Show download pdf controls
  • Individuals not in business 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 individuals not in business income tax gap relates to the 2018-19 financial year.

    On this page

    This gap forms a part of our overall tax performance program.

    For the purposes of estimating this gap, our individual not in business population is defined as taxpayers who mainly receive:

    • salary and wages, with
    • some other income, including  
      • non-business income from the sharing economy
      • what we refer to as 'passive income' which can include  
        • dividends
        • interest
        • rental income.   

    In defining this taxpayer population, we exclude individuals that form part of the high wealth private groups to avoid double-counting. These individuals are covered separately in the High wealth private groups income tax gap.

    For 2018–19 we estimate a net gap of 5.6% or $8.4 billion for individuals not in business. In other words, we estimate that these taxpayers paid over 94% of the total theoretical tax payable in 2018–19.

    See more about:

    Trends and latest findings

    Our current gap estimate for individuals not in business is based on findings from five years of our random enquiry program. We are seeing consistent downward trend in the tax gap estimate since 2015-16.

    Internationally, tax gaps are difficult to compare. This is due to the large variations in legal and tax systems, market definitions, availability of data and the methodologies used to estimate gaps across tax jurisdictions.

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

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

    • incorrect claiming of deductions for work-related expenses or rental property expenses (or both)
    • careless administration or careless preparation of an income tax return.

    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 $3.7 billion of the net tax gap with errors relating to incorrect claims for home office, mobile phone and internet.

    While the 2018-19 estimate is not impacted by COVID-19 lockdowns and higher than normal working from home arrangements, next year's estimate will see the first signs of impact through increased working from home deductions. With more claimants and higher claim amounts we expect to see a corresponding increase in the work-related expenses net tax gap.

    Another key contributor was unreported income from hidden wages contributed around $1.6 billion to the gap in 2018–19. This represents 17.5% of the gross tax gap. This activity is considered part of the shadow economy.

    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, 2013–14 to 2018–19

    Element

    2013–14

    2014–15

    2015–16

    2016–17

    2017–18

    2018–19

    Population (m)

    10.3

    10.5

    10.7

    11

    11.1

    11.3

    Gross gap ($m)

    7,195

    8,499

    9,060

    9,215

    9,321

    9,162

    Amendments ($m)

    816

    802

    786

    855

    613

    734

    Net gap ($m)

    6,379

    7,697

    8,274

    8,360

    8,708

    8,428

    Tax paid ($m)

    111,268

    118,796

    125,650

    129,547

    139,035

    142,919

    Theoretical liability ($m)

    117,647

    126,493

    133,925

    137,907

    147,743

    151,346

    Gross gap (%)

    6.1

    6.7

    6.8

    6.7

    6.3

    6.1

    Net gap (%)

    5.4

    6.1

    6.2

    6.1

    5.9

    5.6

    Figure 1 displays these trends as a percentage.

    Figure 1: Gross and net tax gap percentage – individuals not in business, 2013–14 to 2018–19

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

    The random enquiry program

    Within 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.

    Details are verified 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 these taxpayers are not manually reviewed, they remain part of our overall sample, contributing to our gap analysis.

    The remainder of the sample progress to a review (the random enquiry program). Once we have gathered information from the random enquiry program, we estimate the gap by using the incidence rate of adjustments and mean value of amendments resulting from non-compliance. Adjustments refer to the changes we make to items on an income tax return to correct errors identified as part of the review process.

    This method provides insights, not only into the value of non-compliance, but also into the proportion of the sample (and by extension the population) who are incorrectly reporting.

    Findings from the random enquiry program

    The random enquiry programs from 2013–14 to 2017–18 saw 2,493 reviews undertaken across a representative sample of the individuals not in business population.

    The two years from 2016–17 to 2017–18 comprised a total of 1,090 cases that informed our most recent year's estimate. Of these cases, 899 involved manual reviews, while 191 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 the population was stratified 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. This is discussed in detail in the Limitations section. We are confident that the true value of the net gap in 2018–19 lies between 4.8% to 6.4%, or $7.2 billion to $9.7 billion.

    In the full sample of 1,090 cases, the incidence of adjustment was 76%, with 83% of agent-prepared returns being adjusted. This compares with 61% of returns adjusted for people who prepared their own income tax return (self-preparers).

    On average we made three item adjustments per income tax return. The median increase to taxpayers' taxable income (income less deductions) was $1,552. While individually this amount may not be large, when aggregated across the whole population, the effect is significant.

    There were 57 cases where we decreased tax payable. This included seven cases where we adjusted solely in the taxpayer’s favour. There was one additional case where we adjusted solely in the taxpayer’s favour, but with no effect on tax payable.

    Across the random enquiry program, a greater proportion of self-prepared returns (17%) were adjusted at income labels compared to agent prepared returns (13%) Adjustments to deduction items (including rental expenses, work-related expenses, gifts and donations and other deductions) were higher in agent-prepared income tax returns.

    Table 2: Overview of the 2016–17 to 2017–18 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

    899

    682

    76

    217

    24

    Verified cases

    191

    95

    50

    96

    50

    Total finalised cases

    1,090

    777

    71

    313

    29

    Table 3: Comparison of the incidence of adjustment in all finalised cases for the 2016–17 to 2017–18 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

    833

    76

    643

    83

    190

    61

    Cases with adjustments only in the taxpayer’s favour

    8

    1

    6

    1

    2

    1

    Note: The distribution of the value of the item adjustments show that 38% of adjustments are $150 or less and 25% are over $1,000.

    Table 4: Distribution of item adjustment rates and values in the 2016–17 to 2017–18 random enquiry programs (percentage) for individuals not in business

    Range of adjustments

    Self-prepared % of all adjustments

    Self-prepared % of values adjusted

    Agent-prepared % of all adjustments

    Agent-prepared % of values adjusted

    Total % of all adjustments

    Total % of values

    $0–$150

    8

    <1

    30

    1

    38

    1

    $151–$300

    3

    <1

    12

    1

    15

    2

    $301–$500

    2

    1

    8

    2

    10

    2

    $501–$1,000

    2

    1

    10

    4

    12

    5

    More than $1,000

    4

    16

    21

    74

    25

    90

    Total

    19

    18

    81

    82

    100

    100

    Analysis indicated that adjustment rates were broadly similar across types of tax agent practices and locations, although rates for tax agents in small tiers 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 two 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, 2018–19

    Figure 2 shows the breakdown of the net tax gap by the four main drivers: work-related expenses 44%, rental expenses 18%, hidden income 19% and other 19%.

    What is driving the gap

    Through our analysis, we have found several main areas that are contributing 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 was estimated to be $3.7 billion.

    Each case can have multiple adjustments across the income tax return. Of the 3,379 adjustments made in identified cases, around 77% related to deduction items (including rental deductions). Around 46% or 1,541 of adjustments were made at work-related expense items. Of those work-related expenses adjustments, 80% or 1,237 were made in agent-prepared returns.

    Common reasons for adjustments in the random enquiry program included:

    • claims for ‘standard’ deductions where exceptions to substantiation provisions exist (e.g. $300 for work related expenses without having spent the money)
    • no link between the expense and the taxpayer earning their income
    • incorrect apportionment (private use vs work-related use) – claiming expenses that aren’t apportioned for personal use, e.g. claiming 100% of mobile phone expenses
    • claims that appeared legitimate, but could not be substantiated (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 two 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 shows the number of adjustments to work-related expenses.

    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 296, travel 125, clothing 469, self-education 46 and other 605.

    Figure 4 shows the reasons for these adjustments.

    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 31%, nexus and substantiation 25%, nexus 10%, over-claimed 10%, voluntary disclosure 7%, calculation error 5% and other reasons combined 12%.

    Undeclared income

    Income that has been omitted, particularly cash wages and income from the sharing economy, also contributes to the tax gap for individuals not in business.

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

    We estimate the portion of the tax gap for 2018–19 attributable to unreported income was $1.6 billion.

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

    We draw on our other broader tax gap program, specifically, the pay as you go (PAYG) withholding gap and the super guarantee gap to help us estimate the undeclared wages in the individuals not in business population.

    Our approach to addressing the non-reporting of cash wages is incorporated in our shadow economy strategy.

    Other findings and observations

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

    Deductions for rental property expenses are also a key contributor to the gap. The rental component of the individuals not in business net tax gap is estimated to be $1.6 billion.

    Our observations indicate that the most common reasons for adjustments to rental items on an income tax return are a lack of, or incorrect, apportionment of expenses.

    This includes, for example, deduction claims where the property was only available to rent for part of the year. Or claims for interest expenses where a portion of the loan was used for private purposes. We also see mistakes relating to capital works and capital allowance deductions.

    See more about:

    ATO action to reduce the gap

    The key to an effective tax system is a high level of willing participation. The level of willing participation depends on the extent to which the community values the system and has trust and confidence in us as administrators.

    Individuals who are not in business are the largest community segment interacting with the tax and superannuation system in Australia. We talk about their contribution to our economy by paying tax voluntarily and their key features in Tax and individuals – not in business. In this document, we discuss the challenges faced, and how we are improving the system for people who want to do the right thing, while taking firm action with those who don't.

    While the vast majority of tax collected is paid voluntarily through the pay as you go (PAYG) withholding system, we are concerned with how many taxpayers are over-claiming deductions. We commonly, see errors relating to work-related expenses, rental properties and omission of income, particularly where wages are paid in cash. There are a range of factors contributing to why some people misreport this information.

    Our strategies to reduce the individuals not in business gap, based on the principle of willing participation, include:

    • improving and tailoring our public advice and guidance material, tools and services (including advice on emerging risks such as the sharing economy and cryptocurrencies)
    • increasing the quantity and quality of the data we collect
    • adopting new ways of using data and technology to make lodging income tax returns and substantiating deductions simpler for taxpayers and their tax agents (includes streamlining reporting processes and pre-filling more information in income tax returns)
    • helping taxpayers and their tax agents report correctly, using 'nudge' messages and other correspondence to alert them where we see something unusual
    • better understanding the circumstances of debt, doing what we can to prevent it and offering practical repayment options
    • taking firmer action to address non-compliance among higher-risk taxpayers and tax agents, including additional audits, particularly in areas driving the tax gap
    • pursuing penalties or prosecution – or referring tax agents to the Tax Practitioners Board in the most serious of cases.

    We also provide insights to government, through the Treasury, about potential opportunities for statutory law reform to improve the tax and superannuation system. We do this where we see the law is difficult for both taxpayers and ourselves to apply, and may increase compliance costs. In addition, we suggest where the law can be strengthened to allow us to more effectively deal with compliance risks.

    We seek to administer the tax and superannuation system in a way that is fair and consistent. We design our interactions with taxpayers and their tax agents to be professional, contemporary and tailored to individual circumstances, making it easy to comply and hard not to.

    While we focus on preventing non-compliance to reduce the gap, we will take action to protect the integrity of the tax and superannuation system and ensure that everyone – from each individual taxpayer through to the largest corporate group – pays the right amount of tax.

    Methodology

    The individuals not in business tax gap estimate is derived through applying a bottom-up random enquiry approach. Random sampling methods are considered highly credible, best practice, and are commonly used by international jurisdictions to estimate tax gaps for this type of population.

    There are four steps in applying the random enquiry program bottom-up methodology to estimate the individuals not in business income tax gap. These steps are expanded on below followed by a summary of the overall estimate:

    Step 1: Estimate unreported amounts and extrapolate to population. Apply estimate for people outside the system

    In each year we draw on a bundled sample of up to three years from the random enquiry program. The bundled sample is split into two key groups:

    • those who are progressed to manual review
    • those who are verified.

    We combine the incidence rates and means from these two groups. We then extrapolate to the population of individuals not in business to estimate the unreported tax liability.

    Additionally, we estimate the impact of people outside the system (non-registration or non-lodgment). This estimate draws on comparisons of Australian Bureau of Statistics (ABS) Census of Population and Housing (census) data to income tax return data to estimate the number of non-lodging individuals who are not in business. We then estimate a dollar impact drawing on the random sample data to determine the final amount. We discuss this further in Limitations.

    Step 2: Estimate for errors not detected

    We apply an uplift to the unreported tax liability estimate to correct for errors not identified through the random enquiry program. The uplift factors are based on the midpoint of international ranges and account for non-detected amounts relating to:

    • income misreporting
    • deductions and other issues.

    We also apply an uplift for non-detected amounts that relate to hidden wages, consistent with our wider program for wages. We discuss this further in Limitations.

    Step 3: Estimate for non-pursuable debt

    We add in the value of non-pursuable debt. This is debt that the Commissioner of Taxation has assessed as being not legally recoverable, uneconomical to pursue, or unable to be pursued due to another Act.

    Debt trends show that it takes upwards of five years for non-pursuable amounts to crystallise (or be considered finalised) in any one financial year. As a result, we add a provisional amount of non-pursuable debt to the actual amount recorded in the most recent four years, based on historical amounts.

    Step 4: Consolidate the gap estimates

    The gross gap is calculated by adding the unreported amounts from Steps 1 to 3. 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. Both net and gross gap ratios are derived by dividing the dollar amounts by the theoretical liability.

    Summary of the estimation process

    Table 5 provides a summary of each step of the estimation process and the results for each year.

    Table 5: Summary of estimation process for individuals not in business income tax gap

    Step

    Description

    2013–14

    2014–15

    2015–16

    2016–17

    2017–18

    2018–19

    1.1

    Estimate unreported amounts and extrapolate to population (m)

    5,481

    6,664

    7,135

    7,229

    7,294

    7,065

    1.2

    Apply estimate for people outside the system ($m)

    149

    147

    144

    143

    109

    98

    2.1

    Apply estimate for non-detection (excluding hidden wages) ($m)

    183

    202

    237

    246

    226

    215

    2.2

    Apply estimate for hidden wages ($m)

    1,213

    1,309

    1,368

    1,420

    1,515

    1,607

    3

    Estimate for non-pursuable debt ($m)

    170

    177

    177

    177

    177

    177

    4.1

    Estimate the gross gap (by adding together the results of Steps 1 to 3) ($m)

    7,195

    8,499

    9,060

    9,215

    9,321

    9,162

    4.2

    Subtract compliance outcomes and voluntary disclosures ($m)

    816

    802

    786

    855

    613

    734

    4.3

    Net gap ($m)

    6,379

    7,697

    8,274

    8,360

    8,708

    8,428

    4.4

    Add tax paid ($m)

    110,452

    117,994

    124,864

    128,692

    138,422

    142,185

    4.5

    Theoretical liability ($m)

    117,647

    126,493

    133,925

    137,907

    147,743

    151,346

    4.6

    Gross gap (%)

    6.1

    6.7

    6.8

    6.7

    6.3

    6.1

    4.7

    Net gap (%)

    5.4

    6.1

    6.2

    6.1

    5.9

    5.6

    Limitations

    The limitations associated with estimation of the individuals not in business tax gap are listed as follows:

    • The 2019 estimate uses two of the three finalised random enquiry program sample years. This will be updated in future estimates.
    • The precision of the tax gap estimate is limited by the sample size. Through the use of an ongoing bundled sample, we seek to maintain suitable confidence intervals over time.
    • To reduce compliance costs for the taxpayer, materiality thresholds were applied at the data-driven review stage. However, if a case develops into a manual review, all items in the income tax return are investigated regardless of value.
    • There is no independent data source that can provide a credible or reliable macroeconomic-based estimate (unlike for indirect taxes).
    • The 2013–14 financial year estimates do not account for the effect on offsets of adjustments to income and deductions. Where there are adjustments to income and deductions, the estimates reflect the change in tax on taxable income.
    • A further limitation of the random enquiry program, and similar programs undertaken by tax administrators in other jurisdictions, is uncertainty around the impact of the non-detection error. The enquiries undertaken do not discover the full extent of non-compliance.

    Accounting for non-detection in the gap

    Not all errors are detected through the random enquiry program. We account for these by applying a non-detection uplift to the unreported tax liability estimate.

    The three sources of non-detection for the individuals not in business income tax gap relate to:

    • income misreporting
    • deductions and other issues
    • hidden wages.

    The unreported tax liability is divided into the above elements, with an appropriate non-detection factor then applied to each portion.

    Table 6 shows a summary of the impact of non-detection on the tax gap for each of these elements.

    Table 6: Summary of the impact of non-detection on the individuals not in business income tax gap

    Source of non-detection

    2013–14
    ($m)

    2014–15
    ($m)

    2015–16
    ($m)

    2016–17
    ($m)

    2017–18
    ($m)

    2018–19 ($m)

    Income misreporting (excluding hidden wages)

    169

    185

    198

    215

    183

    173

    Deductions and other issues

    14

    17

    39

    31

    43

    42

    Hidden wages

    1,213

    1,309

    1,368

    1,420

    1,515

    1,607

    Total non-detection

    1,396

    1,511

    1,605

    1,666

    1,741

    1,822

    Accounting for the shadow economy

    The shadow economy concerns economic activity not declared, which may be a result of attempts to avoid tax obligations. We account for the shadow economy in the individuals not in business income tax gap by considering the impacts of:

    • hidden wages
    • people outside the system
    • undisclosed business activity.

    Table 7 shows a summary of the impact of the shadow economy on the tax gap.

    Table 7: Summary of the impact of the shadow economy on the individuals not in business income tax gap ($ million)

    Element

    2013–14

    2014–15

    2015–16

    2016–17

    2017–18

    2018–19

    Hidden wages

    1,213

    1,309

    1,368

    1,420

    1,515

    1,607

    People outside the system

    149

    147

    144

    143

    109

    98

    Undisclosed business income

    0

    0

    0

    0

    0

    0

    Total shadow economy impact

    1,361

    1,456

    1,512

    1,563

    1,624

    1,705

    Confidence in the random sample findings

    A confidence interval quantifies the 'precision' of the estimate from a random sample relative to the true value from the population.

    A 95% confidence level is considered industry best practice in terms of statistical analysis. It is the most commonly used level by researchers, including Her Majesty's Revenue and Customs (HMRC) in the UK in its equivalent tax gap program.

    Using a 95% confidence level means we are 95% confident that the true value of the net gap for 2018–19 lies in the confidence interval 4.8% to 6.4%, or $7.2 billion to $9.7 billion. The upper and lower bounds of the 95% confidence intervals follow. The gap estimates we make public reflect the mid-point of the lower and upper bound estimates.

    Figure 5: 95% confidence interval – upper and lower bound estimates – individuals not in business income tax gap, 2013–14 to 2018–19

    Figure 5 shows the confidence intervals for the individuals not in business income tax gap estimate. The trend result ranges from 4% to 7% at commencement to the results shown above.

    The estimate from the random enquiry program is not the only component of the individuals not in business income tax gap estimate. To establish the overall gap, we also draw on operational data for specific compliance risk areas. For example, we looked at failure by employers to withhold tax and report wage income of their employees, the non-lodgment of income tax returns and the non-payment of debts.

    We combined the operational and random enquiry program findings to produce an overall gap 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.

    This gap was first published in 2018 and has been revised three times on an annual basis. In 2019 we realigned the population and estimate to be consistent with the wider tax gap research program. All historically revised data points are marginally lower than the original estimates.

    Figure 6 displays the net gap from our current model compared to all previously published estimates.

    Figure 6: Current and previous individuals not in business income tax gap estimates, 2013–14 to 2018–19

    Figure 6 displays our previous and current net gap estimates as outlined in Table 8.

    The data used in Figure 6 is presented in Table 8 below.

    Table 8: Summary of published net tax gap percentages for individuals not in business, 2013–14 to 2018–19

    Gap release year

    2013–14

    2014–15

    2015–16

    2016–17

    2017–18

    2018–19

    2017–18

    5.8%

    6.4%

    n/a

    n/a

    n/a

    n/a

    2018–19

    5.6%

    6.2%

    6.4%

    n/a

    n/a

    n/a

    2019–20

    5.6%

    6.1%

    6.2%

    6%

    5.6%

    n/a

    2020–21

    5.4%

    6.1%

    6.2%

    6.1%

    5.9%

    5.6%

    For more detail on our methodology and approach to revisions, see Principles and approaches to measuring gaps.

    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 rating for this estimate is high (with a score of 22).

    The estimate draws on the results from the random enquiry program and looks at all items on an income tax return, and the taxpayer information we have received. Non-payment is also addressed. The gap has not materially moved between years, giving us confidence in the results we are seeing.

    Figure 7: Reliability rating scale from very low to very high – individuals not in business income tax gap

    Figure 7 is a graphical representation of the reliability rating for the current individuals not in business income tax gap estimate. It graphically represents a rating of high (22), which is a score between 21 and 25. The maximum score is 30.

      Last modified: 18 Nov 2022QC 70865