I was at a meeting last week discussing prices for public transport. One of the government representatives there noted that we needed to be careful about providing concessions on ticket prices because if discounts were too widely available that would limit their revenue and ability to provide services.
At one level this was reasonable response from a departmental officer responsible for service delivery within budget parameters over which they had no control. But at another level, it struck me that it was a statement of a particular political economy and a service delivery model within that political economy. My first thought was that we don’t talk about roads like that: “oh, we can’t reduce motor vehicle registration because we won’t be able to build or maintain roads”.
Of course, vehicle registration fees don’t really pay for roads – no matter how many times motorists yell this at me as they scream past me on my bicycle. Large roads are least partly federally funded (and thus largely funded by income taxes), and most small roads are the work of local councils paid for by rates on property. Even the state government money from vehicle registration does not go directly to roads, it goes into general revenue and is not hypothecated (specifically allocated) to road building and maintenance.
Then again, train and bus tickets do not cover the cost of public transport either. Those services “run at a loss” and are subsidised by taxpayers – although again, (perhaps with the exception of some privately-built expressways) we never talk about roads running at a loss or being “subsidised” by the taxpayer. Yet in theory, we could set vehicle registration to pay the costs of roads. The fact that we don’t do that means that roads and public transport are quite similar in that they are a mix of user-pays charges and tax-payer funded public goods.
The reality is that for both public and private transport, and indeed the provision of any good or service, there are a range of possibilities for how it is provided and paid for. In a sense there is a spectrum with total user pays at one end: the private market is the most obvious example, but public ownership at this end is also possible (think SA Water which returns a dividend to government). At the other end of the spectrum is the total taxpayer-funded provision of services provided basically for free (think public hospitals or schools). And in between there are all manner of shared-cost options from gap payments and below-cost service charges, to direct grants and subsidies to third-party providers.
Where on this spectrum any particular good or service fits is a political-economic choice. We could provide free public transport to everyone as we provide free roads, or even, as I suggested in a previous post, provide electricity in the way we provide public education. Alternatively, we could construct artificial markets to enable user-pays models for the provision of public services – as we actually have done for electricity. There are reasons why such choices might be made in terms of the characteristics of the good or service (e.g. the relative difficulty/cost of capturing payment and excluding non-payers [very difficult on roads, but easier on public transport], or where monopoly provision is preferable to having multiple competing networks [electricity, water]). However, it is not just a technical issue – because we choose to have free public hospitals and schools as well as private user-pays institutions providing the same or similar services.
There is a significant ideological element in the choice of where on the spectrum we locate a particular service provision. It was social democracy that built the public electricity system, and it was neoliberalism that justified its privatisation. And to return to our original example, it is a neoliberal application of business language to public services that sees public transport as “running at a loss” or its provision being governed by the prices charged (rather than the amount of government funding).
The point here is not how public transport should be funded, but rather that not seeing the bigger picture constrains the policy options available. Rather than a suite of possibilities on the spectrum of public and consumer funding, we see prices for public services being set by a business logic which is arguably foreign, and at least only partially relevant to the provision of those services.
And suddenly, we can’t afford to offer concession tickets on half-empty public transport!
As we make our way through the first month of a new financial year, political economic debates are dominated by inflation, interest rates and “full employment”. But the discussion of interest rates is generally focused on their impact on inflation at the macro-level, and on mortgages and cost of living at the micro-level. The impact of interest payments on government budgets is usually noted in budget night commentary on the deficit/surplus scorecard, but promptly forgotten for the rest of the year.
However, an unusual occurrence (at least in recent times) in the South Australian state budget should serve to illustrate why interest rates matter to government and to the community. In 2023-24 the amount of government expenditure going to servicing state debt ($1,254m) will eclipse the budget for the Department of Human Services (DHS) ($1,148m). This difference grows over the forward estimates with the DHS budget subject to real cuts (low indexation and older operational savings) while interest payments increase substantially. By 2026-27, interest payments are predicted to be $1,684m, by comparison with a DHS budget of just $1,233m.
In practice, this means that we are spending more on debt repayments than we are on the Department that is the primary provider of support services for the most vulnerable and disadvantaged people in our state. That feels wrong – but apart from the shock value, does it really matter, or it is just a statistical coincidence with no budget or social impact?
A Debt Problem?
As I pointed out in SACOSS’ post-budget analysis, government debt and deficits are not necessarily a problem – and may represent important economic stimulus or long-term investment. And there is no suggestion that this level of debt in unsustainable, although the budget papers show that a 1 percent point increase interest rates in 2023-24 would equate to an extra $203m in service payments. That would obviously be a significant imposition on the budget, but even with the debt-to-income ratio rising, the government can clearly still maintain payments. However, if debt is unchecked or interest rates continue to rise, at some point interest payments either become unsustainable, or more likely, a significant constraint on budget spending in other areas.
In that sense, the comparison of interest payments and the DHS budget is important because it reminds us of the potential impact and opportunity cost of state debt. I am not suggesting that if we were not paying that money in interest, we would be spending it on human services. That would be wishful thinking! However, all government spending has distributional impacts, and interest payments are no different. The comparison with DHS expenditure simply serves to focus the interest payment discussion on inequality.
Debt, Interest Payments and Inequality
In providing concessions and emergency supports to those on low incomes, and funding charities to provide a range of other supports, the Department of Human Services functions to transfer money and resources from the budget to those most in need. By contrast, interest payments are a transfer from the budget to government bond holders – who, by definition, are those with excess cash to afford to lend money to the government (by buying bonds).
As Piketty has pointed out, (and [as ever] some of the concerns here come from my reading of his work) it is far more advantageous to those with capital to have public deficits and receive interest on their money than to have that capital taxed to balance the budget (Capital in the Twenty-first Century, p.130). So, in creating government debt we have already chosen to favour those with capital by borrowing rather than taxing their money and creating an ongoing flow to rather than from that capital.
Seen in this light, the contrast between the DHS budget and the amount going to debt servicing is an indicator of choices about government priorities – the choice to provide relatively less to the poorest in society (via government expenditure) than to those who are better off (via taxes foregone and interest paid out).
Caveats
Of course, as with everything in economics, it is not as simple as that. The initial use of borrowed capital may be used for things which support those on low incomes, and inflation may quite separately have a counter-balancing impact by undermining the real value of bonds and the interest payable on them. Further, bond-holders may not be South Australian residents and may therefore be outside the tax ambit of the state government. In that sense the taxing v borrowing from capital argument above is not about individual bondholders. Rather it is illustrative of the options of government in general and operates at the level of class: that is, the state government has options to tax local capital rather than borrow from capital in a national or global market.
To the extent that we can look at individual bondholders, it is also worth noting that, as Piketty points out, they are no longer necessarily the wealthiest people in society (as the super-rich can invest more lucratively elsewhere). ABS wealth statistics do not record bonds as a separate category, so it is hard to confirm this. However, it is clear that the low-inflation era of the first years of this century made bonds a safe investment for middle class superannuation and investment funds, so when we talk about bondholders it is likely we are talking about middle and above-average income earners (often via superannuation or investment trusts). In that sense, the DHS/interest payment comparison is not so much about rich vs poor, but about a form of middle-class welfare instead of a transfer to those in most need of the supports that a DHS might offer them.
Finally, there is another (non-taxation) route to balancing the budget and avoiding interest flows to capital owners. That is by cutting expenditure. However, cuts to expenditure (and therefore to services) usually impact disproportionately on the poorest people. Those with the fewest economic resources are likely to be most reliant on support services and have limited or no alternative options, so expenditure cuts usually also impact most on the poor. Further, it is notable that in this SA budget, government debt continues to increase even with operational surpluses from 2023-24 onwards, so balancing the budget is not simply done by cutting expenditure. However, there is little doubt that when government services are cut (the “austerity approach”) this exacerbates inequality, so if fairness or equality is a consideration in balancing the budget, we must ultimately return to revenue issues – and our preference for borrowing rather than taxing capital.
Why Debt and Interest Payments Matter
Budget deficits and surpluses matter, but not for the reasons often touted in economic commentary (“responsible government”, “living within our means”). They matter because they determine the level of debt, which in turn, within any given interest rate regime and revenue base, impacts on the money available to spend on services. And as interest rates increase, so too does the cost of servicing government debt. The choices made to borrow rather than tax capital increasingly manifest in a distribution of government revenue to the middle and upper middle classes rather than to those on the lowest incomes who would benefit most from government service provision.
The fact that the SA state government interest payments now eclipse spending on the Department of Human Services should make us think about government priorities and the need for a stronger tax base.
Today, Adelaide’s online newspaper, InDaily published an opinion piece from my boss, (SACOSS CEO) Ross Womersley. The piece is titled ‘Business as usual’ state budget won’t cut it, and is an analysis that basically says that SA’s economy is in trouble, and that we are becoming poorer as a community.
The article walks through the data that shows the state’s relative economic decline, and concludes that we need a 2023-24 state budget with a bold and interventionist approach, a budget that “provides a vision, strategy and, most importantly, investment on a new scale in industry and regional development, skills development (including raising levels of digital competency and inclusion), and population retention and attraction.” The alternative, as the conclusion makes clear, is decline and inequality.
It does not take a close reading of the InDaily piece to see echoes of my previous post on “Inequality Alarm Bells for South Australia“. It is ok. It is not plagiarism, or theft of intellectual property. More a ghostly presence at my workplace.
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.
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.
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.
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).
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
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).
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.
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.
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.
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.
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.
