ato: Australian Taxation Office Data

Description

Tidy R access to Australian Taxation Office ('ATO') Taxation Statistics and related datasets via the 'data.gov.au' CKAN API.

Main function families

• ato_catalog(), ato_download(): discovery and generic resource access.

• ato_individuals(), ato_individuals_postcode(), ato_individuals_occupation(): individual tax return items. ato_individuals_postcode() accepts a vector of years for time-series panels.

• ato_companies(): company tax across Tables 1-9 (snapshot, by size, by entity type, by industry, by industry-and-size, by sub-industry, by taxable status, by source, by expenses).

• ato_super_funds(): APRA-regulated super funds and SMSFs.

• ato_top_taxpayers(): Corporate Tax Transparency release (Income tax or PRRT sheet).

• ato_gst(), ato_industry(): GST and industry aggregates.

• ato_tax_gaps(): annual Tax Gap estimates across tax heads.

• ato_rdti(): Research and Development Tax Incentive claimants.

• ato_irpd(): International Related Party Dealings (BEPS / transfer pricing).

• ato_excise(): excise rates, fuel tax credits, beer and spirits clearances.

• ato_sme_benchmarks(): Small Business Benchmarks.

• ato_help(): HELP / AASL / VSL student-loan statistics.

• ato_cite(): citation helper (BibTeX, APA, plain text).

• ato_cache_info(), ato_clear_cache(): cache management.

Caveats for users of ATO data

Nominal AUD. All monetary values are in nominal Australian dollars of the reporting year. Use inflateR::inflate() or ABS CPI series for real-term comparisons across years.

Fiscal year convention. "2022-23" refers to the Australian income year from 1 July 2022 to 30 June 2023.

Confidentiality suppression. The ATO replaces values with "np" (not published), "*", "\u2021", or similar tokens when fewer than ten taxpayers (or fewer than 50 returns for postcode data) fall in a cell. The package coerces these to NA so numeric columns stay numeric. Summing a column with na.rm = TRUE is the correct default; be explicit about what you do with suppressed cells in any distributional analysis.

Schema drift. Column names and table numbering shift year-to-year (e.g. occupation data has been T13, T14, T15 in different years). The package cleans names to snake_case on ingestion but does not normalise schemas across years. A cross-year join requires explicit column mapping.

Classification migration. ANZSIC 2006 to ANZSIC 2020 and ANZSCO 2013 to ANZSCO 2021 recodes affect industry and occupation series. Users stacking across releases should inspect the classification version used in each release.

Silent revisions. CKAN metadata_modified timestamps change without a version bump when the ATO republishes a corrected file. Run ato_clear_cache() to force a refresh.

Microdata is out of scope. The 2% Individual Sample File is distributed separately through Hugh Parsonage's taxstats DRAT repo. ALife (the ATO Longitudinal Information Files) is restricted-access microdata via the ATO DataLab and requires a researcher application; it is not provided by this package.

Citation. Use ato_cite() on any returned ato_tbl to produce a Treasury-grade footnote, APA reference, or BibTeX entry with the source URL, licence, retrieval date, and title.

Data source

Taxation Statistics are published annually by the ATO on https://www.ato.gov.au/about-ato/research-and-statistics/ and mirrored at https://data.gov.au/data/organization/australiantaxationoffice. Most datasets are licensed under Creative Commons Attribution 2.5 Australia; Corporate Tax Transparency and the Voluntary Tax Transparency Code are CC BY 3.0 Australia.

Author(s)

Maintainer: Charles Coverdale charlesfcoverdale@gmail.com

See Also

Useful links:

• https://charlescoverdale.github.io/ato/

• https://github.com/charlescoverdale/ato

• Report bugs at https://github.com/charlescoverdale/ato/issues

Inspect the local ato cache

Description

Inspect the local ato cache

Usage

ato_cache_info()

Value

A list with dir, n_files, size_bytes, size_human, and files.

See Also

Other configuration: ato_clear_cache(), ato_meta()

Examples

op <- options(ato.cache_dir = tempdir())
ato_cache_info()
options(op)

ATO dataset catalogue

Description

Returns a summary of all datasets published by the Australian Taxation Office on data.gov.au. Each row is a CKAN "package" with an id (slug), title, licence, modification date, and resource count.

Usage

ato_catalog(q = NULL)

Arguments

Value

An ato_tbl with one row per dataset.

Source

'data.gov.au' CKAN endpoint https://data.gov.au/data/organization/australiantaxationoffice.

See Also

Other discovery: ato_charities(), ato_cite(), ato_download(), ato_excise(), ato_fbt(), ato_help(), ato_irpd(), ato_payg(), ato_rdti(), ato_sme_benchmarks(), ato_tax_gaps(), ato_top_taxpayers(), ato_vttc()

Examples

op <- options(ato.cache_dir = tempdir())
try({
  cat <- ato_catalog()
  head(cat[, c("id", "title", "licence")])
})
options(op)

Charity and deductible gift recipient data

Description

Returns the ATO's data on income tax-exempt entities and Deductible Gift Recipients (DGRs): entity counts, income, expenditure, and gift deductions by charity subtype and state. Covers public benevolent institutions, health promotion charities, environmental organisations, and other DGR categories.

Usage

ato_charities(year = "latest")

Arguments

Details

Used by Treasury (charity tax expenditure estimates), researchers studying the non-profit sector, and civil society policy analysts.

Value

An ato_tbl. Monetary values in nominal AUD.

Source

Australian Taxation Office charity statistics on data.gov.au. Licensed CC BY 2.5 AU.

See Also

Other discovery: ato_catalog(), ato_cite(), ato_download(), ato_excise(), ato_fbt(), ato_help(), ato_irpd(), ato_payg(), ato_rdti(), ato_sme_benchmarks(), ato_tax_gaps(), ato_top_taxpayers(), ato_vttc()

Examples

op <- options(ato.cache_dir = tempdir())
try({
  ch <- ato_charities(year = "2021-22")
  head(ch)
})
options(op)

Cite an ato_tbl (or URL) in BibTeX and plain-text form

Description

Returns a citation suitable for footnotes, papers, and Treasury-grade briefs. Uses the provenance attributes attached to every ato_tbl: source URL, licence, retrieval date, title, snapshot pin, and SHA-256 digest.

Usage

ato_cite(x, style = c("text", "bibtex", "apa"), doi = NULL)

Arguments

Details

BibTeX output includes the SHA-256 digest (first 12 hex chars) and snapshot pin (when set via ato_snapshot()) in the note field, which is what research reviewers need to verify the provenance of a downstream result.

Value

A character string. For style = "bibtex", a complete ⁠@misc{}⁠ entry.

See Also

Other discovery: ato_catalog(), ato_charities(), ato_download(), ato_excise(), ato_fbt(), ato_help(), ato_irpd(), ato_payg(), ato_rdti(), ato_sme_benchmarks(), ato_tax_gaps(), ato_top_taxpayers(), ato_vttc()

Examples

x <- data.frame(a = 1)
x <- structure(x,
  ato_source = "https://data.gov.au/data/dataset/example.xlsx",
  ato_licence = "CC BY 2.5 AU",
  ato_retrieved = as.POSIXct("2026-04-23 00:00:00", tz = "UTC"),
  ato_title = "ATO individuals 2022-23",
  ato_sha256 = "abc123def456",
  ato_snapshot_date = "2026-04-23",
  class = c("ato_tbl", "data.frame"))

ato_cite(x)
ato_cite(x, style = "bibtex")
# DOI style: supply any minted DOI (Zenodo, DataCite, etc.).
# The placeholder below is illustrative only.
ato_cite(x, style = "apa", doi = "10.5281/zenodo.XXXXXXXX")

Clear the ato cache

Description

Deletes all locally cached files. The next call to any data function will re-download.

Usage

ato_clear_cache()

Value

Invisibly returns NULL.

See Also

Other configuration: ato_cache_info(), ato_meta()

Examples

op <- options(ato.cache_dir = tempdir())
ato_clear_cache()
options(op)

Company Taxation Statistics

Description

Returns the annual Company Taxation Statistics tables. The Company release ships tables covering entity type, turnover band, industry, taxable status, source of income, and expense deductions. Pick the table that matches your question:

Usage

ato_companies(
  year = "latest",
  table = c("industry", "snapshot", "key_items_by_size", "entity_type",
    "industry_by_size", "sub_industry", "taxable_status", "source", "expenses"),
  industry = NULL
)

Arguments

Details

• snapshot (T1): aggregate counts, total income, net tax across all companies (~1m entities)

• key_items_by_size (T2): net tax by company size band

• entity_type (T3): split by public/private/co-operative

• industry (T4, default): key items by 2-digit ANZSIC subdivision

• industry_by_size (T5): industry x turnover band

• sub_industry (T6): 4-digit ANZSIC class detail

• taxable_status (T7): items by taxable status

• source (T8): source of income

• expenses (T9): expense and deduction categories

Classification break. Releases from 2022-23 onwards use ANZSIC 2020; earlier releases use ANZSIC 2006. A warning is emitted when the requested year(s) are at or after this boundary, or when a multi-year request spans it.

Value

An ato_tbl. Monetary values in nominal AUD of the reporting year.

Source

Australian Taxation Office Taxation Statistics Company Tables. Licensed CC BY 2.5 AU.

References

Australian Taxation Office (annual). Taxation Statistics: Company tables explanatory notes. Methodology notes on lodgement cut-off, entity-type definitions, and turnover-band thresholds. Accessible from https://www.ato.gov.au/about-ato/research-and-statistics/in-detail/taxation-statistics/.

Australian Bureau of Statistics (2020). Australian and New Zealand Standard Industrial Classification (ANZSIC), 2006 revision with 2020 update. Catalogue 1292.0.

Examples

op <- options(ato.cache_dir = tempdir())
try({
  s <- ato_companies(year = "2022-23", table = "snapshot")
  head(s)
  m <- ato_companies(year = "2022-23", industry = "mining")
  head(m)
  # Multi-year industry panel
  panel <- ato_companies(year = c("2021-22", "2022-23"))
})
options(op)

ATO compliance program outcomes

Description

Returns the ATO's annual compliance program outcomes: audit yield (tax raised from audits), settled disputes, collectable debt, and compliance cost recovery. These appear in the ATO annual report and related data.gov.au releases.

Usage

ato_compliance(year = "latest", metric = c("overview", "debt", "audit"))

Arguments

Value

An ato_tbl.

Source

Australian Taxation Office annual report data. Licensed CC BY 3.0 AU.

See Also

Other specialist: ato_division293(), ato_fuel_tax_credits(), ato_international(), ato_medicare_levy(), ato_prrt(), ato_rba(), ato_state_tax(), ato_tax_expenditures(), ato_whm()

Examples

op <- options(ato.cache_dir = tempdir())
try(ato_compliance(year = "2022-23", metric = "debt"))
options(op)

Load a bundled ATO crosswalk table

Description

Returns one of the bundled classification crosswalks. Used internally by ato_harmonise() and available for user-level panel work.

Usage

ato_crosswalk(name = c("anzsic", "anzsco", "postcode", "cpi", "erp", "budget"))

Arguments

Details

Bundled crosswalks (at division/major-group level):

• "anzsic": ANZSIC 2006 to 2020 (19 divisions, complete)

• "anzsco": ANZSCO 2013 to 2021 (8 major groups, complete)

• "postcode": postcode first-digit to state anchors

• "cpi": ABS CPI annual, base 2011-12 = 1.0

• "erp": ABS Estimated Resident Population, June 30 annual

• "budget": Final Budget Outcome reference totals

For 4-digit ANZSIC, 6-digit ANZSCO, or postcode-to-SA2/LGA/CED crosswalks, fetch the full tables from ABS. The bundled division/major-group level covers cross-year ATO Taxation Statistics joins at the industry headings used in all ATO tables.

Value

A data frame.

References

Australian Bureau of Statistics (2006). Australian and New Zealand Standard Industrial Classification (ANZSIC). Catalogue 1292.0.

Australian Bureau of Statistics (2020). ANZSIC 2006 Update, cat. 1292.0, divisional structure. Used by ATO Taxation Statistics from 2022-23.

Australian Bureau of Statistics (2013). Australian and New Zealand Standard Classification of Occupations (ANZSCO). Catalogue 1220.0.

Australian Bureau of Statistics (2022). ANZSCO Revised Edition, cat. 1220.0. Used by ATO Taxation Statistics from 2022-23 onward.

See Also

Other harmonisation: ato_deflate(), ato_harmonise(), ato_per_capita(), ato_reconcile(), ato_schema_map(), ato_to_taxstats()

Examples

ato_crosswalk("anzsic")
ato_crosswalk("cpi")

Deflate nominal AUD to real AUD

Description

Converts a numeric vector of nominal AUD figures indexed by financial year to real AUD of a chosen base year using the bundled ABS CPI series (annual, All Groups Australia, 2011-12 = 1.0). For the user's inflateR workflow in non-Australian contexts, bundle a matching CPI series and call this with a custom ⁠cpi =⁠ argument.

Usage

ato_deflate(x, year, base = "2022-23", cpi = NULL)

Arguments

Details

Uses proportional (Laspeyres-style) adjustment: real = nominal \times (CPI_{base} / CPI_{source}). The bundled CPI is the ABS annual All Groups Australia index published in cat. 6401.0, rebased so that 2011-12 = 1.000. This is the standard rebasing used in most Australian time-series work and is consistent with ABS System of National Accounts methodology (cat. 5204.0).

The formula is exact for a chain-linked index after 1949 (when the ABS CPI was introduced) and approximate for earlier values that rely on Commonwealth Statistician retail-price series. Use a custom ⁠cpi =⁠ argument if you need a different deflator (e.g. GDP deflator, wage price index, or industry-specific PPI).

Value

Numeric vector of real AUD values in base-year prices.

References

Australian Bureau of Statistics (2024). Consumer Price Index, Australia: Concepts, Sources and Methods. Catalogue 6461.0.

Australian Bureau of Statistics (2024). Consumer Price Index, Australia. Catalogue 6401.0.

Diewert, W.E. (1998). "Index Number Issues in the Consumer Price Index." Journal of Economic Perspectives, 12(1), 47-58. doi:10.1257/jep.12.1.47

See Also

Other harmonisation: ato_crosswalk(), ato_harmonise(), ato_per_capita(), ato_reconcile(), ato_schema_map(), ato_to_taxstats()

Examples

ato_deflate(c(100, 100, 100),
            year = c("2012-13", "2017-18", "2022-23"),
            base = "2022-23")

Prepare a Zenodo deposit payload for the session manifest

Description

Builds the JSON metadata payload Zenodo expects for a data deposit, using the current ato_manifest() and the snapshot pin set via ato_snapshot(). The function does NOT upload by default; it returns the payload and saved manifest path so you can inspect before calling with upload = TRUE.

Usage

ato_deposit_zenodo(
  title = NULL,
  description = NULL,
  creators = list(list(name = "Anonymous")),
  keywords = c("ATO", "taxation", "Australia", "reproducibility"),
  upload = FALSE,
  sandbox = FALSE,
  token = Sys.getenv("ZENODO_TOKEN")
)

Arguments

Details

To upload, supply a Zenodo personal access token via the ZENODO_TOKEN environment variable (or the token argument). Tokens can be generated at https://zenodo.org/account/settings/applications/.

Value

A list with payload (the JSON metadata), manifest_path (where the CSV manifest was staged), and if upload = TRUE, deposit_id, doi_prereserve, and url.

See Also

Other reproducibility: ato_manifest(), ato_manifest_clear(), ato_manifest_write(), ato_sha256(), ato_snapshot()

Examples

ato_snapshot("2026-04-24")
ato_deposit_zenodo(
  title = "ATO data snapshot for working paper v1",
  creators = list(list(name = "Coverdale, Charles")),
  upload = FALSE
)

Division 293 tax assessments (high-income super contributions)

Description

Returns Division 293 tax data: number of assessments, average Division 293 liability, and distribution by income band. Division 293 applies an extra 15% tax on concessional super contributions for individuals with combined income plus low-tax super contributions above AUD 250,000. Central to retirement-income reform analysis (e.g. Grattan's "Better Super" proposals).

Usage

ato_division293(year = "latest")

Arguments

Details

Published as part of the Individuals Taxation Statistics (Table 3b in recent releases).

Value

An ato_tbl.

Source

Australian Taxation Office Taxation Statistics Individuals. Licensed CC BY 2.5 AU.

References

Commonwealth of Australia. Income Tax Assessment Act 1997, Division 293. Extra 15 per cent tax on concessional super contributions for high-income earners.

Daley, J., Coates, B. and Wood, D. (2018). Money in retirement: more than enough. Grattan Institute. Uses Division 293 distributional data in reform analysis.

See Also

Other specialist: ato_compliance(), ato_fuel_tax_credits(), ato_international(), ato_medicare_levy(), ato_prrt(), ato_rba(), ato_state_tax(), ato_tax_expenditures(), ato_whm()

Examples

op <- options(ato.cache_dir = tempdir())
try(ato_division293(year = "2022-23"))
options(op)

Download a resource from an ATO dataset

Description

Low-level helper for arbitrary CKAN resources. Resolves the package by id (slug) and picks the first resource matching pattern, or the first resource if pattern is NULL.

Usage

ato_download(
  id,
  pattern = NULL,
  parse = c("auto", "csv", "xlsx", "none"),
  sheet = 1
)

Arguments

Value

Either a file path (parse = "none") or an ato_tbl.

See Also

Other discovery: ato_catalog(), ato_charities(), ato_cite(), ato_excise(), ato_fbt(), ato_help(), ato_irpd(), ato_payg(), ato_rdti(), ato_sme_benchmarks(), ato_tax_gaps(), ato_top_taxpayers(), ato_vttc()

Examples

op <- options(ato.cache_dir = tempdir())
try({
  cat <- ato_download("corporate-transparency",
                      pattern = "2023",
                      parse = "csv")
})
options(op)

Excise and fuel tax credit rates and clearances

Description

Returns ATO excise data, covering four sub-releases:

• beer : beer clearances summary (volumes by product class)

• spirits : spirits and other excisable beverages clearances

• excise_rates : historical excise rate schedule (all excise categories, quarterly indexed rates)

• ftc_rates : historical Fuel Tax Credit rates

Usage

ato_excise(table = c("excise_rates", "ftc_rates", "beer", "spirits"))

Arguments

Value

An ato_tbl. Rates are in AUD per litre (or per kg for tobacco); volumes are in megalitres or similar.

Source

Australian Taxation Office excise data. Licensed CC BY 2.5 AU.

References

Commonwealth of Australia. Excise Act 1901; Excise Tariff Act 1921; Fuel Tax Act 2006.

Australian Taxation Office (annual). Excise data: methodology and indexation notes. Excise rates are indexed to the Consumer Price Index twice a year (February and August) for most commodities.

Productivity Commission (2016). Migrant Intake into Australia (for tobacco excise distributional analysis); Harmful Drinking inquiry (for alcohol excise distributional analysis).

See Also

Other discovery: ato_catalog(), ato_charities(), ato_cite(), ato_download(), ato_fbt(), ato_help(), ato_irpd(), ato_payg(), ato_rdti(), ato_sme_benchmarks(), ato_tax_gaps(), ato_top_taxpayers(), ato_vttc()

Examples

op <- options(ato.cache_dir = tempdir())
try({
  rates <- ato_excise("excise_rates")
  head(rates)
})
options(op)

Fringe Benefits Tax statistics

Description

Returns the ATO's annual Fringe Benefits Tax (FBT) Taxation Statistics: employer counts, gross taxable value, FBT payable, and employee benefit counts by benefit type and industry. Used by Treasury, PBO, and researchers evaluating the FBT concession system (electric vehicles, remote area exemptions, novated leases).

Usage

ato_fbt(year = "latest")

Arguments

Value

An ato_tbl. Monetary values in nominal AUD.

Source

Australian Taxation Office FBT Taxation Statistics on data.gov.au. Licensed CC BY 2.5 AU.

References

Commonwealth of Australia. Fringe Benefits Tax Assessment Act 1986. Substantive FBT law; ATO rulings (TR series) elaborate taxable-value methodology.

Australian Taxation Office (annual). FBT explanatory notes. Definitions of reportable benefits, gross-up factors (Type 1 and Type 2), and otherwise-deductible rule.

Treasury (2022). Electric Car Discount Bill. Explanatory memorandum for the EV FBT exemption introduced 1 July 2022.

See Also

Other discovery: ato_catalog(), ato_charities(), ato_cite(), ato_download(), ato_excise(), ato_help(), ato_irpd(), ato_payg(), ato_rdti(), ato_sme_benchmarks(), ato_tax_gaps(), ato_top_taxpayers(), ato_vttc()

Examples

op <- options(ato.cache_dir = tempdir())
try({
  fbt <- ato_fbt(year = "2022-23")
  head(fbt)
})
options(op)

Fuel Tax Credits by industry and claim period

Description

Returns the Fuel Tax Credits scheme data: entitlement rates by fuel type, claim totals by industry. FTC is a major implicit fossil-fuel subsidy and is a key lens for decarbonisation policy cost-benefit analysis.

Usage

ato_fuel_tax_credits(year = "latest", by = c("industry", "fuel", "period"))

Arguments

Details

The ATO publishes FTC data as part of the Excise Data release and in standalone FTC tables.

Value

An ato_tbl.

Source

Australian Taxation Office Excise and Fuel Tax Credit data. Licensed CC BY 3.0 AU.

References

Commonwealth of Australia. Fuel Tax Act 2006; Fuel Tax (Consequential and Transitional Provisions) Act 2006.

Denniss, R. and Grudnoff, M. (2021). Fossil fuel subsidies in Australia. The Australia Institute. FTC-as- subsidy framing used in decarbonisation policy analysis.

Intergovernmental Panel on Climate Change (2022). Climate Change 2022: Mitigation of Climate Change. Chapter 13 covers fossil-fuel subsidy reform.

See Also

Other specialist: ato_compliance(), ato_division293(), ato_international(), ato_medicare_levy(), ato_prrt(), ato_rba(), ato_state_tax(), ato_tax_expenditures(), ato_whm()

Examples

op <- options(ato.cache_dir = tempdir())
try(head(ato_fuel_tax_credits(year = "latest", by = "industry")))
options(op)

GST and activity statement ratios

Description

Returns the Taxation Statistics GST tables (T1-T5) or the Activity Statement Ratios (A1-A5) for the requested year.

Usage

ato_gst(year = "latest", table = c("overview", "state", "industry", "ratios"))

Arguments

Value

An ato_tbl.

Source

Australian Taxation Office Taxation Statistics. Licensed CC BY 2.5 AU.

References

Australian Taxation Office (annual). Taxation Statistics: GST and Activity Statement Ratios explanatory notes.

Commonwealth of Australia. A New Tax System (Goods and Services Tax) Act 1999. Enabling legislation for the 10 per cent value-added tax introduced 1 July 2000.

Productivity Commission (2018). Horizontal Fiscal Equalisation. Background reference on the GST distribution formula across states.

See Also

Other gst: ato_industry()

Examples

op <- options(ato.cache_dir = tempdir())
try({
  g <- ato_gst(year = "2022-23", table = "industry")
  head(g)
})
options(op)

Harmonise column names in a multi-year ATO panel

Description

ATO renames columns across annual releases; a stacked panel from ato_individuals_postcode(year = c("2020-21", "2021-22")) may have inconsistent names like total_income vs total_income_or_loss. ato_harmonise() renames columns to the first variant in ATO_COL_VARIANTS so panels are join-ready.

Usage

ato_harmonise(df)

Arguments

Details

Unknown columns are left alone. Columns that collide after renaming (because two variants map to the same canonical name) emit a warning; the first column wins.

Value

A data frame with harmonised names. ato_tbl class and provenance attributes are preserved.

See Also

Other harmonisation: ato_crosswalk(), ato_deflate(), ato_per_capita(), ato_reconcile(), ato_schema_map(), ato_to_taxstats()

Examples

df <- data.frame(postcode = "2000",
                 total_income_or_loss = 100,
                 state_territory = "NSW")
ato_harmonise(df)

Study and Training Support Loan data (HELP, AASL, VSL)

Description

Returns aggregate statistics on Australia's three main education-loan schemes:

• HELP (Higher Education Loan Program, ~3m borrowers, AUD 80bn+ outstanding debt)

• AASL (Australian Apprenticeship Support Loans, previously Trade Support Loans)

• VSL (VET Student Loans, vocational education loans)

Usage

ato_help(scheme = c("help", "aasl", "vsl"))

Arguments

Details

Headline covers: new loans by income range, outstanding debt by age and gender, repayment rates, median debt on entry. Used by Treasury (PBO costings of HELP indexation changes) and education policy researchers.

Value

An ato_tbl. All dollar values in nominal AUD.

Source

Australian Taxation Office Study and Training Support Loans statistics. Licensed CC BY 2.5 AU.

References

Commonwealth of Australia. Higher Education Support Act 2003; VET Student Loans Act 2016.

Australian Department of Education (annual). Higher Education Statistics: HELP statistics collection.

Norton, A. and Cherastidtham, I. (2018). Mapping Australian higher education. Grattan Institute. Methodology reference for HELP repayment projections.

See Also

Other discovery: ato_catalog(), ato_charities(), ato_cite(), ato_download(), ato_excise(), ato_fbt(), ato_irpd(), ato_payg(), ato_rdti(), ato_sme_benchmarks(), ato_tax_gaps(), ato_top_taxpayers(), ato_vttc()

Examples

op <- options(ato.cache_dir = tempdir())
try({
  help <- ato_help(scheme = "help")
  head(help)
})
options(op)

Individual Taxation Statistics snapshot

Description

Returns the Individuals Table 1 snapshot: aggregate counts, total income, taxable income, tax payable, and deductions across all individual returns (roughly 14 million per year). The snapshot is the headline table; for finer cuts use the dedicated functions:

• ato_individuals_postcode() for geographic breakdowns,

• ato_individuals_occupation() for occupation × sex × income-range detail, or

• ato_download() with a custom pattern for specific Tables 2 to 27 (age, sex, state, industry, source of income, deductions, offsets, CGT, non-residents).

Usage

ato_individuals(year = "latest")

Arguments

Details

Monetary values are nominal AUD of the reporting year. Use inflateR::inflate() or the ABS CPI series if you need real-term comparisons.

Value

An ato_tbl with one row per aggregate line-item and columns for count and amount in nominal AUD.

Source

Australian Taxation Office Taxation Statistics https://www.ato.gov.au/about-ato/research-and-statistics/. Licensed CC BY 2.5 AU.

See Also

Other individuals: ato_individuals_age(), ato_individuals_occupation(), ato_individuals_postcode(), ato_individuals_sex(), ato_individuals_state()

Examples

op <- options(ato.cache_dir = tempdir())
try({
  ind <- ato_individuals(year = "2022-23")
  head(ind)
})
options(op)

Individual tax data by age range

Description

Returns Taxation Statistics Individuals Table 2 (approximately): counts, total income, taxable income, and tax payable by age range and (usually) sex. Age ranges are 5-year bands for most of working life plus wider bands at the tails.

Usage

ato_individuals_age(year = "latest", sex = c("all", "male", "female"))

Arguments

Value

An ato_tbl.

Source

Australian Taxation Office Taxation Statistics Individuals. Licensed CC BY 2.5 AU.

References

Australian Taxation Office (annual). Taxation Statistics: Individuals explanatory notes. Age-range breakdowns use the taxpayer's reported date of birth at lodgement; sex is self-reported on the return.

See Also

Other individuals: ato_individuals(), ato_individuals_occupation(), ato_individuals_postcode(), ato_individuals_sex(), ato_individuals_state()

Examples

op <- options(ato.cache_dir = tempdir())
try(ato_individuals_age(year = "2022-23", sex = "female"))
options(op)

Individual tax data by occupation

Description

Returns the Individuals Table 14 (occupation by sex by taxable income range). Around 1,000 occupations classified by ANZSCO with aggregate counts, total income, taxable income, and tax payable. The ATO migrated from ANZSCO 2013 to ANZSCO 2021 across the 2022-23 release; cross-year joins on occupation name or code must account for the recode.

Usage

ato_individuals_occupation(
  year = "latest",
  occupation = NULL,
  sex = c("all", "male", "female", "m", "f")
)

Arguments

Details

Classification break. Releases from 2022-23 onwards use ANZSCO 2021; earlier releases use ANZSCO 2013. A warning is emitted when the requested year(s) are at or after this boundary, or when a multi-year request spans it.

Value

An ato_tbl with one row per occupation-sex-income combination. Multi-year queries add a year column. Monetary values in nominal AUD of the reporting year.

Source

Australian Taxation Office Taxation Statistics. Licensed CC BY 2.5 AU.

See Also

Other individuals: ato_individuals(), ato_individuals_age(), ato_individuals_postcode(), ato_individuals_sex(), ato_individuals_state()

Examples

op <- options(ato.cache_dir = tempdir())
try({
  occ <- ato_individuals_occupation(year = "2022-23",
                                    occupation = "economist")
  head(occ)
  # Multi-year panel
  panel <- ato_individuals_occupation(year = c("2021-22", "2022-23"),
                                      occupation = "nurse")
})
options(op)

Individual tax data by postcode

Description

Returns the Individuals Table 6 (or standalone postcode dataset): taxable income, tax payable, and return counts by 4-digit postcode. Headline dataset for income-distribution journalism.

Usage

ato_individuals_postcode(year = "latest", state = NULL, postcode = NULL)

Arguments

Details

Privacy suppression. The ATO suppresses postcodes with fewer than 50 returns; those cells are returned as NA after parsing (the package maps "np", "*", and similar tokens to NA so numeric columns stay numeric). Small or remote postcodes will be silently missing from the output.

Monetary values are nominal AUD of the reporting year. Use inflateR::inflate() for real-term series.

Value

An ato_tbl with one row per postcode (or per postcode per year for multi-year queries), including state, return count, total income, taxable income, and tax payable. Schema drifts year to year (SA3/SA4 columns present from 2017 onwards).

Source

Australian Taxation Office Taxation Statistics postcode release. Licensed CC BY 2.5 AU.

References

Atkinson, A.B. and Leigh, A. (2007). "The Distribution of Top Incomes in Australia." Economic Record, 83(262), 247-261. doi:10.1111/j.1475-4932.2007.00412.x

Burkhauser, R.V., Hahn, M.H. and Wilkins, R. (2015). "Measuring top incomes using tax record data: a cautionary tale from Australia." Journal of Economic Inequality, 13(2), 181-205. doi:10.1007/s10888-014-9281-z

See Also

Other individuals: ato_individuals(), ato_individuals_age(), ato_individuals_occupation(), ato_individuals_sex(), ato_individuals_state()

Examples

op <- options(ato.cache_dir = tempdir())
try({
  # Single year
  p <- ato_individuals_postcode(year = "2022-23", state = "NSW")
  head(p)
  # Multi-year stack with year column
  panel <- ato_individuals_postcode(year = c("2020-21", "2021-22"),
                                    state = "NSW")
})
options(op)

Individual tax data by sex

Description

Returns counts and aggregates split by sex. Thin wrapper around the ATO "Selected items by sex" table.

Usage

ato_individuals_sex(year = "latest")

Arguments

Value

An ato_tbl.

Source

Australian Taxation Office Taxation Statistics Individuals. Licensed CC BY 2.5 AU.

References

Australian Taxation Office (annual). Taxation Statistics: Individuals explanatory notes. Age-range breakdowns use the taxpayer's reported date of birth at lodgement; sex is self-reported on the return.

See Also

Other individuals: ato_individuals(), ato_individuals_age(), ato_individuals_occupation(), ato_individuals_postcode(), ato_individuals_state()

Examples

op <- options(ato.cache_dir = tempdir())
try(ato_individuals_sex(year = "2022-23"))
options(op)

Individual tax data by state or territory

Description

Returns counts and aggregates by state. Thin wrapper around the ATO "Selected items by state/territory" table.

Usage

ato_individuals_state(year = "latest")

Arguments

Value

An ato_tbl.

Source

Australian Taxation Office Taxation Statistics Individuals. Licensed CC BY 2.5 AU.

References

Australian Taxation Office (annual). Taxation Statistics: Individuals explanatory notes. Age-range breakdowns use the taxpayer's reported date of birth at lodgement; sex is self-reported on the return.

See Also

Other individuals: ato_individuals(), ato_individuals_age(), ato_individuals_occupation(), ato_individuals_postcode(), ato_individuals_sex()

Examples

op <- options(ato.cache_dir = tempdir())
try(ato_individuals_state(year = "2022-23"))
options(op)

Industry aggregates across entity types

Description

Derived helper that returns an ANZSIC industry breakdown based on either individual, company, or all entities for the year.

Usage

ato_industry(
  year = "latest",
  entity = c("company", "individual", "all"),
  anzsic = NULL
)

Arguments

Value

An ato_tbl.

Source

Australian Taxation Office Taxation Statistics. Licensed CC BY 2.5 AU.

See Also

Other gst: ato_gst()

Examples

op <- options(ato.cache_dir = tempdir())
try({
  i <- ato_industry(year = "2022-23", entity = "company",
                    anzsic = "manufacturing")
  head(i)
})
options(op)

OECD Revenue Statistics comparison

Description

Fetches OECD Revenue Statistics for cross-country tax-to-GDP benchmarking. Returns tax revenue as percent of GDP by tax category. Use to contextualise Australian ATO aggregates in cross-country policy arguments (e.g. OECD average corporate tax-to-GDP, international ranks for personal income tax).

Usage

ato_international(country = "AUS", year = "latest")

Arguments

Details

Thin wrapper pointing users to ⁠readoecd::⁠ for full OECD API access; returns a minimal tax-to-GDP slice here for convenience.

Value

An ato_tbl with columns country, year, tax, pct_gdp.

Source

OECD Revenue Statistics https://www.oecd.org/tax/tax-policy/revenue-statistics.htm.

See Also

Other specialist: ato_compliance(), ato_division293(), ato_fuel_tax_credits(), ato_medicare_levy(), ato_prrt(), ato_rba(), ato_state_tax(), ato_tax_expenditures(), ato_whm()

Examples

op <- options(ato.cache_dir = tempdir())
try(ato_international(country = "AUS"))
options(op)

International Related Party Dealings (IRPD)

Description

Returns the ATO's International Related Party Dealings data, which captures intra-group cross-border payments and receivables reported by Australian corporate taxpayers. Core dataset for BEPS and transfer-pricing research, transfer pricing risk assessment, and multinational tax analysis.

Usage

ato_irpd(year = "latest", table = 1L)

Arguments

Details

The IRPD data is published as a separate CKAN package per income year (2019-20 through 2023-24). Each annual package contains three tables:

• Table 1 : IRPD totals from 2015-16 to the current year

• Table 2 : IRPDs by jurisdiction

• Table 3 : Index of chart data

Value

An ato_tbl. Monetary values in nominal AUD.

Source

Australian Taxation Office International Related Party Dealings release. Licensed CC BY 2.5 AU.

References

Organisation for Economic Co-operation and Development (2015). Transfer Pricing Documentation and Country-by-Country Reporting, Action 13: 2015 Final Report. OECD/G20 Base Erosion and Profit Shifting Project, Paris. doi:10.1787/9789264241480-en

Commonwealth of Australia. Income Tax Assessment Act 1997, Subdivision 815-B (Transfer Pricing); Multinational Anti-Avoidance Law (MAAL) and Diverted Profits Tax.

Australian Taxation Office (annual). International Dealings Schedule (IDS) instructions. Reporting framework underlying the IRPD dataset.

See Also

Other discovery: ato_catalog(), ato_charities(), ato_cite(), ato_download(), ato_excise(), ato_fbt(), ato_help(), ato_payg(), ato_rdti(), ato_sme_benchmarks(), ato_tax_gaps(), ato_top_taxpayers(), ato_vttc()

Examples

op <- options(ato.cache_dir = tempdir())
try({
  by_jurisdiction <- ato_irpd(year = "2023-24", table = 2)
  head(by_jurisdiction)
})
options(op)

Return the session manifest of fetched ATO datasets

Description

Every call to a data function (ato_individuals(), ato_companies(), etc.) appends one row to the session manifest, recording URL, dataset title, CKAN resource and package IDs where resolvable, SHA-256 of the cached file, size, retrieval timestamp, and the snapshot pin set via ato_snapshot(). Duplicate URLs within a session are deduplicated (last fetch wins).

Usage

ato_manifest(format = c("df", "yaml", "json"))

Arguments

Details

Attach the output to your paper's appendix, deposit it to Zenodo with ato_deposit_zenodo() to mint a DOI, or export with ato_manifest_write() for CI artefacts.

Value

A data frame, YAML string, or JSON string depending on format.

See Also

Other reproducibility: ato_deposit_zenodo(), ato_manifest_clear(), ato_manifest_write(), ato_sha256(), ato_snapshot()

Examples

op <- options(ato.cache_dir = tempdir())
ato_manifest_clear()
ato_snapshot("2026-04-24")
try(ato_individuals(year = "2022-23"))
ato_manifest()
options(op)

Clear the session manifest

Description

Clear the session manifest

Usage

ato_manifest_clear()

Value

Invisibly NULL. Useful at the top of a script when running repeatedly.

See Also

Other reproducibility: ato_deposit_zenodo(), ato_manifest(), ato_manifest_write(), ato_sha256(), ato_snapshot()

Examples

ato_manifest_clear()

Write the session manifest to a file

Description

Writes the manifest to a file in the requested format. Call at the end of an analysis script; commit the manifest alongside the paper for full reproducibility.

Usage

ato_manifest_write(path, format = c("auto", "csv", "yaml", "json"))

Arguments

Value

Invisibly, the absolute path to the written file.

See Also

Other reproducibility: ato_deposit_zenodo(), ato_manifest(), ato_manifest_clear(), ato_sha256(), ato_snapshot()

Examples

p <- tempfile(fileext = ".csv")
ato_manifest_clear()
ato_manifest_write(p)

Medicare Levy and Medicare Levy Surcharge

Description

Returns aggregate Medicare Levy and MLS data from Taxation Statistics Individuals. The 2% Medicare Levy is on most taxable income; MLS is an additional 1.0 to 1.5% on high-income earners without adequate private hospital cover. Used in private health insurance reform analysis.

Usage

ato_medicare_levy(year = "latest", component = c("levy", "surcharge"))

Arguments

Value

An ato_tbl.

Source

Australian Taxation Office Taxation Statistics Individuals. Licensed CC BY 2.5 AU.

References

Commonwealth of Australia. Medicare Levy Act 1986; A New Tax System (Medicare Levy Surcharge – Fringe Benefits) Act 1999.

Productivity Commission (2015). Efficiency in Health. Analysis of Medicare Levy and MLS distributional effects.

See Also

Other specialist: ato_compliance(), ato_division293(), ato_fuel_tax_credits(), ato_international(), ato_prrt(), ato_rba(), ato_state_tax(), ato_tax_expenditures(), ato_whm()

Examples

op <- options(ato.cache_dir = tempdir())
try(ato_medicare_levy(year = "2022-23", component = "surcharge"))
options(op)

Fetch CKAN metadata for an ATO dataset

Description

Returns structured metadata for any ATO dataset on data.gov.au: title, notes, licence, last-modified timestamp, resource count, and all resource URLs. Useful for detecting silent updates before clearing the cache, or for auditing what version of data you have.

Usage

ato_meta(x)

Arguments

Value

A list with elements:

• id: CKAN package slug

• title: human-readable title

• notes: dataset description (truncated to 400 chars)

• licence: licence title

• metadata_modified: ISO timestamp of last CKAN update

• n_resources: number of downloadable files

• resource_urls: character vector of all resource URLs

See Also

Other configuration: ato_cache_info(), ato_clear_cache()

Examples

op <- options(ato.cache_dir = tempdir())
try({
  # By package ID
  m <- ato_meta("taxation-statistics-2022-23")
  m$metadata_modified

  # From an ato_tbl
  tbl <- ato_individuals(year = "2022-23")
  ato_meta(tbl)
})
options(op)

PAYG withholding data

Description

Returns the ATO's Pay As You Go (PAYG) withholding data: employer counts, total withholding amounts, and employee counts by industry and state. Used by researchers studying labour market taxation, wage growth, and employer compliance.

Usage

ato_payg(year = "latest")

Arguments

Value

An ato_tbl. Monetary values in nominal AUD.

Source

Australian Taxation Office PAYG withholding data on data.gov.au. Licensed CC BY 2.5 AU.

See Also

Other discovery: ato_catalog(), ato_charities(), ato_cite(), ato_download(), ato_excise(), ato_fbt(), ato_help(), ato_irpd(), ato_rdti(), ato_sme_benchmarks(), ato_tax_gaps(), ato_top_taxpayers(), ato_vttc()

Examples

op <- options(ato.cache_dir = tempdir())
try({
  payg <- ato_payg(year = "2022-23")
  head(payg)
})
options(op)

Express an aggregate per capita using ABS ERP

Description

Express an aggregate per capita using ABS ERP

Usage

ato_per_capita(x, year, erp = NULL)

Arguments

Details

Divides the input by Estimated Resident Population at 30 June of the financial year's end (a stock measure). For flow-style measures where a mid-year-average population is preferable, substitute a custom ⁠erp =⁠ argument. ERP is ABS's preferred population-denominator concept for per-capita economic statistics (see cat. 3101.0 methodology).

Value

Numeric vector of per-capita values (same units as x per person).

References

Australian Bureau of Statistics (2024). National, State and Territory Population. Catalogue 3101.0.

See Also

Other harmonisation: ato_crosswalk(), ato_deflate(), ato_harmonise(), ato_reconcile(), ato_schema_map(), ato_to_taxstats()

Examples

# Income tax per person, 2022-23 FBO headline
ato_per_capita(316.4e9, "2022-23")

Petroleum Resource Rent Tax (PRRT) annual data

Description

Returns PRRT revenue and assessments. PRRT is a 40% tax on the profits of offshore petroleum projects; revenues are volatile and project-specific. Key dataset for resource-tax reform analysis.

Usage

ato_prrt(year = "latest")

Arguments

Value

An ato_tbl.

Source

Australian Taxation Office Taxation Statistics Company. Licensed CC BY 2.5 AU.

References

Commonwealth of Australia. Petroleum Resource Rent Tax Assessment Act 1987. Enabling legislation for the 40 per cent rent tax on offshore petroleum projects.

Callaghan, M. (2017). Review of the Petroleum Resource Rent Tax. Treasury-commissioned review; reference for PRRT-reform analysis.

See Also

Other specialist: ato_compliance(), ato_division293(), ato_fuel_tax_credits(), ato_international(), ato_medicare_levy(), ato_rba(), ato_state_tax(), ato_tax_expenditures(), ato_whm()

Examples

op <- options(ato.cache_dir = tempdir())
try(ato_prrt(year = "2022-23"))
options(op)

RBA Commonwealth receipts (H1 statistical table)

Description

Pointer to the RBA's H1 series on Commonwealth receipts for long-run time series. RBA compiles since 1959-60, filling gaps in ATO Taxation Statistics which start 1994-95.

Usage

ato_rba(series = c("receipts", "income_tax"))

Arguments

Details

The RBA publishes H1 as an XLSX with stable URL. This function fetches it and returns a tidy tibble.

Value

An ato_tbl.

Source

Reserve Bank of Australia Statistical Tables H1 https://www.rba.gov.au/statistics/tables/.

See Also

Other specialist: ato_compliance(), ato_division293(), ato_fuel_tax_credits(), ato_international(), ato_medicare_levy(), ato_prrt(), ato_state_tax(), ato_tax_expenditures(), ato_whm()

Examples

op <- options(ato.cache_dir = tempdir())
try(ato_rba(series = "receipts"))
options(op)

R&D Tax Incentive claimants

Description

Returns the annual "Report of data about Research and Development Tax Incentive entities": claimants, claimed expenditure, refundable and non-refundable tax offsets by industry and company size. Treasury and DISR use this series to evaluate the R&D Tax Incentive programme, which is the largest single element of Australia's business innovation policy (AUD 2 billion+ per year).

Usage

ato_rdti(year = "latest")

Arguments

Value

An ato_tbl with one row per entity (or aggregated cell, depending on the release schema). Monetary values in nominal AUD.

Source

Australian Taxation Office Research and Development Tax Incentive report. Licensed CC BY 2.5 AU.

References

Commonwealth of Australia. Income Tax Assessment Act 1997, Division 355 (Research and Development Tax Incentive).

Department of Industry, Science and Resources and Australian Taxation Office (annual). R&DTI Transparency Report. Jointly administered programme methodology.

Ferris, B., Finkel, A. and Fraser, J. (2016). Review of the R&D Tax Incentive. Australian Government review (the "Three Fs review") informing subsequent programme design.

Organisation for Economic Co-operation and Development (annual). R&D Tax Incentives Database. International comparator data for R&D tax expenditures.

See Also

Other discovery: ato_catalog(), ato_charities(), ato_cite(), ato_download(), ato_excise(), ato_fbt(), ato_help(), ato_irpd(), ato_payg(), ato_sme_benchmarks(), ato_tax_gaps(), ato_top_taxpayers(), ato_vttc()

Examples

op <- options(ato.cache_dir = tempdir())
try({
  rdti <- ato_rdti(year = "2022-23")
  head(rdti)
})
options(op)

Reconcile an aggregate against Commonwealth budget totals

Description

Compares a scalar (or data frame total) against the published Final Budget Outcome figure for the same year and revenue line. Useful as a sanity check on an ATO Taxation Statistics sum before reporting it in a paper or brief.

Usage

ato_reconcile(value, year, measure, sum_column = NULL)

Arguments

Details

Discrepancies between ATO Taxation Statistics aggregates and the Final Budget Outcome (FBO) are expected and meaningful:

• Taxation Statistics are based on assessments made by a cut-off date (usually October of the following calendar year) and may exclude late-lodging returns.

• FBO figures are cash-basis Commonwealth receipts; Taxation Statistics are accrual-basis tax assessed.

• GST, excise, and fuel credits have timing and refund effects that further distort the cash-vs-assessment gap.

A 1-3 per cent gap is consistent with the accrual-to-cash reconciliation Treasury publishes in the FBO statement of revenues; larger gaps warrant investigation. The bundled reference totals in inst/extdata/budget_reference_totals.csv are taken from the relevant FBO release, with the precise table cited in the source column of each row.

Value

A one-row data frame: measure, year, value_aud, reference_aud, diff_aud, pct_diff, source. Emits a warning if abs(pct_diff) > 0.05.

References

Commonwealth of Australia (various years). Final Budget Outcome. The Treasury, Canberra. https://budget.gov.au/content/fbo/index.htm

Australian Bureau of Statistics (various years). Taxation Revenue, Australia. Catalogue 5506.0.

Australian Taxation Office (annual). Australian tax gaps – overview, methodology notes on accrual-vs-cash reconciliation.

See Also

Other harmonisation: ato_crosswalk(), ato_deflate(), ato_harmonise(), ato_per_capita(), ato_schema_map(), ato_to_taxstats()

Examples

ato_reconcile(value = 316.4e9,
              year = "2022-23",
              measure = "individuals_income_tax_net")

Print the ATO -> taxstats schema map

Description

Convenience accessor for the bundled column-name mapping.

Usage

ato_schema_map()

Value

A data frame with columns ato_aggregate and taxstats_microdata.

See Also

Other harmonisation: ato_crosswalk(), ato_deflate(), ato_harmonise(), ato_per_capita(), ato_reconcile(), ato_to_taxstats()

Examples

head(ato_schema_map())

Compute the SHA-256 digest of a file

Description

Wraps tools::md5sum() style behaviour for SHA-256 via the digest package when available, or falls back to a pure-R implementation via tools::md5sum() + file length as a weaker check. For integrity work PBO/Grattan-grade, install the digest package (Suggests).

Usage

ato_sha256(file)

Arguments

Value

A length-1 character string (hex digest), or NA if the file does not exist.

See Also

Other reproducibility: ato_deposit_zenodo(), ato_manifest(), ato_manifest_clear(), ato_manifest_write(), ato_snapshot()

Examples

f <- tempfile()
writeLines("hello", f)
ato_sha256(f)

Small Business Benchmarks

Description

Returns the ATO's Small Business Benchmarks: industry-specific performance ranges (cost of sales / turnover, total expenses / turnover, labour / turnover, etc.) derived from small-business income tax returns. Used by the ATO to identify outlier taxpayers, by small-business advisors for comparative analysis, and by tax integrity researchers.

Usage

ato_sme_benchmarks(year = "latest")

Arguments

Value

An ato_tbl with one row per (industry, turnover band, ratio) combination. Ratios are percentages.

Source

Australian Taxation Office Small Business Benchmarks. Licensed CC BY 2.5 AU.

See Also

Other discovery: ato_catalog(), ato_charities(), ato_cite(), ato_download(), ato_excise(), ato_fbt(), ato_help(), ato_irpd(), ato_payg(), ato_rdti(), ato_tax_gaps(), ato_top_taxpayers(), ato_vttc()

Examples

op <- options(ato.cache_dir = tempdir())
try({
  bm <- ato_sme_benchmarks(year = "2023-24")
  head(bm)
})
options(op)

Pin or inspect the session snapshot date

Description

Call once at the top of an analysis script to declare the vintage of ATO data you intend to use. Every subsequent ⁠ato_*⁠ fetch records this date in the ato_tbl provenance header, in ato_manifest() entries, and in ato_cite() output. Combined with SHA-256 integrity (see ato_sha256() and ato_manifest()), this gives a reproducible audit trail acceptable for PBO or Grattan-style published work.

Usage

ato_snapshot(date)

Arguments

Details

If called with no arguments, returns the current pin (or NULL if unset).

Value

Invisibly, the new pinned date (as Date), or NULL.

See Also

Other reproducibility: ato_deposit_zenodo(), ato_manifest(), ato_manifest_clear(), ato_manifest_write(), ato_sha256()

Examples

ato_snapshot("2026-04-24")
ato_snapshot()
ato_snapshot(NULL)

State and territory tax revenue (ABS 5506.0)

Description

Fetches the ABS Taxation Revenue collection (cat. 5506.0), which gives land tax, payroll tax, stamp duty, motor vehicle taxes, and other state taxes by jurisdiction. Needed for complete-tax-system analysis alongside ATO Commonwealth data.

Usage

ato_state_tax(year = "latest")

Arguments

Value

An ato_tbl.

Source

Australian Bureau of Statistics, Taxation Revenue, catalogue 5506.0 https://www.abs.gov.au/statistics/economy/government/taxation-revenue-australia. Licensed CC BY 4.0.

See Also

Other specialist: ato_compliance(), ato_division293(), ato_fuel_tax_credits(), ato_international(), ato_medicare_levy(), ato_prrt(), ato_rba(), ato_tax_expenditures(), ato_whm()

Examples

op <- options(ato.cache_dir = tempdir())
try(ato_state_tax(year = "latest"))
options(op)

Superannuation fund aggregates

Description

Returns Taxation Statistics Super Funds tables or Self-Managed Superannuation Fund ('SMSF') aggregates, depending on type.

Usage

ato_super_funds(year = "latest", type = c("apra", "smsf", "all"))

Arguments

Value

An ato_tbl.

Source

Australian Taxation Office Taxation Statistics Super Funds tables + SMSF statistical overview. Licensed CC BY 2.5 AU.

References

Australian Taxation Office (annual). Taxation Statistics: Super funds and SMSF explanatory notes. Distinguishes reporting populations: APRA-regulated large funds, SMSFs, and Pooled Superannuation Trusts.

Australian Prudential Regulation Authority (annual). Annual Superannuation Bulletin. Complementary APRA-regulated fund statistics.

Commonwealth of Australia. Superannuation Industry (Supervision) Act 1993 (SIS Act); Superannuation Guarantee (Administration) Act 1992 (SGAA).

Productivity Commission (2018). Superannuation: Assessing Efficiency and Competitiveness. Inquiry report.

Examples

op <- options(ato.cache_dir = tempdir())
try({
  s <- ato_super_funds(year = "2022-23", type = "apra")
  head(s)
})
options(op)

Tax Expenditures and Insights Statement (TEIS)

Description

Returns the Treasury TEIS annual table of concession-by-concession tax expenditure estimates in AUD millions. TEIS is the authoritative cost-of-concessions dataset used in PBO and Grattan tax reform costings.

Usage

ato_tax_expenditures(year = "latest")

Arguments

Details

TEIS is published by Treasury, not ATO; the function attempts a CKAN search on data.gov.au for the TEIS release, and falls back to the Treasury web URL if not indexed.

Key concessions covered: CGT main residence exemption, CGT 50% discount, superannuation earnings tax concession, franking credit refundability, work-related deductions, fuel tax credit scheme, R&D tax incentive, GST food exemption, and many more.

Value

An ato_tbl with one row per tax expenditure: label, category, estimated revenue forgone in AUD millions by year.

Source

Treasury Tax Expenditures and Insights Statement https://treasury.gov.au/publication/p2025-721342.

References

Commonwealth of Australia (annual). Tax Expenditures and Insights Statement. The Treasury, Canberra. https://treasury.gov.au/publication/p2025-721342

See Also

Other specialist: ato_compliance(), ato_division293(), ato_fuel_tax_credits(), ato_international(), ato_medicare_levy(), ato_prrt(), ato_rba(), ato_state_tax(), ato_whm()

Examples

op <- options(ato.cache_dir = tempdir())
try(head(ato_tax_expenditures("latest")))
options(op)

Australian tax gaps estimates

Description

Returns the ATO's annual Tax Gap publication: estimates of the difference between the tax theoretically payable under current law and the tax actually collected, across each tax type and taxpayer population (individuals not in business, small business, large corporate, GST, excise, fuel tax credits, PRRT, superannuation guarantee).

Usage

ato_tax_gaps(sheet = 1)

Arguments

Details

The Tax Gap series is used by Treasury (every MYEFO), the Parliamentary Budget Office, and academic researchers as the headline measure of revenue integrity.

Value

An ato_tbl. Tax-gap estimates are in nominal AUD millions of the reporting year and typically accompanied by a percentage-gap column.

Source

Australian Taxation Office Tax Gaps publication, CC BY 2.5 AU.

References

Australian Taxation Office (annual). Australian tax gaps – overview. Methodology notes on bottom-up, top-down, and random-inquiry approaches to the tax-gap estimation.

HMRC (annual). Measuring tax gaps. Sister methodology paper applied by HM Revenue and Customs in the UK; the ATO series was partly inspired by this literature.

Organisation for Economic Co-operation and Development (2017). Shining Light on the Shadow Economy: Opportunities and Threats. Paris. Synthesises tax-gap measurement practice across OECD member countries.

See Also

Other discovery: ato_catalog(), ato_charities(), ato_cite(), ato_download(), ato_excise(), ato_fbt(), ato_help(), ato_irpd(), ato_payg(), ato_rdti(), ato_sme_benchmarks(), ato_top_taxpayers(), ato_vttc()

Examples

op <- options(ato.cache_dir = tempdir())
try({
  gaps <- ato_tax_gaps()
  head(gaps)
})
options(op)

Remap an ato_tbl to the taxstats microdata column schema

Description

Takes an ato_tbl with aggregate column names (produced by any ⁠ato_*⁠ function) and renames columns to match the taxstats (or taxstats2) 2% microdata sample schema used by Hugh Parsonage's DRAT package. Enables consistent variable definitions when moving between aggregate views and microdata prototyping.

Usage

ato_to_taxstats(df, direction = c("to_taxstats", "from_taxstats"))

Arguments

Details

The bundled schema map (ato_schema_map()) mirrors the column names from Parsonage's taxstats and taxstats2 packages, which in turn use the ATO Individual Sample File variable names. Because taxstats is DRAT-distributed and not on CRAN, this function imposes the mapping as a static table rather than programmatically introspecting the taxstats namespace. Re-check the bundled map against the taxstats NAMESPACE when the ATO publishes a revised Sample File schema.

Unknown columns pass through unchanged. Use ato_harmonise first if the input panel has drift in source column names.

Value

A data frame with renamed columns. ato_tbl class and provenance attributes preserved.

References

Parsonage, H. (2019). taxstats: 2 per cent Individual Sample File from the Australian Taxation Office. R package (DRAT). https://github.com/HughParsonage/taxstats

Parsonage, H. (2024). grattan: Perform Common Quantitative Tasks for Australian Analysts. R package version 2026.1.1. https://cran.r-project.org/package=grattan

Australian Taxation Office (2024). Taxation Statistics: Individual Sample File documentation.

See Also

Other harmonisation: ato_crosswalk(), ato_deflate(), ato_harmonise(), ato_per_capita(), ato_reconcile(), ato_schema_map()

Examples

df <- data.frame(postcode = "2000", taxable_income = 80000,
                 medicare_levy = 1600)
ato_to_taxstats(df)

Corporate Tax Transparency

Description

Returns the ATO's annual Corporate Tax Transparency release, mandated by Part 5-25 of the Taxation Administration Act 1953. Covers every Australian public company, foreign-owned company, or Australian-owned private company above the AUD 100 million total-income threshold (the private-company threshold was lowered from AUD 200 million to AUD 100 million for the 2022-23 income year onwards, making all three categories uniform). The 2023-24 release was published 1 October 2025 and covered 4,110 entities.

Usage

ato_top_taxpayers(
  year = "latest",
  entity_type = c("all", "public", "private", "foreign"),
  sheet = c("income_tax", "prrt")
)

Arguments

Details

The underlying XLSX has three sheets:

• Information (cover/metadata, ~7 rows).

• Income tax details (the headline dataset, ~4,000 entities: total income, taxable income, tax payable).

• PRRT details (petroleum resource rent tax filers, typically 10-20 entities).

Licensed under CC BY 3.0 Australia (the Corporate Tax Transparency and Voluntary Tax Transparency Code releases use CC BY 3.0 AU; most other Taxation Statistics use CC BY 2.5 AU).

Value

An ato_tbl with one row per disclosed entity. All monetary values are nominal AUD of the reporting year.

Source

Australian Taxation Office Corporate Tax Transparency release. Licensed CC BY 3.0 AU.

References

Commonwealth of Australia. Taxation Administration Act 1953, Part 5-25 (Corporate Tax Transparency).

Australian Taxation Office (annual). Report of entity tax information. The statutory Corporate Tax Transparency release.

Commonwealth Treasury (2013). Improving the transparency of Australia's business tax system: Exposure draft explanatory memorandum. Rationale for the Part 5-25 regime.

See Also

Other discovery: ato_catalog(), ato_charities(), ato_cite(), ato_download(), ato_excise(), ato_fbt(), ato_help(), ato_irpd(), ato_payg(), ato_rdti(), ato_sme_benchmarks(), ato_tax_gaps(), ato_vttc()

Examples

op <- options(ato.cache_dir = tempdir())
try({
  top <- ato_top_taxpayers(year = "2023-24")
  head(top)
  # Petroleum resource rent tax sheet
  prrt <- ato_top_taxpayers(year = "2023-24", sheet = "prrt")
  head(prrt)
})
options(op)

Voluntary Tax Transparency Code disclosures

Description

Returns the ATO's Voluntary Tax Transparency Code (VTTC) disclosures: large private companies that voluntarily publish tax information beyond the Corporate Tax Transparency mandate. Covers total income, taxable income, tax payable, and effective tax rate for each disclosing entity.

Usage

ato_vttc(year = "latest")

Arguments

Details

The VTTC complements ato_top_taxpayers() (which covers mandatory CTT disclosures for entities above AUD 100m total income). VTTC signatories may be below or above the CTT threshold.

Licensed under CC BY 3.0 Australia (same as CTT data).

Value

An ato_tbl. Monetary values in nominal AUD.

Source

Australian Taxation Office Voluntary Tax Transparency Code disclosures on data.gov.au. Licensed CC BY 3.0 AU.

See Also

Other discovery: ato_catalog(), ato_charities(), ato_cite(), ato_download(), ato_excise(), ato_fbt(), ato_help(), ato_irpd(), ato_payg(), ato_rdti(), ato_sme_benchmarks(), ato_tax_gaps(), ato_top_taxpayers()

Examples

op <- options(ato.cache_dir = tempdir())
try({
  vttc <- ato_vttc(year = "2022-23")
  head(vttc)
})
options(op)

Working Holiday Maker tax data

Description

Returns aggregate Working Holiday Maker tax data: number of backpackers, total earnings, tax paid. Relevant for migration and labour-market policy analysis.

Usage

ato_whm(year = "latest")

Arguments

Value

An ato_tbl.

Source

Australian Taxation Office Taxation Statistics. Licensed CC BY 2.5 AU.

References

Commonwealth of Australia. Migration Act 1958, visa subclasses 417 and 462; Working Holiday Maker Reform Act 2016. Establishes the 15 per cent flat tax rate from the first dollar of WHM earnings.

Productivity Commission (2016). Migrant Intake into Australia. Includes WHM labour-market analysis.

See Also

Other specialist: ato_compliance(), ato_division293(), ato_fuel_tax_credits(), ato_international(), ato_medicare_levy(), ato_prrt(), ato_rba(), ato_state_tax(), ato_tax_expenditures()

Examples

op <- options(ato.cache_dir = tempdir())
try(ato_whm(year = "2022-23"))
options(op)

Print an ato_tbl

Description

Prints a provenance header (title, source, licence, retrieval time, dimensions) followed by the data frame.

Usage

## S3 method for class 'ato_tbl'
print(x, ...)

Arguments

Value

Invisibly returns x.

Examples

x <- data.frame(postcode = "2000", taxable_income = 82000)
x <- structure(x, ato_title = "Demo", ato_source = "https://data.gov.au",
               ato_licence = "CC BY 2.5 AU", ato_retrieved = Sys.time(),
               class = c("ato_tbl", "data.frame"))
print(x)