Housing costs and living standards among the elderly

Occasional Paper N0. 31

Housing costs and living standards among the elderly

BRUCE BRADBURY1

BINA GUBHAJU2

1 Social Policy Research Centre, University Of New South Wales

2 Australian Demographic and Social Research Institute,

Australian National University

Improving the lives of Australians

ISSN 1833-4415

CONTENTS

iii

Contents

Executive summary vii

1 Introduction 1

2 Housing and living standards 3 2.1 Household size and relative needs 5

3 Data and measures of income and consumption 7 3.1 Data sources 7 3.2 Population and adjustment for price changes and household size 7 3.3 Income/consumption measures 7

4 Living standards in 2005–06 11 4.1 Living standards among Australians over retirement age 11 4.2 The fall in living standards associated with retirement in 2005–06 14 4.3 Gender, household composition and living standards 18

5 Trends from 1988–89 to 2007–08 27

6 Trends in market and transfer income since 1988–89 35

7 Inequality among the older population 39

8 Conclusions 43 8.1 Housing and the measurement of living standards 43 8.2 Cohort living standards and the retirement-consumption puzzle 43 8.3 Variations within the older population 44

Appendixes Appendix A: Rationale for and calculation of adjusted disposable income (ADI) 45 Appendix B: Non-durable expenditures 47 Appendix C: Mean income by age group and year of survey, population aged 15 years and over (2005–06 equivalent $ per week) 49 Appendix D: Additional figures 59

List of shortened forms 65

Endnotes 67

References 71

HOUSING COSTS AND LIVING STANDARDS AMONG THE ELDERLY

Occasional Paper No. 31iv

List of tables

Table 1: Disposable and adjusted disposable income: people aged 65 years and over 8Table 2: Median income by tenure, people aged 65 years and over, 2005–06 11Table 3: Median income by usual residence, people aged 65 years and over, 2005–06 12Table 4: Median income and percentiles relative to median, people aged 65 years and over, 2005–06 13Table 5: Median income and percentiles relative to median, people aged 65 years and over, 2003–04 14Table 6: Sample size by age and household composition, population 50 years and over, 2005 19Table 7: Quintile boundaries of disposable income, people aged 65 years and over

(2005–06 equivalent $ per week) 35

Appendix tablesTable C1: Disposable income (DI) 49Table C2: Adjusted disposable income (ADI) 50Table C3: Disposable income after housing (DIaH) 51Table C4: Adjusted disposable income after housing (ADIaH) 52Table C5: Total consumption (TC) 53Table C6: Adjusted total consumption (ATC) 54Table C7: Non-housing expenditure (NHX) 55Table C8: Non-housing expenditure plus housing consumption (NHX+HC) 56Table C9: Non-durable expenditure (NDX) 57Table C10: Non-durable expenditure plus housing consumption (NDX+HC) 58

v

CONTENTS

List of figures

Figure 1: Housing-related income and consumption concepts 4Figure 2: Ratio of income percentiles (median, 10, 25, 75, 90, 95) of persons aged 50–54 to 80 years

and over to persons aged 50–54 years, 2005–06 15Figure 3: Median, 25th and 75th percentile disposable income by household composition

and age, 2005–06 19Figure 4: Median, 25th and 75th percentile disposable income after housing by household composition

and age, 2005–06 21Figure 5: Median, 25th and 75th percentile total consumption by household composition

and age, 2005–06 22Figure 6: Median total consumption by household composition, age and education, 2005–06 24Figure 7: 25th percentile total consumption by household composition, age and education, 2005–06 25Figure 8: 75th percentile total consumption by household composition, age and education, 2005–06 26Figure 9: Median income of persons aged 65 years and over, by year (2005–06 equivalent $ per week) 27Figure 10: 90-day bank bill interest rate, 1985–2009 28Figure 11: Ratio of median income of persons aged 65 years and over to median income of all aged

15 years and over, by year 29Figure 12: Median disposable income by age 30Figure 13: Median disposable income by age in 2003–04 30Figure 14: Median adjusted disposable income after housing 31Figure 15: Median adjusted total consumption 32Figure 16: Median non-housing expenditures plus housing consumption 32Figure 17: Median non-housing expenditures plus housing consumption by age in 2003–04 33Figure 18: Median non-durable expenditures plus housing consumption 33Figure 19: Median non-durable expenditures plus housing consumption by age in 2003–04 34Figure 20: Ratio of mean market income, gross social transfers, and tax to mean disposable income by

quintiles of disposable income, people aged 65 years and over 36Figure 21: P10/50 percentile ratio for persons aged 65 years and over, by year 40Figure 22: P25/50 percentile ratio for persons aged 65 years and over, by year 40Figure 23: P75/50 percentile ratio for persons aged 65 years and over, by year 41Figure 24: P90/50 percentile ratio for persons aged 65 years and over, by year 41

Appendix figuresFigure D1: Median, 25th and 75th percentile adjusted disposable income by household composition

and age, 2005–06 59Figure D2: Median, 25th and 75th percentile adjusted disposable income after housing by household

composition and age, 2005–06 60Figure D3: Median, 25th and 75th percentile adjusted total consumption by household composition

and age, 2005–06 62


Occasional Paper No. 31vi

vii

EXECUTIVE SUMMARY

Executive summary

How do the living standards of older Australians compare with those of the overall population? How much variation in living standards is there across the elderly population and how have their living standards changed over time?

Home ownership has been identified as an important aspect of the retirement support package in Australia. Do the answers to these questions change when account is taken of the reduced housing costs and the housing consumption services provided by owner-occupied housing?

This report examines these questions using data from the Australian Bureau of Statistics (ABS) Household Expenditure Surveys (HES) from 1988–89 to 2003–04 and the ABS Surveys of Income and Housing (SIH) from 2003–04 to 2007–08.

A number of different measures of living standards are used:

◗◗ disposable income (DI)

◗◗ adjusted disposable income (ADI)—income is adjusted to be not less than the base pension for people over Age Pension age

◗◗ disposable income after housing (DIaH)—disposable income minus housing costs

◗◗ total consumption (TC)—disposable income after housing plus an estimate of housing consumption

◗◗ non-housing expenditure (NHX) and a corresponding measure including housing consumption (NHX+HC)

◗◗ non-durable expenditure (NDX) and a corresponding measure including housing consumption (NDX+HC)—these remove durable expenditures other than housing from the above measures.

All measures are adjusted using an equivalence scale to take account of the needs of households of different sizes (based on the Age Pension single/couple relativity). Data for the four expenditure measures are available only in the HES surveys.

Living standards in 2005–06

Section 4 examines the impact of using these different measures when assessing the living standards of Australians over retirement age.

Measures of wellbeing that do not take account of housing consumption overstate the degree of inequality at the top end of the distribution, but understate it at the bottom end. In general terms, the first result comes from the fact that many middle-income households have substantial housing wealth, and the second result comes from the fact that low-income households have substantial rental expenditures.

On all of the measures, average living standards are shown to decline with age after 50 years of age. This decline is less at the bottom of the income distribution where incomes are cushioned by the Age Pension.

This drop in consumption with age is smaller (but still present) when housing costs and housing consumption are taken into account—because most of the elderly have paid off their houses and have greater housing wealth.

Note, however, that these results refer to one point in time only and do not necessarily follow the situation of individuals as they age. Part of the income decline after age 50 years reflects the fact that the younger cohorts have higher living standards, rather than any actual decline of individual living standards with age. Section 5 presents some cohort results that partly address this.


Occasional Paper No. 31viii

Gender and household composition are two key determinants of living standards after retirement. Women tend to have lower consumption in retirement because of their greater longevity and lower lifetime employment income. This is confirmed by the data in this report. The drop in average consumption for those aged between the early 50s and early 70s is greatest for couples, but single women have the lowest average standard of living at all ages.

At the bottom of the distribution, single men also fare poorly at all ages. At the top of the distribution, single women both have a large drop across all age groups and the lowest standard of living in retirement. For older women, the income disparity between being single or partnered is greater the higher their education level.

Trends in average incomes from 1988–89 to 2007–08

Across all the different measures of resources, the median living standard for the older population has increased steadily since 1988–89, particularly in the last few years up to 2007–08. However, the growth was small in the first five-year period because income in 1988–89 was unusually high as a result of the high interest rates at the end of the 1980s.

The last 15 years have been a period of strong income growth for the whole population, but the relative position of the elderly began to fall after the turn of the century, even though the Age Pension has been indexed in line with wage growth for much of this period, and even though the coverage of superannuation has increased. This stabilised after 2005–06, and the trend might possibly reverse now that we are entering a period of reduced economic growth.

Despite the cross-sectional finding that income continues to fall after retirement, for the cohort of people aged 60 to 65 years in 1988–89, median disposable income has been relatively constant subsequently. Nonetheless, for the cohorts starting at earlier ages, a fall in cohort income over the retirement years is still apparent.

The two expenditure-based measures show somewhat different patterns from each other. On the one hand, a clear decline in living standards across the retirement transition is seen when using the non-housing expenditure plus housing consumption measure for cohorts—though it is not as large as the fall in disposable income. On the other hand, the non-durable expenditure plus housing consumption stays relatively constant between pre-retirement and post-retirement years. The difference between these two measures is consumer durable expenditure. Even though many durables purchased before retirement are likely to last into the retirement phase, the quality of service obtained from them is likely to deteriorate as they age. Hence it is likely that the average consumption level of cohorts is decreasing across the retirement transition.

Trends in market and transfer income, and in inequality

The impact of changes in market income and transfers on disposable income inequality is described in Section 6. Since 1993–94 (after a fall in interest rates), the share of disposable income received from the market has steadily increased for the top three quintiles of the elderly.

This has been associated with a growth of inequality among the aged population since 1993–94. In 1993–94 the 10th percentile had an adjusted disposable income of 83 per cent of the median household. By 2007–08 this had fallen to under 70 per cent. The fall was particularly large between 2005–06 and 2007–08. Similarly, the 75th and 90th percentile households moved away from the median household over this period as their income increased. The picture is somewhat different when consumption of services from housing wealth is taken into account. This had an equalising tendency for some years after 1993–94 (particularly in the bottom half of the income distribution), but inequality has started to increase again after 2005–06.

In light of the large changes in income levels and inequality among the elderly associated with the high interest rates at the end of the 1980s, the above changes in inequality among the aged population cannot be assumed to represent a long-term trend.

1

INTRODUCTION

1 Introduction

How well are the older population in Australia faring? How do they compare with younger groups and which subgroups of the elderly population are worst off? This report sheds light on these questions using data on household income and expenditure collected by the Australian Bureau of Statistics (ABS). A particular focus of the report is on the role of housing costs in influencing living standards, with several alternative measures of household consumption developed and compared.

Across nations, Australia is unusual in the prominent role given to housing in maintaining the living standards of the elderly. Older people in Australia have relatively low incomes but high levels of home ownership and housing wealth (Bradbury 2008a, 2008b). On average, the reduction in housing costs and the increase in housing consumption associated with home ownership offset the lower income among the Australian retired, so that the average consumption drop associated with retirement ends up being comparable to that in other countries. A similar story applies to the living standards of the most disadvantaged. Compared to other countries, Australia’s older people have high income poverty rates, but their rates of poverty after housing are more typical (Yates & Bradbury 2009).

However, not all retired Australians own their own homes. The wide variation in housing wealth means that studies of the living standards of the Australian elderly need to take housing into account. Indeed, there is a long tradition in Australia of doing just this. The most common method used has been to subtract housing costs from income. Early work using this ‘income after housing costs’ measure includes the Commission of Inquiry into Poverty (1975) and Bradbury, Rossiter and Vipond (1986). More recent work includes McNamara, Tanton and Phillips (2007).

The rationale for this measure is that households can have very different expenditure costs for a given standard of housing, depending upon whether the housing is rented, being purchased or owned outright. Disposable income minus housing costs is an estimate of the income available for the consumption of non-housing goods, and is comparable across households in different tenures.

An alternative approach is to add to disposable income (DI) an imputed rental income that could be obtained from the owner-occupied dwelling. This takes account of the quality of the housing that people live in.1 However, home ownership is a relatively illiquid asset and living in a mansion might not be much compensation if one has little income. You cannot eat your house.

Whether the after-housing measure or the imputed-rent measure is a better indicator of living standards depends upon the degree of substitution between the two in consumers’ welfare functions and the liquidity of housing assets. If there is a great deal of substitutability, then the value of living in a grand house might well offset any shortage of cash for other consumption goods. If we think this is the case, or think that it is easy for people to liquidate their housing assets to finance other forms of consumption if they choose to do so, then the more comprehensive measure of resources including imputed rent is most appropriate.

On the other hand, if we think there is little substitution, that housing is illiquid and that the elderly are more likely to be overconsuming rather than underconsuming housing,2 then the after-housing measure will be a more appropriate indicator of living standards. This might particularly be the case when we consider the living standards of the most disadvantaged, who might not be able to meet minimum standards for the consumption of non-housing goods.

In this report we thus use several different indicators of household consumption (or potential consumption) and compare the patterns of living standards that they imply. Various measures take account of housing costs, housing wealth, household expenditures and misrecording of household incomes. The key questions that we examine include:


2 Occasional Paper No. 31

◗◗ By how much do living standards drop after retirement?

◗◗ How much variation in living standards is there across the elderly population?

◗◗ How have the living standards of older Australians changed over time? Have they kept up with income growth in the rest of the population?

◗◗ Have the income sources of the older population changed? How has this varied across the income distribution?

◗◗ Has inequality among the elderly increased or decreased?

For most of these questions, the answers are much the same no matter which measure of household resources is used. However, for others, there is substantial variation. We discuss these differences and their interpretation.

The next section (Section 2) outlines the different measures of household living standards, and the following section (Section 3) describes the data used in these measures. Recent (2005–06) patterns in living standards based on income survey data are described in Section 4. Section 5 presents evidence from the ABS Household Expenditure Survey (HES) from 1988–89 to 2003–04, and the Survey of Income and Housing (SIH) from 2003–04 to 2007–08, and considers trends in living standards. Section 6 disaggregates these trends by income source and Section 7 examines trends in inequality among the older population. Section 8 concludes the report.

3

HOUSING AND LIVING STANDARDS

2 Housing and living standards

Several different approaches can be used to describe the impact on living standards of housing costs and accumulated housing wealth. One simple measure often used in the housing literature is housing stress, that is, the ratio of housing costs to disposable income. Among the elderly, housing costs are typically a high proportion of income if they rent in the private rental market and have low retirement incomes. Home ownership substantially reduces housing costs in retirement, and hence housing stress, as does access to subsidised rental.

However, although this housing stress measure is convenient for describing the impact of housing costs, it is only an indirect measure of living standards. Some people with seemingly high levels of housing stress (that is, costs amounting to more than 30 per cent of their income) would nonetheless have a high standard of living if they had high incomes as well as high housing costs. Similarly, some people with low incomes may have low levels of financial housing stress simply because they live in poor quality accommodation. This problem is often dealt with by combining it with a measure of income. Even in this case, however, the approach is limited as it takes no account of the quality of the dwelling.

To address this and other related issues we use a number of different living standards measures (Figure 1). This represents the key elements of consumption and income for home owners and people paying market rents. (The treatment of people paying subsidised rents is described in the next section.)

The first three columns in Figure 1 describe the economic (‘Haig-Simons’) concepts of consumption, saving and income.3 Consumption is defined as the consumption of non-housing goods and services, plus the services obtained from housing. For market renters, the latter is assumed to be equal to the rent paid. For home owners, the equivalent measure is the potential gross rental value of the dwelling (the ‘gross imputed rent’). Mortgage interest and principal repayments are ignored for this calculation because they are a function of the saving and financing aspects of housing that are separate from the consumption value.

Saving is equal to the increase in wealth of the household. This includes mortgage principal repayments because they represent a decline in debt (ideally inflation-adjusted). Cash saving (increases or decreases in relatively liquid assets such as bank accounts) is generally one of the smaller forms of saving. Other forms of saving, such as capital gains and superannuation contributions, are more important. Income is defined as the sum of consumption and saving.

The remaining five columns in Figure 1 describe the empirical concepts measured in this report. Disposable income, as it is typically measured in household surveys, comprises regular monetary inflows to the household, but excludes irregular and/or unrealised sources such as capital gains. It differs from the economic concept of ‘income’ in the third column in Figure 1, in that many important forms of saving, such as employer and employee superannuation contributions and capital gains, are not included. Once received by the household, disposable income is allocated to expenditures on non-housing consumption, current housing expenditures (rent, mortgage interest and principal where applicable) and cash saving. If people are running down their financial assets then the cash saving item might be negative, which will mean the sum of the other items will be greater than disposable income.

Income after housing is shown in the fifth column—calculated as disposable income minus housing expenditures (where information is available, housing maintenance expenditures and landlords’ costs such as insurance and rates should be treated in the same way as rent or mortgage interest). As shown in Figure 1, this is approximately equal to non-housing consumption (apart from the inclusion of cash saving or dissaving).



Figure 1: Housing-related income and consumption concepts

Component

Theoretical concepts Measures used in this study

Cons

umpt

ion

Sav

ing

Inco

me

Dis

posa

ble

inco

me

(DI)

Inco

me

afte

r ho

usin

g (D

IaH

)

Tota

l con

sum

ptio

n (T

C)

Non

-hou

sing

ex

pend

itur

e (N

HX

) (a

lso

NH

X+

HC)

Non

-dur

able

ex

pend

itur

e (N

DX

) (a

lso

ND

X+

HC)

Non-housing consumption (non-durables)

Non-housing consumption (durables)

Rent paid (a) (a)

Mortgage interest payments

Mortgage principal repayments

Housing consumption (gross rental value of house)

(a) (a)

Cash saving

Other forms of saving

(a) Excluding the light shaded area represents NHX and NDX respectively. Including it represents NHX+HC and NDX+HC respectively.

The total consumption (TC) concept defined here adds the housing components of consumption shown in the first column to income after housing in the fifth column to obtain an estimate of total household consumption of both housing and non-housing goods (again, plus cash saving).

This total consumption concept is similar to the concept of ‘disposable income plus imputed rent’ that is used in some research. However, the latter is a measure of household income, whereas we focus on a measure of household consumption. The difference is that our total consumption measure also deducts mortgage principal repayments from disposable income.4 Principal repayments form part of saving and are thus part of income, but not of consumption. We do not present results on this basis here, though a comparison of the income and consumption measures can be found in Yates and Bradbury (2009).

5

HOUSING AND LIVING STANDARDS

Note that, although our interest is focused on consumption (non-housing and housing), all of the measures described above are derived from data on household incomes rather than expenditures. There are two reasons for this. First, income data is easier to collect, and hence available for more years. Second, expenditure data is typically collected over quite short time periods (for example, two weeks for many items in the ABS surveys). For example, someone who has no clothing purchases during this period is unlikely to be naked. Even when longer recall time periods are used for consumer durables, these are generally much shorter than the goods’ effective lifetimes. Indeed these timing issues also apply to non-durables such as food. If a household typically does its grocery shopping once a week but on different days, its expenditure on groceries during the two-week diary period could reflect shopping only for one week, or for two or even three weeks.

Hence, the quantity of service that an individual receives from their purchased goods might be quite different to their recorded expenditure. Though this does not bias estimates of mean consumption, it does bias distributional measures. In general, we would expect the inequality of consumption to be much less than the inequality of household expenditure. (A similar problem also applies with respect to income fluctuations, but to a lesser extent.)

One partial solution to this ‘shopping variability’ problem is to consider only expenditure on non-durable goods. We have compiled estimates on this basis using data from the HES. A limitation of this is that expenditures on non-durables might change in systematic ways—for example, because of income effects or taste changes with age. For comparison we also include some results using a measure of total expenditures that includes expenditures on both durables and non-durables.

2.1 Household size and relative needs

To compare the situations of people living in households of different sizes, it is necessary to account for consumption sharing. For example, both a single person and a couple need only one kitchen. Estimates of these relative needs are known as consumer equivalence scales, and income relative to a measure of needs is termed equivalent income.

In this report, equivalent income is defined as Y/n0.7, where Y is any one of the income/consumption measures described above and n is the number of people in the household. This power function formula is commonly used in international comparisons, although with an exponent of 0.5 rather than 0.7. However, the latter is used here because it approximates the relativity between the single and the couple Age Pension rates in Australia in the years for which we have data. As of early 2009, the pension rate (including supplements) for aged singles was 61.1 per cent of that of a couple (Harmer 2009, p. 46). The ratio for a couple relative to a single was thus 1/0.611=1.637=20.711≈20.7. Using this equivalence scale, couples and singles with the pension as their only income source will have approximately equal equivalent incomes. For simplicity we use this same formula for larger households and also for households with children when they are considered in this report.

There is evidence that the current pension relativities, and hence this equivalence scale formula, understates the relative needs of single people (Bradbury 2009). This is also the conclusion of the recent Pension review report (Harmer 2009), which recommended an increase in the relative pension for single people (which the government implemented in September 2009). This needs to be borne in mind in the results below comparing singles with couples.

Finally, housing costs have different economies of scale to non-housing costs. This should imply different equivalence scales for the different measures of household resources used here. However, for simplicity, we use this same equivalence scale for all measures in this report.

7

DATA AND MEASURES OF INCOME AND CONSUMPTION

3 Data and measures of income and consumption

3.1 Data sources

We use data from the 1988–89, 1993–94, 1998–99 and 2003–04 HES and the 2003–04, 2005–06 and 2007–08 SIH. These surveys were conducted on a reasonably consistent basis over this time. The main changes were:

◗◗ an improvement in the population weighting system after 1988–89

◗◗ several differences between the survey methodology of the HES and the SIH

◗◗ higher response rates in the SIH, although it is difficult to evaluate whether this had an impact once weighting was incorporated

◗◗ minor differences in the income definitions in the more recent surveys5

◗◗ a broader definition of housing costs in the HES.

3.2 Population and adjustment for price changes and household size

The survey scope covers most people in private dwellings. People in non-private dwellings such as nursing homes, however, are excluded.

All the measures of economic wellbeing described below are aggregated to the household level. The household income or consumption measure is then divided by n0.7 where n is the number of people in the household. The result is then adjusted to 2005–06 dollars using the consumer price index. Any negative values are set to zero.

The counting unit in the results below is the individual, who is assigned the income/consumption measure calculated for their household. All household members are thus assumed to have the same living standard. The different income/consumption measures used are described below.

3.3 Income/consumption measures

Drawing on the framework presented in Section 2, we define several different indicators of household economic wellbeing:

◗◗ disposable income (DI)

◗◗ adjusted disposable income (ADI)—income is adjusted to be not less than the base pension for people over Age Pension age

◗◗ disposable income after housing (DIaH) and the corresponding measure based on ADI (adjusted disposable income after housing, or ADIaH)—this is income minus housing costs

◗◗ total consumption (TC and adjusted total consumption, or ATC)—this is DIaH/ADIaH plus an estimate of housing consumption (HC)

◗◗ non-housing expenditure (NHX) and the corresponding measure including housing consumption (NHX+HC)—this is only available in the HES surveys



◗◗ non-durable expenditure (NDX) and the corresponding measure including housing consumption (NDX+HC)—these remove other durable expenditures (that is, other than housing) from the above measures.

Disposable income (DI)This is current usual income, minus imputed income tax payable. We use current income rather than annual, because this more closely matches the period used for housing costs. Also, it is more straightforward to calculate the adjusted disposable income measure on this basis. This is collected at the individual level and aggregated to the household level.

Adjusted disposable income (ADI)One concern with Australian income distribution data is that much of the recorded incidence of low income could represent measurement error—people not reporting all of their income. To address this issue, we calculate an adjusted disposable income (ADI). This is the maximum of actual disposable income and the base rate of Age Pension. It is only calculated for the population over Age Pension age (it is set equal to DI for the younger population). Details of the calculation method are shown in Appendix A.

The difference between DI and ADI measures is summarised in Table 1. Around 12 to 23 per cent of people aged 65 years and over have incomes that are adjusted upwards as a result of this calculation. Most adjustments are quite small, but there are a small number of cases where negative incomes have been adjusted to the pension level.6

Disposable income after housing (DIaH and ADIaH)As noted above, disposable income minus housing costs is an indicator of the income available for non-housing consumption. If there is neither non-housing saving nor dissaving, disposable income minus housing costs is equal to non-housing consumption. We also calculate a corresponding variable based on adjusted disposable income.

To ensure comparable treatment of renters and home owners, such a measure should deduct landlord costs incurred by home owners but not normally directly paid by renters. These include body corporate fees, dwelling insurance (but not contents), maintenance costs and depreciation, land taxes and water charges (when these are not passed on to tenants). We follow this approach, though data availability means that we cannot include some of these costs in the SIH surveys.7

Table 1: Disposable and adjusted disposable income: people aged 65 years and over

When DI ≠ ADI

% where DI ≠ ADIMean value of difference

$ per week

Median value of difference $ per week

HES 1988–89 17.0 51 7

HES 1993–94 15.5 79 25

HES 1998–99 21.7 54 7

HES 2003–04 21.1 47 14

SIH 2003–04 22.5 51 12

SIH 2005–06 17.6 73 21

SIH 2007–08 11.7 106 42

Note: Income is not equivalised.

9

DATA AND MEASURES OF INCOME AND CONSUMPTION

Total consumption (TC and ATC)As mentioned above, if there is no non-housing saving or dissaving, then disposable income minus housing costs is equal to non-housing consumption. We thus approximate total consumption by adding an estimate of housing consumption to disposable income after housing.

For private renters, housing consumption is defined as equal to the rent paid by the household. For public renters we replace the rent paid with an estimate of market rent (subsidised rent paid plus an estimate of government rental subsidy as calculated in the ABS Fiscal Incidence Study).8 In this report, we do not impute any housing consumption for those people living rent free (that is, their housing consumption level is set at zero). These people, however, represent only a small fraction of the population.9

For home owners we impute an estimated rent following the method used by Saunders and Siminski (2005).10 This imputes rent on the basis of the estimated value of the dwelling. The imputation removes the effect of fluctuations in house-price values, though the imputed consumption does vary in line with cyclical fluctuations in rents.

Non-housing expenditure (NHX and NHX+HC) and non-durable expenditure (NDX and NDX+HC)An alternative method of estimating household consumption is to use household expenditure data. The main problem with this method, however, is that the timing of expenditure and consumption might be different. The most obvious example of this is housing. Owners, who may have low housing expenditures once they have paid off their mortgage, nonetheless still consume a significant flow of services from their housing.

We include some results here where consumption is estimated using total expenditure on non-housing expenditures (NHX), and also using this with our estimates of housing consumption (NHX+HC).

While these measures might be good indicators of average consumption levels, they are not very good indicators of the distribution of consumption, because of the shopping variability issue discussed above. Some people will have low expenditures on non-housing goods because they did not shop in a particular fortnight, even though they have substantial consumption because of previous purchases.

We remove some of these purchasing fluctuations by using a measure of non-durable expenditures (NDX) and a corresponding measure that includes housing consumption (NDX+HC). This follows the approach of Barrett, Crossley and Worswick (2000) who define non-durables as food, alcohol and tobacco, clothing, personal and medical care, transport, recreation, household services and operations, and current housing. We also exclude clothing-related expenditures (except expenses pertaining to dry cleaning, laundering, hiring and repairs of clothing and footwear), and major expenses that are not likely to be purchased on a regular basis, such as vehicles. We also smooth gambling expenditures (see Appendix B).

These expenditure-based measures are not available for the years after 2003–04 HES because the SIH does not collect expenditure data.

11

LIVING STANDARDS IN 2005–06

4 Living standards in 2005–06

In this section we examine the living standards of Australians over retirement age, using data from the 2005–06 SIH.11 Note that none of the expenditure-based measures are included here as they are only available in the HES.

4.1 Living standards among Australians over retirement age

The most obvious effect of incorporating housing costs and wealth into a standard-of-living measure is that the relative positions of people in different housing tenures change. Table 2 shows the median values of these measures across tenure types for people aged 65 years and over for 2005–06. Compared with just disposable income (DI), income after housing (DIaH) is lower (by definition) and total consumption (TC) usually higher, but these differences vary substantially across the different tenures.

Table 2: Median income by tenure, people aged 65 years and over, 2005–06

TenureDisposable

income (DI)

Adjusted disposable

income (ADI)

Disposable income

after housing (DIaH)

Adjusted disposable

income after

housing (ADIaH)

Total consumption

(TC)

Adjusted total consumption

(ATC)

Equivalent $ per week

Owner/purchasing

340 342 321 323 459 463

Renting private 306 306 199 202 306 306

Renting government

255 256 193 205 324 328

Occupied rent free

285 285 274 274 274 274

Relative to owner/purchaser

Renting private 0.90 0.89 0.62 0.63 0.67 0.66

Renting government

0.75 0.75 0.60 0.63 0.71 0.71

Occupied rent free

0.84 0.83 0.85 0.85 0.60 0.59

Source: SIH 2005–06.

The bottom panel of Table 2 shows the proportion of median income of each type of tenure compared with the most common tenure type, owning or purchasing.12 The average owner has a higher disposable income than the average renter or person living rent-free. The adjusted disposable income (ADI) measure is similar. After deducting housing costs, however, this gap widens considerably, with the average renter (private or government) having only 60 to 63 per cent of the income available for non-housing expenditures as the average home owner.13 Adding the consumption value of the home back in (that is, rent for renters and imputed gross rent for owners) reduces this gap somewhat because the rental/imputed rental values are more similar than are the



income differences. (Imputed rents for owners are nonetheless greater than for renters—as can be seen from the difference between the TC and DIaH columns in the top panel of Table 2.)

The regional dimension is summarised in Table 3. Overall, older people living outside state capital cities have incomes 5 per cent lower than those living in the state capital cities. After housing costs are deducted, average incomes are somewhat closer, but not by much. This is because most elderly people are home owners in both city and non-city areas. Taking account of total consumption, however, widens the gap considerably because of the greater value of urban dwellings.

Table 3: Median income by usual residence, people aged 65 years and over, 2005–06

ResidenceDisposable

income (DI)

Adjusted disposable

income (ADI)

Disposable income

after housing (DIaH)

Adjusted disposable

income after

housing (ADIaH)

Total consumption

(TC)

Adjusted total consumption

(ATC)

Capital city 339 341 309 312 467 477

Balance of state 322 322 299 299 411 414

Ratio: balance to capital

0.95 0.94 0.97 0.96 0.88 0.87

Note: The Australian Capital Territory and the Northern Territory are not included in table.


This points to an important feature of the total consumption measure. On the one hand, according to the valuation of the market, capital city dwellers consume more housing services. On the other hand, this market valuation is set by supply and demand across the whole market—which might not be relevant to the elderly. In particular, a major reason for higher capital city land prices is the greater access to high-wage jobs in cities. So caution is required when interpreting the impact of these wider measures of wellbeing in comparing groups where the nature of housing consumption is fundamentally different.

The overall distribution of the non–expenditure based living-standard measures is shown in Table 4. We also show in Table 5 results for 2003–04 that include the expenditure-based measures.

At the bottom of the income distribution in 2005–06 (Table 4), the 10th percentile is lowest relative to the median for the disposable income after housing (DIaH) measure. This is because some households have high housing costs (mainly renters in this age group).

13


Table 4: Median income and percentiles relative to median, people aged 65 years and over, 2005–06

Percentile relative to median

Median 10th 25th 75th 90th 95th

Equivalent $ per week

Disposable income (DI) 332 0.73 0.80 1.40 1.97 2.54

Adjusted disposable income (ADI) 333 0.75 0.80 1.41 1.98 2.53

Disposable income after housing (DIaH)

305 0.63 0.79 1.41 2.02 2.66

Adjusted disposable income after housing (ADIaH)

308 0.71 0.80 1.40 2.01 2.65

Total consumption (TC) 440 0.67 0.80 1.34 1.82 2.34

Adjusted total consumption (ATC) 444 0.69 0.81 1.33 1.81 2.32


The pattern is similar in 2003–04 for the income-based measures (Table 5). However, the expenditure measures generally show more inequality—as we might expect due to the influence of shopping variability. This is particularly apparent in the NHX measures, which include many infrequently purchased durables.

It is also interesting to observe the impact of the adjustments for apparently underrecorded income. In both years, median adjusted disposable income (ADI) is slightly higher than unadjusted income, even though the median is well above pension levels. This is because of multiple income-unit households, where people over Age Pension age are living with younger family members. At the bottom of the income distribution, the ratio of the 10th percentile to the median is very similar for the DI and ADI measures in both years, suggesting that for many purposes it is not necessary to make this type of adjustment.

However, there is a larger gap between the DIaH and ADIaH measures in both years. In this case, the adjusted measures suggest that older people at the bottom of the income distribution are much closer to the median than the unadjusted measures suggest. This different result arises because the adjustment to disposable income mainly takes place among people with incomes below the 10th percentile. However, variations in housing costs mean that these people are more evenly spread among the bottom half of the DIaH distribution, and so the 10th percentile of the ADIaH measure is higher than the unadjusted measure. In some circumstances, therefore, adjustments to income for apparent underreporting might have a significant influence on distributional estimates.

At the other end of the distribution, the total consumption measures show less variability than the measures that do not take account of the imputed value of home ownership. This reflects the less than perfect correlation between housing wealth and income in retirement.

We might thus consider that measures of wellbeing that do not account for housing consumption overstate the degree of inequality at the top end of the distribution, but understate it at the bottom end. In general terms, the first result comes from the situation that many middle-income households have substantial housing wealth, and the second result comes from the situation that households with no housing wealth have substantial rental expenditures.14



Table 5: Median income and percentiles relative to median, people aged 65 years and over, 2003–04

Percentile relative to median

Median 10th 25th 75th 90th 95th

2005–06 equivalent $ per week

Disposable income (DI) 318 0.75 0.80 1.41 2.05 2.70

Adjusted disposable income (ADI)

319 0.76 0.80 1.41 2.04 2.70

Disposable income after housing (DIaH)

280 0.63 0.79 1.46 2.15 2.88

Adjusted disposable income after housing (ADIaH)

281 0.68 0.81 1.46 2.14 2.87

Total consumption (TC) 415 0.64 0.78 1.34 1.96 2.57

Adjusted total consumption (ATC)

418 0.65 0.78 1.34 1.94 2.56

Non-durable expenditures (NDX)

230 0.48 0.70 1.49 2.23 2.72

Non-durable expenditures plus housing consumption (NDX+HC)

360 0.57 0.74 1.43 1.99 2.53

Non-housing expenditures (NHX)

280 0.39 0.62 1.75 2.90 4.20

Non-housing expenditures plus housing consumption (NHX+HC)

412 0.50 0.69 1.58 2.51 3.46

Source: HES 2003–04.

4.2 The fall in living standards associated with retirement in 2005–06

By how much do household consumption levels drop after retirement? As noted in the introduction, the income replacement rate associated with the Australian pension is relatively low by international standards. This, however, is offset by the greater holdings of housing and other forms of private wealth.

Figure 2 shows the age-related fall in living standards as measured by the different living-standard indicators. These are all shown relative to the situation of people aged 50 to 54 years. In most cases, this represents the age category with the highest living standard. Figure 2a shows the median living standard in each age category for each living-standard measure, divided by the corresponding estimate for those aged 50 to 54 years. It thus shows that there was a relative drop in living standards for a hypothetical person who was at the median 2005–06 living standard at each age.

15


Figure 2: Ratio of income percentiles (median, 10, 25, 75, 90, 95) of persons aged 50–54 to 80 years and over to persons aged 50–54 years, 2005–06

Figure 2a: Median

Age (years)

DI TC

1.21.11.00.90.80.70.60.50.4

50–54 55–59 60–64 65–69 70–74 75–79 80+

DIaH

Figure 2b: 10th percentile

Age (years)

1.21.11.00.90.80.70.60.50.4

50–54 55–59 60–64 65–69 70–74 75–79 80+

DI DIaHADI ADIaH ATCTC

Figure 2c: 25th percentile

Age (years)

DI TC

1.21.11.00.90.80.70.60.50.4

50–54 55–59 60–64 65–69 70–74 75–79 80+

DIaH



Figure 2d: 75th percentile

Age (years)

DI TC

1.21.11.00.90.80.70.60.50.4

50–54 55–59 60–64 65–69 70–74 75–79 80+

DIaH

Figure 2e: 90th percentile

Age (years)

DI TC

1.21.11.00.90.80.70.60.50.4

50–54 55–59 60–64 65–69 70–74 75–79 80+

DIaH

Figure 2f: 95th percentile

Age (years)

DI TC

1.21.11.00.90.80.70.60.50.4

50–54 55–59 60–64 65–69 70–74 75–79 80+

DIaH


17


Note that the results shown in this figure are cross-sectional, and do not necessarily show the trajectory of the median person as they age. Indeed, part of the income decline after age 50 years reflects higher living standards of younger cohorts, rather than the fact that the living standards of individuals decline with age. Although, for convenience, we describe changes in terms of increases or decreases with age, it must be remembered that these are cross-sectional rather than cohort estimates.

Figure 2 contains one line for each of the measures of resources based on income data. Where the measures based on adjustable disposable income are indistinguishable from the corresponding unadjusted estimate, we do not show the adjusted measure. Generally, the adjusted and unadjusted measures are different only at the bottom of the income distribution.

Figure 2a shows the median living standard indicators for five-year age groups, pre-retirement and post-retirement. All the indicators are scaled relative to the value for the youngest age group (50 to 54 years). The graph shows that the drop in the median disposable income as people age is large. Those in their 70s have a median disposable income only a little over half that of people aged 50 to 54 years. The fall in median disposable income after housing costs is smaller, although some of this is because housing costs are already falling in pre-retirement years. If we were to take living standards at age 55 to 59 years as the reference point, the fall in median incomes after housing would be almost as large as the fall in disposable income.

Irrespective of the pre-retirement reference year, however, the fall in total consumption (taking account of consumption of housing wealth) is substantially less than the drop in the other two measures (DI and DIaH). Nonetheless, there is still a fall in consumption of around 30 per cent from the pre-retirement years.

As noted above, these are single point-in-time patterns. Part of this pattern is due to higher incomes among younger cohorts. This is considered further in the next section.

At the very bottom of the income distribution, where people are relying on income support in both pre-retirement and post-retirement years, there is only a small drop in living standards with increasing age. Here the adjusted measures show a different picture from that shown by the unadjusted measures. On the basis of adjusted incomes after housing, it would appear that the living standards of the most disadvantaged increase with age. However, this is probably not the case. The adjustment to apparently misrecorded low incomes is only made for people over retirement age, so the 10th percentile of income in the pre-retirement years is not really an appropriate value against which to scale incomes.

At the 25th percentile, the adjusted and unadjusted measures are similar (and so the adjusted measures are not shown). Compared to the patterns experienced by median households, the fall in income with age is smaller because of the cushioning effect of the Age Pension. From age 50 to 54 years to 70 to 74 years, equivalent disposable income falls by about 37 per cent, disposable income after housing falls by about one-quarter, and total consumption falls by about one-fifth.

For higher income households, the fall in living standards associated with retirement is generally similar to the picture at the median—though if age 55 to 59 years were used as the starting point for the 95th percentile, the fall would be greater.

In general, based on the situation in 2005–06, households over retirement age have lower living standards than younger households. This applies to all parts of the distribution except for the very bottom, and the relative fall is greatest for those in the top half. This fall in living standards with age is smaller if we take account of housing expenditures and wealth, but it is still substantial. Bradbury (2008a, 2008b) finds that the income fall is greater in Australia than in several other rich countries, but the fall in total consumption found in Australia is similar.

This fall in consumption with age has been termed the ‘retirement consumption puzzle’ (Barrett & Brzozowski 2009). Economic theories of lifecycle consumption patterns suggest that people seek to equalise their marginal utility of consumption in the different periods across their lifetime. Under plausible models of consumption preferences, this suggests that resources would be shifted between periods to equalise consumption.



Explanations for these patterns can be classified under four headings.

1) Measurement issues

— The trends for individuals might be different from the cross-sectional patterns.

— The total consumption measure used here may be incomplete. In particular, the running down of savings and liquidation of assets is generally not included, although it should be in a measure of consumption. Note, however, that some forms of dissaving are included if they result in regular income streams—for example, purchasing an annuity with a superannuation payout.

2) Changing marginal utility of consumption with age

— Reductions in work-related expenditures, increases in leisure and home production time, and decreases in the prices of some goods because of pensioner concessions will all alter the need for expenditure in retirement.

— Changes in tastes with age—for example, poorer health—might lead to reduced demand for out-of-home expenditures. But they might have the opposite effect if greater support services are needed (for example, taxi fares). Tastes might also change because of historically established social norms for consumption at different ages.

3) Saving constraints

— These could make it difficult to shift resources across the lifecycle.

4) Myopic preferences

— These would mean that people do not consider consumption needs in future periods.

Each of these classifications is likely to play at least some part in explaining the apparent fall in living standards with age, as observed in earlier figures. Some information on cohort trends in income (which better approximate trends for individuals) is presented in Section 5. In this case, the falls are flatter, but there is still a fall between pre-retirement and post-retirement years.

Questions of the changing marginal utility of consumption with age are addressed in more detail in another research project—‘Expenditure costs’—currently underway at the Social Policy Research Centre, which seeks to estimate the cost savings associated with retirement.

4.3 Gender, household composition and living standards

Gender and household composition are two key determinants of living standards after retirement. Women live longer and are thus more likely to live in single-person households. Their greater longevity also means they will be more likely to exhaust savings and rely solely on their pension. This is compounded by the fact that women also have lower lifetime employment income. Women who do not partner or who separate from their partners before retirement will thus tend (on average) to have lower levels of wealth in retirement.

In the figures below, we disaggregate the different living-standard indicators by age, gender and household composition. Table 6 shows the sample size in the 2005–06 SIH in each cell. Across all age groups—other than 50 to 54 years—couples are the most prevalent household type, with single-women households almost as prevalent in the 80 years and over age group. The ‘other’ household type is also quite common in post-retirement years. Because this group is quite heterogeneous, we focus on the couple and single-person households in the discussion below Table 6.

19


Table 6: Sample size by age and household composition, population 50 years and over, 2005

Age (years) Couple Single man Single woman Other

50–54 543 106 123 883

55–59 809 123 154 564

60–64 742 63 139 264

65–69 604 78 147 146

70–74 490 71 164 115

75–79 375 53 157 84

80+ 275 70 232 121

Source: SIH 2005–06. Couples are households comprising a partnered couple and no other people. The single households only contain one person. Other multi-person households (including couples with non-dependent children) are classed in the ‘other’ category. People in non-private dwellings such as nursing homes are not included in the ABS household surveys.

Figure 3 shows the age trends of equivalent disposable income by household type. Note that all these results use individuals as the counting unit, but households as the income aggregation unit. For example, the higher incomes of people aged 65 to 69 years in couples could be due to the fact that some have younger, workforce-age partners. Similarly, the higher income for people in the ‘other’ category reflects the presence of workforce-age people in the household.

Figure 3: Median, 25th and 75th percentile disposable income by household composition and age, 2005–06

Figure 3a: Median

Age (years)

Dis

posa

ble

inco

me

($)

900800700600500400300200100

50–54 55–59 60–64 65–69 70–74 75–79 80+

couple single womansingle man other




Age (years)

Dis

posa

ble

inco

me

($)

900800700600500400300200100

50–54 55–59 60–64 65–69 70–74 75–79 80+



Age (years)

Dis

posa

ble

inco

me

($)

900800700600500400300200100

50–54 55–59 60–64 65–69 70–74 75–79 80+



At age 50 to 54 years, median equivalent incomes in all household types are quite similar. However, this gap widens dramatically for single women in their late 50s and early 60s. The gap between single and couple income narrows after age 65 years, and by the time they are in their 70s, couples and singles have similar median incomes—reflecting that both are largely reliant upon the Age Pension. (The equivalence scale is defined so that singles and couples reliant solely on the Age Pension have the same equivalent income.)

At the bottom of the distribution (the 25th percentile of each household type) the disposable incomes of singles do not change with age. The most disadvantaged single men and women are reliant upon income support in their 50s as well as in their post-retirement years. Couples at the 25th percentile have higher pre-retirement incomes, but these quickly converge to the pension level after retirement.

At the top of the income distribution (75th percentile), the gap between singles and couples continues into the retirement years. High-income single women in their early 50s have incomes similar to those of single men, but for older ages the upper end of the single female distribution is well below that of single men. After their mid-60s, few single women have incomes that are substantially above the Age Pension rate.

The patterns for the adjusted disposable income (ADI) measure are similar (Figure D1).

21


Figure 4 shows the fall in living standards with age when measured using equivalent disposable income after housing. (The similar figure using adjusted income is in Appendix D, Figure D2.) As noted above, this measure has a slightly flatter age profile because of the lower housing costs of the elderly. Across household composition, however, the story is much the same as for disposable income. One exception is the lower DIaH (due to higher housing costs) for single men and women at age 50 to 54 years.

Generally, at younger ages, the median couple is better off than the median single, with this gap being substantially (but not entirely) reduced after retirement. After retirement, the living standard distribution of single women is quite compressed, and those at the top of the income distribution have a significantly lower standard than men and couples at the top of their distribution.

The patterns differ somewhat when using total consumption (Figure 5) or the corresponding adjusted measure (Figure D3). At the 25th percentile, there is a small increase in total consumption among older singles, due to the greater housing wealth of this group. This is probably mainly due to people moving between household types. In the pre-retirement years, singles have less wealth than couples, but as they get older, mortality moves the surviving partners of the wealthier couples into the singles category.

Figure 4: Median, 25th and 75th percentile disposable income after housing by household composition and age, 2005–06

Figure 4a: Median

Age (years)

Dis

posa

ble

inco

me

($)

900800700600500400300200100

50–54 55–59 60–64 65–69 70–74 75–79 80+



Age (years)

Dis

posa

ble

inco

me

($)

900800700600500400300200100

50–54 55–59 60–64 65–69 70–74 75–79 80+





Age (years)

Dis

posa

ble

inco

me

($)

900800700600500400300200100

50–54 55–59 60–64 65–69 70–74 75–79 80+



Figure 5: Median, 25th and 75th percentile total consumption by household composition and age, 2005–06

Figure 5a: Median

Age (years)

Tota

l con

sum

ptio

n ($

)

900800700600500400300200100

50–54 55–59 60–64 65–69 70–74 75–79 80+


23



Age (years)

Tota

l con

sum

ptio

n ($

)

900800700600500400300200100

50–54 55–59 60–64 65–69 70–74 75–79 80+



Age (years)

Tota

l con

sum

ptio

n ($

)

900800700600500400300200100

50–54 55–59 60–64 65–69 70–74 75–79 80+



At the median and especially at the 75th percentile, single men have the highest living standard in the oldest age categories. These changes in total consumption with age among single men are probably driven by differential mortality, with the surviving single men wealthier than the average single man at younger ages.

Summarising these patterns, and focusing on the more comprehensive total consumption results in Figure 5, some consistent patterns are evident. For average (median) households, the drop in consumption between the early 50s and the early 70s is greatest for couples, but the standard of living for single women is generally lowest at all ages. At the bottom of the distribution, single men also fare poorly at all ages. At the top of the distribution, single women have both a large drop and the lowest standard of living in retirement.

Once again it is important to note that these results are only a snapshot of one point in time, and hence they do not tell us about the circumstances of people who change household composition. It is likely that many of the patterns shown here reflect compositional differences across the age groups. For example, women who move from couple to single status probably have, on average, greater wealth than do long-term single women. The older single women shown in the figures will be a mixture of long-term single and recently widowed, which suggests that the long-term single will have lower living standards than will the average single woman.



Moreover, because the data only refer to a single time period, we cannot assume that the patterns observed at different ages are due to the ageing process as such. In general, younger cohorts are wealthier and so we might find that the living standards of the elderly will increase in future. Some information on cohort patterns of living standards is presented in Section 5; however, because we do not have longitudinal data, we cannot follow individuals as their household composition changes.

The remaining figures in this section show the distribution of equivalent total consumption disaggregated by education level. High education is defined as completion of Year 11 or above, and comprises about one-third of the population aged 50 years and over. Median equivalent total consumption is shown in Figure 6. High education couples in their 50s and 60s have substantially higher total consumption than do single men, women and the ‘other’ household types, but for ages 70 years and above the gap narrows considerably (with the exception of single men whose income rises at ages 70 years and above).15 Total consumption for couples and single women falls as people age, though the fall is steeper for couples.

This contrasts with the patterns for the elderly with low education, where couples’ income falls post-retirement while income of single men and women is relatively stable across all age groups. Thus, couples have substantially higher income than do single men and women at ages 50 to 59 years, which converges with single men and women at ages 70 years and over.

Figure 6: Median total consumption by household composition, age and education, 2005–06

Figure 6a: High education (Year 11 and above)

Age (years)

Med

ian

tota

l con

sum

ptio

n ($

) 1,1001,000

900800700600500400300200

50–59 60–69 70+


Figure 6b: Low education (Year 10 and below)

Age (years)

Med

ian

tota

l con

sum

ptio

n ($

) 1,1001,000

900800700600500400300200

50–59 60–69 70+



25


Figure 7 and Figure 8 show differences in the equivalent total consumption measure by education at the 25th and 75th percentile of each household type. At the 25th percentile, for couples with low education, total consumption falls somewhat with age, but it does not change for any other household types. For the elderly with high education the significant gap between couples and singles at age 50 to 59 years converges at age 70 years and over.

At the top of the income distribution (75th percentile), total consumption decreases with age for all household types and for those with both high and low education (with the exception of single men at age 70 years and over). Among the elderly with high education the gap between couples and single women widens considerably at age 60 to 69 years.

Figure 7: 25th percentile total consumption by household composition, age and education, 2005–06


Age (years)

Tota

l con

sum

ptio

n ($

)

1,1001,000

900800700600500400300200

50–59 60–69 70+



Age (years)

Tota

l con

sum

ptio

n ($

)

1,1001,000

900800700600500400300200

50–59 60–69 70+



Summarising these results, we find that couples (and ‘other’ household types) tend to have higher living standards than do single men and women in most age/education/income percentile groups. The situation of single men, however, is quite volatile, with some groups having relatively high living standards (for example, median single men aged 70 years and over). We should not place too much weight on this as there are only



about 40 single men aged 70 years and over with high education in the sample. Moreover, the higher mortality rate among men means that single men aged 70 years and over are a more selected population subgroup than are single women. Their higher income is thus more likely to be due to ‘survivor bias’—rich men being more likely to survive.

Comparing single women to couples, it is interesting to note that the gap between singles and couples is greater the higher their education. This is particularly noticeable at the top of the income distribution (Figure 8). However, in the absence of longitudinal data, we cannot discount the possibility that these patterns are due to differential patterns of marital separation and mortality in different income groups.

Figure 8: 75th percentile total consumption by household composition, age and education, 2005–06


Age (years)

Tota

l con

sum

ptio

n ($

)

1,1001,000

900800700600500400300200

50–59 60–69 70+



Age (years)

Tota

l con

sum

ptio

n ($

)

1,1001,000

900800700600500400300200

50–59 60–69 70+



27

TRENDS FROM 1988–89 TO 2007–08

5 Trends from 1988–89 to 2007–08

How has the relative economic position of the older population changed over time? Is the picture obtained from more comprehensive measures of living standards different from that given by disposable income?

We begin by examining the median living standards of people 65 years and over using the different income measures.16 These results are shown in Figure 9 for each of the HES years from 1988–89 to 2003–04, and the SIH from 2003–04 onwards.

Note that the 2003–04 SIH results are from the same survey as the HES, but the two surveys collect different information on housing costs.17 Both include rent and mortgage repayments, but the HES also includes repairs and maintenance and building insurance. Income after housing (DIaH) and total consumption (TC) are thus higher in the more recent observations based on the SIH.

Using all the measures, the median income for the older population has steadily increased since 1988–89, particularly in the last few years up to 2007–08. However, the growth in disposable income and disposable income after housing was relatively small during the first five-year period after 1988–89. This is due to the very high interest rates experienced at the end of the 1980s. Figure 10, for example, shows that the 90-day bank interest rate ranged from 13 to 18 per cent during 1988–89. In subsequent survey years, the rate was generally under 6 per cent. Since many older people have significant savings in bank deposits or related financial instruments, this meant that their incomes in 1988–89 were particularly high. These higher incomes, however, were not reflected in greater expenditures, and the median non-housing (NHX) and non-durable (NDX) expenditures were much lower in 1988–89 than they were in 1993–94.18

In the decade after 1993–94, all the income measures grew at a similar rate, around 18 to 20 per cent over the 10 years. Non-housing and non-durable expenditures, however, grew by only 10 per cent over this decade (expenditure growth was particularly low after 1998–99). After 2005–06, real disposable income (together with the other indicators that include this) then rose rapidly.

Figure 9: Median income of persons aged 65 years and over, by year (2005–06 equivalent $ per week)

Med

ian

inco

me

($ p

er w

eek) 500

450

400

350

300

250

200

1501985 1990 20001995 20102005

DI DIaH TC NDX NDX+HC NHX NHX+HC

Source: HES 1988–89 to 2003–04 and SIH 2003–04 to 2007–08.



Figure 10: 90-day bank bill interest rate, 1985–2009

Per c

ent

20.0

18.0

16.0

14.0

12.0

10.0

8.0

6.0

4.0

2.0

0.0

Jan 1985

Mar 1986

May 1987

Jul 1

988

Sep 1989

Nov 1990

Jan 1992

Mar 1993

May 1994

Jul 1

995

Sep 1996

Nov 1997

Jan 1999

Mar 2000

May 2001

Jan 2006

Mar 2007

May 2008

Jul 2

002

Sep 2003

Nov 2004

Source: Reserve Bank of Australia, data spreadsheet F01HIST.XLS.

The last two decades have been a period of strong income growth for all age groups. Has the older population kept up with the younger generation, however? Figure 11 shows the different measures of median income for the population aged 65 years and over relative to the overall population median. All these measures are adjusted for household size using the square-root equivalence scale. This assumes relatively high costs for large families when compared to the most common equivalence scales generally used, and so possibly overestimates the relative living standards of the elderly.

Despite this, the elderly have much lower levels of equivalent non-housing expenditure than do the non-elderly (the NHX ratio is around 55 per cent). This is mainly because they spend less on durable goods (the NDX ratio is much higher).

Among the income-based measures, the lowest ratio is for disposable income, where the median elderly person has an income of around 65 to 72 per cent of the overall population. Deducting housing costs reduces this gap, because housing costs are low for the elderly. The total consumption (TC) measure adds housing consumption to the DIaH measure. On this basis, elderly consumption levels are around 85 per cent of overall consumption (though the equivalence scale assumption must be borne in mind). Using the non-durable expenditure plus housing consumption measure (NDX+HC) gives them an even higher relative consumption level.

When considering the trends over time evident in Figure 11, the higher values for DI and DIaH in 1988–89 should largely be discounted as an aberration due to the high interest rates in that year (note that the expenditure series does not show this pattern). Between 1993–94 and 1998–99, the disposable income of the older population was constant relative to the overall population. After this, the relative position of the elderly fell, though with a slight increase after 2005–06. As shown in Figure 9, the real disposable income of the aged was rising strongly over the whole period, so the periods of declining relative income shown in Figure 11 reflect the even stronger growth in income among the workforce-age population.

29


Figure 11: Ratio of median income of persons aged 65 years and over to median income of all aged 15 years and over, by year

1.000.950.900.850.800.750.700.650.600.550.50

1985 1990 20001995 20102005

DI DIaH TC NDX NDX+HC NHX NHX+HC


After deducting housing costs, the DIaH measure shows a smaller drop in relative living standards after 1998–99, reflecting a greater increase in housing costs among the non-elderly.19

Overall, though, the different measures generally show a decrease in the relative living standards of the average person aged 65 years and over, particularly between 1998–99 and 2005–06. Despite the indexing of pensions to average earnings, the older population still fell behind the average household in this period of strong economic growth. This trend might, of course, now reverse as we re-enter a period of reduced economic growth—though the elderly might also suffer from decreases in investment income.

More detail on the changing relationship between median disposable income and age is shown in Figure 12. The pattern of rising incomes over time for all age groups is clear, with a particularly strong growth in the younger age groups—but also a substantial increase in income for the older groups in 2007–08.

This same data (for the four HES years) is re-presented in Figure 13 in cohort form. Each line represents the experiences of a given cohort—defined here by the cohort age in 2003–04. For example, the line corresponding to the legend entry ‘65–69’ represents people who were aged 65 to 69 years in 2003–04. The right-most point on this line in Figure 13 is the same as the ‘65–69’ point on the h2003–04 line in Figure 12. The next point to the left is the ‘60–64’ point from line h1998–99 in Figure 12 and so on. The age ‘50–54’ at the left-most point on the line indicates that this cohort was aged 50 to 54 years in 1988–89, and so on for each of the other lines. The youngest cohort shown in Figure 13, those aged 50 to 54 years in 2003–04, is indicated by a diamond.



Figure 12: Median disposable income by age

Age (years)

700

600

500

400

300

20050–54 55–59 60–64 65–69 70–74 75–79 80+

h1988–89 h1998–99h1993–94

h2003–04 i2005–06 i2007–08

Med

ian

disp

osab

le in

com

e ($

)

Source: HES 1988–89 to 2003–04 and SIH 2003–04 to 2007–08. h1988–89 represents 1988–89 HES and so on. i2005–06 represents 2005–06 SIH. The i2003–04 line is visually indistinguishable from the h2003–04 line and so is omitted. For the 1998–99 HES, the last data point is for people aged 75 years and over.

The line corresponding to the group aged 75 to 79 years in Figure 13 represents the situation of people who were aged 75 to 79 years in 2003–04, and hence aged 60 to 64 years in 1988–89. Their disposable income profile has been essentially flat over this period. This is the result of a combination of the falling age–income profile after age 60 years, as shown in Figure 12, and the rise in income at each age (also shown in Figure 12). Nonetheless, for the cohorts starting at earlier ages, a fall in cohort income with age is still apparent, despite income growth over time.20

Figure 13: Median disposable income by age in 2003–04

700

600

500

400

300

2001988–89 1993–94 1998–99 2003–04

70–7450–54 60–6455–59 65–69 75–79 80+

Med

ian

disp

osab

le in

com

e ($

)

Source: Calculated from Figure 12. Each line represents the median income of a given cohort. The cohort age in 2003–04 is indicated in the legend, while the cohort age for the first observation is indicated in the body of the figure. We do not include information for the cohorts at ages under 50 years.

31


Figure 14 shows trends in the median of the ADIaH measure, while Figure 15 shows the trends in the ATC measures (the unadjusted measures are similar). The age profiles of the measures that take housing into account are generally flatter, but the trends over time are similar to those found for disposable income.

The two expenditure-based measures show somewhat different patterns from each other. Figure 16 shows the changes across the different age groups for the non-housing expenditure plus housing consumption measure (NHX+HC). This is our most comprehensive expenditure-based measure of consumption. The same data is shown in Figure 17 in cohort form. Figure 17 shows a clear decline in cohort living standards across the retirement transition—though nowhere as dramatic as the fall in disposable income shown in Figure 13.

Figure 18 and Figure 19 show the corresponding information for the non-durable expenditure variable (NDX+HC). Here there is little reduction in consumption over the retirement period. The difference between this measure and NHX+HC is due to the exclusion of purchases of consumer durables, and hence the relative constancy of living standards is an artefact of the measure. Even though many durables purchased before retirement are likely to last well into the retirement phase, the quality of service obtained from them is likely to deteriorate as they age. This suggests that the average consumption level of cohorts is decreasing across the retirement transition, rather than holding steady.

Figure 14: Median adjusted disposable income after housing

700

600

500

400

300

20070–7450–54

h1988–89

i2003–04 i2005–06 i2007–08

h1993–94 h1998–99 h2003–04

60–6455–59 65–69

Age (years)

75–79 80+

Med

ian

adju

sted

dis

posa

ble

inco

me

($)




Figure 15: Median adjusted total consumption

700

600

500

400

300

20070–7450–54

i2003–04 i2005–06 i2007–08

h1993–94 h1998–99 h2003–04

60–6455–59 65–69

Age (years)

75–79 80+

Med

ian

adju

sted

tota

l con

sum

ptio

n ($

)


Figure 16: Median non-housing expenditures plus housing consumption

800

700

600

500

400

300

20070–7450–54

h1993–94 h1998–99 h2003–04

60–6455–59 65–69

Age (years)

75–79 80+

Med

ian

non-

hous

ing

expe

nditu

res

plus

ho

usin

g co

nsum

ptio

n ($

)

Source: HES 1993–94 to 2003–04.

33


Figure 17: Median non-housing expenditures plus housing consumption by age in 2003–04

800

700

600

500

400

300

2001993–94 1998–99 2003–04

Med

ian

non-

hous

ing

expe

nditu

res

plus

ho

usin

g co

nsum

ptio

n ($

)

70–7450–54 60–6455–59 65–69 75–79 80+

Source: Calculated from Figure 16.

Figure 18: Median non-durable expenditures plus housing consumption

700

600

500

400

300

20070–7450–54

h1993–94

60–6455–59 65–69

Age (years)

75–79 80+

h1998–99 h1998–99

Med

ian

non-

dura

ble

expe

nditu

res

plus

hou

sing

con

sum

ptio

n ($

)

Source: HES 1993–94 to 2003–04.



Figure 19: Median non-durable expenditures plus housing consumption by age in 2003–04

700

600

500

400

300

2001993–94 1998–99 2003–04

Med

ian

non-

dura

ble

expe

nditu

res

plus

ho

usin

g co

nsum

ptio

n ($

)

70–7450–54 60–6455–59 65–69 75–79 80+

Source: Calculated from Figure 18.

35

TRENDS IN MARKET AND TRANSFER INCOME SINCE 1988–89

6 Trends in market and transfer income since 1988–89

What have been the driving forces behind the growth in incomes of the elderly in recent years? In particular, what has been the role of market incomes and government transfers over this period? Figure 20 provides an overview of the impact of market and transfer incomes on the income trends of high-income and low-income people aged 65 years and over.

Figures 20a, 20b and 20c separate disposable income into market income (mainly investment, but also including some wage income), gross social transfers, and income taxation.21 In each panel, five lines present the situations of quintile groups of disposable income. The first quintile (q1) represents the one-fifth of the population aged 65 years and over with the lowest disposable income, q2 the next highest disposable income group, and so on. The quintile boundaries are shown in Table 7. They are calculated in equivalent dollars, and so, for example, the 80th percentile boundary of $508 for 2005–06 represents a household income of $825 for a couple-only household (825=508x20.7).

Table 7: Quintile boundaries of disposable income, people aged 65 years and over (2005–06 equivalent $ per week)

Percentile

Total n20th 40th 60th 80th 100th

HES 1988–89 210 236 278 395 2,119 1,858

HES 1993–94 225 247 291 368 4,007 2,254

HES 1998–99 231 271 323 426 2,794 1,814

HES 2003–04 249 291 358 495 4,536 2,071

SIH 2003–04 249 294 352 491 9,352 3,397

SIH 2005–06 259 304 374 508 8,061 3,182

SIH 2007–08 277 333 432 596 11,370 3,015

Figure 20a shows the mean market income in each quintile in each year divided by the mean disposable income of the quintile in that year. Figure 20b shows the corresponding gross social transfer share, and Figure 20c shows the income taxation share. Taking the negative of the taxation share, these shares add up to one across the three panels. For example, the top-left point in the first panel is the market share for q5 in 1988–89. Market income is 1.09 times disposable income for this group in this year. The corresponding social transfer share is 0.16 and the taxation share is 0.25. Adding these together produces the following equation: 1.09+0.16–0.25=1.00.



Figure 20: Ratio of mean market income, gross social transfers, and tax to mean disposable income by quintiles of disposable income, people aged 65 years and over

Figure 20a: Ratio of mean market income to disposable income

1.2

1.0

0.8

0.6

0.4

0.2

0.01985 1990 20001995 20102005

q1 (lowest) q3 q4q2 q5 (highest)

Figure 20b: Ratio of mean gross social transfers to disposable income

1.2

1.0

0.8

0.6

0.4

0.2

0.01985 1990 20001995 20102005


Figure 20c: Ratio of mean tax to disposable income

0.25

0.20

0.15

0.10

0.05

0.001985 1990 20001995 20102005



37

TRENDS IN MARKET AND TRANSFER INCOME SINCE 1988–89

Across the whole period, the bottom two quintiles received less than 20 per cent of their income from the market. For the top three quintiles, the market income share fell from 1988–89 to 1993–94 (reflecting the fall in interest rates) and then it rose thereafter.

The strong growth for the second-highest quintile, in particular, probably reflects increasing wealth in the top half of the income distribution driven in part by the growth of superannuation. Note also that the market income share of the middle quintile also began to grow after 2003–04.

The pattern for social transfers is largely the mirror image of that for market income. By 2003–04, the top two quintiles (of disposable income) were receiving less than half of their income in retirement from social transfers. After 1993–94, the absolute drop was largest for the second-highest quintile (from 66 to 46 per cent of income), though in proportionate terms the drop was greatest for the highest income quintile (halving over the period). The transfer share of the middle quintile also dropped over the period, to below 70 per cent in 2007–08.

Finally, though the bottom three quintiles have paid negligible tax over this period, the income tax share of the richest households has fluctuated significantly. The high proportion in 1988–89 again reflects high levels of interest income.

39

INEQUALITY AMONG THE OLDER POPULATION

7 Inequality among the older population

How has inequality among the elderly changed over time?

Figure 21 shows the ratio between the 10th and 50th percentiles of the different income measures, estimated over the population of people aged 65 years and over. This ratio is an indicator of how far the bottom of the income distribution is from the median older person. The trends vary somewhat according to the different measures of living standard used, but there are also common trends evident.

Setting aside the first year, where median incomes were high because of high interest rates, income inequality in the bottom half of the distribution steadily increased. In 1993–94 the 10th percentile had an adjusted disposable income of 83 per cent of the median household. By 2007–08 this had fallen to under 70 per cent. The fall was particularly large between 2005–06 and 2007–08.

Deducting housing costs does not change this picture (DIaH and ADIaH fall over time once we take account of the break in continuity in 2003–04). Similarly, the gap between the bottom and middle of non-housing and non-durable expenditure steadily widened up to 2003–04 (where the series finishes).22

The exceptions to this trend are the measures that take account of housing wealth. The total consumption ratio increased after 1993–94 but also declined after 2005–06. This result needs to be interpreted cautiously, however, as total consumption at the very bottom of the distribution includes few people with housing wealth, while the trends over time for the average household depend upon the appropriateness of the inflator used to convert wealth to consumption.

The corresponding results for the 25th percentile compared to the median are shown in Figure 22. Again, there has been a widening of the gap between the bottom and the middle for most measures, but this has been cushioned in the last few years by housing consumption.

The picture in the top half of the distribution is largely a mirror image (Figure 23 and Figure 24). Though income inequality among the elderly fell after the high interest rates of the late 1980s ended, it rose strongly thereafter. In the top half of the distribution the main change in the degree of inequality among the elderly was between 1998–99 and 2003–04.

Nonetheless, the large changes in income levels and inequality among the elderly associated with the high interest rates at the end of the 1980s suggests caution in assuming that these changes in inequality among the aged population represent a long-term trend. It is possible that the turmoil in financial markets in 2009 will reverse some of the changes that occurred during the previous economic boom years.



Figure 21: P10/50 percentile ratio for persons aged 65 years and over, by year

0.85

0.80

0.75

0.70

0.65

0.60

0.55

0.50

0.45

0.40

0.351985 1990 1995 2000 2005 2010

TCDI DIaHADI ADIaH

ATC NDX+HC NHX NHX+HCNDX



0.85

0.80

0.75

0.70

0.65

0.601985 1990 1995 2000 2005 2010

TCDI DIaH NDX+HC NHX NHX+HCNDX


41

INEQUALITY AMONG THE OLDER POPULATION


1.80

1.70

1.60

1.50

1.40

1.30

1.201985 1990 1995 2000 2005 2010

NDX+HCDI DIaH TC NHX NHX+HCNDX



2.90

2.70

2.50

2.30

2.10

1.90

1.701985 1990 1995 2000 2005 2010

NDX+HCDI DIaH TC NHX NHX+HCNDX


43

CONCLUSIONS

8 Conclusions

What do these different measures of economic living standards tell us about recent trends and patterns in the wellbeing of the older population in Australia? The key findings of the report can be summarised under three headings—housing and the measurement of living standards; cohort living standards and the retirement-consumption puzzle; and the variations within the older population.

8.1 Housing and the measurement of living standards

Taking account of housing consumption is clearly important when comparing the living standards of households living in different housing tenures. However, it can also be important when, as detailed in this report, the focus is on patterns and trends for the whole population.

When comparing the living standards of pre-retirement and post-retirement populations, income data on its own overstates the fall in consumption associated with retirement. Since the elderly are more likely to own their home, and less likely to be making mortgage repayments, their living standard is substantially higher than implied by income measures alone.

Moreover, within the older population, measures that do not take account of housing consumption overstate the degree of inequality at the top end of the distribution, but understate it at the bottom end. The first result stems from the less-than-perfect correlation between housing wealth and income, and the second result arises because a small but significant fraction of the elderly population have both low incomes and substantial rent expenditures.

There remains scope, however, for further work on fully understanding the differences in results obtained between income and expenditure-based measures of household consumption.

8.2 Cohort living standards and the retirement-consumption puzzle

Even using our more comprehensive measures of living standards, however, we still find that the average living standards decrease as age increases in Australia. The decline is less at the bottom of the income distribution where incomes are cushioned by the Age Pension. Though conclusions such as this are sensitive to the equivalence scale, the one we use is likely, if anything, to overestimate the relative living standards of the elderly.

At the same time, however, there has been steady growth in the living standards of people at each age. This has also occurred for the elderly, though generally at a slower rate than for the overall population. An important exception is at the beginning of our period, in 1988–89, when high interest rates led to unusually high incomes (but not expenditures) among the older population.

This income growth has moderated the impact of age-related income falls for specific cohorts. In terms of disposable income, most of the income drop for each cohort appears up to age 60 to 64 years. After that point, median incomes are relatively flat. In terms of non-housing expenditure, there is a steady but relatively small fall in expenditure across the whole retirement period. Most of this appears to be due to reductions in expenditures on durable goods.

This experience over a period of strong economic growth raises questions about how we should think of consumption in old age. If community incomes are growing strongly is it reasonable to expect that the standard of living of the elderly should stand still? If we accept this, then the expenditure data reported here come close to explaining the retirement-consumption puzzle. If we take account of changing preferences for durable goods, then consumption is roughly constant over retirement. However, if we do not accept that the elderly should be left behind as general living standards rise, then the puzzle remains incomplete and so does the policy challenge.



8.3 Variations within the older population

The data investigated here confirm that women tend to have lower consumption in retirement because of their greater longevity and lower lifetime employment income. Though the drop in average consumption for those aged between the early 50s and early 70s is greatest for couples, single women have the lowest average standard of living at all ages. For older women, the income disparity between being single and being partnered is greater the higher their education level. The bottom half of the single male distribution also has a relatively low standard of living. Some single men have a relatively high standard of living, but the sample size is very small for this group.

However, comparisons of this type are complicated by variations in patterns of separation, widowhood and mortality. Further expansion of longitudinal datasets, such as the HILDA survey, will permit this to be investigated in more detail.

Since the early 1990s, the income sources of the elderly have changed substantially in Australia. In particular, the share of disposable income received from the market has steadily increased for the top three quintiles of the elderly.

This has been associated with a growth of inequality among the aged population. In 1993–94 the 10th percentile had an adjusted disposable income of 83 per cent of the median household. By 2007–08 this has fallen to under 70 per cent. The fall has been particularly large over the last two years. Similarly, the 75th and 90th percentile households also moved away from the median household over this period as they became wealthier. The picture is somewhat different when consumption of services from housing wealth is taken into account. This appears to have had an equalising tendency after 1993–94 (particularly at the bottom of the income distribution), but between 2005–06 and 2007–08 inequality increased.

Nonetheless, the large changes in income levels and inequality among the elderly associated with the high interest rates at the end of the 1980s suggests caution in assuming that these changes in inequality among the aged population represent a long-term trend. Subsequent to the data analysed in this report, there have been significant increases in Age Pension rates (particularly for singles), economic upheaval associated with the global financial crisis and the continuing development of the superannuation system in Australia.

45

APPENDIX A

Appendix A: Rationale for and calculation of adjusted disposable income (ADI)

The rationale for this adjustment flows from the basic entitlement features of the Age Pension. To receive the full rate of pension, older people must meet three main requirements:

◗◗ be over the qualifying age threshold (65 years for men, 60 to 63 years for women)23

◗◗ have been a permanent resident of Australia for at least 10 years (with some exceptions)

◗◗ have income and assets below certain thresholds (the pension is gradually reduced as income and/or assets increase beyond these thresholds).

By setting adjusted disposable income (ADI) at the maximum of either the base pension rate or the actual disposable income (for people over the age threshold), we are effectively assuming that those who do not meet the residence requirements have other forms of support, and that those with other income and assets have sufficient resources to lift them up to the pension standard of living. These are reasonable assumptions, although they are not unchallengeable. When older migrants come to Australia they are generally required to prove they have some form of family support. Similarly, if the income and assets assessed for pension eligibility are available for consumption, then people with pensions reduced under these tests should at least be able to meet the pension standard of living.

The assumptions underlying the use of the ADI measure will lead to an overestimate of current living standards if non-residents are not receiving family support, and if the assets that exclude a person from eligibility cannot be liquidated (for example, a family farm). This adjustment has no impact upon measured living standards above the level of the base pension, even if this income is under or overreported.

The ADI adjustment used here is quite simple. The adjustment is undertaken for income units24 where either person is over Age Pension age. Income unit disposable income is increased to be not less than either the single or couple base rate of pension (as appropriate), including the Pharmaceutical Allowance. We do not include the incomes of dependent children in this measure of income unit disposable income and we ignore the impact of rent allowance. Income unit incomes are then aggregated to form household adjusted disposable income.

47

APPENDIX B

Appendix B: Non-durable expenditures

Our measure of non-durable expenditures (NDX) is derived from selected items of the following expenditure categories:

EXP01. Current housing costsWe exclude all items.EXP02. Fuel and powerWe include all items.EXP03. Food and non-alcoholic beveragesWe include all items.EXP04. Alcoholic beveragesWe include all items.EXP05. TobaccoWe include all items.EXP06. Clothing and footwearWe exclude most items except clothing and footwear service items: dry cleaning and laundering, clothing repairs, footwear repairs, hiring of clothing and footwear.EXP07. Household furnishings and equipmentWe exclude all items.EXP08. Household services and operationsWe include all items.EXP09. Medical care and expensesWe include all items.EXP10. TransportWe include most items except motor vehicle and other vehicle purchase items: purchase of motor vehicles, motorcycles, caravans, trailers, bicycles.EXP11. RecreationWe include most items except television and other audiovisual equipment items and recreational equipment items: television, television aerial, radio/stereo/hi-fi equipment, video cassette recorder and equipment, home computer equipment and software, television and computer games, musical instruments and accessories, purchase of boats, parts and operation, purchase of aircraft, parts and operation, camping equipment, sport equipment not elsewhere classified (n.e.c), recreational equipment n.e.c., animal purchases. Gambling expenditures are modified so winners are all assumed to have the same average expenditures as losers, while all expenditures are scaled to keep mean net returns identical to the original. Average expenditure for casino games is actually negative so we remove this expenditure from our calculation.EXP12. Personal care itemsWe include all items.EXP13. Miscellaneous goods and servicesWe include most items except watches and clocks, jewellery, travel goods, handbags, umbrellas, wallets and related goods.EXP14 to EXP17. Selected other payments (income tax, mortgage principal repayments, other capital housing costs, superannuation and life insurance)We exclude all items.

We assign a value of 1 to all items included as non-durable expenditures at the expenditure level, and calculate the sum of these expenditures aggregated to the household level to create a non-durable expenditure measure.

49

APPENDIX C

Appendix C: Mean income by age group and year of survey, population aged 15 years and over (2005–06 equivalent $ per week)

Table C1: Disposable income (DI)

Age

(years)

HES

1988–89

HES

1993–94

HES

1998–99

HES

2003–04

SIH

2003–04

SIH

2005–06

SIH

2007–08

$(a) n $(a) n $(a) n $(a) n $(a) n $(a) n $(a) n

15–19 359 6,862 428 1,620 461 1,303 525 1,150 520 1,877 558 1,523 628 1,555

20–24 532 1,150 518 1,708 569 1,156 591 1,060 601 1,704 649 1,473 765 1,448

25–29 498 1,684 512 1,705 562 1,283 647 1,047 647 1,702 688 1,408 784 1,470

30–34 413 1,616 454 1,879 513 1,396 578 1,284 577 2,044 637 1,753 681 1,500

35–39 395 1,634 428 1,778 481 1,548 526 1,351 522 2,162 569 1,725 684 1,691

40–44 453 1,563 473 1,739 485 1,398 533 1,409 539 2,254 583 1,801 676 1,659

45–49 509 1,082 520 1,560 554 1,313 593 1,257 592 2,081 677 1,812 707 1,698

50–54 525 928 530 1,173 584 1,190 633 1,151 618 1,914 665 1,655 802 1,594

55–59 466 830 419 946 497 844 555 1,069 575 1,755 653 1,650 751 1,446

60–64 372 897 378 909 394 719 482 877 474 1,396 574 1,208 653 1,228

65–69 330 705 323 784 359 622 422 670 423 1,104 440 975 516 939

70–74 320 557 304 709 343 539 382 560 405 886 407 840 479 774

75–79 332 370 310 404338 653

390 466 380 783 410 669 433 638

80+ 315 226 317 357 386 375 389 624 411 698 454 664

All 412 20,104 449 17,271 490 13,964 542 13,726 543 22,286 594 19,190 676 18,304

(a) 2005–06 equivalent $ per week.

Note: In the 1998–99 HES, the oldest age group is 75 years and over.



Table C2: Adjusted disposable income (ADI)

Age

(years)

HES

1988–89

HES

1993–94

HES

1998–99

HES

2003–04

SIH

2003–04

SIH

2005–06

SIH

2007–08

$(a) n $(a) n $(a) n $(a) n $(a) n $(a) n $(a) n

15–19 359 6,862 429 1,620 461 1,303 525 1,150 520 1,877 558 1,523 628 1,555

20–24 532 1,150 519 1,708 569 1,156 591 1,060 601 1,704 649 1,473 765 1,448

25–29 499 1,684 513 1,705 563 1,283 647 1,047 648 1,702 688 1,408 784 1,470

30–34 414 1,616 454 1,879 513 1,396 578 1,284 577 2,044 637 1,753 682 1,500

35–39 396 1,634 429 1,778 481 1,548 527 1,351 522 2,162 571 1,725 685 1,691

40–44 453 1,563 473 1,739 486 1,398 534 1,409 539 2,254 584 1,801 677 1,659

45–49 509 1,082 520 1,560 554 1,313 593 1,257 592 2,081 677 1,812 707 1,698

50–54 525 928 531 1,173 585 1,190 633 1,151 618 1,914 666 1,655 803 1,594

55–59 467 830 421 946 497 844 556 1,069 575 1,755 654 1,650 752 1,446

60–64 377 897 388 909 399 719 486 877 479 1,396 577 1,208 656 1,228

65–69 337 705 333 784 368 622 430 670 430 1,104 449 975 525 939

70–74 324 557 311 709 350 539 389 560 412 886 414 840 486 774

75–79 336 370 316 404346 653

394 466 385 783 418 669 439 638

80+ 319 226 325 357 394 375 398 624 417 698 463 664

All 413 20,104 451 17,271 491 13,964 543 13,726 544 22,286 596 19,190 678 18,304



51

APPENDIX C

Table C3: Disposable income after housing (DIaH)

Age

(years)

HES

1988–89

HES

1993–94

HES

1998–99

HES

2003–04

SIH

2003–04

SIH

2005–06

SIH

2007–08

$(a) n $(a) n $(a) n $(a) n $(a) n $(a) n $(a) n

15–19 300 6,862 365 1,620 395 1,303 443 1,150 447 1,877 474 1,523 538 1,555

20–24 446 1,150 432 1,708 482 1,156 486 1,060 502 1,704 549 1,473 654 1,448

25–29 402 1,684 403 1,705 445 1,283 500 1,047 512 1,702 543 1,408 627 1,470

30–34 328 1,616 347 1,879 400 1,396 433 1,284 445 2,044 490 1,753 525 1,500

35–39 324 1,634 340 1,778 379 1,548 403 1,351 410 2,162 444 1,725 536 1,691

40–44 387 1,563 395 1,739 396 1,398 423 1,409 440 2,254 471 1,801 550 1,659

45–49 449 1,082 444 1,560 475 1,313 494 1,257 503 2,081 569 1,812 596 1,698

50–54 477 928 469 1,173 513 1,190 538 1,151 537 1,914 574 1,655 705 1,594

55–59 428 830 370 946 437 844 481 1,069 515 1,755 579 1,650 672 1,446

60–64 333 897 334 909 348 719 425 877 432 1,396 521 1,208 595 1,228

65–69 294 705 284 784 315 622 371 670 391 1,104 404 975 476 939

70–74 290 557 268 709 304 539 333 560 374 886 373 840 448 774

75–79 297 370 268 404298 653

347 466 351 783 378 669 399 638

80+ 281 226 277 357 333 375 359 624 381 698 417 664

All 350 20,104 375 17,271 410 13,964 444 13,726 458 22,286 499 19,190 573 18,304





Table C4: Adjusted disposable income after housing (ADIaH)

Age

(years)

HES

1988–89

HES

1993–94

HES

1998–99

HES

2003–04

SIH

2003–04

SIH

2005–06

SIH

2007–08

$(a) n $(a) n $(a) n $(a) n $(a) n $(a) n $(a) n

15–19 300 6,862 366 1,620 395 1,303 443 1,150 447 1,877 475 1,523 538 1,555

20–24 446 1,150 433 1,708 482 1,156 486 1,060 503 1,704 549 1,473 654 1,448

25–29 403 1,684 404 1,705 445 1,283 501 1,047 512 1,702 543 1,408 627 1,470

30–34 328 1,616 347 1,879 401 1,396 434 1,284 446 2,044 491 1,753 526 1,500

35–39 325 1,634 341 1,778 380 1,548 404 1,351 410 2,162 445 1,725 537 1,691

40–44 387 1,563 395 1,739 397 1,398 423 1,409 441 2,254 472 1,801 550 1,659

45–49 449 1,082 445 1,560 475 1,313 494 1,257 503 2,081 569 1,812 596 1,698

50–54 477 928 469 1,173 513 1,190 539 1,151 537 1,914 575 1,655 706 1,594

55–59 428 830 372 946 438 844 481 1,069 516 1,755 580 1,650 673 1,446

60–64 338 897 343 909 352 719 429 877 437 1,396 524 1,208 598 1,228

65–69 300 705 294 784 322 622 378 670 398 1,104 412 975 485 939

70–74 293 557 274 709 310 539 339 560 381 886 380 840 455 774

75–79 301 370 274 404305 653

350 466 356 783 385 669 404 638

80+ 284 226 283 357 340 375 367 624 387 698 425 664

All 351 20,104 377 17,271 412 13,964 446 13,726 459 22,286 501 19,190 575 18,304



53

APPENDIX C

Table C5: Total consumption (TC)

Age

(years)

HES

1988–89

HES

1993–94

HES

1998–99

HES

2003–04

SIH

2003–04

SIH

2005–06

SIH

2007–08

$(a) n $(a) n $(a) n $(a) n $(a) n $(a) n $(a) n

15–19 n.a. 6,862 433 1,620 461 1,303 533 1,150 537 1,877 574 1,523 643 1,555

20–24 n.a. 1,150 482 1,708 539 1,156 589 1,060 608 1,704 659 1,473 780 1,448

25–29 n.a. 1,684 457 1,705 496 1,283 604 1,047 620 1,702 662 1,408 756 1,470

30–34 n.a. 1,616 405 1,879 464 1,396 534 1,284 550 2,044 602 1,753 645 1,500

35–39 n.a. 1,634 409 1,778 449 1,548 503 1,351 513 2,162 555 1,725 660 1,691

40–44 n.a. 1,563 478 1,739 475 1,398 524 1,409 545 2,254 584 1,801 674 1,659

45–49 n.a. 1,082 539 1,560 563 1,313 605 1,257 613 2,081 686 1,812 727 1,698

50–54 n.a. 928 572 1,173 620 1,190 660 1,151 660 1,914 706 1,655 849 1,594

55–59 n.a. 830 470 946 546 844 617 1,069 654 1,755 723 1,650 838 1,446

60–64 n.a. 897 447 909 459 719 564 877 572 1,396 669 1,208 762 1,228

65–69 n.a. 705 403 784 436 622 515 670 537 1,104 554 975 639 939

70–74 n.a. 557 389 709 429 539 469 560 513 886 516 840 609 774

75–79 n.a. 370 390 404428 653

495 466 500 783 529 669 553 638

80+ n.a. 226 397 357 485 375 514 624 522 698 585 664

All n.a. 20,104 457 17,271 494 13,964 559 13,726 574 22,286 622 19,190 710 18,304


Note: n.a. denotes not available.

In the 1998–99 HES, the oldest age group is 75 years and over.



Table C6: Adjusted total consumption (ATC)

Age

(years)

HES

1988–89

HES

1993–94

HES

1998–99

HES

2003–04

SIH

2003–04

SIH

2005–06

SIH

2007–08

$(a) n $(a) n $(a) n $(a) n $(a) n $(a) n $(a) n

15–19 n.a. 6,862 434 1,620 461 1,303 534 1,150 537 1,877 574 1,523 643 1,555

20–24 n.a. 1,150 483 1,708 539 1,156 589 1,060 609 1,704 659 1,473 780 1,448

25–29 n.a. 1,684 457 1,705 496 1,283 605 1,047 621 1,702 663 1,408 756 1,470

30–34 n.a. 1,616 406 1,879 465 1,396 534 1,284 551 2,044 602 1,753 646 1,500

35–39 n.a. 1,634 409 1,778 449 1,548 503 1,351 513 2,162 556 1,725 661 1,691

40–44 n.a. 1,563 478 1,739 475 1,398 524 1,409 545 2,254 585 1,801 675 1,659

45–49 n.a. 1,082 539 1,560 563 1,313 605 1,257 613 2,081 686 1,812 727 1,698

50–54 n.a. 928 572 1,173 620 1,190 660 1,151 660 1,914 706 1,655 849 1,594

55–59 n.a. 830 471 946 547 844 618 1,069 655 1,755 724 1,650 839 1,446

60–64 n.a. 897 457 909 464 719 568 877 576 1,396 672 1,208 765 1,228

65–69 n.a. 705 413 784 445 622 523 670 544 1,104 562 975 647 939

70–74 n.a. 557 395 709 436 539 475 560 521 886 523 840 616 774

75–79 n.a. 370 396 404436 653

499 466 505 783 536 669 558 638

80+ n.a. 226 404 357 493 375 523 624 528 698 593 664

All n.a. 20,104 459 17,271 496 13,964 560 13,726 576 22,286 624 19,190 712 18,304




55

APPENDIX C

Table C7: Non-housing expenditure (NHX)

Age

(years)

HES

1988–89

HES

1993–94

HES

1998–99

HES

2003–04

SIH

2003–04

SIH

2005–06

SIH

2007–08

$(a) n $(a) n $(a) n $(a) n $(a) n $(a) n $(a) n

15–19 441 6,862 551 1,620 582 1,303 663 1,150 n.a. 1,877 n.a. 1,523 n.a. 1,555

20–24 610 1,150 606 1,708 656 1,156 669 1,060 n.a. 1,704 n.a. 1,473 n.a. 1,448

25–29 615 1,684 606 1,705 663 1,283 724 1,047 n.a. 1,702 n.a. 1,408 n.a. 1,470

30–34 507 1,616 569 1,879 618 1,396 677 1,284 n.a. 2,044 n.a. 1,753 n.a. 1,500

35–39 487 1,634 555 1,778 617 1,548 642 1,351 n.a. 2,162 n.a. 1,725 n.a. 1,691

40–44 566 1,563 624 1,739 627 1,398 675 1,409 n.a. 2,254 n.a. 1,801 n.a. 1,659

45–49 619 1,082 657 1,560 700 1,313 746 1,257 n.a. 2,081 n.a. 1,812 n.a. 1,698

50–54 631 928 668 1,173 730 1,190 752 1,151 n.a. 1,914 n.a. 1,655 n.a. 1,594

55–59 583 830 534 946 639 844 705 1,069 n.a. 1,755 n.a. 1,650 n.a. 1,446

60–64 452 897 519 909 504 719 580 877 n.a. 1,396 n.a. 1,208 n.a. 1,228

65–69 403 705 383 784 437 622 485 670 n.a. 1,104 n.a. 975 n.a. 939

70–74 309 557 322 709 360 539 426 560 n.a. 886 n.a. 840 n.a. 774

75–79 303 370 298 404328 653

385 466 n.a. 783 n.a. 669 n.a. 638

80+ 274 226 284 357 341 375 n.a. 624 n.a. 698 n.a. 664

All 498 20,104 556 17,271 599 13,964 645 13,726 n.a. 22,286 n.a. 19,190 n.a. 18,304






Table C8: Non-housing expenditure plus housing consumption (NHX+HC)

Age

(years)

HES

1988–89

HES

1993–94

HES

1998–99

HES

2003–04

SIH

2003–04

SIH

2005–06

SIH

2007–08

$(a) n $(a) n $(a) n $(a) n $(a) n $(a) n $(a) n

15–19 n.a. 6,862 618 1,620 649 1,303 754 1,150 n.a. 1,877 n.a. 1,523 n.a. 1,555

20–24 n.a. 1,150 657 1,708 712 1,156 773 1,060 n.a. 1,704 n.a. 1,473 n.a. 1,448

25–29 n.a. 1,684 660 1,705 715 1,283 828 1,047 n.a. 1,702 n.a. 1,408 n.a. 1,470

30–34 n.a. 1,616 627 1,879 682 1,396 779 1,284 n.a. 2,044 n.a. 1,753 n.a. 1,500

35–39 n.a. 1,634 624 1,778 688 1,548 743 1,351 n.a. 2,162 n.a. 1,725 n.a. 1,691

40–44 n.a. 1,563 707 1,739 706 1,398 778 1,409 n.a. 2,254 n.a. 1,801 n.a. 1,659

45–49 n.a. 1,082 751 1,560 790 1,313 857 1,257 n.a. 2,081 n.a. 1,812 n.a. 1,698

50–54 n.a. 928 771 1,173 835 1,190 874 1,151 n.a. 1,914 n.a. 1,655 n.a. 1,594

55–59 n.a. 830 635 946 747 844 842 1,069 n.a. 1,755 n.a. 1,650 n.a. 1,446

60–64 n.a. 897 632 909 616 719 718 877 n.a. 1,396 n.a. 1,208 n.a. 1,228

65–69 n.a. 705 500 784 558 622 623 670 n.a. 1,104 n.a. 975 n.a. 939

70–74 n.a. 557 440 709 483 539 560 560 n.a. 886 n.a. 840 n.a. 774

75–79 n.a. 370 419 404458 653

532 466 n.a. 783 n.a. 669 n.a. 638

80+ n.a. 226 404 357 492 375 n.a. 624 n.a. 698 n.a. 664

All n.a. 20,104 638 17,271 683 13,964 759 13,726 n.a. 22,286 n.a. 19,190 n.a. 18,304




57

APPENDIX C

Table C9: Non-durable expenditure (NDX)

Age

(years)

HES

1988–89

HES

1993–94

HES

1998–99

HES

2003–04

SIH

2003–04

SIH

2005–06

SIH

2007–08

$(a) n $(a) n $(a) n $(a) n $(a) n $(a) n $(a) n

15–19 241 6,862 303 1,620 322 1,303 350 1,150 n.a. 1,877 n.a. 1,523 n.a. 1,555

20–24 332 1,150 331 1,708 359 1,156 366 1,060 n.a. 1,704 n.a. 1,473 n.a. 1,448

25–29 306 1,684 308 1,705 326 1,283 372 1,047 n.a. 1,702 n.a. 1,408 n.a. 1,470

30–34 260 1,616 278 1,879 297 1,396 326 1,284 n.a. 2,044 n.a. 1,753 n.a. 1,500

35–39 254 1,634 277 1,778 298 1,548 314 1,351 n.a. 2,162 n.a. 1,725 n.a. 1,691

40–44 294 1,563 310 1,739 315 1,398 343 1,409 n.a. 2,254 n.a. 1,801 n.a. 1,659

45–49 324 1,082 342 1,560 361 1,313 380 1,257 n.a. 2,081 n.a. 1,812 n.a. 1,698

50–54 336 928 350 1,173 384 1,190 388 1,151 n.a. 1,914 n.a. 1,655 n.a. 1,594

55–59 310 830 315 946 357 844 386 1,069 n.a. 1,755 n.a. 1,650 n.a. 1,446

60–64 269 897 315 909 311 719 358 877 n.a. 1,396 n.a. 1,208 n.a. 1,228

65–69 237 705 263 784 289 622 330 670 n.a. 1,104 n.a. 975 n.a. 939

70–74 205 557 237 709 258 539 291 560 n.a. 886 n.a. 840 n.a. 774

75–79 197 370 213 404230 653

265 466 n.a. 783 n.a. 669 n.a. 638

80+ 183 226 208 357 227 375 n.a. 624 n.a. 698 n.a. 664

All 268 20,104 301 17,271 321 13,964 346 13,726 n.a. 22,286 n.a. 19,190 n.a. 18,304






Table C10: Non-durable expenditure plus housing consumption (NDX+HC)

Age

(years)

HES

1988–89

HES

1993–94

HES

1998–99

HES

2003–04

SIH

2003–04

SIH

2005–06

SIH

2007–08

$(a) n $(a) n $(a) n $(a) n $(a) n $(a) n $(a) n

15–19 n.a. 6,862 372 1,620 388 1,303 442 1,150 n.a. 1,877 n.a. 1,523 n.a. 1,555

20–24 n.a. 1,150 383 1,708 416 1,156 471 1,060 n.a. 1,704 n.a. 1,473 n.a. 1,448

25–29 n.a. 1,684 362 1,705 378 1,283 478 1,047 n.a. 1,702 n.a. 1,408 n.a. 1,470

30–34 n.a. 1,616 338 1,879 362 1,396 431 1,284 n.a. 2,044 n.a. 1,753 n.a. 1,500

35–39 n.a. 1,634 347 1,778 369 1,548 415 1,351 n.a. 2,162 n.a. 1,725 n.a. 1,691

40–44 n.a. 1,563 395 1,739 395 1,398 448 1,409 n.a. 2,254 n.a. 1,801 n.a. 1,659

45–49 n.a. 1,082 438 1,560 452 1,313 493 1,257 n.a. 2,081 n.a. 1,812 n.a. 1,698

50–54 n.a. 928 455 1,173 493 1,190 511 1,151 n.a. 1,914 n.a. 1,655 n.a. 1,594

55–59 n.a. 830 417 946 468 844 527 1,069 n.a. 1,755 n.a. 1,650 n.a. 1,446

60–64 n.a. 897 429 909 424 719 500 877 n.a. 1,396 n.a. 1,208 n.a. 1,228

65–69 n.a. 705 382 784 412 622 475 670 n.a. 1,104 n.a. 975 n.a. 939

70–74 n.a. 557 357 709 384 539 428 560 n.a. 886 n.a. 840 n.a. 774

75–79 n.a. 370 335 404361 653

414 466 n.a. 783 n.a. 669 n.a. 638

80+ n.a. 226 328 357 381 375 n.a. 624 n.a. 698 n.a. 664

All n.a. 20,104 384 17,271 406 13,964 463 13,726 n.a. 22,286 n.a. 19,190 n.a. 18,304




59

APPENDIX D

Appendix D: Additional figures

Figure D1: Median, 25th and 75th percentile adjusted disposable income by household composition and age, 2005–06

Figure D1a: Median

Age (years)

Adj

uste

d di

spos

able

inco

me

($)

900800700600500400300200100

50–54 55–59 60–64 65–69 70–74 75–79 80+


Figure D1b: 25th percentile

Age (years)

Adj

uste

d di

spos

able

inco

me

($)

900800700600500400300200100

50–54 55–59 60–64 65–69 70–74 75–79 80+




Figure D1c: 75th percentile

Age (years)

Adj

uste

d di

spos

able

inco

me

($)

900800700600500400300200100

50–54 55–59 60–64 65–69 70–74 75–79 80+



Figure D2: Median, 25th and 75th percentile adjusted disposable income after housing by household composition and age, 2005–06

Figure D2a: Median

Age (years)

Adj

uste

d di

spos

able

inco

me

afte

r hou

sing

($)

900800700600500400300200100

50–54 55–59 60–64 65–69 70–74 75–79 80+


61

APPENDIX D


Age (years)

Adj

uste

d di

spos

able

inco

me

afte

r hou

sing

($)

900800700600500400300200100

50–54 55–59 60–64 65–69 70–74 75–79 80+



Age (years)

Adj

uste

d di

spos

able

inco

me

afte

r hou

sing

($)

900800700600500400300200100

50–54 55–59 60–64 65–69 70–74 75–79 80+





Figure D3: Median, 25th and 75th percentile adjusted total consumption by household composition and age, 2005–06

Figure D3a: Median

Age (years)

Adj

uste

d to

tal c

onsu

mpt

ion

($)

900800700600500400300200100

50–54 55–59 60–64 65–69 70–74 75–79 80+



Age (years)

Adj

uste

d to

tal c

onsu

mpt

ion

($)

900800700600500400300200100

50–54 55–59 60–64 65–69 70–74 75–79 80+


63

APPENDIX D


Age (years)

Adj

uste

d to

tal c

onsu

mpt

ion

($)

900800700600500400300200100

50–54 55–59 60–64 65–69 70–74 75–79 80+



65

LIST OF SHORTENED FORMS

List of shortened forms

ABS Australian Bureau of StatisticsADI adjusted disposable incomeADIaH adjusted disposable income after housingATC adjusted total consumptionDI disposable incomeDIaH disposable income after housingHC housing consumptionHES Household Expenditure SurveyNDX non-durable expenditureNDX+HC non-durable expenditure plus housing consumptionNHX non-housing expenditureNHX+HC non-housing expenditure plus housing consumptionSIH Survey of Income and HousingTC total consumption

67

ENDNOTES

Endnotes

1 See Saunders and Siminski (2005) for a survey of these imputation methods.

2 Bradbury (2008a, 2008b) shows that the average housing share of consumption steadily increases with age in most countries.

3 To keep the focus on income and housing, we ignore leisure, home production and services received directly from the state. Partly, this is because of valuation problems (particularly with respect to home production and leisure); partly it is to simplify the presentation of the role of housing costs and to permit a focus on them; and partly it is because of the conceptual difficulties in taking account of the needs for non-cash services in different household types. In relation to this latter point, older people receive more non-cash health services, but this is because their health needs are greater. Taking account of the resource flows, while ignoring the need differences, would lead to a biased picture of the relative living standards of young and old. Indeed, if the additional health care services received by the elderly simply reflected their additional needs, then the best indicator of their relative living standards would be to ignore health care services.

4 That is, disposable income plus imputed rent is defined as disposable income + imputed gross rent – mortgage interest payments. Our ‘total consumption’ measure is defined as disposable income + imputed gross rent – mortgage interest and principal payments. (In both cases, maintenance and similar costs are treated the same as interest where available.)

5 There are some differences between the HES and the 2003–04 SIH in their income measures (even though they were collected at the same time and the samples partly overlap). The HES income measure includes some sources of income that are only recorded in the HES diaries (such as employee income in kind, income from goods received from own unincorporated business and children’s income). Also, the HES records current income from own unincorporated business and investments using per financial year data, while the 2003–04 SIH records it as reported. In the 2005–06 and 2007–08 SIH, we use the income measure designed to be comparable to the 2003–04 SIH. The 2005–06 and 2007–08 SIH incorporate improved estimates of family tax benefits. The 2007–08 SIH additionally incorporates improved reported income from trusts and the inclusion of broader measures of income from family members outside the household instead of restricting to regular cash income from persons outside the household.

6 The DI variable also has negatives set to zero, but at the household level.

7 In the data from the HES, we define housing costs as household expenditure on current housing costs for their dwelling (not for second dwellings), plus household expenditure on mortgage repayments for the dwelling. This definition includes: rent, mortgage interest, rates, water and sewerage rates and charges, land tax, insurance (both dwelling and contents—because not separately recorded), repairs and maintenance, loans for alternations and additions, body corporate payments, plus mortgage principal repayments. (In the 1988–89, 1993–94, 1998–99 and 2003–04 HES Confidentialised Unit Record Files, our housing cost definition is equal to the sum of the exp01 and exp15 variables.) The SIH housing-cost measure does not include costs associated with repairs and maintenance, or dwelling insurance. We do not include other capital expenditures such as renovations.

8 This information is not available for SIH. For the 2003–04 survey, the mean value of government rental subsidy from the 2003–04 Fiscal Incidence Study (FIS) (estimated for the HES sub-sample) is added to current weekly rent paid. For the 2005–06 and 2007–08 SIH the mean value of government rental subsidy from the 2003–04 FIS is inflated to 2005–06 and 2007–08 prices using the national rent price index in the Consumer Price Index.



9 These are about 2 per cent of the population aged 15 years and above for every HES and SIH survey year. Note that our analysis is conducted at the household level. The background paper for the Harmer Review shows that there are substantial numbers of non-home owner Age Pensioners living rent-free (Harmer 2009, p. 42). However, most of these are living with other family members (usually home owners). These cases are treated here as home owners, and their housing consumption estimated on the basis of the sale value of the dwelling.

10 Annual gross imputed rent is calculated as 4.899, 4.731, 3.163, 3.026, and 3.018 per cent of owner-occupiers’ estimated value of their homes in 1993–94, 1998–99, 2003–04, 2005–06, and 2007–08 respectively. House value is not available in the 1988–89 HES (it was collected, but not released by the ABS) and so we do not have estimates of total consumption for that year. The scaling values are derived from the National Accounts estimates of imputed rent relative to aggregate house values. Note that in 2003–04, 2005–06 and 2007–08, when house values were particularly high relative to rents, the inflation factor is lower. The implication of this is that these cyclical fluctuations in price/rent ratios are removed from our estimates of imputed rents.

11 The most recent SIH (2007–08) was released after work on this section was completed. Data from the 2007–08 SIH are included in the section examining trends in living standards.

12 Tenure here is defined at the household level. So a person living with their adult children who own the dwelling is classified as an owner.

13 This gap is overstated slightly because we do not deduct home maintenance or building insurance expenses in the 2005–06 SIH data. These expenses are deducted in the HES data shown in Table 5 and in subsequent sections.

14 See Yates and Bradbury (2009) for an analysis of the implications of these patterns for after-housing poverty in Australia compared to other countries.

15 Results in these figures are presented in 10 year age groups because of the small sample sizes for single men, women and ‘other’ households at older ages. Single men with high education are still a small number (fewer than 50 cases) at ages 60 to 69 years and 70 years and over.

16 As before, where the adjusted measures are indistinguishable from the unadjusted, they are not shown in the figures. Detailed tables with means and sample sizes of the different income measures by age and year of survey can be found in Appendix C.

17 The samples are also of different size (the HES is a subset of the SIH sample).

18 The high interest rates were also reflected in higher mortgage interest repayments, and hence in the DIaH measure. However, because the aged have relatively small mortgage balances, this effect was less important for them.

19 Among the elderly (65 years and over) median housing costs increased from $27 (in HES 1988–89) to $38 (in HES 2003–04) per week, while among the non-elderly (aged 15 to 64 years) median housing costs increased from $62 to $102 per week in the same period (in equivalent 2005–06 dollars).

20 One needs to exercise some caution in interpreting these cohort results because of mortality (particularly for the older groups). If low-income people are more likely to die early, then the cohort incomes will be artificially inflated over time. Changing family composition will also influence the results.

21 Market income = total income – government transfers; net social transfers = disposable income – market income; gross social transfers = net social transfers + tax. Any negative income in total income and disposable income is set to zero.

22 Note, however, that the non-housing expenditure measure in particular is subject to shopping variability, so

69

ENDNOTES

we cannot make much of the fact that this line is always at the bottom of Figure 21 and Figure 22. We need to assume that shopping variability has remained constant over time in order to draw inferences about trends in this measure.

23 Women’s qualifying age threshold is 60 years for the 1988–89 and 1993–94 HES cohorts. It is 61 years for the 1998–99 HES cohort but kept at 60 years in the analysis because the exact age 61 years is not available in the dataset. It is 62 years for the 2003–04 HES and SIH cohort, and 63 years for the 2005–06 and 2007–08 SIH cohort.

24 Income units are defined by the ABS as singles or couples plus dependent children. Dependent children for this purpose are full-time students aged 15 to 20 years who had a parent or relative in the household (but no partner or child of their own). The age bracket is changed to 15 to 24 years from 1998–99 onwards.

71

REFERENCES

References

Barrett, GF & Brzozowski, B 2009, ‘The retirement-income puzzle downunder’, presentation at the HILDA survey research conference, 16–17 July.

Barrett, GF, Crossley, TF & Worswick, C 2000, ‘Demographic trends and consumption inequality in Australia between 1975 and 1993’, Review of Income and Wealth, vol. 46, no. 4, pp. 437–56.

Bradbury, B 2008a ‘Housing wealth as retirement saving: does the Australian system lead to over-consumption of housing?’, paper presented at the 30th general conference of the International Association for Research in Income and Wealth, Portoroz, Slovenia, <http://www.iariw.org/papers/2008/bradbury.pdf>.

——2008b, Asset rich, but income poor: Australian housing wealth and retirement in international context, final report of the project, ‘Wealth holding patterns of Australia’s elderly’, report prepared for the Australian Government Department of Families, Housing, Community Services and Indigenous Affairs, Canberra (forthcoming FaHCSIA Social Policy Research Paper).

——2009, Relative needs of single and couple age pensioners, final report from the project: ‘Relative needs across the Age Pension population’, report prepared for the Australian Government Department of Families, Housing, Community Services and Indigenous Affairs, Canberra.

Bradbury, B, Rossiter, C & Vipond, J 1986, Poverty, before and after paying for housing, SWRC reports and proceedings no. 56, Social Welfare Research Centre, University of New South Wales.

Commission of Inquiry into Poverty (Chairman, Ronald F Henderson) 1975, Poverty in Australia, Australian Government Publishing Services, Canberra.

Harmer, J 2009, Pension review report, Australian Government, Canberra.

McNamara, J, Tanton, R & Phillips, B 2007, The regional impact of housing costs and assistance on financial disadvantage, Australian Housing and Urban Research Institute, final report no. 109, AHURI.

Saunders, P & Siminski, P 2005, Home ownership and inequality: imputed rent and income distribution in Australia, Social Policy Research Centre discussion paper no. 144, SPRC, Sydney.

Yates, J & Bradbury, B 2009, ‘Home ownership as a (crumbling) fourth pillar of social insurance in Australia’, Luxembourg Wealth Study, working paper no. 8, <www.lisproject.org/publications/lwswps/lws8.pdf>.

Occasional Papers

1. Income support and related statistics: a ten-year compendium, 1989–99Kim Bond and Jie Wang (2001)

2. Low fertility: a discussion paperAlison Barnes (2001)

3. The identification and analysis of indicators of community strength and outcomesAlan Black and Phillip Hughes (2001)

4. Hardship in Australia: an analysis of financial stress indicators in the 1998–99 Australian Bureau of Statistics Household Expenditure Survey J Rob Bray (2001)

5. Welfare Reform Pilots: characteristics and participation patterns of three disadvantaged groupsChris Carlile, Michael Fuery, Carole Heyworth, Mary Ivec, Kerry Marshall and Marie Newey (2002)

6. The Australian system of social protection—an overview (second edition)Peter Whiteford and Gregory Angenent (2002)

7. Income support customers: a statistical overview 2001Corporate Information and Mapping Services, Strategic Policy and Knowledge Branch, Family and Community Services (2003)

8. Inquiry into long-term strategies to address the ageing of the Australian population over the next 40 yearsCommonwealth Department of Family and Community Services submission to the 2003 House of Representatives Standing Committee on Ageing (2003)

9. Inquiry into poverty and financial hardshipCommonwealth Department of Family and Community Services submission to the Senate Community Affairs References Committee (2003)

10. Families of prisoners: literature review on issues and difficultiesRosemary Woodward (2003)

11. Inquiries into retirement and superannuationAustralian Government Department of Family and Community Services submissions to the Senate Select Committee on Superannuation (2003)

12. A compendium of legislative changes in social security 1908–1982 (2006)

13. A compendium of legislative changes in social security 1983–2000Part 1 1983–1993, Part 2 1994–2000 Bob Daprè (2006)

14. Evaluation of Fixing Houses for Better Health Projects 2, 3 and 4SGS Economics & Planning in conjunction with Tallegalla Consultants Pty Ltd (2006)

15. The ‘growing up’ of Aboriginal and Torres Strait Islander children: a literature reviewProfessor Robyn Penman (2006)

16. Aboriginal and Torres Strait Islander views on research in their communitiesProfessor Robyn Penman (2006)

17. Growing up in the Torres Strait Islands: a report from the Footprints in Time trialsCooperative Research Centre for Aboriginal Health in collaboration with the Telethon Institute for Child Health Research and the Department of Families, Community Services and Indigenous Affairs (2006)

18. Costs of children: research commissioned by the Ministerial Taskforce on Child SupportPaul Henman; Richard Percival and Ann Harding; Matthew Gray (2007)

19. Lessons learnt about strengthening Indigenous families and communities: what’s working and what’s not?John Scougall (2008)

20. Stories on ‘growing up’ from Indigenous people in the ACT metro/Queanbeyan regionCooperative Research Centre for Aboriginal Health in collaboration with the Telethon Institute for Child Health Research and the Department of Families, Housing, Community Services and Indigenous Affairs (2008)

21. Inquiry into the cost of living pressures on older AustraliansAustralian Government Department of Families, Housing, Community Services and Indigenous Affairs submissions to the Senate Standing Committee on Community Affairs (2008)

22. Engaging fathers in child and family services: participation, perception and good practiceClaire Berlyn, Sarah Wise and Grace Soriano (2008)

23. Indigenous families and children: coordination and provision of servicesSaul Flaxman, Kristy Muir and Ioana Oprea (2009)

24. National evaluation (2004–2008) of the Stronger Families and Communities Strategy 2004–2009Kristy Muir, Ilan Katz, Christiane Purcal, Roger Patulny, Saul Flaxman, David Abelló, Natasha Cortis, Cathy Thomson, Ioana Oprea, Sarah Wise, Ben Edwards, Matthew Gray and Alan Hayes (2009)

25. Stronger Families in Australia study: the impact of Communities for ChildrenBen Edwards, Sarah Wise, Matthew Gray, Alan Hayes, Ilan Katz, Sebastian Misson, Roger Patulny and Kristy Muir (2009)

26. Engaging hard-to-reach families and childrenNatasha Cortis, Ilan Katz and Roger Patulny (2009)

27. Ageing and Australian Disability EnterprisesShannon McDermott, Robyn Edwards, David Abelló and Ilan Katz (2010)

28. Needs of clients in the Supported Accommodation Assistance ProgramAustralian Institute of Health and Welfare (2010)

29. Effectiveness of individual funding approaches for disability supportKaren R Fisher, Ryan Gleeson, Robyn Edwards, Christiane Purcal, Tomasz Sitek, Brooke Dinning, Carmel Laragy, Lel D’aegher and Denise Thompson (2010)

30. Families’ experiences of servicesMorag McArthur, Lorraine Thomson, Gail Winkworth and Kate Butler (2010)

Housing costs and living standards among the elderly

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