RDP 2015-15: Household Economic Inequality in Australia 2. Definitions of Household Consumption and Income

2.1 Data

The analysis in this paper is primarily based on unit record data from the HES for six different surveys: 1984, 1988/89, 1993/94, 1998/99, 2003/04 and 2009/10. The HES is the most comprehensive source of cross-sectional information on household expenditure in Australia.^[3] For comparability with the spending estimates, we focus on the HES estimates of income. To examine the drivers of inequality we also examine measures based on the HILDA Survey. In the Appendices, we provide alternative estimates of inequality using tax records.

It is not straightforward to use the HES to derive a long time series of either expenditure or income. A key obstacle to making time series comparisons of income inequality is that the ABS has developed more sophisticated ways to measure income over time. For example, in 2003/04, the ABS incorporated information on salary sacrificed income into their household income estimates for the first time. This is likely to have boosted measured inequality relative to earlier surveys as high-income earners are more likely to engage in salary sacrificing. Despite this, in each HES, the ABS provides estimates of income based on definitions from earlier surveys. This helps us match the income measures over time to generate a reasonably comparable time series. Moreover, we have found that the income definitions can affect the estimated level of inequality in any given survey, but the broad trends in measured inequality are similar regardless of the definition of income.^[4]

In this paper we examine inequality in both gross and disposable household income. This allows us to examine the role of government taxes and transfers in affecting inequality. We follow the ABS in defining disposable income as gross income after deducting personal income tax and the Medicare levy. In addition to changes in the definitions of income, the ABS also changed the way it collects household-level tax data. Prior to the late 1980s, the tax data are calculated using a combination of actual reported taxes and imputations, but the tax data for the later surveys are entirely imputed, which is now the preferred method of the ABS for estimating taxes in household surveys. This complicates comparisons of inequality in disposable income before and after the early 1990s (Barrett et al 1999). Partly for this reason, we mainly focus our analysis on the period since the early 1990s.

2.2 Imputing Housing Expenditure and Income

To construct our preferred estimates of household consumption and income we adjust the raw data. Most importantly, we add a service-flow equivalent of housing expenditure for owner-occupiers (or ‘net imputed rent’) to both the consumption and income estimates. Imputed rent is the value of housing services that owner-occupiers receive from living in a rent-free dwelling and it constitutes a significant component of non-cash household income and consumption.

Most guidelines for the compilation of income distribution statistics recommend the inclusion of imputed rent in both consumption and income. Conceptually, the inclusion of imputed rent as part of income treats owner-occupiers as if they were renting the home from themselves, so they are simultaneously paying rent and earning rental income (Saunders and Siminski 2005). The imputed rent adjustment essentially makes estimates of consumption and income for renters comparable to those of owner-occupiers. Doing otherwise can lead to unintuitive results.

To see this, consider the following example. Persons A and B live next door to each other in identical homes. They are the same in all respects; they pay the same amount of rent, spend the same amount on other goods and services, and they have the same income and wealth. Suppose that person A decides to buy the home they currently rent by running down their savings in a bank deposit. In contrast, person B continues to rent. Without any imputed rent adjustment, person A's measured expenditure falls relative to person B because they no longer pay rent. And their measured income also falls relative to person B because they lose the interest earnings on their deposit account. In a sense, without adjusting for imputed rent, person A would appear ‘worse off’ than person B simply because they became a home owner.

In contrast, with an imputed rent adjustment, person A's consumption is unchanged as, under reasonable assumptions, the rent that is imputed is the same as the existing market rent. Their income is also unchanged to the extent that the imputed rent is the same as the interest they previously earned on their savings account.^[5] In other words, with the adjustment for imputed rent, persons A and B are still basically in the same welfare position as before, despite person A becoming a home owner.^[6]

Net imputed rent is equal to the estimated market rent of a dwelling (‘gross imputed rent’) less housing costs normally paid by a landlord such as mortgage interest, rates, insurance and repairs. Total household ‘consumption’ is then equal to total household ‘expenditure’ on goods and services plus net imputed rent. Similarly, ‘adjusted’ income is equal to reported income plus net imputed rent. In Appendix A, we provide a more detailed description of the differences between household consumption and expenditure.

The gross imputed rent estimates are based on the self-reported value of each owner-occupier's dwelling; weekly gross imputed rent is defined to be equal to 5 per cent of the self-reported value of the owner-occupier's dwelling (divided by 52 weeks). The choice of 5 per cent for the ‘imputed rental yield’ is based on previous Australian research (Yates 1994; Saunders and Siminski 2005). The benefit of this approach to estimating imputed rent is that it is straightforward to implement and it fully utilises the available self-reported data on dwelling values. As the ABS has only made information on the reported dwelling value publicly available from 1993/94 onwards, we concentrate on the most recent four surveys: 1993/94, 1998/99, 2003/04 and 2009/10.

In Appendix B, we provide estimates of inequality using an alternative measure of imputed rent based on a hedonic modelling framework. This modelling approach estimates the market value of the rental equivalent for owner-occupied dwellings using information on comparable rented dwellings. This alternative approach allows the implied rental yield to vary over time. A comparison of the two approaches highlights the fact that measures of inequality are somewhat sensitive to the treatment of housing income and expenditure. Nevertheless, the general trends in household economic inequality are fairly similar under this alternative approach. We find that consumption and income inequality have increased since the early 1990s using either the baseline or alternative approach to estimating imputed rent. For a more detailed discussion of the inequality estimates using this alternative approach, see Beech et al (2014).

Our estimates of consumption deduct both mortgage interest payments and interest payments on other forms of debt (e.g. personal loans and credit cards) from total expenditure. Interest payments do not represent a flow of services to the household. All income and consumption estimates are population weighted and divided by an equivalence factor to control for household size and composition.^[7]

There are some caveats to our consumption estimates. First, consumption is a better guide to living standards than current income, but it is still not a complete measure of household wellbeing. Most notably, our estimates do not include measures of consumption of public goods (e.g. recreational facilities), social transfers in kind (e.g. government-funded goods and services such as public health care and education), or goods that are produced within the home. Data limitations prevent us from constructing these broader estimates of consumption. By excluding items such as social transfers in kind, we will tend to overstate the level of economic inequality (Barrett et al 1999).^[8] But it is less clear whether the exclusion of these items affects the estimated trends in inequality. Second, we do not convert all durable goods expenditure to a service-flow equivalent because we do not have long-run household-level data on the stock of such durable goods. However, we have found that excluding spending on particular durable goods, such as motor vehicles, has little discernible effect on our inequality estimates.^[9] Third, we also do not examine trends in the distribution of leisure time, which is another indicator of household wellbeing (Attanasio, Hurst and Pistaferri 2014).

Footnotes

The HILDA Survey also collects annual estimates of expenditure. However, the expenditure definitions have changed over time and are not as complete as the HES. [3]

Despite these caveats, the ABS publishes its own time series of income inequality estimates based on the SIH. The trends in the SIH estimates broadly align with those identified in this paper. Wilkins (2013) provides a very detailed discussion of the relative merits of the inequality estimates obtained from the various data sources. [4]

This requires some ‘hand waving’, as standard theory would suggest the returns on the home and the bank deposit need not be the same every period but only over the lives of the two assets. [5]

Similar logic applies if person A borrows the full amount to buy the home rather than selling an existing asset. For simplicity, assume it is an interest-only mortgage loan. Without the imputed rent adjustment, person A's measured expenditure falls relative to person B because the home owner pays interest rather than rent, and interest payments are not part of consumption. Person A's measured income also falls as interest payments are deducted from income (otherwise interest earnings and interest payments are treated differently). With the imputed rent adjustment, person A's consumption is unchanged by the home ownership decision (as before). And their income is unchanged to the extent that the imputed rent is equal to the interest paid on the loan. If the imputed rent is larger (smaller) than the interest paid then person A's income rises (falls) relative to person B. [6]

The estimated trends in inequality presented in this paper are largely unaffected by the use of an equivalence factor. [7]

The most recent HES for 2009/10 provides estimates of social transfers in kind. The inclusion of such transfers reduces disposable income inequality by about one-quarter, on average. [8]

The 2003/04 and 2009/10 HES provide information on the total (net) value of the stock of vehicles owned by households. Replacing the reported expenditure on motor vehicles with the service-flow equivalent (measured as 10 per cent of the net value of the stock of vehicles) slightly reduces the estimates of expenditure inequality for the two survey years, and leads to a larger increase in measured inequality between the two periods. [9]