Category Archives: Energy

Revisiting Issues of Affordability, Income and Inequality

This post updates and collects in one place my previous writings about how policy arguments around inequality which are based solely on income data (e.g. income percentiles) fundamentally misunderstand and misrepresent inequality.

The basic argument is that standard income deciles/percentiles are misleading because they create a picture of a continuous income distribution spectrum, rather than differential flows of income to certain parts of the economy. More specifically, they ignore fundamental differences in income arising from housing tenure/ownership, income and capital gains on wealth, and social transfers in kind.

In short, such analysis reflects a 1980s world – before housing costs ate household budgets and superannuation turned wage earners into stock holders.

Housing

Housing tenure matters because it creates differences in effective household income (i.e. actual purchasing power) and living standards. In an earlier post I compared the effective income of a renter and homeowner with identical annual salaries. The homeowner (without a mortgage) ended up nearly $30,000 a year better off than the renter on the same $100,000 p.a. income. This result was driven by:

  • differences in housing costs (imputing rental income to homeowners for the value of housing services received)
  • income from investing the cash that would otherwise have gone to rents, and
  • tax advantages that go with that investment.

This comparison did not take account of capital gains which could heighten the gap, and the renter/homeowner difference is probably worse now with rent prices going up faster than income (so proportionately higher imputed income for homeowners) and a booming housing market seeing higher capital gains.

This is all pretty obvious, and echoes why poverty studies tend to focus on “after-housing” income. However, it does suggest that plotting an income spectrum just based on cash incomes is very misleading when it comes to understanding difference in purchasing power and standards of living. At a minimum, we need to be basing analysis on the intersection of income and housing tenure.

Wealth

While housing is the primary form of wealth for most Australian households, the issues above are magnified when all forms of wealth are taken into account. Capital gains and tax advantages are increased, while wealth also creates additional ability to invest in money-saving technologies (e.g. energy efficient devices) which in turn increases future purchasing power without a change in income. And there are financial, health and psychological benefits of having savings/wealth to fall back on in emergencies.

But what is important here is that we can’t simply assume that income and wealth go hand-in-hand. The last ABS data (before the national statistician created an inequality data black-hole), shows that just under a third (32%) of low-income households also had low wealth, but 23% had moderate wealth (probably owning their own home), while 11% of low-income households had high wealth (See the graph below).

Column graph showing percent of households in lowest, middle and high income brackets that have low, moderate and high wealth.
Source: ABS, Household Income and Wealth

A concrete example of this wealth-income divergence emerges from the government’s data on age pensioners. The data for the September Quarter 2025 shows that 72% of pensioners own their own home, and around two-thirds of those homeowner pensioners have more than $100,000 in financial assets beyond their home. These pensioners have low-moderate incomes (otherwise they would not be eligible for the pension), but substantial enough capital to be protected against poverty and to have a better standard of living than many renters on higher incomes.

In short, low income does not necessarily mean low wealth or low purchasing power, and an income spectrum based solely on income figures misleads as to who is likely to be struggling.

Social Transfers in Kind

The final piece of the puzzle would be the inclusion of 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. Many of these transfers go disproportionately to those on lower incomes, which then increases their effective consumption and standard of living. In turn, this decreases inequality – which was the finding of a leading Australian scholar in this field, Yuvisthi Naidoo, whose work I have summarised here.

However, the analysis is more complicated. A very useful recent briefing paper from the e61 Institute shows that while social transfers in kind are generally progressive (i.e. disproportionately benefit those on lowest incomes), there are significant differences between different transfers. The graph below from their report shows the distribution of transfers across both income and wealth quintiles. We can see, for instance, that pharmaceutical concessions are one of the more progressive transfers when plotted against income, with about two-thirds going to those in the lowest two income quintiles. However, those pharmaceutical benefits are far less progressive when plotted by wealth – in part because older people have more needs and eligibility, and are also likely to have accumulated more wealth (mostly in the form of home ownership).

Bar graph showing the percent of each of 15 different government transfers going to each income quintile. Social/public housing is the most progressive, while community health services and private health insurance rebate are the least progressive.
Source: e61 Micronote: Welfare for the Well Off?

It is worth tracking the comparison of progressivity in this graph for each transfer, and there is further discussion below on energy concessions, but the main point here is simply that inequality looks different when wealth and social transfers in kind are considered.

Why Does It Matter?

Overall, all this matters because it means that the level of inequality we see in standard income spectrums may be misleading, but also because actual households will be in different places on the income spectrum when extended incomes are taken into account. 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. At the other end of the spectrum, accounting for extended income meant that 26% of older households were in the highest quintile, up from 7.1% when based on standard income alone. (Naidoo, Appendix Tables C8-11) .

These issues have very direct implications for policy fairness. My attention was recently drawn to this in relation to energy affordability, where there is a legitimate concern to alleviate and avoid energy costs for low-income households. Obviously we don’t want households to go without power, or be bankrupted by power bills, but targeting energy assistance to those on low incomes may be poor targeting. Worse, a focus simply on income might mean imposing more network and other costs on those least able to pay.

Consider the pensioner households noted above. The nearly one-half of age pensioners who own their own home and have more than $100,000 in financial assets can easily afford solar power and energy saving technologies (if they have not got them already). They are far less likely to be facing energy hardship than renters on the age pension without access to the same technologies (who, incidentally, would be seen to have a higher income due to receipt of Commonwealth Rent Assistance). This is important because both pensioner households would receive the same energy concessions (at least in states like SA where the concession is a flat rate) because concession eligibility is based on income rather than ability to pay.

Further, those homeowner pensioners are also far less likely to be in energy hardship than renter families in waged poverty, yet the age pensioner will get an energy concession while those in waged poverty may not qualify. This is a different type of income fetishism (based on income type rather than quantum), but again we see income as an unreliable indicator of affordability and need for support.

More broadly, we can see in the e61 graph above that energy concessions are more progressive by income than by wealth. Nearly half of all concessions go to those in the lowest income quintiles, but only around a quarter go to those in lowest wealth quintile.

There are lots more intricate issues around who bears (and should bear) the necessary costs of the energy transition and how network costs are paid for (apportioned between customers). But what is clear is that a distributional analysis of energy costs based on a simple income spectrum would be misleading in terms of both ability to pay (income) and access to energy-saving technology (cost).

The Way Forward

Energy is just one area where there is a need for a far more sophisticated analysis of income inequality. We need an analysis of affordability for a range of essential expenditures that takes account of housing tenure, but also extended incomes and the real ability to pay for essential consumption.

Ultimately what I would like to see is, firstly, for the ABS to get themselves resourced and organised to do another Household Expenditure Survey (the last one was 2025-16!), and then to be able to analyse those expenditures based on an extended income spectrum combining wealth, housing and income. Only then will we really know which expenditures are genuinely regressive (have disproportionately highest impact on those with the least ability to pay) and where and how to target support.

In the meantime, caution and an analysis based on housing tenure is advised.

Social Services and Energy Distribution: The Treatment of Surpluses and Profits in Pseudo Markets

Arising from neoliberalism’s obsession to not just analyse the world in market terms, but to make the world into a market, governments in Australia and elsewhere have privatised or outsourced a range of services which had previously been provided by government departments or authorities. South Australia followed this ideological venture in a range of areas, but in this post I simply want to focus on two examples: social service provision and the electricity distribution network.

While the two industries are obviously different, in both cases there was an attempt to mimic or impose market discipline where there was no competition and no real market. Social services are a government monopsony where service users are not the customers so the theoretical link between utility, market demand and price is broken, while energy distribution networks are a natural and legislated monopoly.

Much could be written about the structures and regulation of the “markets” that were established, but I want to focus on just one aspect: the inconsistency in the treatment of profit. This treatment has consequences for social service delivery and energy prices, and ultimately therefore, for equality.

Social Services

The provision of social services, such child and family support, financial counselling, community health, housing and homelessness support, addiction help, and disability services are an essential part of a government’s role in a modern society. But the neoliberal vision and the potential to cut costs by outsourcing services to organisations with lower pay or less regulation led to the creation of pseudo-markets where charities and not-for-profit (NFP) organisations (and some private companies) periodically bid for government tenders to provide services. The successful tenderer is then contracted to provide services at the agreed price, with the government apparently happy in the knowledge that the competition between tenders has ensured value for money.

Heading text from SA government contracts for social services. The terms prevent surplus accumulation.

There are some good reasons for government outsourcing of some social services (and much hubris in relation others), but the treatment of the cost of services and profit in the South Australian government contracts is curious. The government holds most of the cards in any contract negotiation, and generally does not allow for an operational surplus in a contract price. Further, given that the government pays for service provision in advance, it wants to ensure that the money is spent on the services it paid for. And so, the standard SA government contract with NFP service providers has a clause (10) allowing the government to require repayment of any advanced funding which has not been expended in a given year. While there is flexibility for the government not to require repayment, some departments aggressively pursue such repayment.

At best this is a lop-sided contract, with one party (the government) agreeing a price for the provision of a service, and then reducing that price if the service provider manages to make savings – even though the service has been provided as agreed. Despite government rhetoric of outcome-based approaches, the clawing back of unexpended funds is completely input-focused.

However, the ramifications are broader because the lack of operational surpluses and the claw-back of funding means that NFPs struggle to find surpluses to build robust balance sheets and invest in organisational sustainability and development. It is then no surprise that the sector is characterised by an under-investment in technology (as reported in multiple annual surveys) and by short-horizons with a reliance on the next government contract to maintain staff and services.

To be clear, the fact that organisations are not-for-profit does not mean that they can’t lawfully or shouldn’t make a surplus on any service or in any year – it simply means that any surplus has to be put back in to the organisation and can’t be allocated to members as a dividend or other profit distribution. However, the contractual limitations on building and keeping such operational surpluses is detrimental to the sustainability of NFPs and stops them providing more and better services to the people who rely on them.

Electricity Distribution

The pseudo-market created in energy distribution is quite different. By contrast to the government monopsony in social services, the energy companies who bought the privatised energy networks operate in a more standard business framework with the cost of services being paid for by energy consumers (accounting for about 40% of energy bills). However, because the networks have monopoly power, their operations are regulated by laws which limit the aggregate revenue they can get from consumers.

As I have noted in a previous post, the calculation of this aggregate is complex and contested, but it is theoretically based on the cost of service provision, including an agreed rate of return on capital (i.e. profit) – with the regulator determining what costs and profit rates are appropriate.

This allowance of a return on capital contrasts to social service provision in that an agreed rate of profit is viewed as a normal cost of service provision – a cost not usually allowed in NFP contracting (noting that, in theory at least, both have separate allowances for administrative overheads). The result of this is that these private companies can accumulate profit to re-invest to build the company and to distribute to shareholders in a way that NFPs can’t.

However, the difference does not stop there. As I have reported previously, the Institute for Energy Economics and Financial Analysis has produced reports highlighting the “supernormal” profits energy distribution companies have made when their actual costs have come in below the costs agreed by the regulator. In 2022, this amounted to $199m for SA Power Networks and around $2bn across all network providers nationally. While the differences in estimated and actual costs may be factored into future regulatory determinations, this money is not immediately clawed back by the regulator or consumer – indeed, there is a whole incentive scheme built in to the cost calculation to encourage such cost-savings.

A Modest Proposal

There is no doubt that NFP service providers would love to be able to keep their operational savings and surpluses to reinvest in their organisation and services, or even to have an incentive system which mirrored that which enables energy networks to benefit from cost savings.

For governments to be consistent, they should either allow NFP service providers to retain profit (i.e. money not spent when they have provided the agreed services) as per the energy regulation, or force energy networks to refund to customers the above-regulated profits when their costs of service provision are lower than the regulated amount. Energy network owners would still be better off than social service NFPs as the former would still get their guaranteed return on capital, but in relation to the unexpected savings and surpluses, it is a simple proposition that what is good for the goose is good for the gander. But such outcomes are about power (of the political economic kind), not policy, and I suspect in this case it is energy consumers who will continue to be plucked.

Energy Bill Relief and the Inflation Dragon: A Fairy Tale?

Last week the official inflation data came in higher than expected with a 1% rise in the Consumer Price Index (CPI) for the March Quarter (up from 0.6% for the previous quarter). That led to much commentary that it was the end to hopes for a cut in interest rates later this year. Apparently the inflation dragon is yet to be slayed, and, as noted in an earlier post, despite an alleged broadening of its focus, the Reserve Bank still aims its sole and somewhat blunt weapon first and foremost at the dragon.

The concern about the inflation dragon also flows through to the upcoming federal budget. The government is under significant pressure to provide cost of living relief, but its options are limited by the need to avoid contributing to further inflation by spending money or enabling more household expenditure. This is all premised on standard monetary macroeconomics which sees increasing money supply leading to increased demand and (absent proportionate production increases) to inflation.

But since neoliberal economics has seen governments of both political stripes outsource monetary policy (to the RBA), abandon fiscal policy (because higher taxes are bad) and largely ignore direct price controls[1] as means of constraining demand and inflation, how can the government help households without being economically irresponsible?

The Quest

The answer appears to lie in a magical quest to slay the inflation dragon (or at least control it) with a new weapon of “non-inflationary” spending. And in this quest, the government is aided by the good folk at the Australian Bureau of Statistics (ABS) who produce inflation data and some lazy economists who think that the data (the CPI) is the actual thing (inflation). Marx would probably call this data fetishism, but in a post-structural twist on ye olde dragon tale, the quest morphs into slaying not the inflation dragon, but its signifier – the CPI.

Image of the CPI header from the ABS website - but no mention of an inflation dragon.

How does this work and why is it important?

Let’s consider the Energy Bill Relief package announced in the last Federal Budget. It is a prime exemplar of this non-inflationary spending.

In the face of sky-rocketing energy prices, the federal government spent some $1.5bn (matched by state and territory governments) to provide a rebate on electricity bills for low-income households and small businesses. Without the rebate, the ABS estimates that electricity prices would have gone up by 17% since June 2023, rather than the 3.9% increase measured in the CPI. (This is because the CPI measures changes in the prices paid by households, so the government subsidy reduces that price – even if the actual price charged by the energy company has still gone up by the higher amount).

Sidenote: a similar calculation applies to the 15% increase in Commonwealth Rent Assistance in the last budget (totalling $540m this year) which took 1.7 percent points off what would have otherwise been a 9.5% increase in CPI for rent over the last year.

These policies provided welcome relief for low-income households struggling to pay for essential items, and as the data shows, they brought inflation down.

But this is just a mirage. Let’s consider what happens in the real world not defined by CPI.

Electricity Bill Relief v the Inflation Dragon

Ignore for a moment the problem that (at this stage) the energy bill relief is temporary, so electricity prices in the CPI will rise when it runs out. But remember that the package was introduced in the face of massive predicted energy bill increases. So, if a household’s electricity bill was $1,000 (to keep the maths simple) in June 2023, according to the CPI the household would now be paying $1,039 instead of the $1,170 that would apply without the rebate. There is still a cost increase to the household (inflation), but just looking at the bill, the government expenditure has at least constrained the dragon rather than fuelling its inflationary fire.

However, the analysis gets a bit trickier when we look at the household budget more broadly. Without the rebate the energy bill would be higher, but for many low-income households with no spare capacity in their budgets, a substantial rise in electricity prices is paid for by decreasing other consumption (often food because it is a more flexible expenditure). In that case, the total household expenditure is unchanged and the absence of the rebate does not increase demand or inflationary pressure in the economy – it is just shifts demand from food to electricity. In that context, the energy bill rebate is a good social policy (because the household can afford food), but it would have no impact on the inflationary pressure generated by household demand.  

That said, some households who received the energy bill rebate would have some savings or savings capacity (not least because the relief was poorly targeted). The increased cost of electricity could be met by those savings, or simply spending more and saving less in the budget. Either way, the total household expenditure would increase, and as this money flowed into the economy, it would increase demand and inflation.

While the energy bill rebate appears to lower inflation when we just look at the electricity bill (as the CPI does), when we look at the household more broadly it may have little impact or may fuel inflationary pressures.

The Macro-economy and the Inflation Dragon

But dragons fly higher than houses and it is only at the macro level that we see the inflationary impacts plainly. While in the above example, the household electricity bill went up by $39, the actual bill still went up by $170 and that extra money was paid – by the government. That money ($3bn in total) is out there in the economy. It initially goes to the energy companies, then to suppliers, workers and shareholders and is multiplied through their additional income and expenditure (with leakages for savings and overseas ownership).

All other things being equal (i.e. unless the government taxes back the energy bill relief expenditure, or it cuts spending elsewhere), this is just $3bn that governments are pumping into the economy and in standard economics that adds to demand and potentially to inflation. It is not magically non-inflationary simply because it is invisible in the CPI (which was not designed to capture it).

Just because you can’t see the dragon does not mean that the economy around you is not heating up!

Conclusion

None of this is to say that the Energy Bill Relief rebate (or the increase in rent assistance) were bad policies. They were not bad (notwithstanding the poor targeting of the energy bill relief, and the eligibility restrictions for CRA). Both measures provided much-needed support for people and households in need – I am just unconvinced that they would not add to inflation pressures.

If there is a magic trick to be had in this tale of the inflation dragon, it is not in the designation of some government expenditure as non-inflationary or imagining that restricting CPI is the same as controlling inflation. The real magic is probably in questioning the economic theory of the relationship between money supply, demand and inflation. There are some examples of this (in MMT and in the analysis of profit-led inflation), but that is a story for another day.

[1]              The exception here was the Federal government temporary cap on gas prices, but beyond that, there is no political will for such a controls – witness state and federal governments running a mile from rent freezes or even capping rent increases.

3G Phones, Energy Smart Meters and the Neoliberal Fantasy

Below is a link to an Opinion piece I ghost wrote and which was published today in Adelaide’s online news site, InDaily. It is a critique of the narrowness of industry initiatives and regulatory responses to the impending closure of the 3G mobile network and the roll out of energy smart meters. The response is based almost exclusively around the need to fully inform consumers, rather addressing the fuller needs of consumers and the consequences for people dealing with the technology changes.

While the piece finishes with some implications for how we provide essential services, in a short piece it was impossible to draw out any broader theoretical concerns. However, in the back of my mind was always a critique of neoliberalism.

It is neoliberal ideology that posits people as consumers, makes essential services into commodities and imagines oligopolies as markets. It was in the neoliberal moment of Australian history that energy and telecommunication networks were privatised, and pseudo markets were constructed with rules that reflected the economic fantasy that if consumers are fully informed they will shop around and that this will deliver optimum outcomes. As the article shows,  we are still paying the price for that delusion.

Read the opinion piece here: https://www.indaily.com.au/opinion/2024/04/17/consumers-bear-the-cost-of-essential-service-changes

Image of InDaily page with Opinion piece "Consumers bear the cost of essential service changes"

Revisiting Energy Supernormal Profits – A Tale of Two Graphs

In a previous post I highlighted the work of Simon Orme and the Institute for Energy Economics and Financial Analysis (IEEFA) exposing the supernormal profits reaped by monopoly energy networks. They define supernormal profits as the actual profits made by these statutory monopolies over and above that which was allowed for under regulation. (Under national energy laws, the Australian Energy Regulator [AER] regulates the total amount of revenue that can be collected by energy transmission and distribution networks to avoid profiteering from their monopoly position).

Supernormal Profits

The context and how supernormal profits are realised is highlighted in the earlier post, which was based on IEEFA’s 2022 report. They have now published a new report which updates and refines the first report and includes figures for the 2022 financial year. The headline finding is that in the last year the energy networks reaped a massive $2bn in supernormal profits (on top of and eclipsing their regulated “allowed” profit of $1.4bn). This was a significant increase on the approximate $800m supernormal profits across the networks in 2021 and brings the total supernormal profits reaped since 2014 to over $11bn. Overall, this added an average of $185 per customer to energy bills in 2022, although there were significant differences between states and network providers.

The industry attacked the report, claiming the IEEFA analysis is flawed because it treats every variation from the AER’s allowance as a potential supernormal profit, and because consumers benefit from the incentive schemes which contribute to the extra profits. Unsurprisingly, I disagree with the industry critique, but I also have a different approach to that of the IEEFA.

As per my previous post, I think this work on supernormal profits is really important. It is a welcome focus on and quantification of profit-levels, particularly when the issue of profit-taking is largely ignored in energy debates dominated by prices, reliability and emissions. However, I also suggested that, despite the industry reaction, the IEEFA approach is fairly conservative – a critique (deliberately) from within the regulated monopoly framework which utilises a neoclassical concept of profit that is limited and problematic.

Two Graphs – Two Theories of Normal Profit[i]

This neoclassical conception of profit as a normal and unobjectionable cost of production (and hence the target of attack being “supernormal” profits) is clearly evident in the graph below from the 2023 IEEFA report.

Figure 6 from IEEFA report showing FY22 network cost and profit outcomes, on two lines: 1. Revenue = $8.7bn cost + $1.4bn profit + $2bn supernormal profit. 2. Cost = $8.7bn cost base + $1.4bn profit

The second line of the graph clearly includes the normal profit allowed by the regulator as a standard part of the cost. Indeed, the fact that they use the same cost base for both actual revenue and allowed costs is a nod to what it theoretically should cost in a properly regulated (perfect?) market.

The detail of the report goes further in allowing up to a 30% increment on allowed profits before the supernormal profits are viewed as “excessive”. This is to allow for the asymmetry of information (where the regulator has less information on network costs than the network businesses). In this context, I pity the poor consumer advocates in underfunded NGOs being asked to comment on billions of dollars of expenditure and financial engineering! The concern around lack of information reflects traditional economic literature on imperfect markets, a concept which not only implies and centres a “perfect market”, but also adopts the orthodox economic interpretation of profit as a cost of production. Indeed, the distinction drawn between normal and supernormal profits inevitably normalises a certain level of profit as a return on capital.

However, it is possible to draw the graph differently using the same IEEFA data, but with a different theoretical starting point.

Alternative model of the IEEFA data on network costs and profits, showing two lines of the same length: 1. Allowed = $10.7bn costs + $1.4bn normal profits 2. Actual = $8.7bn costs + $3.4bn profits.

This graph more clearly shows that in both the projected (allowed) and actual cases, the customers are paying the same ($12.1bn), and that $3.4bn of that is going in profits to the network owners. I argue that this is a better reflection of the dynamics at play because the goal of any capitalist enterprise is to maximise profit. With total revenue set, the only way to grow or maximise profit is to cut costs – which is clearly shown in the second line of my graph. In this sense, IEEFA’s “supernormal profits” are simply the outcome of normal business operation.

Side note: given this normal business operation, there appears little justification for the additional funding provided to network providers under efficiency incentive schemes. Those schemes cost rather than benefit consumers, and are unnecessary when the networks already have normal business incentives to improve efficiency/cut costs. I note that the IEEFA report (pg 26) comes to the same conclusion, despite the differences in our theoretical frameworks.

Conclusions

Again, there are caveats to the above discussion (see endnote), but the differences in the two graphs reflect not just different theories of profit, but different purposes and outcomes.

The IEEFA analysis is an argument for better regulation, so the analysis of supernormal profits in the first graph shows a revenue-take and profit above a theoretical optimum cost-base that would apply if regulation had been better.

By contrast, my graph, based on the same data, draws attention to the overall cost to consumers of the privatisation (or corporatisation) of these natural monopolies. In this context, I note that some energy networks remain in public hands, but the regulation and mode of operation of such government businesses is the same – with the important distinction that what energy consumers pay in profits to state enterprises has benefits in lower taxes or better public services. This is not the case for private companies. But either way, the quantum impact is clear: this network model added $3.4bn in total to energy consumers’ bills in 2022.

Economic orthodoxy and business interest would suggest that this cost to consumers would be more than balanced by the greater efficiencies of capitalist production which result in lower prices in the long term. However, this is ideology rather than analysis. The data shows that very little of the increased profit is driven by improved technology and processes.

According to AER data, in 2022 capital structures and cost of debt were the two biggest contributors to cost savings, while the IEEFA report (pg 26) explicitly rejects the idea that increased productivity is the source of supernormal profits. It points out that networks with average and even below-average productivity have still been getting very substantial supernormal profits.

Given this, and the $3.4bn cost last year for the privilege of privatised/corporatised energy network provision, I again wonder if it is time to think about whether there are better ways to supply energy.

Endnote

[i]              The depiction in the graphs is obviously over-simplified. In reality, the picture of energy profits is more complicated than either of the graphs above. The total revenue figure is more flexible than shown as projections for allowed revenue will inevitably be imprecise even if all assumptions are correct, and the amount of revenue allowed to be collected each year is varied by the regulator to take account of some financial changes (e.g. interest rates and inflation), allowed cost pass-throughs and other factors. Allowed revenue is also reset every 5 years, based in part on previous outcomes.

Further, as the IEEFA report (Appendix 1) notes, there are limitations on the AER’s published data, and definitive profitability data for each of the 18 network providers is not publicly available. Partly this is because these regulated networks often operate as part of larger financial entities with regulated and unregulated revenues and expenditures. In this context, I am grateful to IEEFA for piecing together the available data and providing both data and analysis that is accessible and understandable by “energy outsiders” like me.