Tag Archives: labour market

“Hard Labour”: A Review of Wage Theft in the Age of Inequality

For a book on industrial relations, Ben Schneiders’ Hard Labour is a good read – interesting, passionate, depressing and hopeful in equal measure. Based on investigative journalism done for the Age newspaper, it traces the rise and exposure of wage theft in Australia over the last 10 years.

Cover Photo: Hard Labour - Wage Theft in the Age of Inequality by Ben Schneiders

I am not sure Schneiders ever gives a formal definition of wage theft, but the book is concerned with workers being paid at rates below the legal minimum or award wages. Many of the examples are familiar (including from Schneiders own reporting): Spotless laundry, McDonald’s, Coles, 7-Eleven, Woolworths, a series of high-end restaurants, and piece-work on farms and in the gig economy. That is the depressing part, but what is interesting is the different models of underpayment and wage theft.

Three Types of Wage Theft

The most straight-forward was unpaid work hours forced on workers by bosses threatening visas, or by industry norms or by the star-power of the workplace. Celebrity chefs and fancy restaurants were Schneiders’ case studies for the later – made even more egregious in some cases by corporate structures which evaded tax as well as industrial relations responsibility. But such unpaid work is also a norm in industries not considered in the book: for instance, for young academics and young lawyers needing to work their way into a decreasing number of secure jobs.

Beyond this enforced free labour, the book also details cases where the standard piece-rates of fruit-pickers, farm workers, delivery drivers and task workers in the gig economy are set so low that it is impossible to make the minimum wage. This is a long-stranding problem, but the stories of successful new union organising among migrant workers in farms on Melbourne’s periphery was one of the most hopeful parts of the book.

Perhaps the most outrageous form of wage theft was hidden in plain sight: workplace agreements which traded away penalty rates and left workers earning less than the award wage. These were negotiated with the union and were rubber-stamped by the Fair Work Commission. The book covers cases with supermarket and fast-food giants effectively sidestepping the “better-off-overall test” (although eventually many of these agreements were voided after legal challenges). Ever-present here was the union, the SDA, which not only failed to protect low paid members, but actively colluded in the negotiation of these (ultimately) illegal workplace agreements – sometimes in the context of cosy closed-shop recruitment schemes.

That matters not just for the workers affected, but for the future of unionism. In one of his most chilling observations, Schneiders notes that in 2020 only about 5% of young workers were members of unions. The rest were rarely exposed to unions, indeed barely knew they existed – or perhaps their first or only experience was with a union that had sold them out. And their remedies appeared to lie outside of union structures (in local organising, in media, or in government watchdogs). It is not a pretty picture for unionism, notwithstanding that some of the heroes in the book are organisers in other unions.

The Bigger Picture

Many of the stories of wage theft in Hard Labour are well known and have been documented by media, Senate Inquiries, and finally in Fair Work Commission findings. But the book is much more than a series of stories lifted from old reporting. It also gives us the background to the media stories (i.e. the campaign organising), the reaction to publication and the industry push-back, and the development of the issue as it unfolded over the last decade.

That story is interesting, but for me the power of the book lies in the broader context. While he says it is not a book of economic or political theory, Schneiders nonetheless puts the story of wage theft in the context of neoliberalism: the choices made to deregulate the economy and to curtail union and worker rights. In this context, wage theft is not a coincidence, nor the work of a few rogue companies. It is a manifestation of a fundamental shift in power in favour of (global) capital. For Schneiders, wage theft is ultimately not an industrial relations story, but a story of power and inequality – and I am not going to argue with a framing that starts with Thomas Piketty and the statistics on rising inequality and the accumulation of wealth and income at the top end.

The point of Hard Labour is that wage theft is both a manifestation of and a contributor to that disproportionate rise of capital incomes and inequality.

Yet despite everything, there is some hope in the book with cases where wage theft was addressed and wages paid out. Perhaps the “golden age” of wage theft is over – or perhaps (as I hinted above) we simply await another series of reports from different firms and different industries?

Time, and further activism, will tell.

Sidenote

Underlying my reading of the book was of our research at SACOSS on waged poverty. One in four Australian households below the poverty line have wages as their main source of income – and that that employment adds costs to already impossible household budgets. Not every worker below the poverty line will suffer wage theft, but many live in the same milieu of precarious work, and wage theft is inevitably part of the story of waged poverty.

Hard Labour is another reminder that (as I argued in my previous post) poverty and inequality need to be tackled in the primary distribution between wages and capital, not just in after-the-fact welfare redistributions.

Industrial Relations, Income Flows and Inequality

With Australia’s new industrial relations law now through the federal parliament, there is talk of increased wages, or at least a hope that real wage increases will be possible with workers having better bargaining tools to try to secure them. After years of wage stagnation, obviously any increase in wage levels is welcome, but much of the public debate has focused on the need for wage increases to help households, especially low-income households, with increased cost of living. But increasing wages is also fundamentally important to macroeconomic income flows and equality.

In his landmark Captial in the Twentieth Century, Thomas Piketty noted that in many western countries inequality was increasing to levels unprecedented since the turn of the last century because the growth of capital incomes was outstripping wage incomes. Capital incomes are concentrated at the high end of income distribution, so the relative share of society’s income going to capital and to labour was a crucial determinant of inequality.

However, in a really interesting exchange after the release of Piketty’s book, political economist Anwar Shaikh argues that Piketty’s work focuses largely on the final distribution of income, but a far more nuanced understanding of inequality could be gained by tracing the primary, secondary and tertiary income flows which lead into that final distribution.

Shaikh argues that in a capitalist economy, production is based on the harnessing of labour power to produce new value from which capital can make a profit. Accordingly, the primary income distribution is that between labour and capital in the production process. At the macro level this primary distribution is captured in the structure of the national accounts where the income side of Gross Domestic Product is divided into compensation of employees (labour income) and gross operating surplus (capital income). In June 2022, labour received 44% of GDP, and the historically low labour share was one of the driving forces of the government’s Future Work Summit and the push industrial relation changes (see for instance the ACTU Job Summit Paper: An Economy that Works for People).

However, this primary distribution does not tell us the full story because from this primary distribution there are secondary distributions. Wages (compensation of employees) is split between taxes and disposable “take-home” income – an important distribution as progressive taxation is a significant factor in equalising take home wages from what is a much more unequal original distribution between wage earners. But gross operating surplus is also split into rents, royalties, profits, interest and taxes. These distributions are the property claims of different types of capital on the surplus income. The relative amounts of the secondary flows between these types of capital reflect the structure of production and the balance of class power within capitalism – so that, for instance, it has been suggested that finance capital has claimed most of the gains of neoliberal economic growth over the last 20 years.

Finally, there is the tertiary distribution which is redistribution of the taxes (taken in the secondary distribution) to households through transfer payments and to capital via subsidies and industry support. This is important because these social security transfers are the most visible face of “redistribution” and efforts to over-come inequality (e.g. campaigns to increase income support payments, or to provide public services). However, as we will see below, it is also the smallest of the distributions. While interventions in this space are necessary – especially for those outside of the circuits of capital and production income – they are also necessarily limited as the size of the tertiary flow is inevitably determined by the primary and secondary income flows.

The focus on primary, secondary and tertiary income flows arises out of classical and Marxian political economy, but they are difficult to quantify because our national accounts are based on Keynesian and neoclassical principles. Accordingly, the accounts do not necessarily record these flows. However, some data is available and is captured in the table below.

Income Distributions, Australia, June Quarter 2022

Table showing primary, secondary and tertiary income flows: GDP $609,133m Wages $268,573m Surplus $182,263m Total Taxes $174,807m Social Security Transfers $36,991m

Source ABS, Australian National Accounts, June Quarter 2022, Tables 7, 22, 23.

These numbers are important because they show the magnitude of the different income flows and the potential impact of changes in them. For instance, a 2 percentage point increase in the labour share of the economy (compensation of employees), which would return labour to the levels of twenty years ago, equates to a $12bn or 4.5% increase in total wages for the quarter. By contrast, even a 10% increase in social security payments (personal benefit transfers), would only see a $3.6bn redistribution of income.

Again, this is not to say that arguments for social security increases are unimportant, but it does emphasise the importance of industrial contestation over the primary income distribution. Or put another way, it emphasises the importance of class (income flows based on relationship to the means of production) to understanding inequality.

A similar argument could be made around gender. Applying the proportion of the total wage pool noted in a previous post to the above national accounts data, a 2 percentage point increase in the female wage share would equate to a $5.3bn (5.1%) increase in women’s wages in the quarter. Again, that is more than the total of social security transfers (which also disproportionately go to women). Arguably then, closing the gender pay gap or increasing women’s labour force participation is a more direct route to gender equality than social security payments – albeit with application to different women.

Obviously these class and gender arguments reprise my previous arguments about the importance of a structural approach to addressing inequality, but they may be particularly important as the labour movement goes forward with the campaigns under the new industrial relation system.

Inequality Alarm Bells for South Australia

The data presented in my earlier “Snapshot of Inequality” shows that levels of inequality in South Australia are lower than the national average in a number of areas, but there are alarm bells ringing in the background – and they are getting louder.

The First Warning

At first glance it looks like good news for croweaters. Income distribution between households is slightly more even in South Australia with proportionately fewer households on very high incomes. Compensation for workers in South Australia is higher as a proportion of the state economy than the equivalent national figure (the labour share). The “official” gender wage gap is around half the national average, and households in regional South Australia earned closer to the average Adelaide household than the regional/capital city divide nationally.

However, the apparently good South Australian outcomes come against a background of South Australia having lower average incomes and wealth than the national averages. For instance, the gender wage gap is lower in South Australia – but so are women’s wages with average full-time ordinary time earnings for women $68 per week lower than the national average for women. Similarly, the average income of households in regional SA is closer to the Adelaide average, but $217 a week lower than the national average for regional households.

Wellbeing is about quantum as well as relativity to others (equality). However, the picture here is also complicated by differences in housing costs, service provision and the need for a fuller accounting of income (alluded to in a previous post, but beyond the scope of this work).

The Alarm Bells for South Australia

In the context of this study, what is ringing the alarm bells loudest for South Australia is not the current gap to the national averages, but the general decline in the position of South Australia relative to the rest of the country over the last 30 years. The South Australian share of the national economy (GSP as a proportion of GDP) has fallen from 7.71% in 1990 to 5.7% in 2021. The data in the graph below shows the impact of this relative decline on inequality statistics. Cue the alarm bells: South Australia’s share of national household income, SA labour’s share of the national economy and even the SA female share of the national wage pool, all declined over the period.

Cue the alarm bells: time series (2001-2021) showing downward sloping lines (i.e. declines) of SA shares of national population, household income, labour share, and female wage share.

It is important to note that this is not, or not necessarily, about average incomes declining relative to the rest of country. Equivalised household disposable income in SA was 92% of the national average in 2001, and the same in 2020. Similarly, female full-time total earnings in South Australia were 96% of the national equivalent in May 2001 and the same in May 2022.

Population Impacts

A key factor driving the data, but which is not evident in the average income data is the decline in South Australia’s population share. This decline is evident in the top line of the graph. The drop was less than 1 percentage point (from 7.8% in 2001 to 6.9% in 2020), but this is still significant.

Had SA retained its population share (that is, grown at the same rate as the rest of the country) over the period, there would be around 220,000 or 13% more people in the state. On current averages of household size and income, those population differences equate to around $9.7bn of household income per year extra that would have been in the SA economy (not counting any multipliers arising from extra population).

Clearly the relative loss of population has a major impact on the SA economy. Combined with the changes in the various average incomes, it gives the downward trajectories in most of the data (even where the income share actually increased in relation to the SA economy). Capturing both population and income changes is the whole point of using income shares rather than household averages, and in this case it highlights several concerns for South Australia.

Firstly, with a declining share of national household income, the gap between South Australia and much of the rest of the country is growing. SA is becoming poorer as a community, even if that is not reflected in the individual household data. That is the alarm bell ringing in the background. As I noted in relation to regional South Australia (where this process is heightened with a further decline in regional communities), this impacts on the ability of communities to provide infrastructure, growth and the ability to attract and retain people. It becomes a self-reinforcing cycle, and the alarm bells become a symphony.

Secondly, as the data above shows, the relative decline of South Australia as a whole means that inequalities within South Australia are also made worse – not internally, but in relation to the rest of the country. Put another way, the more egalitarian income spread and distributions within South Australia may ameliorate, but do not overcome the growing inequality between South Australia and the average of the rest of the country (hence the downward sloping graphs).

As a whole, the South Australian data provides an example of how different inequalities interact with eachother. In this case the geographic inequalities undermine greater gender and class equalities (or alternatively, greater gender and class equality ameliorate increasing geographic inequalities).

Policy Response

South Australia is not alone in this predicament. The same is probably true of other smaller jurisdictions (although I have not done the numbers), and it is certainly true of regional South Australia where the decline of local communities is truly alarming. Clearly a policy response is needed: the current policy settings are not working as South Australia and the regions are being left behind. However, the interactions of different forms of inequality make the policy response complicated.

I have previously noted the importance of government redistribution through mechanisms like the sharing of the GST pool. The data here clearly shows the ongoing need for a sharing from the high-income states to the rest of the country. I have also noted that traditional responses in economies at the periphery (be it regional areas, struggling Australian states or developing countries) has been to attempt to intensify the use of natural resources. However, academic literature suggests that this “extractivism” offers no guarantee of genuine development and may exacerbate inequality and environmental degradation.

In South Australia’s recent history, the Rann/Weatherill Labor governments, like the Liberal state government before them, were desperate to develop new mining operations in the regions and defence technologies in Adelaide. The Marshall government offered a high-tech space future, and the current government spruiks a hydrogen future. Whatever we make of these ideas, the obvious point is that they did not stop the relative decline of South Australia and regional South Australia in particular, and there was little consideration of the multiple layers of inequality in those policies. A far more comprehensive approach is needed.

There are no easy answers here, and there are contradictions in dealing with ininequality. For instance, as my post “the super-rich don’t live here” indicated, the biggest areas of geographic inequality between South Australia and the rest of the country, and between regional SA and Adelaide, exist at the higher end of the income spectrum. This creates a contradiction because policies aimed at creating high paying jobs in particular areas would be a step towards reducing inequality between geographic areas, but would increase inequality within those same areas (as there would be a greater spread of incomes). For instance, policies which pay highly skilled workers loadings for working in regional or remote areas may increase incomes at higher levels (and may be necessary to ensure service provision), but they will increase the income gap between those people/households and most other households in that area. Similarly, regional development based on extractive industries may increase regional incomes and geographic equality, but is also likely to favour male workers and exacerbate the gender wage gap.

Conclusion

The contradictions of development and inequality are difficult to navigate, and the focus on multiple dimensions of inequality (in this case, how the inequality between South Australia and the nation as a whole intersects with inequalities within South Australia) complicates the picture of inequality. However, such a focus is important.

The examples above and the use of data on gender and class inequality alongside household income remind us that inequality is built in to economic activity. In turn, this suggests that addressing inequality can’t simply be a distributional after-thought where we drive policy for narrow economic goals, then catalogue how the results are distributed and perhaps seek to address inequalities at that point through welfare provision.

At best, with that approach we will always be playing catch-up – looking for payments and services to paper over fundamental cracks. More likely, we will simply lose. The macro-dynamics will overwhelm any welfare provision.

I will say more about that in a future post, but from the inequality data presented here and in previous posts, it is clear that greater economic intervention is essential. If left to themselves, market forces and demographic patterns will continue to channel money and population to existing growth areas, and continue the decline of South Australia. And if intervention and governance is done without a focus on inequality, or with too narrow a focus only on some inequalities, we will see people or groups within South Australia (and elsewhere) left behind.

The alarm bells are ringing – we need to pay attention.

Snapshot of Inequality – South Australia and National

This snapshot of inequality summarises my series of recent posts on this subject. The series has been a journey. I didn’t completely know where the data would take me and I am now asking different questions than when I started. However, frustrated by the mono-dimensional analyses that often dominate discussion of inequality (including in my own work) I was keen to explore the multi-layered nature of the beast.

Inequalities in income and wealth distribution between households, across states and regions, and between structurally differentiated social groups all matter, so I was keen to analyse the data on all of these – even if in an iterative fashion. I also wanted to look particularly at South Australia, partly for local relevance and partly because state-level data is often not factored in to the analysis of inequality.

Snapshot of Current Inequality

Overall the data examined in this series (almost all it sourced from the Australian Bureau of Statistics) showed significant levels of inequality across the country, as summarised in the table below.

 AustraliaSouth Australia
Household Income (between states) (2019-20)Australian average (mean gross) income $2329 per week, but state averages range from $1,736 (Tas) to $2,422 (NSW)Average household income $1,989 p.w. = 85.4% of national average, although difference mainly at top end. SA receiving 6.3% of all household income (which is below its population share).
Household Income (within states) (2019-20)  Bottom 40% of households received 13.4% of the total income. High-income households (90th percentile) received 9 times the income of low-income households (10th percentile).Inequality broadly reflects national patterns, but relatively lower incomes at the top end of the income spectrum
Household Income (Regional Areas) (2019-20)Regional Australia accounted for 31% of the population, but received only 27% of income.Regional SA share even smaller with 19.9% of population, but just 17.7% of income.
Household Wealth (2019-20)Distribution more unequal than distribution of income: highest wealth quintile held 62.2% of all household wealth, while the bottom 40% of households held only 6.1% of wealth.Distribution data not available, but wealth holdings in SA have a different structure (relatively less wealth in home ownership, more in financial assets).
Labour Share of the Economy (2021)“Compensation of employees” at historically low levels (47.7% of GDP).Labour share slightly higher (49.3% of GSP)
Gendered Wage Patterns (2022)Gender pay gap of 14.1% in full-time ordinary-time earnings. Bigger gaps when all earnings and all employees included.At 7.4%, f/t ordinary-time earnings gap is around half the national average, but on lower earnings and relatively lower male earnings. Difference between national and SA figures narrows when all earnings and employees included.

Changes Over Time

The above snapshot of inequality is precisely that – just a snapshot at the current point in time. Arguably, a more important story is evident when changes over recent decades are considered.

That story is not straight-forward and has been explored more fully in the earlier posts. However, the short version is that, at the national level:

  • income inequality between households has increased slightly,
  • inequality between cities and the regions, between capital and labour, and inequalities in household wealth have all increased more markedly,
  • gender wage inequality was the only measure where inequality decreased.

These trends are evident in the graphs below which trace changes in the share of the various pools of total income (or wealth, or production), alongside the same data for South Australia (i.e. share of SA total income/product). The time periods vary depending on data availability.

Household Income and Wealth

As can be seen, nationally, the share of total household income of the lowest two (equivalised) income quintiles has been relatively stable, peaking in 1996-97 at 21.4% and falling to 20% in 2019-20. However, while this fall in income share appears small, every 0.1% change represents over $22.6m (in 2019-20) going from the lower to higher income quintiles. Even more significantly, the share of national wealth held by the poorest two wealth quintiles fell more markedly, although the data is more limited, and is not available for South Australia.

Time series snapshot of inequality: share of household income and wealth captured by the bottom two (equivalised) income quintiles, 1994-2020.

Households in Regional Areas

The share of total income received by households outside Australian capital cities fell from 30.7% of the national total in 2000-01 to 27% in 2019-20. (Note: not all years are included in this data). The South Australian data is more volatile, and shows a lower share overall (with proportionately fewer households outside the capital), but the trend is similar.

Time series snapshot of Inequality: Share of national and SA income captured by households in respective regional areas, 2000-2020.

Class

Nationally, labour’s share of the economy fell from 48.8% in June 1994 to 47.7% in June 2021, with each 0.1% change in this data set representing $2bn (in 2021) lost from labour payments. However, the South Australian data here is different, falling more swiftly from a higher share of the economy to a low point in June 2004, then recovering to 49.3% of Gross State Product in 2021 – a larger share of the economy than the labour share nationally.

Time series snapshot of inequality: labour compensation's share of the economy, SA and Australia, 1990-2020.

Gender

As noted above, the gender wage share is the only indicator to see a reduction of inequality with women increasing their share of the national wage pool from 33.1% in November 1994 to 39% in May this year.

Time series snapshot of inequality: female share of total wage pool, SA and national, 10094-2022.

Caveats and Conclusions: Why the Numbers Matter

This snapshot of inequality focuses on shares of total pools of income/wealth, rather than the more traditional but disparate average income figures. My approach enables some consistency of analysis across the different data sets, but I make no claim of a causal relationship or that the inequalities are comparable in nature. Clearly, inequalities can contribute to each other and the data sets overlap, but they are analytically separate and the different trajectories show why it is flawed to simply focus on one dimension (usually household income) when considering questions like whether inequality is increasing or not.

In a future post examining the South Australian data in more detail I will explore more specific interactions between different axes of inequality, but the point of this snapshot of inequality is simply to summarise the data and note the importance of considering multiple forms of inequality alongside each other, rather than the usual mono-dimensional focuses.

In arguing for a broader focus on the multiple forms or layers of inequality, I am not calling for endless sets of data or the infinite division of society until we are left only with individuals (as in the neoliberal dream). Rather, my point is that statistics (and all research data) is a reflection of the questions we ask and the theoretical understandings underpinning the research. Our national economic statistics are a product of the neoclassical and Keynesian theories that gave rise to them (that was Chapter 1 of my PhD). So too, the data we use to describe inequality reflects particular theoretical standpoints.

More than that, the data can limit the way we see society and the policies we might pursue to address both inequality and political economy more generally. For instance, data on the distribution of income between households tends towards a tax-and-transfer redistribution (after the fact) to support households in the lowest income brackets. By contrast, labour share data begets industrial policies, while regional data inevitably leads to development debates.

In saying that, I am mindful that my analysis is not comprehensive. I am sure that people with better statistical programs and skills could provide more nuanced numbers, and not all structures of inequality have been examined. Most notably, there is no consideration of structures of racial inequality, although with relevant census data to be released later this year I may be able to add to the analysis later. Perhaps more importantly, I am also acutely aware that race, gender and class inequality is ultimately not reducible to numbers – or even to the economic.

All that said, the economic aspects of inequality are important, and the numbers do provide useful points of reference. At its most basic, it seems to me to be important to have some sense of the scale of inequality, whether things are getting better or worse, and in what areas.

South Australia’s Small Gender Pay Gap: Is it Good News?

The gender pay gap in South Australia is around half the national figure – but is this really good news?

This is the sixth post in the series on inequality in South Australia, with the early posts dealing with inequality between households and the later posts looking at structural inequalities. This post continues the focus on structural inequality, and looks at gender inequality – or at least one aspect of gendered economic inequality.

Gender Pay Gaps – Official

The “official” gender pay gap figures used by the government’s Workplace Gender Equity Agency show that the gender pay gap is significantly narrower in South Australia than in the country as a whole. At 7.4% the gender pay gap in South Australia is around half the national average, and is the lowest in the country. However, there is devil in the detail of this official figure.

While the gender pay gap is lower in South Australia, this gap is on lower wages overall and does not necessarily reflect women doing relatively better. ABS Labour Force data shows that the $1541 per week full-time ordinary time earnings for women in South Australia was 95.8% of the equivalent figure at the national level. For men in SA, full-time ordinary time earnings were 89% of the national figure. In theory, this difference could mean that SA has proportionately more women in higher paying jobs, but more likely it reflects labour market segmentation where proportionately more women are in jobs with wages set nationally (e.g. minimum wages or modern awards), while men are overly represented in non-award industries where wages may differ more across the country.

This suggests that much of the difference in the national and SA gender pay gaps is not about women’s pay, but rather because men’s wages in SA are disproportionately lower than the national average. Put another way, rather than the labour market in SA bringing women’s wages up closer to men’s, it is an “equalling down” based on relatively lower men’s wages.

This creates particular challenges for the left and the union movement: how to increase wages in South Australia to closer to national averages without also increasing the gender wage gap? Obviously, a focus on gender segmentation and increasing wages in highly feminized industries like childcare is a start, but it should also be a factor in changes to enterprise bargaining currently under consideration.

Bigger Gender Pay Gaps Beyond the Headline Figure

The “official gender pay gap” based on full time ordinary time figures is only one measure of gendered pay inequality. The table below shows a range of key gender pay gap and wage share data for Australia and South Australia and is necessary because the full-time ordinary time data is limited. It ignores (and arguably institutionalises) gender differences in access to overtime and bonuses.

The first line in the table is the official full-time ordinary time data, but as can be seen in the second line of the table, when overtime, bonuses and other extras are taken into account in total full-time weekly earnings the gender pay gap is much larger. It is still less of a gap in South Australia, but the difference in the national and SA figures is narrower.

However, even these full-time figures ignore the over-representation of women in part-time and casual work. As evident in the third line in the table, the gender pay gap jumps markedly when the average weekly earnings of all employees are included. The gap between South Australian and national figures is much lower here, presumably because of a higher proportion of women in part-time jobs in South Australia. This is confirmed by the gender wage share data in the bottom line of the table, where the difference between the national and SA figures is lowest.

Gender Pay Gaps, May 2022

 AustraliaSA
F/T Ordinary Time Earnings14.1%7.4%
F/T Total Earnings16.5%9.6%
Average Earnings29.7%27.7%
Women’s Participation Rate62.2%58.4%
Gender Wage Share39.0%40.0%
Source: Calculations from ABS Average Weekly Earnings and Labour Force

Gender Wage Share

I have set out elsewhere a rationale for considering, alongside the traditional average pay gap data, the gender wage share – that is, the female share of the total wage pool. The importance of that wage share data can be seen here.

Both nationally and in South Australia, the female half of the population takes home around 40% of the total wage pool. In actual dollars, the May 2022 figures show that men as a whole in South Australia take home $221m more than women each week, for an annual return to gender of $11.5bn. To put that in the context of the local economy, the total sales revenue of South Australia’s biggest company, SANTOS was around $6.9bn in 2021, around 60% of the gender wage share differential.

As I argued in an earlier post about the corresponding national figure of a $200bn annual wage differential, the aggregate gender wage share difference is a significant economic flow that not just reflects but contributes to the reproduction of that inequality.

Changes Over Time

The 2022 data above shows, in short, that while the official gender pay gap is much lower in South Australia, the benefit of this is diluted by lesser participation in paid work by women (both relatively lower participation in the workforce, and relatively fewer hours by those engaged in paid work). As we will see below, these patterns are not new.

The following graph shows the full-time (all earnings) gender wage gap in Australia and South Australia over the last 25 years. While the data on South Australia is more volatile, the gender pay gap in South Australia has generally been below the national figure. In both data sets, the gender pay gap shrinks in the late 1990s, but grows again from 2000 nationally and from 2004 in South Australia through to 2014. The gap then shrinks over the next few years before flattening out in the last few years.

Time series of gender pay gap in full-time total earnings in South Australia and Australia.

However, the gender wage share data tells a slightly different story. There is little difference in the time-series data on South Australian and Australian women’s share of their respective total wage pools. In both data sets there is a small but sustained increase in women’s share (apart from a small dip after the Global Financial Crisis in 2008) (see the black SA line in the graph below). In South Australia women’s share of the total wage pool increased from 35.1% in November 1994 to 40% in May this year. The national figures showed an increase from 33.1% to 39% over the same period.

Crucially though, this story is set against the backdrop noted in a number of my previous posts of a general decline in South Australia’s economy relative to the national economy. This was evident in SA’s share of household income and the labour share of the economy. The graph below shows that this decline also impacts on the gender wage share. While the top line shows that women have been increasing their share of the South Australian wages pool, with that pool in relative decline, South Australian women’s share of the national wages pool has actually shrunk from 2.6% in 1994 to 2.41% this year.

Time series (1994-2022) of female share of total wages pool in South Australia, and South Australian female wages as proportion of Australian wage pool.

While this decline in South Australian women’s share of the national wage pool is alarming, it is made even more problematic because, as noted in the previous post, the wage pool itself is declining as a proportion of the economy.

Summing Up

The official gender pay gap data shows South Australia doing relatively well with the smallest gap in the country, but a closer look at the data tells a less rosy story. The smaller gender wage gap is based on lower women’s participation rates and relatively lower male wages in South Australia. It is not a story of greater female agency in the labour market. The national/SA differences almost disappear when the share of the total wage pool is considered.

And regardless of the comparative story, the gender wage inequalities in South Australia remain significant – with a 27.7% gap in average earnings leading to an aggregate $11.5bn annual wage gap. Further, while women’s share of the South Australian wage pool has increased over the last 25 years, these gains are undermined by the shrinking of that wage pool relative to the national wage pool – a national pool which, with historically low labour shares of GDP, is itself shrinking relative to the economy as a whole.

Beneath the headline gender pay gap data, for South Australian women workers there is a particularly problematic intersection of gender, geographic and class inequalities.