1 Some implications of the crises for indicators on non-financial corporations and households Paul Schreyer OECD Statistics Directorate

2 Contents Features of the crises and a framework for monitoring Statistical implications in specific domains Balance sheets, asset prices and sector accounts Distributional contents

3 Features of the crises and a framework for monitoring Focal point of the crisis has been the financial sector, in particular the “shadow” banking sector The crisis also reflected the existence of an over- stretched household sector, which had accumulated high amounts of debt, especially mortgages. Much of this debt build-up was based on expectations of ever-increasing housing prices. All sectors are affected by the crises and there are financial, real economy, social and long-term sustainability effects This can be brought together in a framework

4 Framework: crises area and sectors

5 Features of the crises and a framework for monitoring Monitoring the way out of the crises requires keeping an eye on all these sectors and components, not only on the financial sector and/or financial asptects of other sectors The following statistical areas would seem of particular importance for this purpose

6 Statistical implications (1): Sector accounts, balance sheets and asset prices Potentially large differences in sectoral effects Desirable: quarterly sector accounts Quarterly data on financial and non-financial accounts by sector are still missing or patchy for many countries Many OECD countries have annual data by sector, but even there, the sequence of accounts is often incomplete  develop sectoral quarterly data with a pragmatic level of detail but as good a coverage of the whole sequence of accounts as possible

7 Statistical implications (1): Sector accounts, balance sheets and asset prices Example: work by Eurostat/ECB Quarterly sector accounts quite timely (as of early July 09, Q4 08 data are available) integrated financial and non-financial data on stocks and flows presentation in tables and with a set of graphs for zones only Example of indicator

8 Statistical implications (1): Balance sheets, asset prices and sector accounts

9 Statistical implications (1): Balance sheets Data availability: Annual data: reasonable coverage of sectoral balance sheets Part of the Eurostat/OECD transmission programme Differences in asset coverage and sector coverage Most widely covered asset type: dwellings Visible progress in the recent past Quarterly data: very scarce

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12 Statistical implications (1): Sector accounts, balance sheets and asset prices However, data comparability largely unknown In particular, statistical bases for dwellings stocks are likely to vary considerably between countries Well-known problems: measurement of depreciation and maintenance Needed: reliable physical measures of stocks of dwellings, including their characteristics Prices that reflect characteristics in space and over time  link to CPI and consumption

13 Statistical implications (2): Household income and its distribution Average measures less meaningful than in the past Need to be complemented by measures with distributional content Monitoring trends in poverty and income inequality is an important element for policy makers to guide action exiting the crises Equally important for the assessment of living standards: distribution of household wealth and household consumption Requires matching of micro- and macro-economic data

14 Example: household income and its distribution: INSEE study that breaks HH accounts down by type of household Savings ratio increases with disposable income Source: INSEE (2009)

15 Conclusions 1.There are considerable gaps in quarterly sectoral data. Special efforts should be devoted to developing quarterly accounts for main sectors 2.Sectoral balance sheet data is increasingly becoming available at least in OECD countries. Most data is annually, however. 3.A key ingredient for good information about household wealth is data on the stocks of dwellings and the associated price levels and their changes over time. Data exists, but the degree of its international comparability is unknown.

16 Conclusions 3.Average measures of income and wealth need to be complemented by distributional information. This requires linking national accounts concepts with micro-economic concepts of income and wealth and merging macro- and micro-data sets.

17 Thank you !