How complete and how comparable are data on non-financial corporates, household sector balance...
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Transcript of How complete and how comparable are data on non-financial corporates, household sector balance...
How complete and how comparable are data on non-financial corporates,
household sector balance sheets, and housing markets
across countries?
Luci EllisHead 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
US Canada Spain Australia NZ UK
0
50
100
150
200
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50
100
150
200
House Prices and Household DebtPercentage point change in ratios to household income*
(2000 to 2006)
* Household income is after tax, before interest payments.Sources: BIS; Standard & Poor’s; national sources
House prices Household debt
% pts % pts
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
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1
2
3
4
5
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1
2
3
4
5
Non-performing Housing LoansPer cent of loans*
* 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
2009
US
% %
200520011997
Australia**
UK
Spain
Canada**
1993
+
+
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2
4
6
8
10
12
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2
4
6
8
10
12
US Residential Mortgage ArrearsPer cent of outstandings
Sources: Federal Reserve; Mortgage Bankers Association
2009
MBA: 30+ days orin foreclosure
%
Federal Reserve:30+ days
%
2005200119971993198919851981
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