Wealth Statistics for Australia Recent Developments






  1. National and sectoral balance sheets have been included in the Australian System of National Accounts (ASNA) on a current price basis for some time. The national balance sheet provides a breakdown of Australia's assets and liabilities; and sectoral balance sheets tell a similar story for sectors such as general government, financial and non-financial corporations and households.
  2. Recently, the Australian Bureau of Statistics (ABS) has been developing two new types of wealth statistics:

•a real/volume national balance sheet that excludes the effects of price change; and

•a dissection of the current price household balance sheet by household type.

A Real/Volume National Balance Sheet

  1. A real/volume balance sheet for Australia was included for the first time in the March quarter 2001 edition of Australian National Accounts: National Income Expenditure and Product (Cat. no. 5206.0). These data allow comparison of Australia's aggregate wealth over time, excluding the effects of price changes. Real national net worth has been derived by aggregating the chain volume estimates of the non-financial assets with the real estimates of financial assets less liabilities.

Volume indexes

  1. The ABS currently calculates the volume measure of an aggregate as a chain Laspeyres index referenced to the current price value of the aggregate in the latest base year. For the estimates presented here, this is the Australian financial year 1998-99. As a consequence, the estimates are additive for 1998-99 and 1999-2000, but not for earlier years.
  2. Volume estimates for the major categories of fixed asset stocks described as 'produced assets' -such as dwellings, other buildings and structures and machinery and equipment- have been available for many years in the Australian national accounts. However, volume estimates for stocks of non-produced, non-financial assets (land and other natural resources, etc.) and real estimates of financial assets, liabilities and net worth (wealth) have not been available previously. The calculation of volume and real estimates for some of these components are subject to some practical and conceptual difficulties. Thus these estimates are described as 'experimental'.
  3. Volume indexes for produced assets. Chain volume estimates for produced assets (including dwellings, equipment and plantation standing timber) can be derived fairly readily from the volume, price and value underlie the current price estimates.
  4. Volume indexes for non-produced assets. Chain volume estimates for subsoil assets and native standing timber can also be derived readily from the existing systems used to produce the current price estimates (explicit price and volume information underlie the current price value estimates in the balance sheet). As current price estimates are derived as the present value of the expected future income stream (resource rents), volume estimates are derived by valuing the physical volumes in each period using the resource rents and interest rates which apply in a base period.
  5. Deriving chain volume estimates of land raises a number of important issues. Can the volume of land change over time, or is change in its value wholly due to price change? The land area of a nation does not change very much, if at all, in the normal course of events. However, as volume change is also defined to include changes in quality, it seems clear that the volume of land can change due to natural processes, soil conservation and other land improvement measures, and by land degradation due to human activity. Urban land is more economically valuable than rural land because of the higher utility provided to urban dwellers. As urban boundaries expand and land is rezoned for urban use, it can therefore be argued that the volume of the resource changes because it is now available for higher value uses. Location is critical in determining the quality, and hence the volume, of land. For this reason land in a central business district can be said to be of a higher quality than land in the suburbs of a city. The experimental balance sheet is consistent with the concept that land volumes do change over time. However, the practical task of splitting value changes into their price and volume components is a difficult one. As an interim approach the ABS has calculated the growth in volume of urban land at half the rate of growth in the volume of overlying construction. Zero volume growth is assumed for rural land. This assumes that land degradation, reclassification and land improvement net to zero.

Real estimates

  1. Unlike their non-financial counterparts discussed above, financial assets and liabilities cannot be decomposed into prices and volumes, and so it is impossible to derive volume indexes for them. However, it is possible to deflate income flows, financial assets and liabilities by a general price index in order to measure the purchasing power of the aggregate in question over a designated numeraire set of goods and services. Such measures are called 'real' estimates. SNA93, when discussing the deflation of income and transfer flows received from and paid to abroad, recommends that the purchasing power of these flows be expressed in terms of a broad based numeraire, namely the goods and services that make up domestic final demand. Consistent with this, the domestic final demand chain price index has been used as the deflator for financial assets and liabilities with the rest of the world.

Key results

  1. Attachment 1 shows a table of the real/volume national balance sheet for most of the 1990s. Among the major features are the following:

•Australia's real net worth (total assets less total liabilities to the rest of the world) grew by 12.7% between 30 June 1992 and 30 June 2000, compared with an increase of 49.5% in current prices. This represents a real average annual growth rate of 1.5%.

•Total assets, in real terms, grew by 25.8% during this period, driven mainly by increased volumes of dwellings (32%), machinery and equipment (28.8%), subsoil assets (49.5%), and real total financial assets with the rest of the world (120.3%). Real financial liabilities to the rest of the world increased by 94.8% between 30 June 1992 and 30 June 2000.

Future work

  1. The ABS plans to publish both current and real/volume balance sheets in future editions of the annual Australian System of National Accounts (Cat. no. 5204.0). There is also a program of research underway to further develop the balance sheet and to use it to derive alternative measures of income and saving to that used in the conventional national accounts.

Distribution of Household Wealth

  1. The household balance sheet provides a picture of wealth composition and changes for the household sector as a whole, however, it does not provide data on the distribution of wealth between households, or how this changes over time. The second development underway is the construction of experimental estimates of the distribution of wealth between Australian households. This work seeks to bring together aggregates from the ASNA household balance sheet, and distributional data from household surveys and other data sources, to allow dissection of balance sheet assets and liabilities by household characteristics.
  2. This project starts from the aggregate household balance sheet in the ASNA, which provides a breakdown of assets and liabilities. Some additional breakdowns will be developed. For example, the ‘Dwellings’ item of the balance sheet has been further dissected into owner-occupied dwellings and investment properties. The project also seeks to develop estimates of consumer durables.

Broad approach

  1. The Survey of Income and Housing Costs (SIHC) and the Household Expenditure Survey (HES) are being used to build the distributional aspects of the data set, i.e. to determine which types of households own which types of assets and liabilities. The aim is to determine breakdowns of wealth by variables such as stage of life cycle (incorporating information on the ages of the reference person and children), broad geographic region and level of income. The SIHC and HES are the best basis for this type of work, as, for any given year, they contain the largest number of relevant data items in one unit record file. Data from other surveys and administrative sources are then used to provide information on components which are not included in the SIHC or HES questionnaires, and to refine estimates where information was collected in the surveys
  2. A number of problems arise when compiling estimates for items which are not surveyed. In the some cases, a model can be used to assign synthetic asset or liability values to particular units, based on other variables which have been observed in existing surveys or other data sources. However, this relies on the existence of both a fairly rich source of data, and an appropriate model which explains most of the natural variation within the data. In some cases, such a data set or model will not exist, and in these cases the approach will be to apply average asset or liability values to all members of a particular class of income units. The synthetic values may not be robust at the individual level, as there will generally be deviations from the average. However, when these estimates are benchmarked, group by group, to an existing distribution from another source, the cross-tabulations which are produced will give the correct group totals. In this way, the data will support distributional analysis at a group, rather than at an income unit, level.
  3. The final step in the estimation process is to adjust the aggregates derived from the survey data to equal the aggregate figures in the household balance sheet. The scope and coverage of the household balance sheet and a household survey such as the SIHC or HES are not identical, as they have been developed to serve different purposes. However, it is possible to make adjustments to allow for these differences.

Preliminary results

  1. Attachment 2 shows some preliminary distributions of household wealth for the year 1997-98.

Progress so far and future work

  1. Attention is now focussed on the development of a time series of estimates for the years between 1993–94 and 1999–2000, using the methodology outlined in this paper. The exact length of the time series (and the detail with which estimates can be prepared in different periods) is yet to be determined. Experimental estimates have so far been compiled for 1997-98; the compilation of estimates for the other years will no doubt lead to further revisions to our methods. Distributional data for superannuation and consumer durables will also be incorporated into the data set as it nears completion.
  2. The results of this study will be published in early 2002. In the future, estimates of household wealth dissected by type of household and other characteristics may be compiled on an ongoing basis, using the types of methodology outlined in this paper.

For More Information

  1. More details of this work can be obtained from or

Issues for Discussion

1)What is the experience of other countries with compiling real/volume national balance sheets?

2)What is the experience of other countries with synthetic or model-based approaches to dissecting the household balance sheet by household type?



Attachment 1

Australian National Balance Sheet, Real/Volume estimates (a) - as at 30 June of each year

($A billion : 1998-99 dollars)

1992 / 1993 / 1994 / 1995 / 1996 / 1997 / 1998 / 1999 / 2000
Total assets / 2 326.1 / 2 381.5 / 2 432.4 / 2 510.9 / 2 560.5 / 2 643.2 / 2 744.7 / 2 824.4 / 2 925.8
Non-financial assets / 2 195.6 / 2 235.4 / 2 278.3 / 2 326.3 / 2 370.7 / 2 421.4 / 2 484.1 / 2 555.3 / 2 627.2
Produced assets / 1 367.6 / 1 395.6 / 1 424.9 / 1 459.5 / 1 491.0 / 1 529.8 / 1 577.4 / 1 633.4 / 1 691.7
Fixed assets / 1 288.1 / 1 315.4 / 1 343.5 / 1 377.5 / 1 410.8 / 1 450.1 / 1 497.5 / 1 549.6 / 1 603.4
Dwellings / 421.2 / 435.4 / 451.5 / 468.7 / 482.7 / 496.6 / 513.8 / 533.0 / 555.9
Other buildings and structures / 584.7 / 592.2 / 600.0 / 609.3 / 621.0 / 635.4 / 649.6 / 666.2 / 679.0
Machinery and equipment / 254.6 / 256.6 / 259.5 / 269.4 / 279.1 / 290.4 / 304.0 / 315.4 / 327.9
Livestock - fixed assets / 31.1 / 33.9 / 32.4 / 24.3 / 19.4 / 16.6 / 16.6 / 17.7 / 18.4
Computer software / 5.4 / 6.7 / 7.9 / 8.9 / 9.8 / 11.2 / 13.3 / 16.7 / 21.5
Entertainment, literary and artistic originals / 0.4 / 0.4 / 0.4 / 0.4 / 0.4 / 0.5 / 0.5 / 0.5 / 0.5
Inventories / 94.4 / 95.5 / 97.0 / 98.0 / 96.5 / 96.6 / 97.4 / 101.9 / 107.0
Private non-farm inventories (b) / 66.5 / 68.1 / 69.5 / 72.2 / 71.9 / 73.8 / 74.6 / 79.0 / 84.1
Farm inventories / 6.0 / 5.7 / 6.1 / 6.4 / 6.4 / 6.3 / 6.6 / 6.4 / 6.5
Public authorities inventories (c) / 6.9 / 6.5 / 6.6 / 6.8 / 6.2 / 3.9 / 3.4 / 3.7 / 3.6
Livestock - inventories / 14.1 / 13.0 / 12.0 / 8.6 / 6.4 / 5.4 / 5.1 / 5.2 / 5.2
Plantation standing timber / 6.2 / 6.7 / 6.8 / 6.3 / 6.7 / 7.3 / 7.8 / 7.6 / 7.6
Non-produced assets (d) / 833.0 / 843.7 / 856.7 / 869.3 / 882.0 / 892.6 / 906.9 / 922.0 / 935.9
Land / 753.3 / 760.2 / 767.6 / 775.4 / 782.3 / 789.3 / 797.5 / 806.3 / 815.9
Subsoil / 78.8 / 82.7 / 87.7 / 92.4 / 97.6 / 101.2 / 107.1 / 113.4 / 117.7
Native standing timber / 2.3 / 2.5 / 2.5 / 2.6 / 2.4 / 2.3 / 2.4 / 2.3 / 2.3
Total financial assets with RoW (d) / 135.7 / 150.3 / 158.0 / 186.7 / 192.0 / 222.9 / 260.7 / 269.1 / 299.0
Total liabilities (d) / 357.7 / 384.4 / 410.5 / 452.6 / 481.3 / 529.5 / 585.9 / 624.4 / 696.7
Net worth (d) / 1 979.0 / 2 005.9 / 2 029.0 / 2 063.0 / 2 082.9 / 2 115.7 / 2 159.1 / 2 200.2 / 2 230.2

(a) Reference year for real/volume measures is 1998-99.

(b) Includes for all periods the marketing authorities privatised in July 1999.

(c) Includes for all periods the remaining public marketing authorities.

(d) These estimates are regarded as experimental.



Attachment 2

Distribution of Household Wealth in Australia - Preliminary Results

The results presented here relate to 1997–98. The results are intended to indicate the types of outputs that are being generated by the project, however, further revisions to the data are taking place as work continues on generating a time series of estimates, and finalising the methodology for consumer durables and superannuation.

Owner-occupied housing and investment properties

The Survey of Income and Housing Costs (SIHC) has provided data on the ownership of residential dwellings for some time. In the data file constructed in this study, it is possible to look at the distribution of these assets, and rental properties, which are derived using data from the Rental Investors Survey. The graph below shows the average amount of dwelling assets by the age of the income unit reference person. As expected, the average value of assets held increases until retirement, and then decreases in later years.

Loans on owner-occupied housing and investment properties

The distribution of loans taken out on owner occupied homes and investment properties can also be determined from the data. It is clear that the average amount owed on dwellings peaks in the late thirties to early forties, and then falls away as people pay off their mortgage.

Relationship between liabilities and assets

The data set developed in this study can be used to derive a variety of ratios and other comparisons. For example, the graph of average total liabilities as a percentage of average total assets peaks in the 25–34 age group, when asset ownership is low and the majority of loans are yet to be paid off. This graph is almost a mirror image of the graph of average net worth, which peaks in later age groups. The pattern observed in the graph below is likely to be even more pronounced when superannuation estimates are added to the data set.