High wealth income tax gap 2018-19
This information is for historical purposes only. If you require previously published content for past estimates, please email taxgap@ato.gov.au.
This estimate for the high wealth income tax gap relates to the 2018-19 financial year
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This gap forms a part of our overall tax performance program.
High-wealth private groups are defined as Australian resident individuals who, together with their associates, control wealth of more than $50 million.
To estimate this gap, we include:
- registered individuals linked to a high-wealth private group
- companies where ownership by the head individual is 40% or more.
Companies with total business income greater than $250 million are included in the large corporate groups income tax gap.
The income of high-wealth private groups includes distributions from trusts and partnerships that are part of their structure. These amounts are accounted for as part of this gap estimate.
For 2018–19, the net income tax gap estimate for high-wealth private groups was $760 million or 6.9%. This means we estimate they paid more than 93% of the total theoretical tax payable for 2018–19.
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Trends and latest findings
The net high-wealth income tax gap estimate has ranged between 6.5% and 7.1% over the 6-year period between 2013-14 and 2018-19, as shown in Table 1. The overall trend is steady.
Table 1: Income tax gap – high-wealth private groups 2013–14 to 2018–19
Element
|
2013–14
|
2014–15
|
2015–16*
|
2016–17*
|
2017–18*
|
2018–19*
|
Population (groups)
|
5,425
|
6,150
|
6,146
|
6,138
|
6,105
|
5,893
|
Gross gap ($m)
|
730
|
859
|
846
|
913
|
1,032
|
946
|
Amendments ($m)
|
156
|
242
|
186
|
186
|
186
|
186
|
Net gap ($m)
|
573
|
617
|
660
|
727
|
846
|
760
|
Tax paid ($m)
|
8,102
|
8,936
|
9,315
|
9,884
|
11,118
|
10,184
|
Theoretical liability ($m)
|
8,675
|
9,553
|
9,975
|
10,610
|
11,964
|
10,943
|
Gross gap (%)
|
8.4
|
9.0
|
8.5
|
8.6
|
8.6
|
8.6
|
Net gap (%)
|
6.6
|
6.5
|
6.6
|
6.8
|
7.1
|
6.9
|
*Projected years
Figure 1 shows the gross and net gap as a percentage over the same period. The data presented in these images is also available in Table 1 above.
Figure 1: Gross and net tax gap (percentage) – high-wealth private groups, 2013–14 to 2018–19
What is driving the gap
Where high-wealth private groups are getting their tax right, they:
- have strong tax governance practices and system controls
- seek advice from tax professionals when considering making changes to their business or wealth management structures
- talk to us to gain greater certainty about the tax consequences of significant transactions or changes in structure before they happen.
When business owners and wealthy individuals make mistakes, it is usually in how they interpret tax law or because they don't understand their tax obligations.
The most common issues we see from taxpayers include:
- incorrectly recording transactions or not reporting transactions that are outside the normal course of business
- not accounting for private use of business funds or assets
- omitting domestic or foreign-sourced income.
A very small number of high-wealth private groups seek to evade paying the right amount of tax. These groups take advantage of the closely-held nature of their structures. We see these groups undertaking artificial and non-commercial arrangements that are intentionally designed to evade tax. Where we detect deliberate tax evasion, we apply correction strategies such as penalties and prosecutions.
Find out what attracts our attention.
ATO action to reduce the gap
The key to an effective tax system is a high level of willing participation. The extent of taxpayers' willingness to participate depends on whether they:
- value the tax and superannuation systems
- have trust and confidence in us as administrators.
Our strategies to reduce the gap and encourage willing participation are based on these principles.
We understand perceptions of fairness influence willing participation and confidence other taxpayers have in the integrity of the tax system. In addressing the high wealth income tax gap, we seek to improve the overall health of the tax and superannuation systems.
The best way to achieve a sustained reduction in the high-wealth private groups income tax gap is to make it easier for these groups to get their tax right, and hard to get it wrong.
As part of our activities under the Tax Avoidance Taskforce, we closely monitor high-wealth private groups and seek to obtain assurance that the correct amount of tax is being paid. We also have a range of client engagement programs to increase their willing participation in the tax and superannuation system.
We work with high-wealth private groups to give them certainty about how we view their tax affairs, support them to correct mistakes, and mitigate against future tax issues.
Where we detect tax avoidance schemes or evasion, we take firmer action such as penalties and seeking prosecution when appropriate. This keeps the system fair for everyone.
Our analysis shows that many of the risks associated with failing to pay the right amount of tax are associated with the misapplication or misunderstanding of relevant tax laws. Some of the tax law interpretation issues we see include:
- mischaracterisation of receipts as income or capital
- incorrect treatment of payments from companies to individuals and the operation of Division 7A of the Income Tax Assessment Act 1936 and wealth extraction
- incorrect reporting and calculation of capital gains events
- claiming ‘tax incentives’, such as capital gains tax concessions, where there is no entitlement.
Our pre-lodgment activities help taxpayers to get it right in real time. We also help them to correct their prior-year mistakes. These activities include our:
- high-wealth private groups tax performance program
- commercial deals program
- international and trust programs.
Around 30% of amendments made by high-wealth taxpayers were made voluntarily between 2013–14 and 2018–19.
We continue to improve our risk models and develop our data and analytical tools so we can proactively engage high-wealth private groups and help them comply.
We support people trying to do the right thing if they make a mistake – but we take firm actions where we see attempts to evade paying tax.
Tools and tips to help get it right
We offer a range of tools and services to help taxpayers clarify our view of the tax consequences of significant and complex transactions.
We encourage taxpayers to engage with us or their advisers, when planning activity outside their normal business as usual, including expanding activity offshore or transitioning to retirement.
To avoid mistakes, high-wealth private groups should:
- have strong tax governance practices and system controls
- seek advice from tax professionals when considering making changes to their business or wealth management structures
- talk to us to gain greater certainty about the tax consequences of significant transactions or changes in structure before they happen.
See also:
Methodology
The high wealth income tax gap estimate is derived through applying two bottom-up statistical methods:
- 'extreme value theorem' regression model for individuals
- two-stage logistic and linear regressions for companies (the 'logistic linear regressions' model).
The following sections step through the method and results for the two separate models, before being combined as shown in Table 1.
Calculation – high wealth individuals
There are four steps in using the extreme value theorem to estimate the high wealth individuals tax gap:
Step 1: Identify the extreme population
Amendments for high-wealth individual taxpayers follow a power law distribution, with the majority of total tax amendments in value terms represented by a small number of amended income tax returns.
We rank the amendments in descending order and identify the point where the cumulative sum of positive amendments is equal to or less than the total negative amendments. We remove all these small amendments, which have no impact on the net value of total amendments. The remaining amendments are referred to as the 'extreme values'. We calculate the number of extreme values as a ratio of all amendments to be used for extrapolation purposes in Step 2.
Step 2: Estimate the unreported tax amount
We transform the amendment data of the extreme population to estimate a linear relationship between the value and rank of the amendments using a regression approach. To estimate the unreported tax amount, we then extrapolate the relationship to the number of taxpayers expected to contribute to the extreme values in the wider population.
Step 3: Apply a non-detection uplift factor
We need to account for imperfections in the process that could lead to the final gap estimate not reflecting the true tax gap. To account for non-detection, we apply an uplift factor to the unreported tax amount in Step 2.
Step 4: Consolidate the gap estimates
The gross gap is calculated by adding the unreported amounts from Step 2, non-detection uplift from Step 3 and non-pursuable debt. The net gap is calculated by subtracting the total amendment amount from the gross gap. The net gap is then added to the tax paid to estimate the total theoretical liability.
For 2015–16 and onwards, the gross gap estimates are projected using the average gross gap percentage for 2012–13 and 2013–14. This is due to the delay between the lodgment and amendment of income tax returns.
Summary of the estimation process – high wealth individuals
Table 2 displays the individuals population count at Step 1 and dollar values at Steps 2 to 4.6. Steps 4.7 and 4.8 show the percentage figure for the gross and net gaps.
Table 2: Summary of estimation process for high wealth individuals
Step
|
Description
|
2013–14
|
2014–15
|
2015–16*
|
2016–17*
|
2017–18*
|
2018–19*
|
1
|
Total population (count)
|
9,856
|
11,159
|
11,162
|
11,150
|
11,083
|
10,643
|
2
|
Total expected amendments ($m)
|
228
|
285
|
262
|
273
|
334
|
298
|
3
|
Non-detection ($m)
|
146
|
183
|
178
|
183
|
222
|
198
|
4.1
|
Non-pursuable debt ($m)
|
2
|
2
|
2
|
2
|
2
|
2
|
4.2
|
Gross gap ($m)
|
376
|
470
|
441
|
457
|
559
|
498
|
4.3
|
Amendments ($m)
|
111
|
173
|
129
|
129
|
129
|
129
|
4.4
|
Net gap ($m)
|
265
|
297
|
312
|
329
|
430
|
370
|
4.5
|
Tax paid ($m)
|
4,126
|
4,431
|
4,509
|
4,668
|
5,677
|
5,077
|
4.6
|
Total theoretical liability ($m)
|
4,391
|
4,728
|
4,822
|
4,997
|
6,107
|
5,446
|
4.7
|
Gross gap (%)
|
8.6
|
9.9
|
9.1
|
9.1
|
9.1
|
9.1
|
4.8
|
Net gap (%)
|
6.0
|
6.3
|
6.5
|
6.6
|
7.0
|
6.8
|
*Projected years
Calculation – high wealth companies
There are five steps involved in applying logistic linear regressions to the company population:
Step 1: Establish a logistic regression trend
We analyse the income tax return data of companies that have been subject to amendment activities. We apply weights to the data to account for selection bias in our data. We identify the relevant characteristics of companies in general that would contribute to the prediction of whether a company has a tax gap.
Based on these characteristics, each company is assigned a unique probability of having a tax gap. Each company is then modelled to be compliant or non-compliant through a Monte Carlo simulation.
Step 2: Establish a linear regression trend
We analyse the income tax return data of companies known to be non-compliant, to identify relevant characteristics of companies that would contribute to the prediction of the size of a tax gap. Weights are also applied to account for selection bias. The linear regression is then applied to each company to estimate the potential size of the tax gap.
The key difference between Steps 1 and 2 is that Step 1 calculates the likelihood of a company having a tax gap while Step 2 calculates the size of each company's potential tax gap.
Step 3: Combine the results from the two regressions
The estimated unreported tax amount for each simulation is calculated by adding the Step 2 non-compliance amount to the predicted non-compliance companies in Step 1. We estimate total unreported tax (including amendments) by taking an average of the results from 20,000 simulations.
Step 4: Apply a non-detection uplift factor
We uplift the estimates preceding this step to account for non-compliance that is not detected. This ensures that the final estimate is not understated.
Step 5: Consolidate the tax gap estimates
The gross gap is calculated by adding up the unreported amounts from Step 3, non-detection uplift from Step 4 and non-pursuable debt. The net gap is calculated by subtracting the total amendment amount from the gross gap. The net gap is then added to the tax paid to estimate the total theoretical liability.
Summary of the estimation process – high wealth companies
Table 3 shows the dollar values in millions at Steps 1 to 5.6. Step 5.7 shows the company population count. Step 5.8 and 5.9 show the percentage figures for the gross and net gaps.
Table 3: Summary of estimation process for high wealth companies
Step
|
Description
|
2013–14
|
2014–15
|
2015–16
|
2016–17*
|
2017–18*
|
2018–19*
|
1
|
Total population (count)
|
16,812
|
17,712
|
18,729
|
19,482
|
20,239
|
19,733
|
1–3
|
Unreported tax including amendments ($m)
|
213
|
233
|
243
|
274
|
284
|
270
|
4
|
Non-detection ($m)
|
141
|
155
|
160
|
180
|
189
|
177
|
5a
|
Non-pursuable debt ($m)
|
1
|
1
|
2
|
1
|
1
|
1
|
5b
|
Gross gap ($m)
|
354
|
389
|
405
|
456
|
473
|
448
|
5.c
|
Amendments ($m)
|
46
|
69
|
58
|
58
|
58
|
58
|
5.d
|
Net gap ($m)
|
308
|
320
|
347
|
398
|
415
|
390
|
5.e
|
Tax paid ($m)
|
3,976
|
4,505
|
4,805
|
5,215
|
5,441
|
5,107
|
5.f
|
Total theoretical liability ($m)
|
4,284
|
4,824
|
5,153
|
5,613
|
5,856
|
5,497
|
5.g
|
Gross gap (%)
|
8.3
|
8.1
|
7.9
|
8.1
|
8.1
|
8.1
|
5.h
|
Net gap (%)
|
7.2
|
6.6
|
6.7
|
7.1
|
7.1
|
7.1
|
*Projected years
Limitations
The following caveats and limitations apply when interpreting this tax gap estimate:
- There is a considerable delay between an income year and the completion of our compliance activities relating to that year. This means that gap estimates may remain subject to revisions for a considerable period. Company results for 2016–17 onwards, and individual results for 2015–16 onwards are projected. They are expected to be subject to revisions over coming years.
- There is no independent data source that can provide a credible or reliable macroeconomics-driven estimate (unlike indirect taxes).
- The true extent of non-detection is unknown and is extremely challenging to measure. There is no international proxy that can be applied to the individuals or companies in this population.
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.
We published the high wealth income tax gap for the first time in March 2020. The chart below shows that the updated net gap estimates this year are lower than the estimates published last year. This is largely due to the churn in population of high wealth individual entities.
Figure 2: Current and previous net high wealth income tax gap estimates, 2011–12 to 2018–19
This data is presented in Table 3 as a percentage.
Table 4: Current and previous net high wealth income tax gap estimates, 2011–12 to 2018–19
Year
|
2011–12
|
2012–13
|
2013–14
|
2014–15
|
2015–16*
|
2016–17*
|
2017–18*
|
2018–19*
|
2019
|
8.8%
|
6.6%
|
7.7%
|
7.1%
|
7.3%
|
7.7%
|
n/a
|
n/a
|
2020
|
n/a
|
6.5%
|
6.9%
|
8.2%
|
6.9%
|
7.1%
|
7.4%
|
n/a
|
2021
|
n/a
|
n/a
|
6.6%
|
6.5%
|
6.6%
|
6.8%
|
7.1%
|
6.9%
|
*Projected years
Reliability
We seek feedback and advice about the methods we use to estimate the gap from our external and internal subject matter experts. Based on the advice and assessment, the reliability for this estimate is high (with a score of 21).
The methodological validity of the approach is similarly assessed as high. The level of data and information held on the high wealth population is extensive and the population coverage informing the estimates is also high.
The gap estimates remain sensitive to assumptions made, particularly relating to non-detection.
Figure 3 shows the reliability rating for the high wealth income tax gap estimate.
Figure 3: Reliability rating scale from very low to very high – high wealth income tax gap
This estimate for the high wealth income tax gap relates to the 2018-19 financial year.