This document discusses Norway's macroprudential policy framework and the setting of the countercyclical capital buffer (CCB). It outlines Norway's economic conditions, policy actions taken, and the institutional setup for the CCB. Key indicators for assessing financial imbalances are presented, including credit growth, house prices, commercial property prices, and banks' funding ratios. Models for estimating crisis probabilities and the impact of macroprudential policies are discussed. The goal is to develop a new quantitative framework for setting the CCB rate based on these analyses.
2. 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
6. 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
7. 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»
8. 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
9. 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
10. Formulating a macroprudential policy
Clear objective
Explicit criteria and indicators for appropriate policy
Transparency about policy intentions
Credibility and accountability
10
11. 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
12. 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
13. 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
15. 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
16. 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
17. 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
18. 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
19. Reference values for CCB in Norway
Basel “bufferguide”. Per cent of risk weighted assets. 1983 Q1 – 2013 Q4
19Sources: 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
21. 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
22. 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
22Source: 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
24. 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
26. 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
-4 -2 0 2 4
Marginal Effect on Crisis Probability (pp)
28. 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