Trends in Income and Expenditure Inequality in the 1980s and 1990s: A Re-Examination and Further Results

There has been much debate in Australia about whether income inequality is increasing. This study uses the various unit record files of national sample surveys undertaken by the Australian Bureau of Statistics (ABS) to look at this issue. Section 2 briefly summarises the methodology of this study. Much greater detail is provided in appendix A. Section 3 looks at trends in income inequality, first analysing results from the ABS Household Expenditure Surveys and then contrasting these with outcomes from the ABS income surveys (initially named the Income Distribution Survey but replaced in 1994-95 by the Survey of Income and Housing Costs). Arguably, spending is a better measure of economic resources than income and so section 4 examines trends in expenditure inequality in Australia. One of the key findings of this study is that, while income inequality has been increasing, current expenditure inequality appears to have remained stable. Consequently, section 5 explores the relationship between the income and expenditure patterns of Australian households, ranked by their income. This suggests that there was a marked change in the composition of the poorest 10 per cent of households in the past decade. Section 6 summarises the paper.

It must be emphasised that it has recently become apparent that these results can be regarded as only preliminary. The results in this paper rely on the publicly available microdata files released by the ABS. The ABS recently revealed that it has concerns about the accuracy of the income data, particularly at the bottom end of the income distribution (ABS (Australian Bureau of Statistics), 2002). It apparently intends to release revised versions of the unit record files of both the income and expenditure surveys, although the timeline for this is uncertain.

The data and methodology used in this analysis are described in full in appendix A; this section provides only a summary. For reasons explained in the appendix:

• the data sources are the unit record tapes released by the ABS for the Household Expenditure Surveys and the income surveys;

• the income unit used is the household;

• the equivalence scale used is the square root of household size — the so-called ‘international’ scale because it is widely used internationally;

• income is current weekly income;

• negative business and investment incomes in the later surveys were reset to zero to maintain comparability with the earlier surveys;

• the measure of resources is either disposable (after-income tax) income or expenditure, both adjusted by the equivalence scale to take into account the needs of households of different size and by the consumer price index (CPI) to bring all measures to March 2001 dollars; and

• the income distribution is determined by a ranking of people by their equivalent household income, so that a household containing five people is counted five times, not once, when calculating inequality.

Because of concerns with either data quality or data comparability, we did not use the 1975-76 Household Expenditure Survey (HES), the 1982 current income data in the Income Distribution Survey (IDS), the 1985-86 IDS and the 1996-97 Survey of Income and Housing Costs (SIHC). We also recommend treating results using disposable income data from the 1984 HES with caution because the method of imputing income tax was less sophisticated than that for later years.

It is sometimes argued that expenditure is a better guide to the economic wellbeing of households than income because households are able to smooth transitory fluctuations in income by borrowing and saving (see, for example, Tsumori et al., 2002). Thus it is valuable to compare income and expenditure inequality to determine whether this methodological choice alters apparent levels or trends in inequality. The Household Expenditure Surveys allow this comparison because they contain both income and expenditure data, whereas the income surveys do not collect expenditure data. Analysis of HES expenditure data also ensures that comparisons can be made back to the mid-1980s because the 1984 expenditure data are not affected by problems with the imputation of income tax.

The following discussion of expenditure inequality is divided into four parts. First, we study the differences in income and expenditure inequality and compare our results with those from other recent studies of Australian expenditure inequality. Second, we comment on the trends in expenditure inequality revealed by changes in the Gini coefficient. At this point, we pause to discuss different possible measures of expenditure and the difficulty of accounting appropriately for spending on consumer durables. Finally, we supplement the earlier trend analysis by examining changes in decile shares.

In theory, it might be expected that expenditure would be more equally distributed than income, given that high income people do not spend all of their income and low income people typically spend more than their income (for example, by drawing down past savings). Previous studies of expenditure inequality tend to support this view. For example, a study using the Canadian Family Expenditure Survey over a number of years found that expenditure on non-durable items was more equally distributed than income in every year, with the difference being about 0.020 of a Gini coefficient (Pendakur, 1998, p. 266). An Australian study using the HES data also found that expenditure inequality was less than income inequality (Barrett et al., 2000). However, this result for Australia was derived from a modified HES dataset that excluded the top and bottom 3 per cent of observations and all households with a head aged less than 25 years or more than 49 years. This study also adopted a restricted measure of expenditure that excluded some consumer durables (see further discussion of expenditure measures below).

The results in this study for 1993-94 and 1998-99 also support the expected relationship between current expenditure and income, but in 1984 the Gini coefficients for income and expenditure are the same and in 1988-89 the Gini coefficient for expenditure is higher than that for income (Table 3). There are some similarities between our results and another Australian study of expenditure inequality by Blacklow and Ray (2000, p. 324). The methods used by Blacklow and Ray differ significantly from those used in this report.¹ Despite these differences in methodology, they also found that expenditure was more unequal than income in 1984 and 1988-89, but that expenditure was more equal than income in 1993-94.

The trends in current expenditure inequality also differ from the income inequality trends (Table 3). The Gini coefficients are remarkably constant for the 15-year period, so much so that the Lorenz curves cross for every period except from 1984 to 1998-99. Even in this case, the change in the Gini coefficient is so small it is unlikely to be statistically significant. These results indicate that current expenditure inequality has remained unchanged for a long time.

The preceding discussion has focused on inequality in current expenditure on goods and services (such as food, recreation and transport). As noted in appendix A, the ABS collects data not only on current expenditure but also on some capital expenditure (which comprises saving via home loan principal reductions, superannuation and life insurance contributions, and capital housing expenses such as the purchase of investment properties and the installation of swimming pools). Total expenditure is the sum of current and capital expenditure. If capital expenditure is included in the picture, in each of the four years examined in Table 3, total expenditure was more unequally distributed than income. In addition, the results suggest that total expenditure inequality increased between 1984 and 1998-99 (Table 3).

It thus appears that over the whole period (from 1984 to 1998-99), while the inequality of expenditure on goods and services remained constant, the inequality of total expenditure increased. This perhaps reflects the growing ability of those at the top end of the income spectrum to invest in property and their own home as a result of their real income increases. For other periods, crossed Lorenz curves obstruct the drawing of clear conclusions about changes in total expenditure inequality.

Expenditure measures do not depend only on the distinction between expenditure on goods and services and on capital expenses. The difference between durable and non-durable goods and services is equally important, if not more so.² For example, non-durables include food, petrol or renting a video whereas durables refer to items such as fridges, cars or stereos. The distinction is important because the ‘acquisitions approach’ to measuring expenditure used by the ABS means that, for any given period, a household’s expenditure on durable items can be very different from its consumption. For instance, a household that purchased a car before the survey period would be consuming car services but would report no expenditure on a car purchase, so that this household’s consumption would be understated. There is a strong random element to whether a household reports buying many durable items during the survey period, and therefore whether the household’s consumption is overstated or understated.

Because of the number of households in the sample, the expectation is that the HES acquisitions approach provides reasonable estimates of expenditure across reasonably large population subgroups. However, it is possible that the approach may produce distorted measures of expenditure inequality. For example, it may be that a low income household looks affluent because, after saving for a long period, it happens to make a big purchase during the HES survey period. Conversely, a high income household may appear to have low consumption if it is surveyed after purchasing a range of expensive consumer durables and during a period when it is reducing spending to restore its savings.

One way to test for possible distortion is to compare the rankings of individuals when they are ranked first into deciles of current household expenditure and then into deciles of non-durable current household expenditure.³ We would not expect these rankings to be the same but we assume that, in the absence of any distorting effects, the rankings will be similar. Specifically, we assume that the ranking of most individuals will remain unchanged and that, for the remainder, almost all will move up or down only one decile. The movements in decile rankings derived from the 1998-99 expenditure survey are set out in a ‘mobility matrix’ (Table 4). The matrix indicates that, given the previously stated assumptions, there is some distortion: less than half of all individuals remain in the same decile and more than 10 per cent move by more than one decile. A very similar pattern was found in the 1988-89 and 1993-94 expenditure surveys.

What is the impact of the ‘durables effect’? The Gini coefficients for non-durable expenditure in Table 3 are consistently significantly lower than the coefficients for current expenditure. For example, in 1998-99 the Gini coefficient for non-durable current expenditure of 0.277 is substantially lower than the Gini coefficient for current expenditure of 0.302. This is to be expected because many durables are luxury items (for example, jewellery, boats, golf equipment and cars) that are purchased disproportionately by households at the top end of the distribution. In theory, if the acquisitions approach to expenditure measurement causes spending on durables to be distributed somewhat randomly, this might tend to even out the consumer durables expenditure across the distribution. This would lead to an understatement in inequality at any point time. Unfortunately, we were unable to devise a simple method for testing this hypothesis.

Perhaps the more important question relates to the effect of durables on inequality trends. Here the news is surprisingly good: the movements in the Gini coefficients for non-durable and current expenditure are almost identical (Table 3). This consistency is also present in the mobility matrices for each year, strongly suggesting that the impact of the ‘durables effect’ is stable over time. Consequently, the ‘durables effect’ should not undermine our earlier conclusion that current expenditure inequality was stable between 1984 and 1998-99.

In summary, Table 3 suggests that the inequality of disposable income and total expenditure increased between 1984 and 1998-99 but that, in the case of current expenditure, inequality did not vary significantly. How do these results compare with the two academic studies using the same data by Blacklow and Ray, and Barrett et al.? Both of these studies used the 1975 HES data, but we feel these data are not sufficiently comparable and they have not been used in this study. Despite the differences in methodology — and summarising a wide range of results using different equivalence scales and inequality measures — the two previous studies (Blacklow and Ray, 2000; Barrett et al., 2000) and this study essentially agree that between 1984 and 1993-94 income inequality increased whereas current expenditure remained stable. The recently released 1998-99 HES data, which were not available to the authors of the earlier studies, merely serve to confirm the continuing stability of current expenditure inequality.

What are the shares of expenditure by decile? In interpreting these results it is important to distinguish between income deciles, which were used in the previous section, and expenditure deciles used here. The difference is whether the population is ranked by their equivalent income or expenditure before being divided into 10 groups of equal number. It is possible for a household to be in income decile 1 but expenditure decile 4. As noted earlier, the 1984 expenditure results are not subject to the same uncertainty as the 1984 income results, as imputed income tax is not included in the definition of expenditure.

If we look at only the results for 1984 and 1998-99, each decile’s share of total current expenditure is almost the same (Figure 5). This is also reflected in the Gini coefficient, which shows a statistically insignificant increase from 0.298 to 0.302. This consistency in the Gini coefficient reflects the minimal changes in the expenditure shares of the top decile (which experienced a very slight increase) and the bottom decile (which experienced a very slight decrease). Overall, the results suggest that, while income inequality increased appreciably after 1984, current expenditure inequality did not.

Once capital expenditure is included, however, the picture is different again. Including this form of saving results in the Gini coefficient for total expenditure increasing more rapidly between 1984 and 1998-99 than that for income (Table 3). An examination of Figure 6 suggests that the key driver of this apparent increase in total expenditure inequality was the sharp fall in the bottom decile’s share of total expenditure between 1984 and 1998-99. The fall between 1984 and 1988-89 is so pronounced that it suggests a possible issue with the 1988-89 data — perhaps related to the treatment of negative expenditure. The comparability of the 1984 and the 1990s data may also be affected by the ABS’s move from a ‘payments approach’ to an ‘acquisitions approach’ for measuring expenditure (ABS, 1995).

Table 3 summarises the changes in quintile shares. The results suggest that the shares of both the bottom and middle quintiles declined between 1984 and 1998-99 for all three measures of wellbeing, while the share of the top quintile increased for all three measures of wellbeing. Again the known problems with comparability of the income data and possible problems with the comparability of the expenditure data need to be emphasised.

Another interesting issue is the expenditure of Australians once they are ranked by their equivalent disposable income. Figure 7 suggests that the current expenditure of the bottom decile, divided by their income, was the same in 1993-94 as in 1998-99, at about 2.3. In other words, the bottom decile was spending about 2.3 times its income in these years. However, there was a dramatic difference between the two later surveys and the two earlier surveys for the bottom decile. For the remaining deciles, the ratio was remarkably similar in all four of the surveys.

Much the same relationship is apparent between equivalent disposable income and equivalent total expenditure (Figure 8). Once again, the results for the bottom decile match for 1984 and 1988-89 and for 1993-94 and 1998-99. However, the ratio of total expenditure to income of the bottom decile was much greater in the two later years. For the remaining deciles, all four surveys suggest much the same relationship between total expenditure and total income.

Why was the bottom decile spending so much more than its income, particularly in the later years? Given the looser relationship between income and spending for the self-employed, one possibility is that there were more people who were self-employed in the bottom decile. In fact, the proportion of the bottom decile where either the head or the spouse was self-employed remained at 19 per cent between 1988-89 and 1998-99.

A second possibility was that there were more aged persons in the bottom decile who were drawing down savings to finance their expenditure. To test this, ‘retired households’ were identified where the household head was aged 65 years or more at the time. The proportion of the bottom decile that were retired households increased steadily across the four surveys — from 19 per cent in 1988-89 to 24 per cent in 1998-99. So this does seem to be one possible explanation.

Another possibility is that the composition of the bottom decile changed, with social security dependent families with children moving out and being replaced by working age households without children. It is possible that such households if in employment might have greater access than social security dependent households to credit cards and other loan sources to finance their expenditure.

The average number of dependent children in bottom decile households dropped rapidly from 1.45 in 1988-89 to 1.06 in 1998-99 — about four times the drop apparent for all households. So, relatively speaking, children moved out of the bottom decile. If we look at just the population who were not dependent children, the average number per household fell by 0.03 between 1988-89 and 1998-99. But the picture for the bottom decile was very different, with the average number of adults increasing by 0.04.

The story for the number of earners is a little more complex. Suppose we look at the average number of earners in each household, thus including both full-time and part-time earners. For all Australian households, the average number of earners fell by 0.03 between 1988-89 and 1998-99. The only deciles for which the average number of earners increased were deciles 1, 8 and 10. This trend is reflected in both average wage and salary income and average earned income received by the bottom decile. In March 2001 dollars the average wage and salary income of bottom decile households fell by $13 a week from 1988-89 to 1990, while deciles 2–4 sustained losses of $58 to $85 a week. Similarly, while earned income (including self-employment income) of decile 1 fell by $26 a week, deciles 2–4 experienced a drop of between $77 and $98. (Average real ‘earned’ and ‘wage and salary’ income increased during the 1990s for all households, so the losses of the bottom half of the distribution were more than outweighed by the gains of the top half.)

Finally, average government cash benefits received by the bottom decile fell by $5.60 a week between 1988-89 and 1998-99. This was in sharp contrast to the average increases in government cash benefits for deciles 2–4, which ranged from $76 to $102 a week.

Although further exploration is needed, this suggests a significant change in the composition of the bottom decile, with social security dependent families with children moving out, and couples and singles without children and often in low wage full-time or part-time employment moving in. Perhaps the bottom decile contains more of the working poor without children than it did at the beginning of the 1990s. It seems possible that such a group might have better access to credit than welfare-dependent families with children, and that this is one of the factors underlying the sharp change in the relationship between income and expenditure for the bottom decile. Thus, such groups might be demonstrating an ability to maintain their consumption in the face of temporary income shocks. Interestingly, Blacklow and Ray (2000, p. 323) found that ‘the propensity to smooth consumption, in the face of exogenous income shocks by drawing on savings or borrowing, is at its highest for single adults with no dependent children’.

These conclusions may be affected if, as the ABS has very recently indicated, the 1998-99 HES data understate the income of the lowest income quintile by about 11 per cent. The ABS expects to release a modified HES unit record file (ABS, 2002, p. 7).

This paper’s results must be treated with caution given the changes in the methodology of the expenditure and income surveys over time, our relatively unsophisticated imputation of income tax for 1984, the unusually low expenditure by the bottom decile of households in 1988-89, and the ABS’s recent statement that it has concerns about the quality of the 1998–99 data.

With these caveats in mind, the following interim conclusions emerge.

• It appears that income inequality increased between the late 1980s and mid-1990s and there is some evidence to suggest that it has continued increasing since then.

• The increase in inequality was driven by declines in the income shares of the bottom 10 per cent and, to a lesser extent, the middle 20 per cent of Australians during the 1990s, and an increase in the income share of the top 10 per cent.

• The inequality of expenditure on current goods and services did not change significantly over the period 1984 to 1998-99.

• The inequality of all expenditure (including ‘savings’ via expenditure on investment properties, superannuation, etc.) increased between 1984 and 1988-89 but apparently decreased between 1988-89 and 1998-99.

A separate analysis examined the relationship between the income and expenditure of Australians after they were ranked into deciles of equivalent disposable income. This suggested a remarkably consistent relationship between spending and income for each income decile. The only area of major change was the sharp increase in the spending-to-income ratio of the bottom decile. This was not due to growing numbers of self-employed households in the bottom decile. Instead, it seems that the composition of the bottom decile had changed — more retired and childless ‘working poor’ households, and fewer social security dependent households with children. Thus it is possible that the entrants to the bottom decile had greater capacity than social security families with children to run down savings or to borrow to finance their spending, and that this had propped up the spending of the bottom decile in the face of their declining share of income.