Presentation on theme: "Teresa Sbano and Michèle Chavoix-Mannato Towards longer national account data time series Joint project of the OECD Pioneer Investments and UniCredit."— Presentation transcript:
Teresa Sbano and Michèle Chavoix-Mannato Towards longer national account data time series Joint project of the OECD Pioneer Investments and UniCredit
Page 2 Introduction The OECD, jointly with the Economic research Unit of Pioneer Global Asset Management and UniCredit, is working on a project that aims at extending back the currently available time series of the Financial Accounts for a group of OECD countries. This is relevant especially for the following reason: –the introduction of the new method of classification based on the SNA-93 during the 1990s has made it necessary to reconcile past data with the new series, –in order to produce as much as possible consistent time series covering a reasonably long time horizon, –to be used both for studying the changes in the allocation of wealth over time and for comparing the main trends across different countries
Page 3 Opportunities arising from the analysis of longer time series: Longer time series give the opportunity to better analyse many relevant issues such as: –The evolution of the financial structures over the time –The evolution in the liabilities side of non-financial corporations –Correlations between economic cycles and financial cycles –Convergence in the financial structures between European countries, Japan, US and Canada –Measures of wealth effects –Models on the demand of financial assets –Measures of the degree of openness of the different financial markets –The evolution and relative importance of financial institutions
Page 4 Summary: available national account data ITALYfrom 1950 to 2004Bank of Italy US from 1950 to 2004Federal reserve CANADAfrom 1960 to 2004OECD. stat GERMANY from 1970 to 2004 OECD.stat/ golden book SPAINfrom 1980 to 2004OECD.stat/ golden book FRANCEfrom 1980 to 2004 OECD.stat JAPANfrom 1980 to 2004OECD.stat UK from 1987 to 2004OECD.stat Country PeriodSources
Page 5 Households- and non financial corporation - two of the five institutional sectors Households and non- profit organization serving households Non-Financial Corporations Rest of the world General Government Financial Corporations Total economy + Rest of the world
Page 6 From the golden book to the SNA 93 The main changes within SNA 93 refer to the definition of institutional sectors and the classification and method of valuation of financial instruments SNA 93 Golden Book
Page 7 Conversion table : In order to merge data from the two sources, we have constructed the following conversion table, which allows us to obtain a good degree of correspondence both over time and across the majority of the countries analysed:
Page 8 Reasons for the discrepancies between the two sources : Classification of institutional sectors and financial instruments –Changes in the definitions of Household and non financial enterprises –A more detailed breakdown in the SNA 93 classification –A changes in the definition of instruments Financial instrument should undergo a market valuation –ESA 95 methodology establishes that the valuation of financial balance sheets of stocks of financial assets and liabilities shall be at market price. The items most affected by this type of valuation are shares and the other equity and to a lesser extent the item securities other than shares. The application of this valuation rule is problematic for the instruments where valuation cannot be directly calculated
Page 9 JAPAN - From 1980 to 2005 OECD.stat CANADA From 1960 to 1997 Golden Book From1970 To 2005 OECD.stat US - From 1950 to 2005 Federal reserve Work on harmonization also by the Bank of Japan The Bank of Japan has begun releasing the retrospective data for the Flow of Funds Accounts (based on SNA93): from fiscal year 1980 to 1989, and stock data from end of fiscal year 1979 to end of fiscal year 1988. The Federal reserve has been producing the series since 1950 The Federal Reserve makes some adjustments in order to harmonize its data with the OECD format Also from Statistics Canada we have data consistent with SNA93. From Statistics Canada we have data consistent with SNA93 starting from 1970. Looking at the relevant 1969-70 period for series continuity: for non-financial corporations, the data line up fairly well, with the only significant gap being a re-allocation of sub-instruments between F5 and F7; for households, the data also line up fairly well, with the major difference being a historical revision affecting government unfunded pension schemes. We can use directly the data published by the central banks
Page 10 We can use directly the data published by the central banks FRANCE - From 1980 to 2005 OECD.stat AUSTRIA - From1995 To 2005 OECD.stat UK – From 1987 to 2005 OECD.stat ITALY - From 1950 to 2005 Bank of italy In the Golden Book the Austrian data are not available. The Bank of Austria is working on a longer time series (from 1989) and the dataset will be ready for the end of the year We have data from 1980 in the OECD dataset, but historical data are not yet definitive Banque de France is working on the construction of a more consistent data set The Bank of Italy Research Department has already produced series since 1950 Regarding stocks data (assets and liabilities) for all the institutional sectors and for the main financial instruments In the Golden Book the Uk data are available from 1987 to 1997. However, information on balance sheet figures by sector exists in the annual national accounts publications and it is available from 1975 to 1986. In order to use this longer time series we need to harmonize them
Page 11 Germany analysis GERMANY – From 1970 To 2005 Golden book data set - From 1970 to 1997 And OECD.stat - From 1991 to 2005 Starting from 1990 data refer to all Germany previous figures pertain to western Germany alone The most important difference from the SNA lies in the delimitation of the sectors "Non-financial enterprises" and "Households". In the SNA, the sector "Non-financial enterprises" is confined to corporate and "quasi-corporate" enterprises, whereas all other enterprises (small- and medium-sized proprietorships, self-employed persons, farmers, publicly-owned undertakings) are included among households or public authorities, as the case may be. In the capital finance account of the Deutsche Bundesbank, the enterprise sector is much more comprehensive and includes enterprises of all legal forms (sector g, "Producing enterprises"). A separate sector includes private and public housing activities (sector h2, "Housing"). The heading "Households" virtually covers only the sphere of private consumption and saving, but includes saving by self-employed persons only insofar as it does not represent the net retained income of enterprises.
Page 12 Germany – Sector S14-S15 Important discrepancy in the liabilities side of the Household sector. After including the housing sector in the Sector S14-S15 we filled the gap between the two datasets
Page 13 GERMANY Sector S11 Sector S14-S15
Page 14 Household financial assets as a percentage of GDP household wealth as a percentage of GDP presented an upward trend in all countries analysed. The total financial asset in % of GDP appears to have increased moderately during the period 1980 to 1990. First signs of an important growth are evident starting from 1995 mainly in UK and US. Rankings are apparently relatively stable, but volatilities different, possibly because of different asset composition. Source: PGAM estimation on Central Bank data
Page 15 Liabilities of private sector: Households Household liabilities relative to GDP seem to highlight differing trends. In the Euro-zone the data shows a moderate increase during the period under review, with the only exception of Spain which has had an important growth during the last 8 years. In US and UK we witnessed an impressive growth of household liabilities in the last 5 years Source: PGAM estimation on Central Bank data
Page 16 Liabilities of private sector: Non-Financial corporations Source: PGAM estimation on Central Bank data It would appear that for Non-financial Corporations the percentage of liabilities in relation to the GDP in the countries under analysis has increased steadily between 1995 and 2000 with the only exception of Canada and UK and Japan. The levels seem structurally different across countries.
Page 17 A dynamic financial structure in all the macro areas with the only exception of Japan Source: PGAM estimation on Central Bank data It would appear that we are witnessing: A sensible increase of the share of Insurance and pension funds (AF61). Stability in the role of shares and other equity (AF5) At a more detailed level, the indirect participation on the financial market through mutual fund and retirement product in the last 10 years appears to have increased significantly An impressive decrease of safe assets (currency and deposits – AF2) with a noticeable switch towards more risk oriented products and long term instruments Structural differences in relative holdings of risky assets
Page 18 Strong disparities across countries, each of them shows a specific profile Despite the common trend (Securitization and long term investing), Europe appears still a quite heterogeneous region Spain, Germany and France are characterised by the importance of banking deposits UK presents a high level of long term investment (Life insurance and Pension) Italians stand out because of the importance of fixed income securities In Italy and Spain the share of insurance technical reserves and pension funds still remains well below average Source: PGAM estimation on Central Bank data
Page 19 Conclusions The aim of this project is to fill a gap in the Financial Accounts time series in order to help both practitioners and academics to better understand current trends. I would like to express on behalf of the Steering Committee and the research team our warmest thanks to those who have helped us so far. We have been encouraged by the first responses to our work and hope to be able to construct in a reasonable amount of time a more complete and as far as possible reliable dataset.