In April 2018 the Australian Productivity Commission published their draft report “Superannuation: Assessing Efficiency and Competitiveness”. The report mainly focused on APRA funds but also touched on SMSF performance. And these comments about SMSF performance caused commotion in the SMSF industry.
SMSF Performance
Many industry experts and SMSF organisations submitted responses to the Productivity Commission, highlighting various issues. As did Class. Here is our take of the issues based on the submission Class made to the Productivity Commission.
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Contentious parts in the draft report
Class’ submission focuses on two parts of the draft report. The two contentious parts are a set of two graphs and a finding.
The two graphs appear as figure 2.10 of the draft report. The first graph shows the return for APRA funds from 2004 to 2016. The second graph does this for SMSFs from 2006 to 2015. Let’s refer to the APRA fund graph as Graph A and the SMSF one as Graph B.
The finding is in 2.2 of the draft report and says,
The SMSF segment has broadly tracked the long-term investment performance of the APRA-regulated segment on average, but many smaller SMSFs (those with balances under $1 million) have delivered materially lower returns from the smallest SMSFs (with less than $50,000) and the largest (with over $2 million) exceeds 10 percentage points a year.
So this is where it all starts.
Issues
The contention boils down to one big issue. Graph B grossly understates SMSF performance. And it does this for two reasons.
Graph B is based on ATO data using a Return on Assets (ROA) formula. While Graph A is based on APRA data using a Rate of Return (ROR). These are two fundamentally different ways of actually calculating a return. So Graph A and B are comparing apples with pears.
And the second reason is the way in which funds have been selected and grouped in Graph A and B.
And this leads to the misunderstanding and hence the incorrect finding in 2.2.
ROA v ROR
The Productivity Commission notes in numerous places that the ATO’s ROA and APRA’s ROR are not directly comparable. But it then proceeds to do just that anyway. In Technical Supplement 4 accompanying the draft report the Commission explains that:
The Commission has tested the impact of these different methods (figure 4.3), using advice provided by ATO. This entailed calculating ROA for APRA-regulated funds using the ATO’s formula. This results in a fall in the 10-year return for APRA funds (using the same data) and implies that SMSF returns may appear higher if measured using APRA’a ROR method.
So if the ROA and ROR are not directly comparable, why didn’t the regulator do more to standardise or harmonise the approach to reporting performance across the industry?
Let’s look closer at why ROA and ROR are not comparable.
Measuring Investment Performance
And now it gets very technical, but it is important to understand how fundamentally different the two formulas are.
Investment performance for a period is usually measured by:
Earnings / Assets invested
But how to actually measure earnings and assets invested? This is where ROA and ROR differ.
Net Earnings
ROA and ROR use different net earnings. The ATO includes insurance flows (premiums and payouts) and contribution tax in their ROA calculation, while APRA doesn’t when calculating the ROR.
Contribution Tax is effectively income tax (at concessional rate of 15%) on income that has been directed to be invested. It is not tax on earnings derived from that investment. So it shouldn’t be included.
And insurance premiums and insurance payouts are not part of the super system. Insurance payouts are not superannuation income and whether a taxpayer pays the premiums inside or outside of super is a personal decision. So neither should affect superannuation returns.
So APRA’s net earnings calculation makes a lot more sense.
Assets Invested
ROR and ROA calculate assets invested in a different way. Have a close look at this:
ROR = Net earnings after tax / Cash flow adjusted assets
Cash flow adjusted assets = Net assets at start of year + ½ (Net member flows + Insurance flows)
ROA = Net earnings after tax/ Average assets over the period
Average assets = Net assets at start of the year + ½ (Net member flows + Insurance flows + Net earnings after tax)
ROA includes half the period’s earnings in the denominator, while ROR doesn’t.
So if $100 is invested and earns $20 in interest, the ROA shows an 18% return (20/110) rather than the expected 20% return the ROR shows (20/100).
ROR’s 20% return passes the ‘pub test’. ROA’s 18% is counter-intuitive and likely to confuse.
ROA or ROR?
The ROR formula seems to more sense and use a better method. But this is not the main point. The main point is that we need to compare apples with apples. We can’t calculate the return for APRA funds one way and the returns for SMSFs another way. And then compare the two and draw conclusions.
Bracket Bias
The second reason that SMSF performance is grossly understated in Graph B is so-called ‘bracket bias’. The ATO’s ROA calculation is highly prejudiced to small balance funds. And this is due to three reasons.
Insurance
Insurance premiums are regressive. Members with small balances are impacted disproportionally, given the premium amount is a larger proportion of the small balance. This impact applies to small SMSFs just as it does to small member balances.
Since ROA includes the impact of insurance flows, switching to ROR removes this penalty. The impact on smaller balance is dramatic.
Contribution
Like insurance, contribution tax is regressive in its impact. Switching to ROR removes this effect and the impact of switching is more significant the smaller the fund.
Selection Bias
Graph B brackets funds based on their size. It uses the closing balance. This effectively selects for underperformance compared to grouping based on opening balances.
For example, a $46k SMSF with a 10% return will move up to the next bracket but a $55k fund with a -10% return will migrate down into the lower bracket. If the funds reversed their fortunes in the following year, then they would swap brackets. So the poor performers always end up in the lower bracket.
The impact of this bias is substantial. And makes up the majority of the exaggerated underperformance seen in Graph B.
Class Calculations
In its submission Class explains that it re-calculated the return for SMSFs using APRA’s ROR formula and avoiding bracket bias by using the opening balance.
Class found that SMSF performance significantly improved using APRA’s ROR method as opposed to the ATO’s ROA method. They calculated an estimated ROR of 6.71% for SMSFs for the 10 year annualised average from 2006 to 2015. As opposed to the ATO reported ROA of 5.58%.
According to Class, the switch to ROR makes a more than 4% improvement in the average return for smaller funds in the $1-50k bracket.
Avoiding bracket bias also improved SMSF performance but to a lesser extent.
No answer
You might assume that Graph B answers the question…
“How did funds with x dollars in net assets in 2006 perform, on average, over the next 10 years? “
But it doesn’t. What Graph B shows instead is an average of:
- a vastly different group of funds for each year in the period
- funds which migrate up or down through the groups based on their performance – poor performers migrating downward and good performers migrating upward
- many of the funds included do not appear in all years (being wound up and/or established at different points in the period).
So Graph B is not particularly helpful. All it does is state the obvious. Poor performing funds end up with smaller balances over time. Oh really?
It says nothing about how funds that start with small balances have performed over the period.
Conclusion
It is clear that the smaller funds do not have as good a return as larger funds. Because they are hit harder by fixed costs like audit and accounting fees. But the effect is much smaller than indicated in Graph B and it reduces as the funds grow.
To really understand SMSF performance in comparison to APRA funds we need to calculate investment returns the same way for both without any bracket bias. Only then can we really see how SMSFs are doing.
MORE
Class SMSF Benchmark Report December 2017
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