Tag Archives: inequality

Household Wealth Inequality

This is the fourth post in the series on inequality in South Australia. The previous posts focused on different aspects of inequality in the distribution of income. This post looks at the distribution household wealth, again based primarily on the 2019-20 ABS Housing Income and Wealth data released this year.

Wealth Distribution Between Households

It is well-known that the distribution of wealth is far more unequal than the distribution of income. This is a function of both the cumulative impact of income differentials over years, as well as the ability of wealth to beget wealth (through capital gains and higher average returns on capital).

Nationally, the households in the highest wealth quintile hold 62.2% of all household wealth in Australia, while the bottom 40% of households account for on 6.1% of wealth. The P90/P10 wealth ratio sees the high-wealth households (90th percentile) owning some 52 times the wealth of the low-wealth households in the 10th percentile. (By contrast, households at the 90th percentile earn around 9 times the income of the low-income (10th percentile) households.

There is clearly a massive inequality in wealth distribution, but it is important to note that these high wealth households are not necessarily high-income households. Most obviously wealth accumulates over a life-time and at some point people retire which may leave them with some wealth but low incomes. The ABS data suggests that the wealth-income correlation is not straightforward. For instance, 10% of high-wealth households had low-incomes, while only one-third of low-income households also had low wealth. However, Piketty’s work highlights the correlations at the very top of the income/wealth spectrums where income from capital (wealth) becomes the dominant income stream.

Unfortunately, the ABS does not publish wealth ratios or wealth-by-quintile of data on a state basis, so there is limited data on wealth inequality within South Australia. However, there is some useful data on wealth distribution between states.

SA share of total household wealth

As with previous posts, I start with aggregate wealth rather than the ABS household averages because the aggregates adjust for differences in population. The graph below shows the various state and territory share of total wealth held by households in 2019-20, but plotted against the share of total income and population. It can be seen that NSW and Victoria have a greater share of wealth than of total current income, while Queensland and WA a higher share of income than wealth. South Australia’s share of the total wealth held by Australian households is quite close to its share of income (wealth 6.5% of total, income 6.3%), but both are below the state’s population share.

Column graph showing state/territory shares of national household income, population and net household wealth.
(Note: NT data does not include remote areas)

While this graph is a snapshot of 2019-20, the long-term trends are not easy to discern. My previous post showed that South Australia’s share of national household income has declined over the last two decades, driven in large part by a declining share of the population. However, the columns in the graph below, which show the state’s share of total household wealth, do not show a similar pattern of decline – or any pattern really. This could be a trick of data unreliability (wealth data is less reliable than income data), or of different structures of household wealth (see below) or different levels of indebtedness (which would impact on net wealth – although the data is not available over the long term).

Time series showing SA declining population and income share (as % of national aggregate), but no real pattern in share of wealth bouncing between 5.6% (2016) and 7.2% (2006), and overall approximately the same in 2020 as in 2004.
(Note: data not available for 2000-01 and 2007-08)

I have included this time series data for completeness, but I draw no conclusions from it. Nor can I draw any conclusions on the distribution of wealth between households in Adelaide and the rest of the state. Even though the ABS publishes it, the regional wealth data has such high margins of error I would not rely on it. I think the primary take-out of the data above is that South Australia’s share of national household wealth is lower than its share of population. Or put another way, wealth (like income) is disproportionately held elsewhere – and with only around 6% of both wealth and income, this makes it difficult for South Australia to have an impact on Australia’s political economy.

Structure of Household Wealth

Beyond these aggregate figures, the published data based on average household wealth shows some interesting differences between South Australia and other states in the structure of wealth holdings.

The graph below shows a state-by-state comparison of different components of average household net wealth (that is, the value of household assets minus liabilities). At the highest summary level, it is clear that South Australian households on average have less wealth than Australian households generally (approximately 88% of the national average), and significantly less than states like NSW, Victoria and the ACT. This is seen in the height of the columns on the graph, but it is interesting to note that South Australian households have the fourth highest average wealth. By contrast, SA households have the second lowest average household income. Both WA and Queensland have higher average household incomes, but lower average wealth.

South Australian households fare relatively better in wealth distribution than income distribution, but this is even clearer when we look at the components of this total net wealth. One of the key reasons for SA lagging behind the richer eastern states is the higher value of wealth tied up in owner-occupied dwellings there (the blue at the top of the columns). That is, households in other states where housing prices are significantly higher are likely (on average) to have more of their wealth tied up in their homes. Not counting owner-occupied dwellings, the wealth held by the average South Australian household is just $15,000 less than the national average. The SA average is 98% of the national average.

Column graph showing different components of wealth (real estate, and various financial assets) - net of liabilities. SA has 4th highest level of wealth, but below national average - but much closer if owner-occupied housing assets are excluded.

The amount of wealth held in owner-occupied housing is important because there is considerable debate as to whether owner-occupied housing should actually be considered as wealth. At one level it is clearly an asset which can be sold for money, and (as I have argued in an earlier post) provides housing services which is a form of in-kind income which can be imputed as non-cash household income. On the other hand, as Anwar Shaikh and others have argued, it is not real “wealth” because housing is a necessity and cashing in the asset is not simply transferring a physical asset to a cash asset (with an attached transfer of income from imputed rent to other investment income). Liquidating an owner-occupied house actually leaves the owner worse-off as they will now have to pay rent.

Obviously though, the same is not true for housing properties not occupied by the owner as these are held as investments and can be liquidated in a simple swap to another form of asset.

The wealth tied up in owner-occupied housing is also important because lower housing costs in South Australia (relative to other states) can also translate to SA households holding relatively more financial assets (because their “savings” are not tied up in housing costs to the same extent). This is evident in the graph in the relatively high shareholdings and business assets held by South Australian households (seen in orange), although the ABS warns that there is a high margin of error on these particular figures and some caution is required.

Further though, (despite lower incomes) lower relative housing costs also potentially translate into lower average household debt. In 2019-20, the principal outstanding on loans for owner-occupied dwellings in SA averaged out at $88,500 per household, which was 77% of the national figure, while total household debt as a proportion of household wealth was also lower in South Australia (14.4% of total household assets in SA, 16.4% nationally).

The debt figures are averages of households with and without debt, so those in debt will have much higher amounts owing than these average figures, and the averages will be impacted by the proportions of households with/without debts. However, on its face it does suggest interest recent and predicted interest rate rises will impact slightly less in South Australia than in states (and territories) where average debt is higher.

Conclusion

What all of the above suggests is that, despite the average income of South Australian households perennially lagging behind the national average, SA fares better in the distribution of household wealth. Indeed, when the wealth data is considered without reference to owner-occupied housing (which is not transferable or income-earning in the same way as other assets), average net household wealth in South Australia is pretty close to the national average.

However, at the aggregate level, South Australia’s small share of both income and wealth shows that there are still significant issues around the state being relatively marginal to income distribution and wealth accumulation in the national economy. This has not (yet) flowed down to impact on average household wealth, but the wealth data does little to relieve the concerns highlighted in previous posts about SA being at the economic periphery.

And finally, this focus on geographic inequality should not blind us to the massive inequality of distribution of wealth within the state. There is little reason to assume South Australia is immune from the national pattern where the majority of wealth is held by the richest households and the lowest quintiles hold almost no wealth. The dual challenges remain: to get a bigger share of national economic development for South Australia, while distributing that share more equitably within the state.

Regional South Australia – Inequality at the Peripheries

Context

This post on regional South Australia is the third of a series of posts on inequality.

The first post looked at inequality of household incomes between states. It found that South Australia’s share of income is below its share of the population, and that the state’s share of both national household income and population has decreased over the last two decades.

The second post looked at inequality within South Australia. It found that while the broad pattern reflected the national spread across income quintiles, the South Australian distribution was characterised by relatively lower incomes at the top end of the income spectrum.

This post looks at regional South Australia. Again, the data is drawn from the ABS Household Income and Wealth series, with “regional” being defined by the ABS “Rest of State” data beyond Greater Adelaide. This categorisation obviously conflates very different regional and remote areas, but it does still reveal some important economic dynamics beyond Adelaide.

Again, I use the share of total/aggregate income as a key analytic. The share of aggregate income captures changes in both income and population, and in a regional context it highlights changes in a key material base of community viability and development.

Regional South Australia’s Share of State and National Income

Incomes in regional areas vary greatly from area to area and from year to year depending on the local industry-base, weather patterns and commodity prices. The 2019-20 data collection also overlapped with bushfires and COVID, but the ABS methodology was designed to minimise the impacts of those events so the data reflects long-term trends.

South Australia has a particular regional demographic (shared with WA) of a particularly dominant capital city. Around 80% of the SA population live in the Greater Adelaide area, while the rest of the state is large and lacking other big cities. This in itself creates economic, social and service-delivery challenges in much of regional South Australia, but it is made worse by lower average incomes.

Average (mean) gross household income in regional South Australia in 2019-20 was $1679 per week, which was 81.6% of the Adelaide average – although household size was also smaller in regional South Australia (2.2 people per household in the regions, 2.4 in Greater Adelaide). However, given average household income in Adelaide was also below the national average, this meant that the average household income in regional South Australia was just 72% of the national average.

At the aggregate level, regional South Australia accounted for just 17.7% of the total household income in the state, while housing 19.9% of the population. By comparison, regional areas in all states accounted for 31% of the Australian population and 27% of all household income. So regional South Australia is struggling relative to both Adelaide and to other regional areas.

Inequality within Regional South Australia

The overall income spectrum in regional South Australia appears to mirror Greater Adelaide. Adjusted for household size, the income share for the bottom two quintiles, the P90/10 ratio and the Gini Coefficient are all fairly similar between Adelaide and the “rest of the state” (more details here). However, the census data mapping the proportion of the population in different income brackets tells a more nuanced story.

The Adelaide and regional SA numbers are shown in the graph below in the same way that my previous post mapped the national/SA figures. In both cases, for the relatively poorer jurisdiction, we see a greater proportion of households in the middle-income categories and significantly fewer among higher income households – in this case, households earning over $2,000 a week.

Line graph showing the proportion of households in Adelaide and Regional South Australia in each of the census income brackets.

Some of the differences evident in the graph above are an effect of household size, where bigger households in Adelaide more likely to contain multiple income-earners, but it is also just a simple question of geography. To extend the conclusion of my previous post: the rich don’t live in regional South Australia (at least not in the same proportions as in Adelaide, or the rest of the country).

Changes over Time

However, the biggest concern about regional inequality may be the changes over time. Just as the national figures show that South Australia has lost both population share and income share over the last twenty years, so too regional South Australia has lost both income and population share within the state.

The graph below is similar to one used in the previous post on South Australia’s share of the national household income, but this shows regional SA’s share of aggregate state household income. Regional SA’s share of income and population is plotted on the left axle, while average household incomes (as a percent of those in Greater Adelaide) are plotted on the right axle.

Line graph plotting regional South Australia's share of state income alongside its two components: changes in population share and average income.

In all years, regional South Australia’s share of aggregate household income was below its population share, but there has also been a clear decline of the regional income share over the last two decades (from 22.6% of SA’s total household income in 2000-01 to 17.7% in 2019-20). As the graph shows, the early years of this decline was associated with a fall in average regional household incomes relative to Adelaide. However, even when this relative fall in average income levelled off and improved, regional South Australia’s share of aggregate household income still fell – driven by significant declines in population share.

Given that this regional decline is relative to a state which is also declining in the national data, the end result is particularly worrying. Regional SA’s share of national household income has declined by nearly a third over the period, from 1.6% in 2000-01 to just 1.1% in 2019-20. This makes maintaining economic (and political) viability harder relative to the rest of the country, a fact which can drive further decline.

Conclusions and Speculations

I have suggested that the picture of regional inequality – the unequal incomes between regional SA and the capital city – mimics the differences between South Australia and the national income distribution. This obviously suggests that there are some similar dynamics at play.

David Peetz (and others) have argued that the majority of the gains of neoliberalist economic growth over the last 30 years have gone to finance capital. The data under consideration here is consistent with that analysis. Such financialisation processes tend to concentrate income in the geographic centres of finance, leading to a relative decline in income in the areas outside those centres. This in turn creates a periphery where households are living at a base rate (arguably propped up by nationally regulated incomes), but where it is more difficult to sustain higher incomes as population and income is attracted to core areas.

This type of effect is compounded for regional South Australia. The core-periphery process happens between South Australia and the financial centres of the Australian economy, and is then repeated between regional South Australia and Greater Adelaide.

I deliberately use the academically contentious (and somewhat dated) term “periphery” because it summons a long history of debate over colonial and post-colonial development. While I will not go over those debates here, some of that “development” should ring warning bells about policies we might adopt to address the under-development and subsequent inequality in our own periphery.

For instance, the Australian regional development default often appears to be to intensify the extraction of natural resources. This is intellectually lazy and driven more by private profit than community development, but crucially, as Joe Collins argues in a recent JAPE article, such “extractivism” does not guarantee development and comes at great costs to the environment, and often to local communities – Indigenous and settler.

Further, the low-wage strategies adopted in parts of the post-colonial world may also be counter-productive. Given the particular shape of the income graphs above, low-wage strategies may simply increase numbers in the low-mid income brackets, but do little to close the gaps identified at the higher end which are drivers of geographic inequality (albeit while making internal distributions more even). At best, it is a levelling-down, rather than levelling-up, approach.

I may return to these policy arguments in future posts, but my main purpose here was simply to examine the data on regional inequality in South Australia. However, the results, which posit regional South Australia as the periphery of the periphery, clearly bode badly for equality and for the economic sustainability of those regional areas. A significant migration and regional development policy response is required.

The super-rich don’t live here: Inequality in South Australia

Context

This is the second of a series of posts on inequality, with a particular focus on South Australia. The first post highlighted differences in the share of the national household income going to different states, and the long-term decline in South Australia’s share of household income.

This post shows that, while household income may be lower than other states (except Tasmania), the distribution of income between households in South Australia is more equal than the national average.

Again, unless otherwise stated, the data here is drawn from the ABS Household Income and Wealth series. However, the data on the “share of total income” that I flagged as crucial in my previous post is less important here because the proportion of households in each quintile is the same. That is, there is no dynamic from changing population numbers.

The ABS Data on Inequality in South Australia

While the overall pattern of income distribution and inequality within South Australia is similar to the national pattern, by almost all measures in the ABS data, income distribution within South Australia is slightly more equal than for the country as a whole.

The table below summarises key measures for both gross household income, and for equivalised disposable income (that is, after-tax income adjusted to equivalent household sizes).

Table showing ABS measures of inequality in South Australia by both gross and equivalised income quintiles.

The first line is the income share of the lowest two income quintiles, with those households in South Australia having a slightly higher share than the national average.

The second line is the P90/P10 ratio which refers to the ratio of income of high and low income households, specifically, high-income households at the top of the 90th percentile by comparison with those in the 10th income percentile. These high-income households in South Australia received 8.19 times the gross income of households at the low (10th percentile) end of the income spectrum. This represents significant inequality within South Australia, although it is less than the Australian average ratio of 8.98.

The third line is the Gini Coefficient, which is a complex statistical measure where lower numbers represent more equal income shares (0 would be perfect equality, and 1 would be absolute inequality with one person receiving all income). While the Gini coefficient is widely used, I don’t find it particularly useful. The number is meaningless of itself (I still have to look it up every time I see it) and the importance of a difference at the second or third decimal point is hard to grasp. Again though, the Gini Coefficient shows SA has a slightly more equal income distribution than the national average.

It is also worth noting that in each case, the equivalised disposable income figures are much more equal than the gross income figures. This demonstrates the importance of both household size and the redistribution impact of taxes. But in each metric in both gross and equivalised data sets, the South Australia figures are slightly more egalitarian than the national ones.

Top End Drivers

It is important to note that the differences between South Australia and the country as a whole are not the same across all income quintiles. The incomes of those on the lowest incomes in South Australia are much closer to those on the lowest incomes nationally than is the case for those in the highest income brackets. The average (equivalised disposable) income of the lowest income quintile households in South Australia was $403p.w. in 2019-20. This was 97% of the national figure for the lowest income quintile. By contrast, for the highest income quintile, the average income in South Australia ($2,015p.w.) was only 90% of the national figure.

The same pattern is evident in the graph below, which shows the income at the top of the selected percentiles. The gap between South Australia and the national average increases as we move up the income spectrum. (The equivalised data provides a more like for like comparison, but the gross data [not plotted below] shows proportionately higher incomes at the top of the range in South Australia. The difference in the two data sets suggests that that relatively higher incomes in gross data are driven by larger household sizes rather than higher individual incomes).

Line graph of equivalised income at the top of percentiles, 2019-20 for South Australia and Australia. Both lines upward sloping but with a gap widening as we move up the income scale.

This overall pattern is perhaps not surprising given that the incomes of many of those in the lowest income brackets are set nationally (e.g. social security and minimum wages) and are the same regardless of location. However, the patterns do highlight a key issue in the analysis of inequality – the importance of what is happening at the top end. In this case, it appears that the incomes at the high end of the South Australian spectrum are much lower than those evident in the national data. This reduces income inequality in South Australia, but also contributes to South Australia’s relatively low income share overall.

Census Data

The recent Census data provides a different perspective on the same phenomenon. The census only collects data in brackets of total household income, but the graph below shows the proportion of households in each bracket. South Australia has proportionately more households in the low-to-middle income brackets, but proportionately fewer in the brackets over $2,500 income per week. In particular, the top income bracket has the biggest gap of any bracket, with 12.4% of households nationally receiving more than $4,000 per week, by comparison with only 8% of South Australian households.

In short, the rich and super-rich don’t live in South Australia (or at least not in the same numbers as elsewhere in the country).

Line graph showing proportion of households in each ABS income bracket for Australia and SA.

Inequality in South Australia Over Time

While my previous post highlighted a long-term decline in South Australia’s share of national household income, the changes over time in inequality within South Australia have been less clear. The graph below shows both the P90/P10 ratio (on the left axis) and the income share of the lowest income quintile (right axis) since 1994/95. Some caution is needed as there were methodological and data series changes in 2003-04 and 2007-08, but both indicators have remained fairly steady over the last 25 years.

The blue line of the P90/P10 ratio does show an increase in inequality in South Australia between high and low income markers from the mid-1990s until the Global Financial Crisis in 2007-08. However, the income gap began closing from that point until 2013-14 when inequality began rising again – at the same time as the income share of the lowest quintile began to fall. It remains to be seen if this is simply a fluctuation or the beginning of a period of further rising inequality. But at a minimum, we can say that the level of inequality in South Australia is long-standing and not getting any better.

Line graph showing time series of two measures of inequality in South Australia: P90/P10 ratio, and the lowest income quintile share from 1995 to 2020.

Conclusions and Caveats

In summary, the data above shows that while South Australia is not getting an even share of national household income, inequality within SA is at least a little less than the national spread. Crucially though, both these phenomena appear to be driven at least in part by a proportionate lack of high-income households.

Again, all this data comes with caveats around the limitations of analysis by income quintile (and the lack of accounting for non-cash incomes). In particular, the crucial top 1% of income earners are invisible in the ABS data.

Perhaps though, the biggest caveat is that South Australia is not a singular entity and the analysis above is based on only one formulation of income inequality (between households). There are other important ways to consider income inequality beyond households, and there are also geographic differences within South Australia. These will be the subject of future posts in this series.

Inequality between Australian States: Household Income

This is the first of a series of posts on inequality, with a particular focus on South Australia. The series begins with income inequality between states, but will then consider inequalities within South Australia. Unless otherwise stated, the data is drawn from the Australian Bureau of Statistics’ Household Income and Wealth series, but the posts often use different categories and ask different questions to those presented in the ABS data.

The primary analytic used here is often the share of total income. It is an aggregate measure used because the more usual “average” figures (mean or median) tend to individualise social and structural issues. Further, the average figures do not account for the changes in numbers of people or households within a category. This is a parallel argument to one I made in relation to the gender wage gap, but in the case of the inequality highlighted in this post, the share of total income takes account of for both differences in household income and population changes. As will be seen, this makes a difference in the story told by the data.

The share of total income as a measure of inequality between states is also important in its own right because it highlights the relative resources available to different communities. A millionaire recluse living on their own island may have a high average income, but that is the only resource available to them. By contrast, a larger community may have much lower average incomes but far more resources which can be taxed and mobilised for the community.

Inequality between States: 2020 data

In 2020 South Australian households accounted for 6.3% of all household income in Australia, while constituting 6.9% of the population. This may appear to be a small difference, but is actually quite significant. This 0.6 percentage point difference is approximately 10% of the income share. It equates to around $130m per week or $6.7bn per year which would be in the South Australian economy if the state’s share of income matched its population share.

Putting the data in this form highlights the wicked dilemma of this inequality between states. South Australia (and other lower-income states) do not have the same income resources to drive the development which could see it catch up to the other higher-income states. If there are no other national financial redistributions, the inequality is perpetuated. This potential cycle is one reason why federal government support and the distribution of the GST pool in favour of the poorer states is crucially important.

As the graph below shows that SA is not alone in having a lower share of income than population. Queensland has the largest gap between income and population shares at 0.8 percentage points, but this is on a relatively large base (equating to just 4% of the income share). Tasmania’s income share is 0.3% below its population share, but this is particularly significant when the population share is only 2.3% of the whole in first place.

By contrast, WA has the highest gap with income share greater than their population share. Their 10.7% share of national household income is 0.5 percentage points above their population share. This equates to about 5% of their population share. Again, the percentage differences may appear small, but constitute significant amounts of money and represent significant inequalities between Australian states.

Australian State and Territory Share of National Household Income plotted alongside share of population to show inequality between states.

It is noteworthy that these figures do not simply reflect differences in household income. Average (gross mean) household income in South Australia was $1,989 per week, which was 85.4% of the national figure ($2,329). Tasmania’s average household income was 75% of the national average. But both SA and Tasmania also have smaller households on average, which pulls their income averages lower.

By contrast, the average gross household income in the Northern Territory was $2,711 – the second highest in the country and 16.4% above the national average. This would seem surprising, but the territory data excludes remote areas. The result is also a product of larger household sizes (average of 2.9 people per household in the Territory, as opposed to 2.6 nationally). The NT’s share of national income roughly reflects their population share.

Of course some of these demographic differences would be captured had I used the ABS equivalised income data sets (which are adjusted to take account of household size). However, using the data on shares of national income to measure inequality between states also provides important insights on changes over time.

Changes over Time: South Australia

While South Australia’s share of national household income is currently below its share of population, its income share has also declined over the last 20 years. As shown in the graph below, the state’s share of national household income reached a high in 2003-04 at 7.4%, but dropped below 7% in 2007-08 and has not recovered.

South Australian share of total national household income 2001 to 2020, showing long term decline.

In all years the SA share of national household income was below its population share, while average household incomes were also consistently below the national average. However, (again) it was not simply about lower average household incomes. As the graph below shows, the South Australian average household income as a percent of the national average fluctuated over the period. It ranged from a high of 91.6% of the national average in 2003-04 to a low of 81.3% in 2013-14, before returning by 2019-20 to close to its 2000-01 value around 85%. In that sense, while changes in household income provide short term fluctuations, what is really evident in the graph below (which plots the three variable as indexes with the same starting point) is that the overall decline in South Australia’s share of income has been driven much more by the decline in population share.

Index of Changes in South Australia's Income and Population showing volatility of average income in SA as % of national, but steady and same decline of population and income share.

Again, the fall of 0.7 percentage points in South Australia’s share of national household income over the period may seem minor, but it is actually a drop of around 10% of South Australia’s share of national income. It equates to well over $8bn annually in current dollars that would be in SA if income share had been maintained its share of national household income over the period.

While the COVID pandemic has changed some migration and population patterns, the longer-term trends remain to be seen and the wicked problem of maintaining income and population shares is likely to remain for a while yet.

Caveats

There are of course a number of caveats to the above data and analysis. In previous posts I have been critical of these household income figures: (here) for not taking account of capital gains and non-cash housing income, and (here) noting Piketty’s critique of the categorisation and data sources. The ABS does publish some data on non-cash income (imputed rents, and “social transfers in-kind” [i.e. provision of free services like health and education which do not appear in household budget]). This provides a fuller account of household income, but it is still without capital gains and is not published at the state level.

Without that state data on total income, the analysis is incomplete. It is likely that imputing rent for owner-occupied dwellings would reflect higher rental prices in eastern states and increase the differences between South Australia and some of those states. By contrast, the social transfers in-kind are likely to disproportionately benefit the lower-income states and reduce inequality. However, without the data I can’t be sure or estimate the extent of impact.

Conclusions and Implications

Even with these caveats though, the income share data does show significant geographic inequality between states. Alarmingly, it also shows the situation is getting worse for South Australia and points to a vicious cycle of falling relative incomes leading to shedding population which itself leads to lower incomes shares and a decreasing ability to generate the things that could build/maintain population and income shares.

It is also coincidental but noteworthy that the period studied here is the period since the GST was introduced. That is important because the formula for the distribution of the GST is explicitly designed with an equalisation objective to “provide states with the opportunity to provide their residents with comparable services” (Commonwealth Grants Commission). The formula is based on a complex range of metrics (not income shares) and the distribution has been controversial. Western Australia in particular in recent times has complained of not getting their fair share. However, the data in this post suggests not only an ongoing need to support a redistributive approach to states with weaker income and revenue, but indeed that more needs to be done (within and/or beyond the GST).

The alternative is greater inequality between states driven by some states capturing a greater and greater share of national income and population, leaving the weaker states in their wake.

Understanding Class: Reflections on Erik Olin Wright’s Multi-layered Synthesis

Class is a key category and concept in political economy. In saying this, I am not saying that class is the totality or the cause of all inequality, or the base of all economic processes. The days of seeing all history as the history of class struggle are long gone, but the distribution of wealth among different classes of people, and the understanding of class behaviour, mobilisation and power remain of critical importance – both to political economy and to society generally.

Yet despite (or because of) this importance, the concept and analysis of class is hotly contested and muddied by different meanings and analytical frameworks. In this context I recently came across a reference to Erik Olin Wright’s attempt to bring together Marxist, Weberian and Durkheimian definitions and theories of class into a coherent (rather than competing) multi-layered framework. (While Wright is famous, I have not read much of his work – not sure why!) The following is my summary and reflections – informed as always by some concrete campaign problems I am currently thinking about.

Photo of book: Understanding Class, by Erik Olin Wright

Understanding Class

In one of his last books, Understanding Class (2015), American sociologist Erik Olin Wright starts with the broadest of framing of different class traditions:

  • Marxist: where class is a system of exploitation structured around the accumulation of wealth based on the ownership of capital;
  • Weberian: where class is a location within market relations built on the hoarding of economic privileges to the exclusion of others (think: education credentials or licencing requirements for middle-class jobs, union closed shops or the exclusive rights of private property);
  • Durkheimian: where class is a collection of attributes and life conditions which determine people’s position in society (e.g. geographic location, occupation, cultural traits, health, housing conditions – all of which impact on access to income and resources).

My first experience of these differences was a long time ago when a mad activist sought to verify my proletarian credentials by grilling me about my parents’ occupation and where I went to school. I replied that I did not own the means of production and had to sell my labour power. Talking at cross-purposes.

However, Wright brings these broad approaches together by seeing them as simply operating at different levels and asking different questions. This is best explained by a metaphor of a game. Marxism is interested in what game is being played (capitalism or socialism). Weberian class is about the rules of the game (how the system is regulated and maintained – with various regulatory regimes being possible within capitalism). The Durkheimian tradition is about moves within the rules of the game – with individuals or interest groups vying within a given set of rules to get a better slice of the pie.

I have adapted one of Wright’s tables (and associated discussion) to summarise the framework.

LevelGame MetaphorPolitical Focus/IssuesClass Analysis
SystemicWhat game to playRevolutionary v counter-revolutionary politicsMarxist
InstitutionalRules of the gameUnion regulation, employer rights/control, role of the stateWeberian
SituationalMoves in the gameGovernment spending, tax rates, subsidiesDurkheimian

Wright takes his analysis in a strange sociological direction with lots of graphs of class politics and political strategy. However, applying his multi-layer model to local politics, I would suggest a mud map of left-of-centre class politics as follows:

  • the NGO left operates mostly at the level of situational inequality (in part because they are formed and funded around particular issues),
  • left-leaning economists, the “industrial left” and the majority of those identifying as “socialist” operate mostly at the institutional level (eg. social democracy v neoliberalism), while
  • everyone claims to be operating at the systemic level!

Critique

As a tool of class analysis, I have a few issues with Wright’s framework. It implies that Marxism has little role in institutional struggles around tax, distribution and regulatory regimes. Yet an analysis of the processes of accumulation is surely central to such politics.

Further, it reduces the “systemic” choice to whole of society changes (revolution or counter-revolution), rather than seeing capitalism as just one particular set of production relations among many – albeit the dominant set (although as noted in an earlier post, even this hegemony is debatable in a digital age). From this perspective, the system-choice politics at the top level of Wright’s analysis may be less than revolutionary – everything from debates over public ownership/privatisation of utilities (i.e. production by the state or by capitalist businesses), to whether a forest is protected (i.e. kept outside production) or felled as a commodity for a capitalist production process. And, most mundanely, the question of whether to cook dinner at home (non-commodified household production) or to eat out (capitalist production) is a system-choice.

Finally, some things will have some characteristics or elements which could fit in to different categories. For instance, a minor concession reform to extend support to someone with a particular attribute (e.g. low paid, precarious work) may simply be a situational move which does not change the position or power of the recipient. However, it still implies and calls for a particular redistributive role for the state – which is an operation at the institutional level. And as Wright notes, the cumulative impacts of a number of situational moves/policies at some point could amount to or force institutional reform.

The Usefulness of the Analysis

However, despite these concerns, the multi-layered framework in Wright’s Understanding Class is important and useful for a number of reasons. Firstly, it reminds us that while we may be using similar terms, such as “class”, we may mean very different things and have very different understandings of what that means. But more importantly, it highlights the incompleteness of any of the paradigms.

This has very direct implications for policy development and what to do about inequality. To focus simply on systemic issues and institutions which promote or challenge class inequality is to ignore the very different ways those structures and institutions impact on people in different situations. Conversely, to simply focus on the attributes of people or their differing situations risks victim-blaming (it is about their attributes) and not challenging the institutions and structures which drive inequality.

As an example, I am thinking about my current work developing a campaign for more public housing. It seems to me that if we simply argue on the basis that certain groups are excluded from housing, then even if we can identify these groups by particular attributes (e.g. older women, ex-prisoners, unemployed youth), we will not get more public housing unless we also win the institutional campaign around the role of the state in providing housing – and perhaps we won’t win that debate without making inroads into the systemic ideology around the limitations of a capitalist market. That said, if we are too focused on big picture debates about economic systems, people won’t see a relevance to their particular circumstances and we won’t mobilise the support needed to change anything. And of course, most organisations/campaigns simply don’t have the resources to operate at all three levels.

Further, it is not even as simple as which level to focus on. There are also questions about the language and data we use. To take a different example, if we define poverty or inequality as being based on household income (the mainstream definitions) and then to do analysis of the dis/proportion of women in poverty, or on different educational levels or sources of income within the poverty cohort, we are talking (often unintentionally) a Durkheimian language of attributes rather than systems (in the Marxist sense) or the institutional arrangements (in the Weberian sense) which drive that poverty and inequality. To talk about those things, we may need different data (e.g. the wage share of GDP, but much more besides) and a different language.

Conclusion – of sorts

Like Erik Olin Wright, I originally came from a particular camp in the great class debate, but now want to acknowledge the power and potential of different perspectives – even if I don’t quite know how to develop this in practice. How can we organise politically at multiple levels – especially if we don’t have a shared language or understanding? What might class alliances look like if they are splintered by the different (and potentially conflicting) attributes and situations that people bring to confronting the institutions and structures of class (and other inequalities for that matter)? Indeed, according to one reading of his last book (2019), Wright himself came to believe that the working class had become too fractured to play the role Marxism traditionally assigns to it.

Or there is the question I ask myself most often at work: how do we address structural inequality if the language, data and rules of the game (including views of what is possible) are already set to a limited field of situational inequality?

I occasionally see opportunities to use data differently, to ask different questions or challenge orthodoxies or unconscious theoretical propositions, but I don’t have a macro-theory or big answers – particularly to the question of organising diversity.

However, despite my questions and lack of answers, I think Wright’s approach in Understanding Class is interesting and provocative. It will be the background I will bring to reading a forthcoming book edited by Steven Threadgold and Jessica Gerard on Class in Australia, which I have just pre-ordered. I look forward to seeing what frameworks are engaged and at what level we might progress. UPDATE: Post on Class in Australia here.