# Chapter 2

## The extent of income inequality in Australia

2.1        This chapter addresses the first term of reference for this inquiry: the extent of income inequality in Australia and the rate at which it is increasing. Income inequality can be measured in a variety of ways. Different measures will yield different findings. Further, the same measure will yield a different result depending on the data source that is used.

2.2        In evidence to the committee, Treasury stated that it is important to consider a range of different indicators of income inequality rather than one or two metrics. Further:

[T]here are alternatives to income which can be used to measure equity, including the distribution of consumption and wellbeing, as well as various measures of material deprivation. It is also necessary to understand what is included or omitted from the analysis and also to consider the impact of policies on opportunity.[1]

2.3        The committee notes that the underlying reasons for a change in the level of inequality can be highly complex. As one submission noted, inequality:

...is affected by many factors, so that it can increase as a result of beneficial changes as well as socially undesirable ones, and can decrease because of changes that reduce overall social wellbeing as well as a result of socially desirable changes.[2]

### Measures of income inequality

2.4        In the course of this inquiry, the committee has received data and research on a range of income inequality measures. These include:

#### The Gini coefficient

2.5        Perhaps the best recognised measure of income inequality is the Gini coefficient. This is a scale from 0 to 1 where 0 is where all incomes are equal and 1 is where there is absolute inequality (ie: a single person has all the income).

2.6        The Gini coefficient is calculated using the Lorenz curve. This curve graphs the cumulative proportion of total income against the cumulative proportion of the population from lowest to highest income. The curve starts at 0 and reaches a maximum of 1.[3] A straight line would denote that everyone has the same income; inequality is reflected in a convex curvature. The Gini coefficient is calculated through dividing the area between the straight line of perfect equality and the actual Lorenz curve by that area and the area under the Lorenz curve.

2.7        The Gini coefficient is used by the Organisation for Economic Cooperation and Development (OECD) as a basis for international comparison. Treasury told the committee that the Gini also allows for useful comparisons. However, Treasury has also noted the limitations of the Gini:

...it does not tell us about changes in the distribution of inequality between income groups, such as the top and the bottom...

a reduction in the Gini coefficient could result from a fall in incomes at the top, without a corresponding rise in incomes at the bottom (that is people becoming more equally poor).[4]

#### Income share

2.8        Points along the Lorenz curve indicate the ratio of people at different ranks in the income distribution. Income share is another common measure of income inequality. It can be expressed in terms of x per cent of households holding y per cent of income. Often, reference is made to the income share of the highest one per cent of the population.

#### The P90/P10 ratio and Q5/Q1 ratio

2.9        A third way to measure income inequality is by charting the ratio of income at different ranks of the income distribution. For example, the P90/P10 ratio is the income of the unit at the 90th percentile relative to that at the 10th percentile. The higher the ratio, the greater the inequality. A variant of this measure is the Q5/Q1 ratio: the ratio of the income share of the richest 20 per cent to that of the poorest 20 per cent. Again, the higher the ratio, the greater the extent of inequality.[5]

2.10      Professor Alan Duncan of the Bankwest Curtin Economics Centre noted his preference for using the income ratios to measure income inequality, as opposed to the Gini coefficient. As he told the committee:

I think the metrics we present, which are based on income ratios or income multiples, are actually far more accessible than, say, Gini coefficients, which are the orthodox metric by which income inequality is judged. The difference between 0.39 and 0.37 in a Gini coefficient means essentially nothing...With income multiples, looking at the typical income in the top 10 per cent of income distribution, in Australia the census was constructed with a series of income bands, where the top income band of \$2,000 per week or more broadly speaking aligned with the top 10 per cent. For the bottom 10 per cent, the income band that characterised the first decile stopped at around \$200 per week. When you are talking about income multiples say of the 90/10 ratio and how that has changed over time, if you look at something like a ratio that is rounded up to five, then you are talking about the difference between somebody who is on \$2,000 a week and somebody who is on \$400 a week.[6]

#### Relative income poverty

2.11      Some studies of income inequality use the concept of relative income poverty.[7] This is the share of the population with an income of less than 50 per cent of the respective national median income.

#### Post-tax and transfers

2.12      The measurement of income inequality can also take into account pre-tax and post-tax and transfer distributions. Studies sometimes compare the two, showing the extent to which the tax and transfer system redistributes income.[8] Most studies of income inequality focus on income after payment of income taxes and receipt of government benefits.[9] The Australian Bureau of Statistics (ABS) typically reports household income survey data. This data includes social security benefits and deducts direct taxes and adjusts for the number of people living in the household.

#### Equivalence

2.13      Income inequality is often measured at the household level using an equivalence scale. This scale adjusts for household size and composition and produces a 'per adult equivalent' measure of income.[10]

### Australian studies into income inequality

2.14      In their submission to this inquiry, Professors Peter Whiteford and Andrew Podger provide an overview of various academic studies of income inequality in Australia over the past 20 years. The table they provide (Table 2.1) shows that most of these studies found that income inequality had increased.

2.15      Professors Whiteford and Podger note that the studies employ a range of data and methods to analyse inequality. The second column in Table 2.1 ('income concept') shows that many Australian studies have used cash disposable income, equivalised to provide a per-adult equivalent measure. Some studies have gone beyond cash income to include the in-kind benefits of health, education, housing and childcare. Associate Professor Roger Wilkins of the University of Melbourne notes that these in‑kind transfers 'can be very important to economic wellbeing and, moreover, when included in the definition of income tend to reduce measured inequality'.[11]

2.16      In commenting on these research findings, Whiteford and Podger observe that while 'the cumulative picture is of rising income inequality over the longer run', there are some periods over which there are 'indications of falling inequality'. They add that the concepts and measures used in these studies 'can make a significant difference'.[12] In similar vein, Professor Wilkins wrote in his submission: '[E]ach measure provides different information on the income distribution, and ideally any study of inequality will examine a battery of measures'.[13]

### Table 2.1: Results of selected studies of inequality in Australia

Study

Income Concept

Period

Data Source

Main Results

Cash disposable income, equivalised

1983–84 to 1989–90

Microsimulation, IDS

Gini increased from .367 to .370

Gregory 1993

Individual gross earnings, not equivalised

1976 to 1990

Weekly Earnings of Employees (WEED)

Growth in low paid and high-paid jobs - the ‘disappearing middle’

Saunders 1993

Cash disposable income, equivalised

1981–82 to 1989–90

IDS

Gini increased from .27 to .29

Harding 1994

Gross income, equivalised

1981–82 to 1989–90

IDS

No change in Gini

Social wage income (health, schooling), equivalised

1982–83 to 1989–90

Microsimulation, IDS

Gini increased from .272 to .276

Whiteford 1994

Cash disposable income, equivalised

1982–83 to 1989–90

Microsimulation, IDS

Gini fell from .328 to .319

Gregory and Hunter 1995

Gross household income of areas, not equivalised

1976 to 1991

Census

Gini increased from .14 to .18; incomes fell for low-income areas between 1976 and 1981 and rose for rich between 1981 and 1991

Harding 1995

Social wage income (health, education, housing, childcare), equivalised after housing

1994

Microsimulation, IDS

Gini for cash disposable income of .308, for final income of .289

Johnson et al.  1995

A. Cash disposable income, equivalised

B. Social wage income (health, education, housing, childcare, concessions), equivalised

1981–82 to 1993–94

Microsimulation, HES

A. Gini fell from .308 to .296

B. Gini fell from .255 to .226

OECD Atkinson et al. 1995

Cash disposable income, equivalised

1981–82 to 1985–86

IDS

Gini increased from .287 to .295; P90–P10 fell from 4.05 to 4.01

ABS 1996

Final income (social wage plus indirect taxes), not equivalised

1984 to 1993–94

Household Expenditure Survey (HES)

Q5–Q1 increased from 4.5 to 4.7

Borland and Wilkins 1996

Individual gross earnings, not equivalised

1975 to 1994

WEED; Income Distribution Survey (IDS)

Real weekly earnings of males fell at 10th percentile and rose at 90th percentile

ABS 1999

Gini - gross income of income units

1994–95 to 1997–98

IDS

Income distribution of all income units almost unchanged. Gini of .446 not significantly different from that of previous years

Barrett et al. 1999

Consumption inequality

1975 to 1993

HES

Income and consumption inequality both rose, income inequality grew much more than consumption inequality

Lloyd et al.  2000

Mean income by location

1986 to 1996

Census

Income of metropolitan residents increased double the rate of those in major urban centres and regional towns. Between 1991 and 1996, rural towns had the largest increase

Saunders 2001

Wage and salary, market income, gross income, disposable income and equivalent disposable

1990 to 1999–2000

IDS, and Survey of Income and Housing Costs

Wage and salary Gini increased from 0.224 in 1990 to 0.275 in 1999–00. Market Gini rose from 0.543 to 0.572. Gross Gini rose from 0.427 to 0.445. Disposable Gini rose from 0.375 to 0.391. Equivalent disposable Gini rose from 0.330 to 0.346. Australia 6th most unequal country out of 20 in 1995

Harding and Greenwell, 2002

Disposable income and household expenditure

1984 to 1998-99

IDS, and Survey of Income and Housing Costs and HES

Income inequality has been increasing ,but  current expenditure inequality has remained stable

Leigh, 2004

Taxable and disposable income

1942 to 2000

Taxation statistics

Inequality fell in the 1950s and the 1970s, and rose during the 1980s and 1990s – a pattern similar to the United Kingdom.

Johnson and Wilkins, 2006

Private income, gross income, disposable income and equivalent disposable and household expenditure

1982 to 1977-78

IDS and HES

Modest increase in inequality over 1980s and 1990s, with most of the increase being in early 1990s. Expenditure inequality is lower but also increased.

Atkinson and Leigh, 2006

Taxable and disposable income

1921 to 2002

Taxation statistics

The income share of the richest fell from the 1920s until the mid-1940s, rose briefly in the post-war decade, and then declined until the early-1980s. During the 1980s and 1990s, top income shares rose rapidly. At the start of the twenty-first century, the income share of the richest was higher than it had been at any point in the previous fifty years.

Austen and Redmond, 2010

Earnings inequality and household income inequality

1982 to 2007

IDS

Male earnings inequality increased substantially across this period, but change in family income inequality was less significant. Women’s earnings played a role in moderating the effects of rising male earnings inequality.

Doiron, 2011

Household disposable income

2000 to 2008

IDS

After a decade of stable even slightly improving income inequality, Australia suffered a sharp widening of its income distribution in the late 2000’s. Although this U-turn is not unique to Australia, the change has seemed more extreme with Australia’s rank in 30 OECD countries falling from 15 in 2004 to 24 in 2008 in terms of income equality.

Bray, 2014

Household disposable income

1990 to 2010

1976 to 2010

2001 to 2010

SIH

HES

HILDA

Rise in inequality 1990 to 1994, fall to 1998, rise to 2000-01, then fall to 2004, rise to 2008 then fall.

Fall in inequality between 1976 and 1984, rise to 1993-94, fall to 2003-04 and rise to 2008-09.

No significant change in inequality between 2001 and 2010.

Source: Professor Peter Whiteford and Professor Andrew Podger, Submission 55, pp 7–9. Note: The Gini coefficient ranges between 0 and 1 with a higher Gini implying greater inequality. The P90/P10 ratio is the income of the unit at the 90th percentile relative to that at the 10th percentile, with a higher ratio implying greater inequality. The Q5/Q1 ratio is the ratio of the income share of the richest 20 per cent to that of the poorest 20 per cent, with a higher ratio implying greater inequality.

Table reproduced with permission.

#### Australian Bureau of Statistics data

2.17      ABS data on income inequality are principally derived from two surveys: the Household, Income and Labour Dynamics in Australia Survey (HILDA) and the Survey of Income and Housing (SIH).

The Household, Income and Labour Dynamics in Australia Survey (HILDA)

The Household, Income and Labour Dynamics in Australia Survey (HILDA) is a longitudinal social and economic survey which tracks all members of an initial sample of households in a series of interviews (waves) over an indefinite life. HILDA is designed to collect data in three main areas: economic and subjective well-being, labour market dynamics and family dynamics. Topics covered in these areas include education, current employment and employment history, job search experience, income, health and well-being, child care, housing, family background, marital history and family formation for those aged 15 years and over. Responsibility for the design and management of the survey rests with the Melbourne Institute of Applied Economic and Social Research. Commencing in 2001, HILDA collects data annually.

The Survey of Income and Housing (SIH)

The Survey of Income and Housing (SIH) (previously known as the Survey of Income and Housing Costs (SIHC)) is a household survey which collects information on sources of income, amounts received, housing characteristics, household characteristics and personal characteristics. Income is collected on both a current and financial year basis. In some cycles from 2003-04, information on household net worth is also collected. The survey scope covers residents of private dwellings in both urban and rural areas of Australia. The survey was conducted for most years from 1994-95 to 2003-04 (no survey was run in 1998-99 or 2001-02), from which year it is being conducted biennially.

##### Household wealth in Australia: ABS Survey of Income and Housing

2.18      Based on its 2011–12 Survey of Income and Housing, the ABS has highlighted the 'asymmetric distribution of wealth between households' in Australia:

While the mean household net worth of all households in Australia in 2011–12 was \$728,000, the median (i.e. the mid-point when all households are ranked in ascending order of net worth) was substantially lower at \$434,000. This difference reflects the asymmetric distribution of wealth between households, where a relatively small number of households had high net worth and a relatively large number of households had low net worth, as illustrated in the following frequency distribution graph.[14]

### Figure 2.1: Distribution of household net worth 2011–12 (ABS 2012)[15]

2.19      The ABS noted various other findings from the survey:

Long-run ABS data on income inequality

2.20      The Australian Council of Trade Unions (ACTU) and Professors Whiteford and Podger present in their submissions a figure (Figure 2.2, below) plotting the Gini coefficient in Australia from 1981–82 to 2011–12. There are two different sources: a series from Johnson and Wilkins using old ABS data and a series from 1994–95 using current ABS data.[18]

2.21      Professors Whiteford and Podger make the following observations on Figure 2.2:

Despite the differences in income measures and equivalence scales, the long run trend is clear. There are periods in which inequality fell – 1986 to 1990, 1994-95 to 1996-97, and 1999-2000 to 2002-03, but overall inequality measured by the Gini coefficient rose over 2000s, and 0.32-0.34 in the mid and late 2000s. Over the most recent period since the Global Financial Crisis, income inequality as measured by the Gini coefficient has fallen, but remains higher than at any point before 2007-08.[19]

### Figure 2.2: Income inequality in Australia, 1982 to 2011

Source: Johnson and Wilkins (2006); ABS (various years).

2.22      On the basis of Figure 2.2, the ACTU commented:

Australia’s Gini coefficient rose from 0.302 in 1994-95 to 0.336 in 2007‑08, an increase in inequality of around 11%. Between 2007-08, income inequality fell a little, with the Gini coefficient coming down to 0.32. While this is lower than the level recorded in 2007-08, it remains higher than the Gini at any time from 1994-95 to 2005-06 (inclusive). The decrease in inequality since the GFC has been ascribed to causes including:

##### Methodological concerns with the ABS data

2.23      In a paper titled Evaluating the evidence on income inequality in Australia in the 2000s, Professor Wilkins noted that there were technical changes in the SIH methodology, which casts doubt on the results from the 2000s. The paper's abstract states:

Published ABS data from the Survey of Income and Housing (SIH) show a substantial increase in income inequality between 2001 and 2010. However, almost all of the increase occurred over a period when changes in survey methodology and income concept were occurring. I document these changes, present results of analysis of the SIH unit record data, and present independent evidence on income inequality trends using the HILDA Survey, tax records and National Accounts. I conclude that the SIH overstates the growth in income inequality, even when the income variable examined is notionally consistently defined across surveys. The extent of overstatement is uncertain, however, reflecting ambiguity about the nature and extent of changes to the distribution of household market income.[21]

2.24      Professor Wilkins concludes:

We are therefore left with the somewhat unsatisfactory conclusion that it is not possible to produce definitive estimates of income inequality trends between 2001 and 2010. There are, however, some seemingly unambiguous facts about income distribution changes over the decade. No data source shows inequality decreasing, and indeed there is agreement between the weekly SIH, annual SIH and the HILDA Survey that inequality increased from approximately 2003‐04 to 2007‐08—albeit by differing magnitudes— and then decreased in the next two years. In addition, all three series show that changes to income taxes and to government benefits acted to increase income inequality over the decade.[22]

2.25      The ACTU has noted that the ABS has 'improved its survey methodology over time and harmonised its definition of income with the international standard'. It argued:

This means that the recent estimates of the Gini coefficient are more likely to be accurate than earlier estimates. Thus, to the extent that the available figures overstate the rise in inequality, it is likely to be due to an underestimate of inequality in earlier years rather than an overestimate of inequality in later years. The ABS (and OECD) figures are used in this submission, as those organisations are confident enough of the comparability of the post-1994/95 estimates to present them as a time series, but the Committee should be aware of the technical issues here.[23]

#### Income inequality and the Australian States

2.26      A Treasury paper on income inequality (see below) provided the following chart which plots the Gini coefficient for each of the six Australian States from 1994–95 to 2011–12.

### Figure 2.3: Gini coefficient for the States[24]

2.27      The chart shows that Gini coefficient trends followed a similar pattern in the Australian States, with the exception of Western Australia. Unlike the other States, income inequality has increased in Western Australia since 2007–08. Treasury stated:

While further work is needed to better understand this trend, it is likely that the increase in income inequality in Western Australia is due to the impact of the mining boom in that state.[25]

2.28      The Bankwest Curtin Economics Centre has conducted research into the distribution of income and the extent of hardship in the boom mining state of Western Australia (WA). In its February 2014 report titled Sharing the boom: the distribution of income and wealth in WA, the Centre found that:

Between 2003–04 and 2011–12, all household income deciles in Western Australia increased by considerably more than was experienced nationally (Figure 9). The exceptions were those households in the first two deciles (those with the lowest incomes) who experienced increases of 27 per cent and 29 per cent respectively over the period. This compares with a national increase of 23 per cent for the two bottom deciles.

Eight out of the ten income deciles in Western Australia have experienced real growth rates of between 44 and 49 per cent in household gross income between 2003–04 and 2011–12. This compares to national growth which remained relatively flat across deciles over the boom period, at rates of between 23 and 27 per cent. While the majority of WA households grew well ahead of the national average, households in the bottom two deciles have kept pace with national rather than WA incomes growth.[26]

2.29      Professor Duncan elaborated:

If you look at real incomes growth in WA compared to the rest of Australia you find that, over the period between, say, 2003 and 2012, over the last decade...the first two deciles in WA track pretty closely to the first two deciles in the rest of Australia...

In deciles 3 to 10, you see a significantly greater degree of incomes growth in WA than the rest of Australia. It is not just the lowest 10 percentile. We see the separation occurring around decile 3.[27]

### Figure 2.4: Real growth in household gross income between 2003–04 and 2011–12 by decile: WA and Australia[28]

OECD data

2.30      Using the Gini coefficient, data from the OECD for Australia for the period 2000–2012 shows that income inequality declined from 2000 to 2004, increased from 2004 to 2008 and fell from 2008 to 2010 and again from 2010 to 2012. When compared with the OECD average, Australian income inequality was marginally higher in 2000, 2008 and 2010. Over the period 2000–2012, the United States recorded a Gini coefficient of between 0.36 and 0.39, while the United Kingdom ranged from 0.33 to 0.35.[29]

2.31      In terms of the top decile of income earners relative to the lowest decline, the multiple in Australia was 8.1 in 2000, falling to 7.7 in 2004 before rising sharply to 9.3 in 2008. It has fallen since and in 2012, the top decile received 8.5 times the income of the bottom decile of income earners. The OECD average was consistently higher on this measure.

2.32      In terms of relative income poverty, in 2000, 12.2 per cent of the Australian population had an income that was less than 50 per cent of national median income. This figure increased to 13.2 per cent in 2004, 14.6 per cent in 2008 before falling in 2010 and 2012. On this measure, in 2000, 2008 and 2010, income inequality in Australia was more pronounced than the average across OECD countries.[30]

### Table 2.2: Income inequality in Australia and OECD averages, 2000–2012

Gini coefficient

Top 10% vs bottom 10%

Relative income poverty

Australia

OECD average

Australia

OECD average

Australia

OECD average

2000

.32

.31

8.1

9.2

12.2

10.5

2004

.31

7.7

13.2

2005

.32

9.4

2008

.34

.32

9.3

9.5

14.6

11.6

2010

.33

.32

8.9

9.8

14.4

11.7

2011

.32

9.8

11.7

2012

.32

8.5

13.8

Source: Organization for Economic Cooperation and Development, 'Social and welfare issues—Inequality', http://www.oecd.org/social/inequality.htm (accessed 10 November 2014)

2.33      Table 2.2 below shows trends in different income inequality measures in each OECD country.[31] The table shows that in 2008:

2.34      Figure 2.5 is taken from the ACTU's submission to this inquiry. It shows that while income inequality in Australia has increased since the mid-1990s, the level of inequality (as measured by the Gini coefficient) has consistently been below that in the United States and the United Kingdom.

### Figure 2.5: Gini coefficient for equivalised disposable household income in Australia, the US, the UK and Canada

Source: Australian Council of Trade Unions, Submission 46, p. 9. Reproduced with permission.

### Treasury's evidence on income inequality

2.35      In 2013, a Treasury paper on income inequality concluded:

...while labour income inequality has been on the decline, overall income inequality in Australia has been rising since the mid-1990s. Measures that focus on the very top income earners show a strong gain in their share of national income, as is the case in most OECD countries.[34]

2.36      The Treasury paper contained the following chart, comparing income inequality for households using the P90/P10 ratio, the P80/P20 ratio and the P80/P50 ratio.

### Figure 2.6: P90/P10, P80/P50 and P80/P20 ratios in Australia (1994–95 to 2011–12)[35]

2.37      Treasury summarised the findings as follows:

...in 2011–12, a household at the 80th income percentile had around 2.61 times the weekly household disposable income of a household at the 20th percentile and around 1.56 times the income of a household at the 50th percentile. A household at the 90th percentile had around 4.1 times the weekly household disposable income of a household at the 10th percentile.

Overall, between 1994–95 and 2011–12 the P80/P20 and the P80/P50 ratios have been fairly steady, with periods of small variation.

The P90/P10 line shows a steeper upwards trend than the other two data lines, with a pronounced drop occurring from 2007–08 to 2011–12. These findings are similar to the trend in the Gini coefficient, and are probably due to rises in investment incomes over this period which accrued mostly to those at the top of the income distribution.[36]

2.38      Treasury emphasised that from 1994–95 until 2011–12, there has been real household income growth across the income distribution, with the biggest gains in the 40th, 80th and 90th percentiles.[37] It added:

While all of the household categories have experienced significant real income growth, the biggest gains have gone to singles between the age of 55 and 64 and couples without children, where both members are 55 or above and at least one member is below 65.

2.39      Interestingly, a lone person of prime working age is the household type that recorded the lowest real growth in disposable household income between 1994–95 and 2011–12.[38]

### The 2013 Productivity Commission report

2.40      In 2013, the Productivity Commission (PC) released a report examining income distribution trends in Australia between 1988–89 and 2009–10. The report found that real incomes for most Australians grew in this period and that higher growth in incomes for the higher deciles has led to a 'wider' spread of incomes. This wider spread has led to an increase in the Gini coefficient. In addition, the report found that:

2.41      Figure 2.7 shows that the distribution of income 'has shifted to the right (indicating rising average incomes) and flattened (indicating greater spread of income), the 'top' tail of the distribution has also lengthened'.[40] In 1988–89, most households earned an income of \$250–1250 per week with a small percentage earning more than \$1500 per week. In 2009–10, most individuals earned an income of \$250–1750 per week with a much larger number earning more than \$1750 per week.[41]

### Figure 2.7: Movements in the distribution of individual labour income, 1988–89 to 2009–10

Source: Australian Government Productivity Commission, Trends in the Distribution of Income in Australia, Staff Working Paper, March 2013, p. 7. Reproduced with permission.

2.42      Cumulative income growth from 1988–89 to 2009–10 is indicated for each decile group in Figure 2.8. A clear gradient of growth from decile 2 to decile 10 can be seen in which lower income groups recorded substantially lower income growth than the higher deciles. This is consistent with the PC finding that those on higher incomes are realising higher wages growth, whilst lower income individuals are simply working more hours with less wages growth. The higher growth in decile 1 was largely accounted for by increases in government payments reflecting the highly targeted nature of the welfare system (see chapter 6).[42]

### Figure 2.8: The percentage change in labour income decile from 1988–89 to 2009–10

Source: Australian Government Productivity Commission, Trends in the Distribution of Income in Australia, Staff Working Paper, March 2013, p. 7. Reproduced with permission.

2.43      The PC has compared the Gini coefficient for three different types of incomes—capital, market and labour—seen in Figure 2.9 below. Most literature focuses on labour income (wages and salary) where the Gini has increased from 0.39 to 0.43 (pre-tax and transfer). Market based income which includes wages, salaries, self-employment and other business income has a much higher Gini, and as such, higher levels of inequality. For example, the self-employed have a Gini of 0.59. The highest level of income inequality occurs amongst those receiving income streams from capital. Over the last two decades, the Gini has ranged from 0.8 to 1.2. This is consistent with the PC finding that most capital income accrues to the top decile.[43]

### Figure 2.9: Gini coefficients for capital, market and labour income

Source: Australian Government Productivity Commission, Trends in the Distribution of Income in Australia, Staff Working Paper, March 2013, p. 7. Reproduced with permission.

2.44      The PC found that Australia had the third highest increase in Gini coefficient out of 19 OECD countries between 2000 and 2008.[44] Contributing to this is that 'the redistributive impact of direct government payments and taxes has fallen in Australia over the last decade'.[45]

### The top 1 per cent income share

2.45      Another measure of inequality is to compare the earnings of the top one per cent of income earners with the rest of the population. Figure 2.10 is drawn from Treasury's paper. It shows that since the early 1980s, there has been a progressive increase in the income share of the top 1 per cent, 0.5 per cent and 0.1 per cent of Australians. Over this period, the share of income held by the top one per cent of earners increased from around 5 per cent to nine per cent.

### Figure 2.10: Income share of the top 1, 0.5 and 0.1 per cent in Australia from 1921–2010[46]

#### Wealth at the very top

2.46      The gains of the very wealthy have been greater. In his book, Battlers and Billionaires, the federal Labor MP and former academic economist, the Hon. Andrew Leigh MP, wrote:

The share of Australian wealth held by the super-rich is steadily rising. Pamela Katic and I estimated that from 1984 to 2012, the richest 0.001 per cent more than tripled their share of household wealth from 0.8 per cent to 2.8 per cent. Over the same period, the top 0.0001 per cent (the richest one-millionth) quintupled their share from 0.25 to 1.4 per cent.[47]

### Submitters' and witnesses' views on poverty in Australia

2.47      Another way to approach the measurement of inequality is through qualitative, survey-based research into the extent of poverty, particularly in a wealthy economy such as Australia's. The committee has taken evidence from submitters and witnesses who noted, in the past few years, poverty and income inequality have increased in Australia.

2.48      In Western Australia, for example, Professor Duncan referred to two research reports released by Bankwest Curtin Economics Centre in 2014.[48] He summarised this work as follows:

WA stayed strong during the course of the economic downturn that has weakened most world economies. The resources boom in particular has benefited the majority of WA households, with rising employment and substantial increases in real income and household net wealth. However, the centre's research does find that lower income households in WA have failed to keep pace with the general growth in incomes for the rest of the population. There have been real gains, financially at least, among the lowest income households but they have not been able to share the benefits of the growth in incomes to the same extent as those higher up the income distribution in WA.

Specifically, relative income inequality has risen in WA at a greater rate than for the rest of Australia. The gap between the richest and poorest households in WA rose consistently from the acceleration of the boom in around 2003 to its peak in 2009...One metric we use is the 90:10 ratio, which compares the incomes of the top 10 per cent of households with those at the bottom 10 per cent of the income distribution. Expressed in those terms, in WA the ratio of household equivalised disposable income of the richest 10 per cent rose to 4.8 times the incomes of the poorest 10 per cent. That is a substantial increase over the period from 2003 to 2009–10, which was at the height of the boom. The figure currently has fallen slightly to 4.5 times, and this compares with a rate of no more than 3.7 times income in 2003.[49]

2.49      Dr Ian Goodwin-Smith from the Australian Centre for Community Services Research at Flinders University referred to the aphorism that 'a rising tide lifts all boats'. However, he said:

It is true to say that there is a rising tide and it is also true to say that it is lifting most of the boats. Even if we ignore those boats which are not being lifted—and there are plenty of them—the important point is that it is not lifting all boats at the same rate. It is a funny tide. In fact, I do not think tides are a very good analogy at all because you do not get tides like that at all. It is very bumpy. What that means is that there continues to be a growth in inequality and disparity of income.[50]

2.50      A South Australian Council of Social Service representative said:

...the evidence suggests that the largest share of [income] growth has been disproportionately captured by those who already have the most resources...we are very aware that rising inequality means increasing levels of poverty, especially for any household or individual whose income does not maintain parity with real living costs.[51]

2.51      Professor David Morawetz from Australia21 similarly explained:

The richest 20 per cent of households in Australia now account for 61 per cent of total household net worth, whereas the poorest 20 per cent of households account for just one per cent of the total. In the last decade, the richest 10 per cent of Australians enjoyed almost half of the growth in incomes, and the richest one per cent received 22 per cent of the gains from growth. At the same time, despite 23 years of uninterrupted economic growth, many of those currently dependent on government benefits, including those on Newstart unemployment benefits, are forced to live well below the poverty line. The poverty line in 2010 for a couple with two children was \$27 per person per day, and that has to cover rent, food, clothing, transport, medical expenses, everything—\$27 per person per day. Scandalously, one child in six in Australia now lives below this poverty line.[52]

2.52      UnitingCare Australia and the St. Vincent de Paul Society National Council indicated, that across their networks, there is more need at the coal face than has previously been the case. Dr John Falzon said that this was a clear manifestation of growing inequality.[53]

2.53      Reverend Bill Crews, who runs UnitingCare Australia's mission in Ashfield (Sydney), provided the following illustration:

We run a loaves and fishes free restaurant, which is open for breakfast, lunch and then we have a mobile food van. We are now preparing and delivering 1,000 meals a day every day. We started 25 years ago by delivering maybe 80. We only target the poorest of the poor and what we find is that they are people generally who have slipped between the cracks...We have an old couple who contacted us about a year ago, they are living on pancakes because they have got disabled children or grandchildren. We regularly find people coming into our restaurant who might be on benefits, but after they have paid medical expenses, transport and whatever they have got less than 50c a day to spend on food. We find that over and over again...On different days, we will give out a \$25 food voucher to the guests in some of our restaurants and particularly the men will say: 'Don't give it to me. Give mine to her. She's got these kids. She can take mine as well.' I can go on and on about inequality.[54]

2.54      The Department of Social Services has advised that the Australian Government's funding allocation for emergency relief (including Foodbank Australia)[55] has been reduced from \$57.457 million in 2013–14 to \$50 million in 2014–15, reflecting a reduction in the number of requests for assistance.[56]

2.55      Some witnesses disputed that there has been any such reduction and advised that demand for assistance from community service organisations has risen.[57] A representative from Anglicare WA said:

Our clients, the people we see every day, are living in challenging times and, despite recent years of high economic growth and low unemployment [in] Western Australia, many of our clients have missed out on the benefits of the boom. Aboriginal communities in particular have seen the boom go by. Our contacts for emergency relief have doubled over the last two years to more than 10,000 people in 2013-14. In the areas of emergency relief, food insecurity and housing, we see that people on benefits in particular and those on minimum wages are increasingly being swept into crisis. Issues of homelessness, food insecurity and social exclusion travel with people on low incomes.[58]

2.56      During the course of the inquiry, Foodbank Australia released its annual report into the 'largely hidden problem of hunger in our community'.[59] The highlights of the report are shown in Diagram 2.1 below.

2.57      The Foodbank Hunger Report 2014 stated that demand for food relief continues to rise, including:

2.58      The Tasmanian Council of Social Service (TASCOSS) indicated that poverty is widespread and is a particularly serious issue for that state, which has the highest proportion of people in the lowest income quintile (32 per cent):

It is estimated that over 14,000 Tasmanian children live in poverty. If we use 50 per cent of median income as a poverty line measure, 14 per cent of Tasmanians live below that poverty line. About one-third of Tasmanians rely on Commonwealth pensions and allowances for their main source of income, and this is the highest percentage of all Australian jurisdictions. Of the recipients of Commonwealth pensions and allowances, 37 per cent of those people live below the poverty line, and that percentage is largely made up of Newstart and Youth Allowance recipients.[61]

2.59      Chapter 6 of this report recommends that the Commonwealth Government urgently review the amount allocated for emergency relief funding to ensure that Australian in need are able to access assistance.

### Diagram 2.1: Highlights of the Foodbank Hunger Report 2014

Source: Foodbank Australia, Foodbank Hunger Report 2014, http://www.foodbankwa.org.au/hunger-in-wa/the-hunger-report/  (accessed 18 November 2014).

### Social mobility

2.60      The committee received evidence that income inequality leads to a lack of social mobility, particularly for those living in poverty. In their submission, Professors Peter Whiteford and Andrew Podger said that:

In considering income mobility by initial location in the income distribution, they found that 55.5 per cent of those in the bottom quintile in 2001 were also in the bottom quintile in 2009; 20.9 per cent were in the second quintile, 11.9 per cent were in the third quintile, 6.2 per cent were in the fourth quintile and 5.5 per cent were in the top quintile. Most people do not move more than one quintile, but equally, relatively few remain in the same quintile. However, the proportions remaining in the top and bottom quintiles are relatively high, at 55.5 per cent for the bottom quintile and 46 per cent for the top quintile.[62]

This evidence shows those on low incomes—especially in the bottom quintile—are unlikely to earn an income that places them in a higher income quintile.

2.61      The issue of poor intergenerational social mobility was also discussed in evidence to the committee. Although Australia compares favourably against the United States on the elasticity of earnings from fathers to sons, there is 'an appreciable level of inequality of opportunity in Australia'.[63] Mr Matt Cowgill of the ACTU, noted that the correlation between income inequality and intergenerational social mobility:

...is nowadays referred to as the Gatsby curve...[T]here is certainly an interdependent relationship between inequality of income in one generation and social mobility over the generations. There is an interdependence there and a correlation there that is not yet fully understood and unpacked, but I think it is quite likely to work in both directions. We highlighted earlier that societies which are less equal in one generation are likely to have less social mobility over time. It is probably also the case that there is some kind of causality working the other way, and that societies which have less mobility over time in which people are less able to achieve their potential are likely to have higher levels of income inequality.[64]

Mr Cowgill continued:

[C]ountries that are more unequal within one generation tend to have lower social mobility across the generations. If you are born into a society that is highly unequal and you are from a relatively poor background, you are less likely to reach up to the middle or higher income levels when you become an adult than if you were born into comparable circumstances in a more equal society. So that distinction between inequality of outcome and inequality of opportunity is largely false. Clearly we are not advocating for complete equality of outcome. But, by the same token, saying that we should ignore the level of income inequality I think ignores the fact that those things are related.[65]

2.62      This evidence shows that the children of those living in poverty are more likely to remain in poverty. Ms Kasy Chambers, the Executive Director of Anglicare Australia, explained the factors that lead to this outcome:

One of the things that concern[s] us and that we see happening increasingly is the lack of social mobility. When children are excluded from education or, as we talk about in our submission, where one child was going to his eighth school in seven years, that is clearly going to affect that child's chances. Even if he makes it through, it would have meant he would have been brilliant if he had not had that kind of disruption very early in his childhood. We would argue that once inequality starts to restrict social mobility, that is when it becomes far too concrete for us as a society to accept.[66]

2.63      The committee considers that there is need for more research into matters of intergenerational social mobility in Australia.

### Conclusion

2.64      This chapter has discussed some of the major research findings on the extent of income inequality in Australia. On a number of metrics, the evidence indicates that income inequality has increased in Australia against the backdrop of rising incomes across all income deciles. The incomes of those in the deciles may have increased but to a lesser extent than those in higher deciles.

2.65      Fast paced economic and income growth has increased income inequality, as the Western Australian example shows. In WA, the gross household income of the top eight deciles increased by an average 46.5 per cent between 2003–04 and 2011–12 (compared with 26 per cent nationally). In comparison, the bottom two deciles only increased their income by an average of 28 per cent (compared with 23 per cent nationally).

2.66      The committee is particularly concerned with anecdotal evidence that the incidence and severity of poverty is increasing in Australia. It draws attention to Reverend Crews' evidence regarding the demand for food experienced at one community centre and Foodbank Australia's report revealing that nationwide 516 000 people rely on food services each month (35 per cent of whom are children).[67] Even in a country that has experienced 15 years of uninterrupted economic growth and one of the highest living standards in the world, there is severe hardship.

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