Category Archives: Inequality Research

Highlighting income and wealth inequality data, issues with inequality data, or research (mine or others’) on income and wealth inequality.

Compare the Pair: Income Inequality on the Same Income

Can a homeowner really be $30,000 a year better off than a renter with the same income?

We are all familiar with superannuation ads asking us to “compare the pair”: two otherwise similar workers in different superannuation funds getting very different financial outcomes. Today I want to do a similar exercise for the extended incomes of two people on identical wages, with the only substantive different in their lives being that one owns their own home, while the other one rents.

The different financial outcomes that result go beyond just the amount of rent that one of the pair pays. Nor are they based on lifestyle or consumption differences, clever investment strategies, complex tax minimisation planning (beyond a basic voluntary superannuation contribution), or any other scheme beloved of financial planners. As such, and with everything else about their lives the same, the compare the pair exercise enables us to draw some interesting conclusions about the role of housing and taxation in inequality.

Inequality - not what you think

Compare the Pair

Renter-Greg and homeowner-occupier-Greg both work as professionals in suburban Adelaide and earned $100,000 last financial year. They both live alone, but are neighbours in the same set of home units. Renter-Greg pays $350 a week in rent, while home-owner-Greg is an owner-occupier who paid off their mortgage six years ago. Ever since paying off the mortgage, homeowner-Greg has been making voluntary superannuation contributions equivalent to renter-Greg’s weekly rent – leaving both with the same weekly consumption expenditure (neither saves or invests any further or has any other source of income).

You get the picture: a standard simplified model where all other factors are equal so any differences in financial outcomes are only the result of different housing costs and the ability of homeowner-Greg to put money into superannuation. Of course, the ability to buy a home and invest in super may be conditioned by all sorts of social factors, but the model could also simply be viewed as a comparison of potential financial outcomes of the same person with different housing tenure.

As the table below shows, the bottom line is that homeowner-Greg is nearly $30,000 a year better off than renter-Greg, despite them having the same employment income.

TABLE 1: Comparing the Pair, 2023-23

Compare the Pair: Table showing renter and homeowner comparison, with homeowner $3k better off after tax, then earning $18,200 in imputed rental income, and $8,565 in return on extra superannuation contributions.

(a) Tax is calculated using the ATO simple tax calculator, with homeowner tax based on income tax on $81,800 salary and 15% of $18,200 voluntary super contribution.

(b) Income from voluntary super contributions does not include the voluntary contributions themselves, only the income on the accumulated balance of these contributions, calculated using an industry average rate of return (9.2% for the 2022-23 year, and 5.8% for each preceding year).

Explanation

The first step in comparing the pair is simple enough and is just based on salary income and tax. As can be seen above, homeowner-Greg has a higher disposable income because of the tax concessions on voluntary superannuation contributions.

When we include housing costs, the difference is starker. As noted in a previous post, accounting for housing-costs in income comparisons is common in poverty research (which is usually based on after-housing incomes), while the national accounts also recognise the value of housing ownership by including a value for rent that owner-occupiers are deemed to pay themselves in their measure of the size of the economy. The value of this imputed rent is added to homeowner-Greg’s income (because the value of this free housing service is income-in-kind). The result is a further increase in income inequality, with homeowner-Greg’s after-housing income being 28% higher than renter-Greg’s income.

The next step is to account for the extra income homeowner-Greg receives from being able to make a voluntary superannuation contribution. When this investment income is included, homeowner-Greg’s extended income is nearly $30,000 higher in the year than renter-Greg’s. Again, this is based solely on home ownership and the ability to invest the money saved on housing costs in superannuation.

Alternatives

A significant part of the difference in financial outcomes above comes from the superannuation investment. If homeowner-Greg just put the savings into a standard bank account, they would not get the benefit of the tax concession and would have lower returns on accumulated savings. However, with a relatively modest interest (2% ->3%), they would still get some $2,600 more income than renter-Greg in the 2022-23 financial year.

Of course, homeowner-Greg could also just spend the money not going on rent rather than invest it, which would mean less difference in the long-term, but significantly higher weekly consumption and standard of living than renter-Greg on the same income.

There is one final calculation that could be made to include the value of the capital-gain on the house in homeowner-Greg’s annual income. Home unit prices in Greg’s neighbourhood increased by 8.8% in 2022-23, so homeowner Greg would have “earned” $39,600 in capital gains on his $450,000 unit (average unit price). That would bring the difference between renter-Greg and homeowner-Greg’s income to $68,650, or more than two-thirds of their starting income (gross salary). I have argued previously that capital gains are an important driver of inequality which are overlooked in most data, but there is also an argument to exclude capital gains for owner-occupied housing. This is because unlike pure financial investments, where capital gains are a key return, owner-occupied homes are not simply an investment product. They fulfill a basic need (housing), and while a capital gain may be realised upon sale, most people selling are buying another house in the same inflated market – so they are really simply swapping one house for another, not gaining wealth through the capital gain.

The arguments here are complex, and excluding capital gains on the owner-occupied residence probably underestimates the differences between renters and homeowners. However, the compare-the-pair data above shows that even on the conservative estimate, homeowner-Greg’s extended income is 39% higher than renter-Greg, despite doing a similar job for the same pay.

Conclusion and Implications for Analysis

The most obvious conclusion from this data is that it pays, literally, to be a homeowner. However, it is also important to note that the capital income from accumulated voluntary super payments, and therefore the extended income differences between home-owners and renters, will grow over time as investment income increases with capital gains and further contributions.

The compare the pair exercise also has broader political economy implications. It provides further evidence that the standard statistics on income inequality which deal only with money income hide significant inequalities between people/households who appear to have similar incomes.

Further it supports the argument put by Lisa Adkins and others that capital gains and capital income, rather than employment income (which in the Gregs’ case is identical) are the preeminent drivers of inequality.

It is also evident in the comparison above that the tax system is failing its redistribution function. In this case the tax system not only does not tax aspects of tax capital income, the concessional tax arrangements applying to superannuation promote the inequality between these two people on the same money income.

Implications for Advocacy

Finally, this compare-the-pair exercise raises questions for my own work at SACOSS and the approach of many anti-poverty advocates who have traditionally focused on championing rental affordability and renters’ rights. This focus undoubtedly supports those likely to be most disadvantaged in the housing market. However, the data above shows that the fact of them renting puts renters on the wrong side of increasing inequality – which might suggest merit in the traditional conservative focus of getting people into home ownership.

Put another way, an anti-poverty agenda would direct policy (and money) to supporting rental affordability, while an equality agenda might direct policy and resources to enabling more people to own their own home.

Of course this is a false dichotomy. Policies such as increasing Commonwealth Rent Assistance address both poverty and inequality issues, while some people will never be able to afford to buy a house so “the Australian dream” policy options are limited (and expensive).

However, the analysis does highlight the fact that even if we secure tenants’ rights so we become Europeanised and life-long renting is becomes a potentially desired option (rather than a forced option), renters will still be disadvantaged. Perhaps most challenging, this analysis also applies to those in public housing, who will be better off than they would be in the private rental market, but will nonetheless be falling behind homeowners on similar incomes.

Clearly, while current policy directions to increase renters’ rights and the provision of rental housing are absolutely necessary, we also need to change tax and other policies to reduce the difference in financial outcomes between renters and homeowners.

Debt, Interest Payments and Choices: A Surprise in the SA State Budget

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.

Column graph comparing SA State Budget expenditure showing interest payments increasing from 2022-23 to 2026, while DHS expenditure remains stable.

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.

The Australian Inequality Index

The public policy think tank, Per Capita, has just released a new multidimensional measure of inequality, the Australian Inequality Index. The index combines various measures of inequality in seven areas: income, wealth, gender, ethnicity, disability, and intergenerational and First Nations inequalities. The measures are weighted and give a measure of inequality for each category, and for overall inequality.

Given my ongoing critique of the use of mono-dimensional and often misleading household income statistics as the primary measure of inequality, I welcome Per Capita’s initiative. In previous posts I have tried to develop consistent indicators of inequality in a number of similar areas, mainly in terms of shares of total income. However, the Per Capita inequality index is broader than simply income (or economics) and includes a range of social measures – something that makes its methodology bolder, and more fraught (more below).

Results

Because the Inequality Index combines different types of measures (for instance, gender inequality includes political representation ratios, crime victimisation rates, and the gender wage gap), it is difficult to get a common language and measure. Per Capita solves this partly by using indexes with values between 0 (perfect equality) and 100 (the furthest distance from equality). So, for instance, if wealth inequality was rates at 70, this would mean that the wealth of the highest income group would need to decrease by 70% for equality to be achieved. These index numbers are then tracked in each area (and combined) for the years since 2010.

The outcome is summed up in the graph below from the Summary Report. It shows stability in the immediate years after the GFC, followed by a bumpy decrease in inequality from 2013 to 2018, primarily due to improvements in gender and ethnic equality, and in some measures of equality for First Nations’ people. However, the first two of these indexes turned around late in the decade and, coupled with rises in income and wealth inequality, the index shows a resurgence in inequality.

Line graph showing the Inequality Index from 2010 to 2021, hovering just under 44 until 2015, declining to 40.5 in 2018 and increasing again to just under 44 by 2020.

Interestingly, alongside these index numbers, there is also an estimate of the time that it would take to reach equality – at the current rate of progress, and with a 1% per annum rate of catch-up. I have created the table below from the Index to sum up the key findings in each area of inequality.

Measure2021 Index NumberChange since 2010: Index PointsYears to Equality based on trend over last 10 yrsYears to Equality at 1% p.a. Catch Up
Income45.4-4.286 yrs45 yrs
Wealth64.47.7Never85 yrs
Gender21.0-9.818 yrs19 yrs
Intergenerational28.51.2Never29 yrs
Ethnicity45.9-4.137 yrs45 yrs
Disability63.416.8Never63 yrs
First Nations36.5-6.751 yrs63 yrs
Overall Inequality43.60.1361 yrs40 yrs

Statistical Issues in the Inequality Index

Given the Inequality Index was put together by a relatively small think tank rather than a government statistical agency, I think there are some minor anomalies in a few places, but this should not distract from the usefulness or ambition of the project. However, there is still devil in the detail.

The full methodology and assumptions have not yet been published, so what follows is based on the information in the Summary Report.

The bringing together of multiple dimensions of inequality requires weighting the relative importance of the various components – otherwise a few areas of harsh inequality potentially impacting relatively few people may overwhelm the index. Yet weighting is tricky: how do you weigh the relative importance of women’s political representation, with the gender wage gap – let alone those issues with rates of Aboriginal incarceration or numbers of people with disability reporting discrimination?

The process is inherently subjective, but all statistics are subjective in that their definitions reflect subjective or theoretical assumptions. The bigger question is whether the weighting and the subsequent index is statistically robust. That is, would the index or the trends be significantly changed by minor changes in the weighting or categories. I don’t have the data (or the statistical skill) to make that judgement, but I am prepared to take the Inequality Index on face value – not least because the important thing about indexes is not so much how they are constructed, but their ability to show trends over time. In some senses, as long as they capture key elements well enough it becomes more important to maintain consistency over time then to continually adjust to political nuances.

Broader Critique

The question then is whether the Inequality Index does actually capture the key elements of inequality well enough – and here I do have some questions and critique. For instance,

  • The income inequality data is based on standard measures household income, which I have argued previously are misleading as they fail to take account of housing incomes, social-transfers-in-kind, capital gains and capital income.
  • The intergenerational inequality index focuses on current differences between age cohorts in rates of poverty and intended retirement age. It is too easy to dismiss these as life-cycle effects, and to me, the bigger intergenerational issues are long-term: what sort of economy, infrastructure, natural resource base and environment are we bequeathing the next generation? Is the next generation going to be better or worse off than the current or previous ones at same point or overall in their lives? These aspects of intergenerational inequality are not considered in the index.
  • Both the ethnicity and disability inequality indexes are based on rates of reported discrimination and labour force participation, but there is no accounting for the income that comes from that participation (or not). I wanted to know the share of income and wealth held by those groups.
  • Similarly, the First National inequality measure has 12 different components, but not one relating to income.

There are all sorts of good reasons for the choices about what to include and leave out, including the challenge (or impossibility) of getting robust and continuous public data on some of the issues above. For that reason, my main critique of the Inequality Index is not the points above (although they remain important), but two areas where I think the issues are of a much greater scale – the omission of class and geographic inequality.

Class

Despite the Summary Report’s Introduction acknowledging the importance of Thomas Piketty’s work, the Index uses the very bald income quintiles which Piketty criticises, and it does not examine the top 10% and top 1% where Piketty sees inequality growing at its most obscene. More importantly, the distribution of (some) income across a stratified income spectrum arbitrarily divided into quintiles does not capture class inequality or the structural inequality of the distribution of income between labour and capital.

The labour share of GDP is a much more robust measure of class inequality, and one for which there is robust ongoing data. While capital and labour incomes eventually land (differentially) in households on the household income spectrum, so to do the wage differentials of the gender wage gap and the differing incomes of varying labour force participations of other groups. This is no reason to exclude class inequality or assume it is covered by household inequality. I would have liked to have seen class, measured by the labour share of GDP included as an eighth sub-index, separate to and alongside the household income data.

Regions

The other significant omission from the Inequality Index is geographic inequality. The Australian population, income and wealth is concentrated in a small number of cities, and the data is clear that residents of some states (SA and Tasmania in particular) and people in regional and remote communities have significantly lower average incomes than those in the capital cities.

Beyond simply income, geography matters in terms of inequality in access to services. Many services cost significantly more (e.g. telecommunications) or are simply unavailable in many regional areas. Differences in access to health, education and other services can be seen as inequalities in the social wage, but they also have direct impacts on quality of life and the sustainability of communities. To ignore the geographic dimensions of inequality is a major oversight in measuring inequality in Australia.

Conclusion

Despite these queries and critiques, I still regard Per Capita’s Inequality Index as a bold and important initiative – a significant step beyond the narrow and flawed income measures used in much inequality analysis. I hope that in time the Index can be revised to incorporate some of the measures noted above, but either way, if Per Capita can sustain the methodology and index, it will be a valuable tool for understanding whether (and where) we are becoming more, or less, equal.

However, any socio-economic index is a tool, not an end in itself, and I suspect the greatest challenge for the Index is not its construction but its use. There are other indexes (e.g. the UN HDI, the Genuine Progress Indicator, and most recently, Wellbeing Budgets) that also reflect multiple dimensions of equality and wellbeing, but they pale in comparison to the use and status of economic statistics like GDP, the unemployment rate and CPI. Those official measures are sometimes misused, misunderstood or politically dubious, but they dominate economic discussion. They do so, not because they are the best scorecards of well-being or economics, but because they are causal variables (within ruling economic theories) used in economic management.

Accordingly, to be truly effective, the Australian Inequality Index will need to be not just a scorecard, but an active instrument of policy. Whether it has the theoretical framework and the mobilising power to play that policy role remains to be seen, but it is a start to build upon– and given my statistical efforts at measuring inequality, I am slightly jealous!

Extended Income and Inequality: Different Data, Surprising Results

In a previous post, I suggested that the treatment of housing in the official income distribution data massively underestimates inequality. This is because it fails to account for imputed rent (the non-monetised value of housing services enjoyed by owner-occupiers) and for capital gains. My calculations in that post were illustrative of why this extended income was important (renters became relatively worse off, homeowners better off), but those illustrative calculations were not analysis of real data. What I wanted to see was an income spectrum which included monetary income, imputed rent and capital gains, but also including an imputation for “social transfers in kind” – that is, the receipt of public services such as education, public health care, child care subsidies as well as a range of rebates and concessions. From there, the standard income inequality questions could be asked to properly analyse inequality in this extended income.

Equals sign with diagonal line through it and the words "Inequality - not what you think" - which relates to extended income.

My Wish Granted

Since writing my original post, my attention has been drawn to the work of Yuvisthi Naidoo, from the UNSW Social Policy Research Centre. Her PhD and subsequent articles calculate many of the above changes (and more). She starts with standard household disposable income and adds values for net imputed rent and social transfers in kind to produce a measure of “full income”. She then converts household wealth into income flows in the form of imputed lifetime annuities (that is, an income equivalent to drawing down on capital to leave zero at the end of life). This is done for household financial assets to produce a measure of “potential consumption”, and then more controversially for owner-occupied housing to get “adjusted potential consumption”.

The incorporation of an income stream from wealth is important because it overcomes a fundamental problem in standard inequality data. Simply focusing on standard money income (and considering wealth separately or not at all) gives a false picture of which households have the most and least economic resources, and the gap between them. For instance, ABS data tells us that 24% of low-income households have moderate wealth, and 9.8% have high wealth, while 60% of households in the highest income bracket do not have high wealth, yet these households are ranked solely on income in most analyses.

The use of annuities to calculate income flows from wealth holdings is not the capital gains accounting I was envisaging: a simple capital gain = income equation. However, it incorporates capital gains into the base on which the annuities are calculated. For instance, in the annuities model, a $50,000 capital gain is not considered income of itself, but the annuity is calculated on the increased asset value and for a 20 year annuity would add $2,500 to the income stream. The annuities approach probably under-estimates the value of capital gains income to households, but it is a better overall accounting of capital wealth and income than simply capital gains – and is certainly better than the nothing in the usual income accounts.

Results

The table below shows Naidoo’s calculations for median household incomes at each step in the process. Surprisingly (to me) the overall result is that extended income is more evenly spread than disposable (cash) income. This is evident in the final column which shows the ratio of median income in the lowest income quintile to the median in the highest quintile decreases. When just standard money income is considered, those in the top income quintile average 4.2 times the income of those in the lowest quintile, but when extended income is considered (as “adjusted personal consumption”), this figure falls to 3.14 times.

Median Incomes $p.aIncome QuintilesRatio Q5/Q1
 Q1Q2Q3Q4Q5
Disposable Income18200300214046152923763994.20
Full income33259446445443865677894872.69
Potential Consumption339824653857763717471030023.03
Adjusted PC360585069362728790061131543.14

The reason for this more equitable distribution in extended income is the impact of social transfers in kind, the benefits of which flow disproportionately to lower-income households. The step from disposable income to full income (that is, the inclusion of net imputed rents and social transfer in kind) produces an 83% increase in income for the lowest income quintile, but only a 17% increase for the highest quintile. By contrast, the inclusion of wealth annuities only adds a further 8% to income in the lowest quintile, but 26% in the highest quintile – so (unsurprisingly) these capital incomes increase inequality.

Naidoo focuses on older-age households, and she goes on to investigate other measures, but for me the impact of government services in reducing inequality (and the quantification of that) is the first standout political point coming out of the analysis of extended income distribution.

However, equally important is the fact that there are different households in each quintile once we incorporate extended income. As I argued previously, the inclusion of imputed rents as income moves homeowners up the income spectrum while renters will be even more clustered among those with low incomes. But it is not just housing tenure. Naidoo’s research showed that nearly a half of all older people (65+) were in the lowest standard (money) income quintile, but the inclusion of imputed rent and social transfers in kind reduced that to 22.5% (because older Australians are disproportionately more likely to own homes and benefit from health services). By the time imputed wealth annuities were included in the analysis, only 17% of older people were in the lowest income quintile, while 26% were in the highest quintile (up from 7.1% when only disposable income was taken into account) (Naidoo, Appendix Tables C8-11) .

Implications

The data in Naidoo’s PhD is now dated (2010 HILDA income data), but the two key implications highlighted above are clear and remain relevant:

  • expenditure on public services has a major impact on reducing inequality, and
  • a more comprehensive income analysis changes who we see and understand as being on the lowest (extended) incomes, and potentially the most vulnerable.

The first point (and the quantification of that impact) is important because it not only makes a further case (beyond the direct health, education and other outcomes) for funding public services, but it may also add to our perception of tax-and-transfer policies. Progressive tax is usually understood as taxing high income earners at higher rates than those on lower incomes. This is a key instrument for limiting income inequality. However, the inclusion of social transfer in kind shows that spending this tax revenue on health, education and community supports is a further transfer from rich to poor.

That said, the second point above confounds the impact of progressive taxation. Since income taxation is largely based on money income, the amount of tax paid will depend partly on the type of income rather than the amount. Those with relatively higher cash incomes may pay much more income tax than those with significantly higher extended incomes but lower cash incomes. The money-based tax system does not follow households as they shift up and down the extended income spectrum and so some progressivity is lost (or mistargeted).

There are of course issue around taxing non-cash income as it would require a conversion of some wealth to cash to pay the tax. This itself may cause hardship – unless of course the wealth was maintained and simply taxed at realisation or end-of-life. Another argument for inheritance taxes – but I digress!

There is a further complication in the progressive tax story. A flat rate tax like the GST is generally regarded as regressive because it impacts disproportionately on lower-income households (who spend a great proportion of their income on GST-taxable consumption). While this is undoubtedly true, the fact that social transfers in kind disproportionately benefit those on low incomes, and that as a state tax the GST goes fairly directly to the provision of those services, provides something of an offset against its regressiveness – although this is probably only partial and not an argument for increasing or broadening the GST.

Finally, the movement of people up and down the extended income scale suggests that when we focus services and concessions on those in the lowest money (disposable) income brackets, we may in some cases be providing services and concessions to those who are relatively better-off, and missing out on people with fewer economic resources (just because all their resources are cash incomes). However, this is not as straightforward as the similar argument above about tax because in some cases it is the provision of concessions and services (i.e. social transfers in kind) which lifts households out of the lower income brackets. There may be a circularity in targeting based on extended incomes, but targeting services and concessions based only on money incomes is equally flawed.

The extended income analysis is not a policy panacea, but I think it does provide a better window on income distribution from which to do policy analysis.

Conclusion

My previous post asked for an analysis of inequality based on a broader understanding of income, one that combined income and wealth into one metric. Having now got data thanks to Yuvisthi Naidoo’s great work, I can see that my first estimate of increased inequality was wrong (because the impact of wealth inequality is offset by the progressive impact of social transfers in kind). But the analysis throws up a whole range of questions and challenges for progressive tax and transfer policies. The discussion above is only the beginning of an analysis, and it is fraught in an era when we must fight for even the basic principle of progressivity. In that sense, my take-home message from all this is: be careful what you wish for!

And yet …

I continue to believe that categories and statistics are socially/politically constructed, not neutral reflections of reality. Uncritically using definitions and statistics that are designed for other purposes or other theories limits our vision and the potential for change.

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.