Statistisches Bundesamt German experiences in estimating households’ non-financial assets OECD Working Party on National Accounts and Financial Statistics Paris, 2-5 October 2007 Presented by Oda Schmalwasser and Marc Peter Radke Federal Statistical Office oda.schmalwasser@destatis.de Deutsche Bundesbank marc-peter.radke@bundesbank.de © Statistisches Bundesamt, Federal Statistical Office of Germany, National Accounts Statistisches Bundesamt Content 1. Introduction 2. Compilation of households’ fixed assets by the Federal Statistical Office 3. Estimation of households’ stock of land underlying buildings and structures by the Deutsche Bundesbank 4. Example of use: Compilation of integrated financial and non-financial household sector balance sheets 5. Conclusion © Statistisches Bundesamt, Federal Statistical Office of Germany, National Accounts Statistisches Bundesamt 1. Introduction Availability of data on households’ non-financial assets Code Non-financial assets (AN) Availability of data AN.1 Produced assets Partly available AN.11 Fixed assets Available, see section 2 AN.12 Inventories Not available AN.13 Valuables Not available AN.2 Non-produced assets Partly available AN.211 Land Partly available AN.2111 Land underlying buildings and structures Available, see section 3 AN.212..4 Other tangible non-produced assets Not available AN.22 Intangible non-produced assets Not available © Statistisches Bundesamt, Federal Statistical Office of Germany, National Accounts Statistisches Bundesamt 2. Compilation of fixed assets Sector S.11 Assets AN 1.1… 1 1 2 AN 1,1,1 . . . . Industries (A60) . 2 ... an ... ... AN 1,an,1 ... . AN Sector S.12 AN 1,AN,1 . Fixed assets. . . AN 1.1 Sector s . . Sector S a AN a,1,1 . . . . . . . . . . . . ... 60 AN 60,1,1 ... AN a,an,1 AN 60,an,1 ... ... AN a,AN,1 AN 60,AN,1 60 © Statistisches Bundesamt, Federal Statistical Office of Germany, National Accounts AN a,an,s AN a,an,S Statistisches Bundesamt 2. Compilation of households’ fixed assets (2) Traditional German non-financial enterprises: S.11+S.14 Dwellings by sector available Basis for the further breakdown: PIM information in a cross classification of other buildings and structures (including major improvements on land and costs of ownership transfer on land) machinery and equipment intangible assets for S.1 – S.12 – S.13 – S.15 = (S.11 + S.14) by 60 industries (A60 of ESA 95) © Statistisches Bundesamt, Federal Statistical Office of Germany, National Accounts Statistisches Bundesamt 2. Households’ fixed assets (3) Net stock at current replacement costs Code Fixed assets by category 2005 2005 EUR bn % in S.1 AN.11 Fixed assets 3244 47.3 AN.111 Tangible fixed assets 3233 47.6 2948 86.0 AN.1112 Other buildings and structures 181 7.5 AN.1113 Machinery and equipment 100 10.6 4 60.0 12 18.9 AN.1111 Dwellings AN.1114 Cultivated assets AN.112 Intangible fixed assets © Statistisches Bundesamt, Federal Statistical Office of Germany, National Accounts 3. Estimation of households’ stock of land underlying buildings and structures 3.1 • Background information Characteristics of the “old” approach to the estimation of land underlying buildings and structures by the Bundesbank 1. Approach was inextricably linked with the estimation of fixed assets 2. Approach was based on an updating procedure of former estimates of fixed assets by Destatis under ESA 1979 and former land estimates by the German Institute for Economic Research (DIW) and the Deutsche Bundesbank • Introduction of Destatis’ sectoral compilation of fixed assets required a “new” approach to the estimation of land underlying buildings and structures 8 3.2 Data requirements Aim of the estimation procedure was to compile • • Market value and real stock of land underlying buildings and structures (AN.2111) for households including non-profit institutions serving households (S.14+S.15) for the period from 1991 to 2006 Breakdown of the results into 1. part of land (AN.2111) underlying dwellings (AN.1111) 2. part of land (AN.2111) underlying other buildings and structures (AN.1112) 9 3.3 Data sources 1. Statistics on purchase values of building land published by Destatis • • • • Transactions: sales volumes of building land (in sq.km) from 1964 up to 2007 (annual data) Transaction/market prices (in €/sqm) Breakdown by building areas (business area, mixed business and residential area, residential area, industrial area, village area) No breakdown by sector and no breakdown into land underlying dwellings and land underlying other buildings and structures according to ESA 1995 2. Statistics on the area of land classified by actual uses published by Destatis • • • Breakdown of the whole economy’s stock of land by kinds-of-use (in sq.km) (quadrennial data: 1992, 1996, 2000, 2004) Definition of item “areas and open areas underlying buildings” corresponds to land underlying buildings and structures (AN.2111) according to ESA 1995. No breakdown into land underlying dwellings and land underlying other buildings and structures according to ESA 1995; no information on land (market) prices 10 3.4 Estimation procedure Step 1: Stock-flow calculation of land underlying buildings and structures at the total economy level (S.1) and breakdown by building areas (business area, mixed business and residential area, residential area, industrial area, village area) from 1991 to 2006 Step 2: Breakdown of the stock-flow calculation into land underlying dwellings and land underlying other buildings and structures at the total economy level (S.1) Step 3: Breakdown of land underlying dwellings and land underlying other buildings and structures by institutional sector 11 3.5 Results (1) Net stock of fixed assets including land underlying buildings and structures of the household sector including non-profit institutions serving households (S.14 + S.15) Other fixed assets (AN.1113+AN.1114+AN.112) 6000.00 € billion 5000.00 4000.00 Land underlying other buildings and structures (part of AN.2111 underlying AN.1112) 3000.00 Other buildings and structures (AN.1112) 2000.00 Land underlying dw ellings (part of AN.2111 underlying AN.1111) 1000.00 0.00 19 91 19 92 19 93 19 94 19 95 19 96 19 97 19 98 19 99 20 00 20 01 20 02 20 03 20 04 20 05 20 06 Dw ellings (AN.1111) Year Notes: Net stock of fixed assets is valued at replacement costs; land underlying buildings and structures is valued at market prices. 12 3.5 Results (2) Shares in net stock of fixed assets including land underlying buildings and structures of households including non-profit institutions serving households (S.14 + S.15) (shares at the beginning of the year) Dw ellings (AN.1111) shares in net stock of fixed assets including land underlying buildings and structures 1.000 0.900 Land underlying dw ellings (part of AN.2111 underlying AN.1111) 0.800 0.700 Other buildings and structures (AN.1112) 0.600 0.500 Land underlying other buildings and structures (part of AN.2111 underlying AN.1112) 0.400 0.300 Other fixed assets (AN.1113+AN.1114+AN.112) 0.200 Households' housing w ealth (dw ellings + land underlying dw ellings) 0.100 0.000 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 Year Notes: Net stock of fixed assets is valued at replacement costs; land underlying buildings and structures is valued at market prices. 13 3.6 Assessment • Estimation approach led to considerable improvements in data quality • But results have to interpreted with due care because 1. sectoral breakdown is based on assumptions (no sectoral data available) 2. estimates can be only considered as a lower limit of the “true“ market value (no information on market values of land which is already built-up) 14 4. Example of use: Compilation of integrated financial and non-financial household sector balance sheets 15 4.1 Compilation procedure • Compilation of balance sheets for households including non-profit institutions serving households (S.14+S.15) from 1992 to 2006 • Data sources and compilation: 1. Net stock of fixed assets (AN.11) from Destatis 2. Land underlying buildings and structures (AN.2111) from Bundesbank 3. Financial assets and liabilities (AF) from Bundesbank (financial accounts) 4. Net worth (B.90) compiled as residual 16 4.2 Results (1) Balance sheet of households and non-profit institutions serving households (S.14+S.15) (stocks at the beginning of the year) 10000.00 Liabilities (AF=AF.4+AF.7) € billion 8000.00 6000.00 Financial assets (AF=AF.2+AF.3+AF.4+AF.5+AF. 6+AF.7) 4000.00 Land underlying buildings and structures (AN.2111) 2000.00 Fixed Assets (AN.11) 0.00 Net Worth (B.90) -2000.00 19 92 19 93 19 94 19 95 19 96 19 97 19 98 19 99 20 00 20 01 20 02 20 03 20 04 20 05 20 06 -4000.00 Year Notes: Net stock of fixed assets is valued at replacement costs; land underlying buildings and structures is valued at market prices. Financial assets and liabilities are predominantly valued at market prices. 17 4.2 Results (2) Net w orth structure of households including non-profit institutions serving households (S.14+S.15) (stocks at the beginning of the year) 8000.00 7000.00 6000.00 Net financial assets (BF.90) € billion 5000.00 4000.00 Non-financial assets (AN.11+AN.2111) 3000.00 Net Worth (B.90) 2000.00 1000.00 19 92 19 93 19 94 19 95 19 96 19 97 19 98 19 99 20 00 20 01 20 02 20 03 20 04 20 05 20 06 0.00 Year Notes: Net stock of fixed assets is valued at replacement costs; land underlying buildings and structures is valued at market prices. Financial assets and liabilities are predominantly valued at market prices. 18 4.3 International Comparison International comparison of households' net worth in per cent of nominal disposible income (stock of net worth at the beginning of the year; nominal disposable income at the end of previous year) Canada 1000 France 900 800 Italy 700 Japan % 600 500 United Kingdom 400 300 United States 200 Germany (w ithout consumer durables) 100 0 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 Germany (including consumer durables) Year Source (except data for Germany): OECD, Economic Outlook, Vol. 2007/1, No. 81, June, Annex Table 58: Household wealth and indebtedness, p. 298. Notes: For Canada, Italy and the United States, data also include consumer durables. For Canada, Germany, France, Japan, the United Kingdom and the United States, data also include non-residential buildings and fixed assets of unincorporated enterprises and of non-profit institutions serving households, although coverage and valuation method may differ. 19 5. Conclusion • Data quality and data availability regarding non-financial assets and respecting household sector balance sheets have been improved considerably by the latest work of Destatis and the Bundesbank • Potential fields of improvement: 1. Regarding data availability: for example, collection of data on nonfinancial assets which have not yet been covered by the current compilation approach 2. Regarding data quality: for example, development of reliable valuation methods for land taking into account regional differences 20