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Housing costs and poverty: analysing recent australian trends

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Abstract

This paper examines recent trends in Australian poverty, both measured using disposable income (before housing costs, BHC) and income after subtracting housing costs (AHC). Household-level data from Australian Bureau of Statistics household income surveys are used to estimate relative poverty rates since 1999–00. Changes in the Australian housing market, especially the large increase in house prices and falling home ownership, mean that trends and relative levels of poverty are quite different when using these two alternative measures of resources. While BHC poverty has decreased, AHC poverty has not—because of rising housing costs. These shifts have changed the profile of AHC poverty and raise important questions about the adequacy and sustainability of existing housing and income support policies.

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Fig. 1

Source ABS Survey of income and Housing, various years; confidentialised unit record files. See Appendix for details

Fig. 2

Source ABS Survey of income and Housing, various years; confidentialised unit record files. See Appendix for details

Fig. 3

Source ABS Survey of income and Housing, various years; confidentialised unit record files. See Appendix for details

Fig. 4

Source ABS Survey of income and Housing, various years; confidentialised unit record files. See Appendix for details

Fig. 5

Source ABS Survey of income and Housing, various years; confidentialised unit record files. See Appendix for details

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Notes

  1. It is important to note that the difference between the BHC and AHC poverty rates measures the net impact of housing costs, as households may move in either direction relative to the poverty line when one measure replaces the other. This net impact differs from the numbers in ‘housing-cost-induced poverty’ which captures only those who are not experiencing poverty until housing costs are taken into account (see Tunstall et al., 2013: 5).

  2. The UK Social Metrics Commission (2018) has recently made the same point, arguing (p. 17) that ‘weekly recurring housing costs should be viewed as an inescapable cost that reduces the overall level of available resources that a family has’. Recurring costs are defined here to include the cost of rental or mortgage payments, ground rents and service changes, water rates and other charges including council tax and structural insurance premiums.

  3. A recent view undertaken for the Joseph Rowntree Foundation found that housing costs ‘constitute the most important direct impact of housing on poverty and deprivation’ and that the poverty rate was 5 percentage points higher in 2011–12 (and the numbers in poverty 3.1 million greater) when housing costs are taken into account (Tunstall et al., 2013).

  4. This point is acknowledged by Jenkins (2016), who still describes the gap between the BHC and AHC measures as ‘an important distinction’. His analysis shows that between 1990 and 2012–13 the UK poverty level and its trend vary according to which measure is applied. Thus, while BHC poverty declined by 6 percentage points over the period, AHC poverty declined by only 3 percentage points and the gap between them doubled.

  5. Another strategy is to place a cap on the housing costs that are deducted (van Dam et al, 2003). However, the heterogeneity of the housing stock makes justifying this approach difficult.

  6. It is arguable that repayments on alterations or extensions should also be omitted because they (like expenditure on repairs and maintenance) are a choice that can often be avoided or deferred, but they are relatively small and do not affect the overall picture very much.

  7. This approach is consistent with the wide adoption of median income-based poverty lines in the international literature (see Atkinson, Rainwater and Smeeding, 1995; Jenkins, 2016). It is common practice in European countries to set the poverty line at 60 per cent of median income, although Australian studies more commonly set the benchmark at 50 per cent and that approach is used here. It should be noted that recent outputs from the OECD use the square root of household size equivalence scale, not the modified OECD scale.

  8. Poverty lines established using other methods such as budget standards studies (as used in the Poverty Commission) can often produce quite different relativities (for Australia, see Saunders et al., 1998: chapter 12).

  9. The Poverty Commission, for example, used a different scale for the AHC poverty measure, though this scale was based on a budget-standards type calculation for New York in the 1950s, and it is difficult to argue that this would have contemporary relevance.

  10. More precisely, an equal-proportionate change in median after-housing income, and after-housing income around the poverty line will leave AHC poverty unchanged. If the increase in housing costs as a proportion of after-housing income is greater near the poverty line, then the AHC poverty rate will increase.

  11. The other main source of national data that can be used to estimate poverty is the longitudinal Household, Income and Labour Dynamics in Australia (HILDA) survey (Summerfield et al, 2018), although this has a smaller sample size, a lower response rate and is potentially subject to the attrition problems that are common among panel surveys. We compare some of our results with this survey below.

  12. For another study of poverty using the HILDA data, see Sila and Dugain (2019).

  13. Detailed results are available from the authors on request.

  14. See Appendix for variance calculation methods.

  15. The higher AHC poverty rate is associated with the fact that housing is a necessity–a good where expenditures are a greater share of the budget for poorer households. This means that housing consumption is more evenly spread across incomes than total consumption, and correspondingly, that non-housing consumption (captured by the AHC measure) is more unevenly spread–leading to a higher poverty rate.

  16. Authors’ calculations from the SIH, confidentialised unit record files. These are home-owners’ estimates of the current sale value and outstanding mortgage on their dwelling. Home-owners with zero mortgage are included when calculating both means.

  17. Source: ABS Cat 6401.0 Consumer Price Index, September Quarter 2018; Table 9.

  18. The gap in 2017–18 is significantly larger than in 2007–08 (p < .01) but not significantly different from the gap in 2015–16.

  19. P < .01 for couples with children, single person households and lone parent households in all years.

  20. The corresponding BHC poverty trend results are available on request from the authors.

  21. The proportion of older singles with a mortgage has also risen over this period, thought the difference is not significant (Table 2).

  22. AHC estimates for all years are in Fig. 5 and BHC results for the years before 2007–08 are available on request from the authors.

  23. Significantly higher at the 5% level in all years for both singles and couples.

  24. The lagged indexation arrangements meant that the Age Pension increased relative to median income up until 2015–16 (and decreased slightly thereafter).

  25. If the latest (2007–08) income measure is used instead of the previous (2005–06) measure, the aggregate poverty rate estimates in 2017–18 are 8.2 per cent (BHC) and 13.2 per cent (AHC). This compares with those based on the 2005–06 income measure of 7.8 per cent (BHC) and 12.8 per cent (AHC) shown in Table 1.

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Funding

This research has been supported by internal University funding, undertaken as part of a Poverty and Inequality Partnership between UNSW Sydney and the Australian Council of Social Service, and also by Australian Research Council (ARC) grant DP170103649.

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  1. Social Policy Research Centre, UNSW, Sydney NSW, Australia

    Bruce Bradbury & Peter Saunders

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  1. Bruce Bradbury
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Correspondence to Bruce Bradbury.

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Appendix

Appendix

1.1 Methods

Our estimates are based on our harmonisation of data from the public release confidentialised unit record files of the Survey of Income and Housing (SIH) conducted biennially by the Australian Bureau of Statistics (ABS) (e.g. ABS, 2019). The surveys provide a representative sample of individuals in private dwellings, with the sample size ranging between 14 and 18,000 households in each year. The SIH is the benchmark Australian collection for household income data.

Population weights calculated by the ABS are used in the calculation of all estimates. Estimates of standard errors and statistical significance take account of the survey design features, using jackknife replication and the replicate weights supplied by the ABS. These variance estimates are calculated conditional on the population median (and hence poverty line) and quintile boundaries estimated on the full sample in each year. SAS 9.4 software was used.

Because of the difficulty of distinguishing between personal and business income, and the ability to finance current living standards by drawing down on business assets, our analysis population excludes households where there is a self-employed person in the household. Self-employment is defined as either reporting any income (negative or positive) from their own unincorporated business, or reporting their labour force status as employer, own account worker, contributing family worker or employee paid in kind in their main or second job. We also exclude households with zero or negative disposable income. These two exclusions together affect about 16 percent of the population (in 2015–16).

The key income variable used is current household disposable (i.e. after-tax) income, adjusted for needs using the modified OECD equivalence scale. This scale assigns a score of 1.0 to the first adult in each household, 0.5 to each other adult and 0.3 to each non-adult (persons under age 15). To ensure time-series comparability, for the surveys from 2007 to 08 onwards, we use the ‘2005–06 basis’ income measure provided by the ABS. This excludes some income components (such as fringe benefits) which were only collected in later years.Footnote 25 In addition, to ensure a consistent population over time, we top-code the number of adults in each household to 6 and the number of children to 4.

Income after housing costs is calculated by deducting housing costs from disposable income. Housing costs include recurrent outlays by household members in providing for their shelter and is limited to major cash outlays on housing, that is, mortgage repayments (both principal and interest and including for any dwelling alterations or additions) and general and water rates for owners, and rent payments for renters. For simplicity, the same equivalence scale is used to adjust both before and after housing costs.

All incomes and housing costs are inflated to 2017–18 values using the consumer price index for the quarter in which the interviews took place.

The counting unit for all results is the individual. People are defined to be poor before housing costs if the equivalised disposable income of their household is less than half the median of equivalised disposable income in the same year (a relative poverty definition). Poverty after housing costs is defined in a similar way, comparing equivalised household income minus housing costs with the median of this after-housing income.

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Bradbury, B., Saunders, P. Housing costs and poverty: analysing recent australian trends. J Hous and the Built Environ 37, 1073–1091 (2022). https://doi.org/10.1007/s10901-021-09899-w

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