2014.06.13 - naec edrc seminar - a macroprundential policy framework
DESCRIPTION
TRANSCRIPT
A MACROPRUDENTIAL POLICY FRAMEWORK
AMUND HOLMSEN, IDA WOLDEN BACHE AND
KARSTEN GERDRUP
OECD 13 JUNE 2014
Agenda
Background
Principles guiding Norges Bank’s advice on the CCB
Decision basis and indicators
Towards a new quantitative framework for setting the CCB
2
BACKGROUND
The Norwegian economy
Sources: Statistics Norway and Norges Bank
-2
1
4
7
-2
1
4
7
1995 1999 2003 2007 2011
GDP mainland Average
0
3
6
9
0
3
6
9
1995 1999 2003 2007 2011
Unemployment rate (ILO)
0
3
6
9
0
3
6
9
1995 1998 2001 2004 2007 2010 2013
Key policy rate
Introduction of
inflation target
-1
1
3
5
-1
1
3
5
1995 1998 2001 2004 2007 2010 2013
CPI (core)
Inflation target
4
Terms of trade
60
80
100
120
140
160
60
80
100
120
140
160
1978 1982 1986 1990 1994 1998 2002 2006 2010 2014
Index. Q1 2000 = 100. Q1 1978 – Q1 2014
5 Sources: Statistics Norway and Norges Bank
House prices Index. Q1 1995 = 100. Q1 1995 – Q1 2014
6
100
150
200
250
300
350
400
450
100
150
200
250
300
350
400
450
1995 1997 1999 2001 2003 2005 2007 2009 2011 2013
Norway Sweden
Denmark UK
Netherlands Spain
1) Denmark and Spain: up to and including Q4 2013
Source: Thomson Reuters
Policy actions
7
Stricter guidelines on prudent mortgage lending (2011)
Higher capital requirements incl. capital conservation buffer, systemic risk
buffer and SIFI buffer (2013-2016)
Higher risk-weights on mortgage lending (2014)
Countercyclical capital buffer activated (2015)
Preparations for new banking resolution regime
Monetary policy «leaning against the wind»
CET1 requirements Norwegian banks
4,5 4,5 4,5
2,5 2,5 2,5
3,0 3,0 3,0
1,0 2,0
0
2
4
6
8
10
12
14
16
0
2
4
6
8
10
12
14
16
31 Dec 2011 31 Dec 2012 31 Dec 2013 1 Jul 2014 1 Jul 2015 1 Jul 2016
Countercyclical buffer
Maximum countercyclical buffer
SIFI-buffer
Systemic Risk Buffer
Capital Conservation Buffer
Minimum requirement
1,0 1,0
Percent of risk weighted assets
8
Sources: Ministry of Finance and Norges Bank
Institutional set-up for CCB in Norway
Norges Bank prepares decision
basis and issues advice on the level
of the CCB
Information exchange with the
Norwegian FSA
Ministry of Finance sets the buffer
rate every quarter
9
Formulating a macroprudential policy
Clear objective
Explicit criteria and indicators for appropriate policy
Transparency about policy intentions
Credibility and accountability
10
Objective of CCB
“The purpose of the countercyclical capital buffer is to strengthen the financial
soundness of banks and their resilience to loan losses in a future downturn and
mitigate the risk that banks will amplify a downturn by reducing their lending.”
Regulation on the CCB (Section 1), 4 Oct 2013
11
Policy parallels
Clear objective
Transparency about – Principles/criteria for appropriate policy
– Key indicators
– Reaction pattern
12
Monetary policy Macroprudential policy
Objective Low and stable inflation Increase resilience of banks to losses in
future downturn and mitigate pro-cyclical
effects of tighter lending
Criteria 1. The inflation target is
achieved
2. The inflation targeting
regime is flexible
3. Monetary policy is robust
1. Banks should become more resilient
during an upturn
2. The size of the buffer should be
viewed in the light of other
requirements applying to banks
3. Stress in the financial system should
be alleviated
Key indicators Forecast of inflation and output • Credit/GDP
• House prices/disposable income
• Real commercial property prices
• Banks’ wholesale funding ratios
Transparency about
policy intentions
Interest rate forecast Explicit statement about reaction pattern
Communicating the reaction pattern
“If there are signs that financial imbalances continue to build up, Norges Bank will issue
advice to increase the buffer rate (…)”
“The CCB is not an instrument for fine-tuning the economy.”
“The buffer rate should not necessarily be reduced even if there are signs that financial
imbalances are receding. In long periods of low loan losses, rising asset prices and
credit growth, banks should normally hold a countercyclical capital buffer.”
“Any future advice to reduce the buffer rate will be based on an assessment of market
turbulence, loss prospects for the banking sector and the risk of a credit-driven downturn
in the Norwegian economy.”
Norges Bank’s letter to the Ministry of Finance March 2014
13
DECISION BASIS AND INDICATORS
Decision basis
“The decision basis shall contain an overview of the credit-to-GDP ratio and the
extent to which it deviates from the long-term trend, as well as other indicators,
and Norges Bank’s assessment of systemic risk that is building up or has built
up over time.” Regulation on the CCB (Section 3), 4 Oct 2013
15
Credit as a share of GDP Percent. 1976 Q1 – 2013 Q4
16 Sources: Statistics Norway and Norges Bank
75
100
125
150
175
200
75
100
125
150
175
200
1976 1984 1992 2000 2008
Crises Credit/GDP
Credit as a share of GDP Percent. 1976 Q1 – 2013 Q4
17 Sources: Statistics Norway and Norges Bank
75
100
125
150
175
200
75
100
125
150
175
200
1976 1984 1992 2000 2008
Crises
Credit/GDP
Augmented HP filter
One-sided HP filter
10-year rolling average
Credit/GDP – deviation from trend Percentage points.
18 Sources: Statistics Norway, IMF and Norges Bank
-30
-10
10
30
50
-30
-10
10
30
50
1983 1991 1999 2007
Variation
One-sided HP-trend
Augmented HP-trend
10 year moving average
Reference values for CCB in Norway Basel “bufferguide”. Per cent of risk weighted assets. 1983 Q1 – 2013 Q4
19 Sources: Statistics Norway, IMF, BIS and Norges Bank
0
0,5
1
1,5
2
2,5
3
3,5
0
0,5
1
1,5
2
2,5
3
3,5
1983 1987 1991 1995 1999 2003 2007 2011
Buffer based on deviation from the Basel Committee's recommended HP trend
Buffer based on deviation from alternative HP trend
20
50
100
150
200
50
100
150
200
1976 1984 1992 2000 2008
Key indicators for build-up of CCB
Real commercial property prices Banks’ wholesale funding ratio
Credit / GDP House prices / disposable income
50
100
150
200
50
100
150
200
1976 1984 1992 2000 2008
50
100
150
200
50
100
150
200
1976 1984 1992 2000 20080
20
40
60
0
20
40
60
1976 1984 1992 2000 2008
Historical average Level
Guided discrection
«Guided discretion»
– Weight on rules depends on reliability of indicators
– More weight on rules as analytical framework is improved?
More judgment needed in release phase?
21
Does it work? Banks’ lending margins on mortgages
18 Jul 2010 – 10 Jun 2014
Credit growth (y-o-y) enterprises
Jan 2008 – Apr 2014
-10
0
10
20
30
40
-10
0
10
20
30
40
2008 2010 2012 2014
Bank debt
Bond debt
22 Source: DNB Markets, Statistics Norway and Norges Bank
0
1
2
3
4
5
6
7
0
1
2
3
4
5
6
7
2010 2011 2012 2013
Risk premium 5-yr covered bond
3m NIBOR - key policy rate
Key policy rate
Residential mortgage rate
Estimated cost of mortgage financing
TOWARDS A NEW QUANTITATIVE
FRAMEWORK FOR THE CCB
Modeling approaches
Empirical cost-benefit analysis:
– Benefits: Smaller probability of systemic crisis and less severe crisis
– Costs: Less financial intermediation in «normal times»
Policy analysis in structural models:
– ESCB’s 3D model
– IMF’s MAPMOD
24
Logit model estimated on panel of 16 countries Q1 1970 – Q2 2013
25
0.1
.2.3
.4.5
.6.7
.8.9
1
1970q1 1980q1 1990q1 2000q1 2010q1Quarter
90% 70%
50% 30%
Norway
0.1
.2.3
.4.5
.6.7
.8.9
1
1970q1 1980q1 1990q1 2000q1 2010q1Quarter
90% 70%
50% 30%
USA0
.1.2
.3.4
.5.6
.7.8
.91
1970q1 1980q1 1990q1 2000q1 2010q1Quarter
90% 70%
50% 30%
UK
0.1
.2.3
.4.5
.6.7
.8.9
11970q1 1980q1 1990q1 2000q1 2010q1
Quarter
90% 70%
50% 30%
Spain
Estimated crisis probabilities
Marginal effects on crisis probability of
different indicators
Household Credit to GDP Gap
NFE Credit to GDP Gap
Wholesale Funding Gap
House Prices to Inc. Gap
Equity/Assets
Effe
cts
with
Res
pect
to
-4 -2 0 2 4Marginal Effect on Crisis Probability (pp)
A MACROPRUDENTIAL POLICY FRAMEWORK
AMUND HOLMSEN, IDA WOLDEN BACHE AND
KARSTEN GERDRUP
OECD 13 JUNE 2014
Logit model for estimating crisis probabilites
Panel of 16 industrialized countries 1970Q1 – 2013Q2 – Australia, Belgium, Canada, Finland, France, Germany, Italy, Japan, Korea,
Netherlands, Norway, Spain, Sweden, Switzerland, UK and USA
28 identified crises
Explanatory variables – Total credit to private non-financial sector, households and non-financial enterprises
– Nominal and real GDP
– House prices and disposable income
– Equity prices
– Inflation and interest rates
– Banking sector variables (leverage and market financing)
– Trade weighted global credit and house prices
28