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# Methodology

What method we use to estimate the small business income tax gap.

Published 30 October 2023

We use a random enquiry program bottom-up method to estimate the small business tax gap. There are estimates within the population for individuals in business and small companies.

We use the same overall steps, but because they have different characteristics, we calculate them separately. We step through the method below and combine the estimates in Table 1.

## Step 1: Estimate unreported amounts and apply the estimate for people outside the system

Identify the average amendment and rate of amendments of reviewed taxpayers for each population. We draw this from the relevant sample data for up to 3 years for any one year. Then we extrapolate this average to the relevant population to estimate the unreported tax liability base.

For the estimate for people outside the system, we draw on comparisons of Australian Bureau of Statistics (ABS) Census of Population and Housing (Census) data with tax return data. This provides an estimate of the number of non-lodging individuals in business.

We then estimate a dollar impact drawing on the random sample data to determine the final amount. See more about accounting for the shadow economy.

## Step 2: Estimate for non-detection and hidden wages

Adjustments for non-detection, are to account for non-compliance that we do not detect through our processes that could lead to the final gap estimate not reflecting the true tax gap. We apply uplifts to observed results based on the midpoint of international ranges.

We also apply an uplift for hidden wages to the individuals in business population. This is consistent with our wider program for wages. See more about accounting for non-detection in the gap.

## Step 3: Estimate for non-pursuable debt

We add in the value of non-pursuable debt. This is debt the Commissioner of Taxation has assessed as:

• not legally recoverable
• uneconomical to pursue
• unable to be pursued due to another Act.

Debt trends show that it takes upwards of 5 years for non-pursuable amounts to crystallise for any one income year. As a result, we add a provisional amount of non-pursuable debt to the actual amount recorded, based on historical amounts. As we refresh and move these estimates forward, we will revise these figures.

Table 2 shows a summary of the actual and provisional amounts of non-pursuable debt.

Table 2: Summary of non-pursuable debt for small business (\$ million)

Description

2015–16

2016–17

2017–18

2018–19

2019–20

2020–21

Actual non-pursuable debt

214

135

75

33

13

13

Provisional non-pursuable debt

127

207

266

309

329

329

Total non-pursuable debt

342

342

342

342

342

342

## Step 4: Estimate gross gap

Next, we add the results of steps 1 to 3 to arrive at the gross gap estimate.

## Step 5: Estimate net gap

We deduct compliance outcomes and voluntary disclosure amounts from the gross gap in step 4 to arrive at the net gap estimate.

Because it can take up to 4 years to complete all compliance results, we use a provision in the 4 most recent years to reflect our expected final amendments. Where actual results are higher than this provision, we reflect the actual amendments present.

## Step 6: Estimate the theoretical liability

We determine the expected collections by adding compliance outcomes and voluntary disclosures to the tax voluntarily reported and paid amount. We then add the net gap to the expected collections amount to estimate the theoretical tax liability.

## Summary of estimation process

Table 3 shows the dollar value in millions at steps 1 to 6.2 for the individuals in business element. Steps 6.3 and 6.4 show percentage figures for the gross and net gaps.

Table 3: Applying the methodology – individuals in business element (\$ million)

Step

Description

2015–16

2016–17

2017–18

2018–19

2019–20

2020–21

1.1

Estimate unreported amounts for sample and extrapolate to population (\$m)

4,934

5,637

5,444

6,930

6,177

6,919

1.2

Apply estimate for people outside the system (\$m)

1,048

1,176

1,441

1,855

1,759

1,662

2.1

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

3,215

3,566

3,642

4,585

4,127

4,532

2.2

Apply estimate for hidden wages (\$m)

522

531

566

598

644

764

3

213

213

213

213

213

213

4

equals Gross gap (\$m)

9,932

11,122

11,306

14,181

12,921

14,090

5.1

subtract Compliance outcomes and voluntary disclosures (\$m)

1,041

973

893

893

893

893

5.2

equals Net gap (\$m)

8,891

10,149

10,413

13,288

12,028

13,197

6.1

66,169

67,157

71,067

73,133

75,145

84,706

6.2

equals Theoretical tax liability (\$m)

75,060

77,306

81,480

86,421

87,173

97,903

6.3

Gross gap (%)

13.2

14.4

13.9

16.4

14.8

14.4

6.4

Net gap (%)

11.8

13.1

12.8

15.4

13.8

13.5

Table 4 shows the dollar value in millions at steps 1 to 6.2 for the small companies element. Steps 6.3 and 6.4 show percentage figures for the gross and net gaps.

Table 4: Applying the methodology – small companies element (\$ million)

Step

Description

2015–16

2016–17

2017–18

2018–19

2019–20

2020–21

1.1

Estimate unreported amounts for sample and extrapolate to population (\$m)

1,403

1,200

1,305

1,127

1,134

1,454

1.2

Apply estimate for people outside the system (\$m)

n/a

n/a

n/a

n/a

n/a

n/a

2.1

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

562

463

523

444

466

514

2.2

Apply estimate for hidden wages (\$m)

n/a

n/a

n/a

n/a

n/a

n/a

3

129

129

129

129

129

129

4

equals Gross gap (\$m)

2,094

1,792

1,957

1,699

1,728

2,097

5.1

subtract Compliance outcomes and voluntary disclosures (\$m)

149

129

250

229

202

202

5.2

equals Net gap (\$m)

1,945

1,663

1,707

1,471

1,526

1,895

6.1

13,130

13,585

14,873

14,723

14,869

17,970

6.2

equals Theoretical tax liability (\$m)

15,075

15,249

16,580

16,194

16,395

19,865

6.3

Gross gap (%)

13.9

11.8

11.8

10.5

10.5

10.6

6.4

Net gap (%)

12.9

10.9

10.3

9.1

9.3

9.5

Find out more about our research methodology, data sources and analysis for creating our tax gap estimates.

## Limitations

The following caveats and limitations apply when interpreting this tax gap estimate:

• The 2021 preliminary estimate uses outcomes finalised to date from the 2019 and 2020 random enquiry program samples. We will update future estimates with additional outcomes from the 2020 and 2021 samples.
• The 2018, 2019 and 2020 sample years were reduced due to the need to support the community during natural disasters and COVID-19.
• The precision of our estimate is limited by the sample size of the random enquiry program. By using an ongoing bundled sample, we seek to maintain suitable confidence intervals over time.
• We are working to develop non-detection estimates for random enquiry programs in the Australian environment. In the interim, we use the midpoint estimate for credible international estimates used by the United Kingdom and United States.
• Estimates for the tax impact of people outside the system are difficult to estimate. This estimate will always be subject to significant uncertainty.
• There is no independent data source that can provide a credible or reliable macroeconomic-based estimate (unlike for indirect taxes).

### Accounting for non-detection in the gap

Our ability to discover the full extent of non-compliance is different across the population. Applying uniform non-detection uplifts to the estimate would exaggerate the size of the final gap. A different uplift is applied to the deduction labels of small business tax returns.

The impact of non-detection across the tax gap is also different across the 2 populations represented in this estimate:

Within the individuals in business population, the following 3 areas require an estimate to account for non-detection:

• deductions

The uplift for business income not detected forms the largest component of non-detection. This recognises the difficulty in detecting omitted income where little or no third-party reporting systems are available.

We apply uplifts to observed results based on the midpoint of international ranges. With increased third-party reporting and data matching being introduced, the uplift factors will be reviewed over the next 12 months.

Non-detection of deductions in the individuals in business population is applied differently. This is because there is no incentive for taxpayers to under-claim deductions on their tax return. Therefore, the uplift for non-detection for deductions is confined to the capacity to detect errors in tax returns where deductions have been claimed.

Actual wages received by individuals in business can be difficult to validate in a random enquiry program. We used a macro estimate based on the hidden wages element used in the pay as you go (PAYG) withholding and super guarantee gap estimates.

An estimate for wages not detected in the random enquiry program and for people operating outside the system was reconciled to the hidden wages analysis undertaken in the PAYG withholding gap estimate. The result provides an estimate for wages not detected in the individuals in business population within the small business income tax gap population.

#### Small companies

The small companies element has only 2 areas that require an estimate to account for non-detection:

• deductions.

Like the uplift for individuals in business, the uplift for small company business income not detected forms the largest component of our estimate.

We recognise it is difficult to detect omitted income for small companies. This is where no, or limited, third-party reporting systems are available. We apply uplifts to observed results based on the midpoint of international ranges. With increased third-party reporting and data matching being introduced, we will review the uplift factors over the next 12 months.

Similar to the individuals in business population, non-detection of deductions and other issues in the small companies population is applied differently. This is because there is no incentive for taxpayers to under-claim deductions on their tax return. Therefore, the uplift for non-detection for deductions is confined to the capacity to detect errors in tax returns where deductions have been claimed.

#### Combined impact of non-detection

Table 5 shows a summary of the combined impact of non-detection on the small business income tax gap.

Table 5: Summary of the impact of non-detection on the gap (\$ million)

Source of non-detection

2015–16

2016–17

2017–18

2018–19

2019–20

2020–21

3,716

3,962

4,105

4,958

4,531

4,968

Deductions and other issues

61

67

60

70

63

78

Hidden wages

522

531

566

598

644

764

Total non-detection

4,299

4,560

4,731

5,627

5,238

5,810

### Accounting for the shadow economy

For tax gap purposes we focus on the shadow economy definition in the Shadow Economy Taskforce final report. This is based on Organisation for Economic Co-operation and Development (OECD) definitions of underground production and illegal activityExternal Link.

The OECD definition of underground production is key. It covers activities that are productive and legal but are deliberately concealed to avoid paying taxes or complying with regulations (or both). Therefore, the shadow economy element in this gap is related to underground production.

The shadow economy estimate within the small business income tax gap is also separated into the calculations for individuals in business, and companies. Within these 2 broad categories, there are 3 main elements:

• deliberate non-disclosure of business income and deliberate over-claiming of business deductions
• hidden wages, predominantly individuals in the population receiving cash-in-hand wages – we estimate this using a top-down model approach drawing on random enquiry observations
• people outside the system – where we use an ABS Census comparison approach.

When analysing the reasons for non-compliance, we sought to identify aspects of behaviour that indicated a deliberate intention to hide business activity.

We added a component to the individuals in business population gap estimate that is not included in non-detection, which is to account for people outside the tax system. This element seeks to estimate the amount of omitted income from these people. To quantify this element, we assumed that the incidence and relative magnitude of income non-compliance in the random enquiry sample is also representative of people outside the system.

The tax effect of the shadow economy for small business in 2020–21 is estimated to be \$10.4 billion. The majority of this, \$7.9 billion, is associated with under-reported business income and over-claimed business deductions.

We outline the impacts of the shadow economy on the community and how we address them in tax and small business.

Table 6 shows a summary of the shadow economy impact on the gross tax gap. This amount has increased from 56% of the overall gross gap in 2015–16 to 64% in 2020–21. For this estimate we assume the same percentage applies to the net gap.

Table 6: Summary of the impact of the shadow economy on the gross gap (\$ million)

Element

2015–16

2016–17

2017–18

2018–19

2019–20

2020–21

Hidden wages

522

531

566

598

644

764

People outside the system

1,048

1,176

1,441

1,855

1,759

1,662

5,165

4,786

4,715

6,560

7,035

7,946

6,735

6,493

6,721

9,013

9,438

10,372

## 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 many reasons, including:

• improvements in methodology
• revisions to data

We refreshed our previous estimate to consider updates in underlying data and refinements to the methodology, so the results between years remain comparable.

The increase in the updated estimates for 2018–19 and 2019–20 is mainly due to additional completed sample cases since the previous publication. The observed variability from year to year is within the expected statistical variability and so is not indicative of a decrease in compliance.

Figure 5 shows the net gap from our current model compared to the previous estimate, undertaken in 2022.

Figure 5: Current and previous small business net tax gap estimates, 2015–16 to 2020–21

The data is set out as a percentage in Table 7.

Table 7: Current and previous small business net tax gap estimates, 2015–16 to 2020–21

2015–16

2016–17

2017–18

2018–19

2019–20

2020–21

2023 Program

12.0%

12.8%

12.4%

14.4%

13.1%

12.8%

2022 Program

12.6%

13.2%

12.6%

12.7%

11.6%

n/a

2021 Program

12.5%

12.5%

11.7%

12.7%

n/a

n/a

2020 Program

12.2%

12.5%

11.5%

n/a

n/a

n/a

2019 Program

12.5%

n/a

n/a

n/a

n/a

n/a

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