Transcript How complete and how comparable are data on non

How complete and how
comparable are data on
non-financial corporates,
household sector balance sheets,
and housing markets
across countries?
Luci Ellis
Head of Financial Stability Department
Reserve Bank of Australia
Context
• Current crisis unusually triggered by
US household sector
– Arrears rates rose and prices fell sharply,
before macro slowdown or credit tightening
• Other financial/banking crises triggered by
excesses in nonfinancial corporates (CRE, LBO)
• But many observers pre-crisis thought US
households less vulnerable than those elsewhere
– What information didn’t they know, that could have
stopped them being led astray?
Encouraged FSIs in IMF Guide
• Nonfinancial corporations sector
–
–
–
–
–
Total debt to equity
Return on equity
Earnings to interest and principal expenses
Net foreign exchange exposure to equity
Number of applications for protection from creditors
• Households
– Household debt to GDP
– Household debt service and principal payments to
income
Source: IMF Financial Soundness Indicators Compilation Guide 2006.
General Principles for Constructing
Suitable Indicators
• Relevant:
provides an informative reading on
vulnerabilities and build-ups of imbalances
• Based on evidence:
grounded in both theory and empirical
evidence
• Risk-oriented:
focussed on tail risks and tails of
distributions, not just averages
Assessing the Size of Changes in
Macro-financial Indicators
• Macro ratios covered by existing SNA etc
– Financial accounts, income, business assets?
• But financial stability is about tail risks:
distribution matters (leverage, interest burden etc)
– Housing: LTVs etc
– Corporates: listed firms’ disclosures
– Limited international comparability: surveys,
different disclosure regimes, proprietary data
Measuring Housing Prices
• Stock versus transactions
– And inclusion of appraisals in transactions
• Quality adjustment
– Repeat-sales, hedonics, stratification
• Coverage of sample
– Cities, whole country, particular dwelling or
buyer type?
• Source of data
– Land titles records, lender, real estate agent
Assessing Extent of Vulnerabilities
• Aggregate ratios often used
– But these can lead us badly astray
– Don’t capture tail of distribution
– Ratios of aggregates are not ratio of average
House Prices and Household Debt
Percentage point change in ratios to household income*
(2000 to 2006)
% pts
% pts
 House prices
 Household debt
200
200
150
150
100
100
50
50
0
0
US
Canada
Spain
Australia
NZ
* Household income is after tax, before interest payments.
Sources: BIS; Standard & Poor’s; national sources
UK
Assessing Extent of Vulnerabilities
• Aggregate ratios often used
– But these can lead us badly astray
– Don’t capture tail of distribution
– Ratios of aggregates are not ratio of average
• Need theoretical and analytical grounding
– e.g. aggregate debt-income ratios not constant if
long-run average inflation or credit constraints change
• Institutions matter (eg penalties for default)
• Market segment matters (owners or landlords?)
• Measuring (sustainable) lending standards
Assessing the Extent of the
Damage
• How badly have things gone wrong?
• What implications for macroeconomy /
financial system?
• Different measures
– NPLs, impaired assets, arrears, foreclosures
– Model effect on consumption, investment,
financial sector’s loan losses, etc
Non-performing Housing Loans
Per cent of loans*
%
%
Spain
5
5
4
4
+
UK
3
3
US
2
1
0
2
1
Canada** +
Australia**
1993
1997
2001
2005
0
2009
* Per cent of loans by value. Includes ‘impaired’ loans unless otherwise stated.
For Australia, only includes loans 90+ days in arrears prior to September 2003.
** Banks only.
+ Per cent of loans by number that are 90+ days in arrears.
Sources: APRA; Bank of Spain; Canadian Bankers’ Association; Council of
Mortgage Lenders; FDIC
US Residential Mortgage Arrears
Per cent of outstandings
%
%
12
12
10
MBA: 30+ days or
in foreclosure
10
8
8
6
6
4
4
2
0
Federal Reserve:
30+ days
1981
1985
1989
2
1993
1997
2001
Sources: Federal Reserve; Mortgage Bankers Association
2005
0
2009
Concluding Remarks
• FSIs (or other rules of thumb) are not a
substitute for human analysis
• Macro indicators alone can lead us astray
• Institutional details matter
• Be aware of distribution across agents
• “Soft signals” might be informative
– Especially the existence of practices unique to
that country