planner achieves lower volatility and higher expected log levels for
capital, output and wages
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Policy
Rubric interventions
1. Policy measures restricting the set of available investment strategies of
bankers
1. Introducing a cap on the volatility of investment returns
2. Introducing a cap on the asset growth of risk types
Those measures mainly yield benefits from their dynamic effects on the
composition of the financial system
Leaning against the “boom-bust” features of the model
2. Bailout policies from workers to “bankers”
Scope for voluntary bailouts
Uniform lump-sum transfers may prove distortive even if bankers incentives are
unaffected
They interfere with the evolutionary selection dynamics
They may also go against the optimal capital allocation
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Discussion
points
Rubric
•
Who are actually the “Bankers”?
Productive capital or bank net worth: economic or financial risk-taking
Heterogeneity in the corporate sector or in the financial system
Types of heterogeneity in the financial system: shadow banking versus traditional banking?
Incomplete risk sharing within a monetary union?
•
How to model the spillovers to the real economy?
Which production function?
Non-monotonic link between risk taking and TFP; endogenous growth features
More sophisticated households: saving behaviour and portfolio decisions
•
How to interpret policy interventions?
Macroprudential policy
Monetary policy
Fiscal policy
How to combine the dynamic compositional
effects of this paper with more microfounded heterogeneity in bank strategies?
Financial services policy
Competition or industrial policy
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Shadow
and Traditional banking in general equilibrium
Rubric
A General Equilibrium model with endogenous fire-sales and bank-runs
exploring the systemic relevance of shadow banks*
• 3-period model with three assets: one ST liquid asset, two LT assets (safe and
risky)
• Two types of bank runs: news driven versus panic driven
• Two equilibrium banking strategies with relative size determined by a free entry
condition (in the spirit of Hanson et al (2014))
– Shadow banking (SB) with high leverage and greater risk-taking, subject to
news-driven bank runs
– Traditional banking (TB) build more conservative portfolios to avert news-driven
bank runs but remain exposed to panic (or self-fulfilling) runs
• SB and TB interactions in secondary markets for LT assets with the possibility of
fire sales
*See Ari, Darracq Pariès, Kok and Zochowski (2016) “Shadow Banking in General Equilibrium” ECB
working paper forthcoming
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Shadow
and Traditional banking in general equilibrium
Rubric
Model solutions after bad news revelations for different values of the shadow banking sector
size ∈ .
Optimal
shadow
banking
sector size
∗
∗
∗
∗
∗
*See Ari, Darracq Pariès, Kok and Zochowski (2016) “Shadow Banking in General Equilibrium” ECB working paper forthcoming
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Taxing
Rubric shadow banks
Model solutions after bad news revelations for different values of the shadow banking sector
size ∈ .
Optimal
shadow
banking
sector size
with tax
∗
∗
∗
∗
∗
*See Ari, Darracq Pariès, Kok and Zochowski (2016) “Shadow Banking in General Equilibrium” ECB working paper forthcoming
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Overview
Rubric
•
The paper intends to bring a new perspective on risk taking and financial
sector composition
Inspired from evolutionary economics
Focus on dynamic compositional effects
Complementary approach to more “static” risk-taking frictions related to fire sales, demand
externalities or bounded rationality
•
The insights from the paper could be applied to a variety of extensions
The paper may well open a full research programme
But some flagship applications should be conducted
•
Which policy lessons to draw from the paper?
The composition of the financial sector and its dynamic evolution should be monitored and
at times, counteracted
Difficult to earmark the paper findings to specific policy frameworks
14
www.ecb.europa.eu ©