We use a 5-step bottom-up micro-analytical approach to estimate the large super funds income tax gap. This approach incorporates tax assured data and projects future amendments.
Step 1: Calculate amendments
The results of amendments, both ATO and client-initiated, are used to estimate the tax gap for the entire population. We use:
- the actual result of compliance activities, including the amendments from completed audits and reviews
- taxpayer voluntary disclosures
- expected future compliance outcomes for material amounts in dispute
- projected future amendments.
We project future amendments to account for the delay between a tax return being lodged, and any final amendments that may be made. Complex tax cases can take years to resolve so the amendments may not be received until several years after the tax return has been lodged.
To account for these future amendments, we use data on the value and timing of past amendments to project amendments we are likely to receive in the future. As we revise the gap in future years, we will use refreshed amendment information to update our amendment results and to improve future projections.
We then aggregate the amendments, including projected amendments, for the population to determine the total amendment result.
Step 2: Integrate tax assured data
We use our tax assured data in our estimation. This allows us to accurately calculate unreported tax and derive a figure for non-detection.
More information about our approach is in Tax assured: gaining confidence the right amount of tax is reported.
Step 3: Calculate unreported tax
Unreported tax is the additional tax we estimate may be raised if we were to undertake compliance activities on the entire population of large super funds. To estimate this, we calculate adjustment factors based on actual and projected future amendments.
These factors are then discounted to account for selection bias. This reflects that our compliance activities are biased towards areas of higher risk than the risk level in the general population.
The factors are then applied to each large super fund in the population to estimate the total amount of unreported tax. The factors may also be discounted where the tax paid by the large super fund has been assured, reflecting our higher confidence in those amounts of tax paid.
Step 4: Estimate non-detection
We uplift the estimates preceding this step to account for non-compliance that is not detected through our compliance activities. We do this by applying uplift factors to the tax amounts based on the level of tax assurance.
Given the confidence we have in tax amounts we have assurance over, we apply a lower non-detection factor to those amounts compared to amounts we have not assured.
Find out more in Ensuring complete estimates: Non-detection.
Step 5: Estimate theoretical liability, gross and net gap
To determine the gross gap, we add:
- total amendments (step 1)
- unreported tax (step 3)
- non-detection (step 4).
We then add the amount of tax voluntarily reported and paid to calculate the theoretical liability.
We then subtract total amendments from the gross gap to determine the net gap.
Summary of the estimation process
Table 2 provides a summary of each step of the estimate for each year. It shows the calculation for each of the steps described from 2014–15 to 2019–20. Steps 1 to 5d are in dollar values, steps 5e and 5f are in percentage values.
Step |
Description |
2014–15 |
2015–16 |
2016–17 |
2017–18 |
2018–19 |
2019–20 |
|---|---|---|---|---|---|---|---|
1a |
Amendments ($m) |
75 |
30 |
134 |
89 |
122 |
96 |
1b |
Projected amendments ($m) |
-4 |
-2 |
0 |
18 |
39 |
52 |
1c |
Total amendments ($m) |
71 |
28 |
134 |
107 |
161 |
148 |
2 |
Tax assured ($m) |
5,214 |
7,423 |
9,742 |
11,164 |
1,899 |
1,139 |
3 |
Unreported tax ($m) |
9 |
159 |
28 |
124 |
94 |
119 |
4 |
Non-detection ($m) |
114 |
114 |
124 |
55 |
73 |
111 |
5a |
Gross tax gap ($m) |
195 |
301 |
286 |
286 |
328 |
378 |
5b |
Tax voluntarily reported and paid ($m) |
7,173 |
8,484 |
10,977 |
12,403 |
8,279 |
11,555 |
5c |
Theoretical liability ($m) |
7,367 |
8,785 |
11,263 |
12,689 |
8,607 |
11,933 |
5d |
Net tax gap ($m) |
123 |
273 |
152 |
179 |
167 |
230 |
5e |
Gross tax gap (%) |
2.6% |
3.4% |
2.5% |
2.3% |
3.8% |
3.2% |
5f |
Net tax gap (%) |
1.7% |
3.1% |
1.3% |
1.4% |
1.9% |
1.9% |
Find out more about our overall methodology, data sources and analysis used for creating our tax gap estimates.
Limitations
The following caveats and limitations apply when interpreting the large super funds income tax gap estimate.
- The estimate doesn't reflect the difference between reasonably arguable positions presented by the ATO and taxpayers where tax law is open to interpretation.
- There is no independent data source that can provide a credible or reliable macroeconomic-based estimate (unlike for indirect taxes).
- Due to the diverse nature of the market and the complexity of large super funds, it would be impractical to apply a statistical approach based on auditing a random sample of funds with a large enough sample to provide a reliable indication of the tax gap.
- Super funds rely on third-party data to complete tax return data. Failure in corporate governance may result in funds understating their tax position. This could also be hiding a larger gross gap than we currently estimate.
Updates and revisions to previous estimates
Each year we refresh our estimates in line with the annual report. Changes from previously published estimates occur for a variety of reasons, including:
- improvements in methodology
- revisions to data
- additional information becoming available.
Figure 2: Current and previous net gap estimates for large super funds, 2010–11 to 2019–20
The data is set out as a percentage in Table 3.
Table 3: Current and previous net gap estimates for large super funds (percentage), 2010–11 to 2018–19
Year |
2010–11 |
2011–12 |
2012–13 |
2013–14 |
2014–15 |
2015–16 |
2016–17 |
2017–18 |
2018–19 |
2019-20 |
|---|---|---|---|---|---|---|---|---|---|---|
2022 program |
n/a |
n/a |
n/a |
n/a |
1.7% |
3.1% |
1.3% |
1.4% |
1.9% |
1.9% |
2021 program |
n/a |
n/a |
n/a |
2.4% |
2.6% |
2.5% |
2.2% |
1.3% |
1.3% |
n/a |
2020 program |
n/a |
n/a |
2.1% |
2.7% |
2.3% |
2.3% |
2.2% |
1.2% |
n/a |
n/a |
2019 program |
n/a |
2.1% |
1.3% |
2.5% |
2.0% |
1.6% |
1.6% |
n/a |
n/a |
n/a |
2018 program |
1.7% |
2.6% |
1.4% |
1.7% |
2.2% |
1.5% |
n/a |
n/a |
n/a |
n/a |
Revisions to these results will be published in future years as further information becomes available. New information generally relates to later years. By including this, we can reduce the uncertainty in the estimates for these years and improve the reliability and credibility of our estimates. Given the higher level of uncertainty with later year gap estimates, caution should be taken in extrapolating these results.