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Latest estimates and trends

Compare the 2020–21 individuals not in business income tax gap to trends from previous years.

Published 24 October 2023

Individuals not in business population

For 2020–21 we estimate a net gap of 6.3% or $10.2 billion for individuals not in business. This means taxpayers paid around 93.7% of the total theoretical tax.

The population for this gap is defined as taxpayers who mainly receive salary and wages, with some other income, including:

  • non-business income from the sharing economy
  • 'passive income' which can include
    • dividends
    • interest
    • rental income.

To avoid double-counting, we exclude individuals that form part of the high wealth private groups. We cover these individuals separately.

This income tax gap is part of our overall tax performance program. Find out more about the concept of tax gaps and latest gaps available.

Overview of the latest estimate

Our current gap estimate is based on findings from 6 years of our random enquiry program. We observe a downward trend from 2015–16 to 2018–19, followed by a stable estimate from 2018–19 to 2020–21.

In our random enquiry program, we found adjustments were made in both tax agent and self-prepared income tax returns, including:

  • incorrect deduction claims for work-related or rental property expenses (or both)
  • careless income tax return administration or preparation.

Lack of connection to income earned or substantiation for expenses were also significant issues.

Work-related expenses continue to be the single largest contributor to the tax gap. They account for $3.6 billion of the net tax gap with errors relating to incorrect claims of work-related expenses due to lack of connection to income producing activities, poor record keeping and not apportioning claims to account for private use.

Another key contributor was unreported income from hidden wages, which is part of the shadow economy. It contributed around $2.9 billion to the gap in 2020–21 or 27% of the gross tax gap. Although this represents an increase from last year's estimate (around $2.1 billion), this increase is driven by changes to our estimation approach, as opposed to an increase in the estimated prevalence of hidden wage activity.

While the amounts over-claimed and under-reported by individual taxpayers may be small, collectively across a large population the overall revenue impact is significant.

Table 1: Income tax gap – individuals not in business, 2015–16 to 2020–21

Element

2015–16

2016–17

2017–18

2018–19

2019–20

2020–21

Population (m)

10.9

11.2

11.4

11.6

11.6

11.6

Gross gap ($m)

10,147

10,486

11,005

10,528

11,084

10,940

Amendments ($m)

750

982

791

687

534

739

Net gap ($m)

9,397

9,504

10,213

9,840

10,550

10,201

Expected collections ($m)

126,446

130,872

141,518

145,650

152,295

151,207

Theoretical liability ($m)

135,843

140,376

151,732

155,490

162,845

161,408

Gross gap (%)

7.5

7.5

7.3

6.8

6.8

6.8

Net gap (%)

6.9

6.8

6.7

6.3

6.5

6.3

Figure 1 displays these trends as a percentage.

Figure 1: Gross and net tax gap percentage – individuals not in business, 2015–16 to 2020–21

Figure 1 shows the gross and net gap in percentage terms, as outlined in Table 1.

Internationally, tax gaps are difficult to compare. This is due to:

  • large variations in legal and tax systems
  • market definitions
  • availability of data
  • methodologies used.

While this estimate is not directly comparable for these reasons, we use methodology that is used in similar tax regimes. The United Kingdom (UK) and United States of America (US) also use random enquiry programs. They are considered best practice when estimating from large and homogenous taxpayer populations.

The random enquiry program

In our random enquiry program, we randomly select and profile a sample of individual taxpayers who are not in business. People in the sample identified as low risk are not inconvenienced by being investigated further.

We verify details where we can confirm the income tax return data by matching all material amounts with our third-party data. We refer to these taxpayers as the 'verified' portion of the sample. While we do not manually review these taxpayers, they remain part of our overall sample, contributing to our gap analysis.

The rest of the sample progress to a review, the random enquiry program, from which we gather information. We estimate the gap by using the incidence rate of adjustments and mean value of amendments resulting from non-compliance. Adjustments refer to changes we make to items on a tax return to correct errors identified in the review process.

This method provides insights into the:

  • value of non-compliance
  • proportion of the sample, and by extension the population, who are incorrectly reporting.

Findings from the random enquiry program

From 2013–14 to 2019–20, we undertook 3,583 random enquiry program reviews across a representative sample of the individuals not in business population.

The 2 years from 2018–19 to 2019–20 comprised 1,090 cases that informed our most recent year's estimate. Of these cases, 836 involved manual reviews, while 254 were verified using third-party data.

This sample was large enough to provide a suitable representation of the population. It is proportionally similar to, or greater than, other comparable countries' programs (for example, UK and US).

During the selection process, we stratified the population across all income bands to ensure the overall population was appropriately represented. Taxpayers in the tax-free threshold and low to very high incomes were represented as well as taxpayers with rental properties.

The sample includes taxpayers who lodged through various channels. The proportion of agent-prepared income tax returns in the random sample was representative of the total individuals not in business population.

We used a confidence interval to quantify the precision of the estimate. See more about limitations. We are confident that the true value of the net gap in 2020–21 lies between 5.2% to 7.4%, or $8.4 billion to $12.0 billion.

In the 2018–19 to 2019–20 sample, the incidence of adjustment was 70%, with 81% of agent-prepared returns being adjusted. This compares with 57% of returns adjusted for people who self-prepared their tax return.

On average we made 2.7 item adjustments per income tax return. The median increase to taxpayers' taxable income (income less deductions) was $953. While individually this amount may not be large, when aggregated across the whole population, the effect is significant.

There were:

  • 61 cases where we decreased tax payable
  • 58 cases where we adjusted solely in the taxpayer's favour.
Table 2: Overview of the 2018–19 to 2019–20 random enquiry programs for individuals not in business

Cases

Sample
(no.)

Agent-prepared sample
(no.)

Agent-prepared sample
(%)

Self-prepared sample
(no.)

Self-prepared sample
(%)

Manually reviewed cases

836

571

68

265

32

Verified cases

254

105

41

149

59

Total finalised cases

1,090

676

62

414

38

Table 3: Comparison of the incidence of adjustment in all finalised cases for the 2018–19 to 2019–20 random enquiry programs for individuals not in business

Cases

Full sample
(no.)

Full sample
(%)

Agent-prepared sample
(no.)

Agent-prepared sample
(%)

Self-prepared sample
(no.)

Self-prepared sample
(%)

Cases with adjustments

782

72

546

81

236

57

Cases with adjustments only in the taxpayer's favour

58

5.3

34

5.0

24

5.8

Note: The distribution of item adjustment values shows that 40% were $150 or less and 24% were over $1,000.

Table 4: Distribution of item adjustment rates and values in the 2018–19 to 2019–20 random enquiry programs (percentage) for individuals not in businessFootnote1

Range of adjustments

% of all adjustments

% of values adjusted

$0–$50

22

<1

$51-$150

17

1

$151–$300

14

2

$301–$500

10

3

$501–$1,000

13

7

More than $1,000

25

88

Our analysis indicated that adjustment rates were broadly similar across tax agent practice and locations, although rates for smaller tax agents were slightly higher.

Based on the analysis and findings of the random enquiry program and insight from our overall engagement program, we can highlight themes that contribute to the gap.

When we look at the most recent tax gap year estimate, we draw on the last 2 years of the sample only. Figure 3 shows a breakdown of the individuals not in business tax gap by the different drivers for the most recent years estimate.

Figure 2: Net tax gap breakdown by driver for individuals not in business, 2020–21

Figure 2 shows the breakdown of the net tax gap by the four main drivers: work-related expenses at 35%, rental expenses at 12%, hidden income at 30% and other at 23%.

 What is driving the gap

Through our analysis, we found several main areas that contribute to the individuals not in business tax gap:

Work-related expenses

Work-related expenses are a key component of the individuals not in business income net tax gap. The work-related expenses net gap estimate is $3.6 billion.

Each case can have multiple adjustments across the tax return. Of the 2,970 adjustments in identified cases, around 77% related to deduction items, including rental deductions. Around 44% or 1,311 were made at work-related expense items. Of those adjustments, 69% or 905 were made in agent-prepared returns.

Common reasons for adjustments in the random enquiry program include:

  • claims for ‘standard’ deductions where exceptions to substantiation provisions exist, for example claiming $300 for work-related expenses without spending the money
  • no link between the expense and taxpayer earning their income
  • incorrect apportionment of private use vs work-related use – claiming expenses that aren’t apportioned for personal use, such as 100% of mobile phone expenses
  • claims that appeared legitimate, but could not be substantiated because there are no receipts, logbook or diary entries
  • claims for expenses that were actually paid for or reimbursed by the employer.

Work-related expenses adjustments and reasons

The following 2 pie charts display the number of adjustments to work-related expense items and the reasons for these adjustments.

The highest rate of adjustments was for 'other expenses'. In particular, incorrect claims for home office, mobile phone and internet. Claims for clothing and car were also frequently adjusted.

Figure 3: Number of adjustments to work-related expenses

 Figure 3 shows a breakdown of the types of work–related expenses adjustments and number of times they occurred: car with a value of 213, travel with a value of 116, clothing with a value of 393, self-education with a value of 50 and other with a value of 539.

Figure 4: Reasons for work-related expense adjustments

 Figure 4 shows the percentage breakdown of the reasons for adjustments made for work-related expenses: substantiation with a value of 31%, nexus and substantiation with a value of 31%,  nexus with a value of 9%, over-claimed with a value of 7%,calculation error with a value of 7% and other reasons combined with a value of 14%.

Undeclared income

Omitted income, particularly cash wages and income from the sharing economy, also contributes to the tax gap.

Some people don't declare income and payments to avoid paying the right amount of tax or super. For example, some businesses may pay their employees 'cash-in-hand’ and some taxpayers do not report all the cash income they earn.

We estimate the portion of the tax gap for 2020–21 attributable to unreported income was $3.5 billion.

Identifying non-declared wages is difficult, even in a random enquiry program. We take a different approach to account for the impact of undeclared cash wages, an aspect of the shadow economy.

To help us estimate the undeclared wages in the individuals not in business population, we draw on 2 of our administrative gaps:

Our approach is incorporated in our shadow economy strategy.

Other findings and observations

Observations from our broader compliance activities reinforce findings from our random enquiry program. This further supports our understanding of what is driving the gap.

Deductions for rental property expenses are also a key contributor. The rental component of the net tax gap is estimated to be $1.2 billion.

Our observations indicate that the most common reasons for adjustments to rental items on a tax return are:

  • no or incorrect apportionment of the loan interest costs where the loan was re-financed for private purposes
  • claiming costs as repair rather than a capital works deduction
  • not apportioning expenses for private use of the property.

Footnote 1

Return to footnote 1 Totals do not equal 100% due to rounding referrer

QC56246