grattan v1.7.1.2


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Australian Tax Policy Analysis

Utilities for costing and evaluating Australian tax policy, including high-performance tax and transfer calculators, a fast method of projecting tax collections, and an interface to common indices from the Australian Bureau of Statistics. Written to support Grattan Institute's Australian Perspectives program. For access to the 'taxstats' package, please run install.packages("taxstats", repos = "", type = "source"). N.B. The 'taxstats' package is approximately 50 MB.


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Important temporary notice (2019-02-09): The vignettes do not run on pandoc v2.4 (or take a very long time). Please upgrade to v2.6 (2019-01-30) if building vignettes. You may need to modify the PATH or change the RSTUDIO_PANDOC env. var after installing.

Australian Tax Policy Analysis


## Last change: sysdata.rda at 2019-02-09 16:11:51 (2 mins ago).


Calculates the income tax for a given taxable income and financial year:

income_tax(50e3, "2015-16")
## [1] 8547

With sample files

income_tax is designed to work well with the ATO’s sample files. You can obtain the sample files from my repo:

# install.packages("taxstats", repos = "")


Simply pass the sample file to .dots.ATO and the complexities of things like Medicare levy and the Seniors and Pensioners Tax Offset are handled for you. For example:

s1314 <-
s1314 %>%
  .[, tax := income_tax(Taxable_Income, "2013-14", .dots.ATO = s1314)] %>%
  .[, .(Taxable_Income, tax)]
##         Taxable_Income       tax
##      1:           4800     0.000
##      2:         126122 36503.970
##      3:          39742  4655.410
##      4:         108123 29574.355
##      5:          85957 21040.445
##     ---                         
## 258770:          24462  1111.710
## 258771:          37055  3701.525
## 258772:          45024  6530.520
## 258773:           5134     0.000
## 258774:          46368  7007.640

model_income_tax: modelling changes to personal income tax

While income_tax is designed to inflexibly return the tax payable as legislated, model_income_tax is designed to calculate income tax when changes are made. For example,

s1314 %>%
  # reduce top threshold from 180,000 to 150,000
  model_income_tax(ordinary_tax_thresholds = c(0, 18200, 37000, 80000, 
                   baseline_fy = "2013-14") %>%
  .[, .(Taxable_Income, baseline_tax, new_tax)]
##         Taxable_Income baseline_tax   new_tax
##      1:           4800            0     0.000
##      2:         126122        36503 36503.970
##      3:          39742         4655  4655.410
##      4:         108123        29574 29574.355
##      5:          85957        21040 21040.445
##     ---                                      
## 258770:          24462         1111  1111.710
## 258771:          37055         3701  3701.525
## 258772:          45024         6530  6530.520
## 258773:           5134            0     0.000
## 258774:          46368         7007  7007.640


Given a sample file, we can project forward a number of years

s1617 <- project(s1314, h = 3L)

or to a particular financial year

s1718 <- project_to(s1314, "2017-18")

Together with model_income_tax, this allows us to make point-predictions of future years. The function revenue_foregone prettily prints the resultant revenue:

sample_file_1314 %>%
  project_to("2018-19") %>%
  model_income_tax(baseline_fy = "2017-18",
                   ordinary_tax_thresholds = c(0, 18200, 37000, 87000, 
                                               150e3)) %>%
## [1] "$1.8 billion"


Create comparison of average tax rates:

lapply(list("30k" = 30e3,
            "36k" = 36e3,
            "42k" = 42e3),
       function(T2) {
                          baseline_fy = "2017-18",
                          ordinary_tax_thresholds = c(0, 
       }) %>%
  rbindlist(idcol = "id",
            use.names = TRUE,
            fill = TRUE) %>%
  compare_avg_tax_rates(baseDT = .[id %ein% "36k"]) %>%
  ggplot(aes(x = Taxable_Income_percentile,
             y = delta_avgTaxRate,
             color = id,
             group = id)) +
  geom_hline(yintercept = 0) +

Access ABS data


Bug fixes

  • income_tax now gives consistent results modulo the existence of completely empty columns that are inputs for sapto (#158)

New functions:

  • awote for weekly earnings


  • age_grouper can now have a custom first label prefix, and is much faster when length(age) is large.
  • income_tax now emits a warning when both age and .dots.ATO are provided, indicating that age will be ignored.
  • The data has been updated to 2019-02-09.


  • mutate_ntile and weighted_ntile now use the hutils equivalents. This broke 3 unit tests because of the specific phrasing of some error messages.
  • The vignette requires pandoc > 2.4. Some chunks have been refactored to avoid excess memory usage.

Bug fixes

  • Fixed failing interaction between temporary budget repair levy and small business tax offset in 2016-17.
  • small_business_tax_offset() is now always positive, fixing the original misinterpretation of the legislation whereby negative business income resulted in a negative offset.
  • *_inflator functions now return correct results for non-standard but supported financial years.
  • inflator no longer fails when to_fy is length > 1 and unordered.

New features

  • mutate_ntile and mutate_weighted_ntile for adding quantile columns
  • New welfare functions (usable for the 2015-16 financial year)
    • age_pension,
    • carer_payment
    • carers_allowance
    • energy_supplement
    • family_tax_benefit
    • newstart_allowance
    • pension_supplement
    • rent_assistance the Commonwealth Rent Assistance
    • model_rent_assistance as experimental function for modelling changes to rent assistance.
    • youth_allowance() now available, though limited
  • compare_avg_tax_rates: create a difference in average tax rates between multiple models and a baseline tax, by percentile.
  • install_taxstats() as a convenient means to install the non-CRAN taxstats dependency.


  • prohibit_vector_recycling() and friends return more informative error messages.
  • Added default values to the following functions:
    • income_tax, income_tax_sapto: the default value for fy.year is the current financial year
    • cpi_inflator, lf_inflator_fy, wage_inflator: if both from_fy and to_fy are missing, the default values become the previous and current financial years respectively. If only one of the two are missing, an error appears.
  • income_tax is about twice as fast since 1.5-2.0s down from 3.0-3.7s on the 100% population (13 million)
  • inflator and cpi_inflator, lf_inflator_fy, and wage_inflator are now much faster when either from_fy or to_fy have more than 100,000 elements:
from_fys <- sample(yr2fy(1995:2010), size = 1e6, replace = TRUE)
microbenchmark(cpi_inflator(from_fy = from_fys, to_fy = "2015-16"))
# Old
Unit: seconds
                                                expr      min      lq     mean   median       uq
 cpi_inflator(from_fy = from_fys, to_fy = "2015-16") 1.519483 1.54438 1.550628 1.549735 1.554507
      max neval
 1.661502   100

# New
Unit: milliseconds
                                                expr      min       lq     mean   median       uq
 cpi_inflator(from_fy = from_fys, to_fy = "2015-16") 40.71753 41.94061 47.93162 42.93946 48.08461
      max neval
 191.3497   100

Potentially breaking changes

  • yr2fy(x) no longer works for x = 1900L, despite a unit test, for the sake of performance.
  #> Last change: NAMESPACE at 2018-08-19 14:47:14 (4 mins ago).
  #> Unit: milliseconds
  #>       expr min  lq mean median  uq max neval cld
  #>   yr2fy(z)  75  88   98     90 101 161   100  a 
  #>  .yr2fy(z) 274 286  298    297 302 359   100   b

Use yr2fy(x, assume1901_2100 = FALSE) if you need the old behaviour.


  • taxstats1516 is now a suggested dependency.


  • Never-legislated Medicare levy change in 2019-20 has been reverted
  • Budget 2018:
    • model_income_tax() no longer coerces WEIGHT to integer.
    • New arguments to support Budget 2018:
      • lito_multi Permits multiple pieces to the linear offset.
      • Budget2018_lamington The Low And Middle Income Tax Offset proposed in the Budget 2018 budget.
      • Budget2018_lito_202223 The proposed change to LITO from 2022-23.
      • Budget2018_watr The offset proposed by the Opposition the Budget Reply.
      • sbto_discount Allows modification of the small business tax offset.
      • clear_tax_cols By default, old tax columns are deleted.
      • warn_upper_thresholds If changed to FALSE allows the automatic changes to be applied without warning.
  • New functions:
    • progressivity() for Gini-based measure of the progressivity of income tax
    • revenue_foregone() as a convenenience for returning the revenue foregone from a modelled sample file.
  • Routine changes:
    • ABS data updated as of 2018-05-21.


  • Labour force data and wage price index updated to 2018-02-21.
  • Update as requested to fix failing unit tests relying on non-standard packages.


New features:

  • New function model_income_tax which attempts to provide every lever of the income tax system that is visible from the tax office’s sample files. Users can model the sample file by changing single parameters to observe the effect on tax collections.
  • small_business_tax_offset: Include the small business tax offset as a standalone function and within income_tax.

Other user-visible changes

  • project and project_to no longer require fy.year.of.sample.file. However, they expect the supplied data.frame to be compatible with the sample file provided. Failling to provide a sample file with the expected number of rows or not providing a sample file with a valid number of rows is a warning, which can be silenced by check_fy_sample_file = FALSE.


  • Update labour force data to November 2017
  • Internal projection tables have been updated for the latest (2014-15) sample file.

Other changes

  • mgcv was used but not declared in Suggests: Thanks to BDR for reporting.
  • (internal) Extend prohibit_vector_recycling to return the maximum permissible length of a list of vectors.


  • Update wage data to 2017-Q3
  • Update labour force data to 2017-09
  • (internal) The lf_trend internal data table used to report the labour force in thousands of persons, as the ABS does. This seemed a bit strange, so now obsValue uses integers (i.e. just the labour force).
  • Vignettes now install taxstats to a temporary directory if not already installed, rather than the user or system’s library.


  • Update CPI data
  • Fix wage data


  • Update labour-force data


  • New internal C++ functions for income_tax, and related functions
  • BTO function now uses tax scales from the Income Tax Regulations


  • Optional argument age in income_tax now NULL rather than 42.
    The default argument continues to result in SAPTO being not applied if .dots.ATO. However, if .dots.ATO is supplied (and the age variable has not been removed from it), the individuals’ SAPTO eligibility is determined by the age variable in .dots.ATO, rather than setting each individual’s SAPTO to 0.


  • Update labour force data. Avoid segfault in separate package in unit test.
  • Added a file to track changes to the package.


  • Update wage, CPI, labour force data


  • Update wage and labour force data
  • Fix breaking build due to change in dplyr API

CRAN Notes

Test results


Test environments:

  • Local Windows CRAN 3.5.1
  • Travis-CI: Ubuntu 14.04. R 3.4, 3.5, and dev (r75443)
  • Appveyor: dev (r75439) and release.
  • winbuilder: dev (r75434) and release.


Possibly mis-spelled words in DESCRIPTION: … ==> Spellings are correct: ‘repos’ and ‘taxstats’ cannot be quoted as they are within R code.

URLs in angle brackets: ==> Not appropriate since the URL is within R code.

Suggests or Enhances not in mainstream repositories: … ==> Normal due to taxstats dependency

Note to CRAN: moderately-large vignette

The vignette is quite lengthy and, while it will run on CRAN, requires the installation of ‘taxstats’, a 58 MB source package, each time the package is checked.

Functions in grattan

Name Description
age_pension_age Age of eligibility for the Age Pension
aus_pop_qtr Australia's population
cpi_inflator_quarters CPI inflator when dates are nice
awote AWOTE
bto Beneficiary tax offset
install_taxstats Install 'taxstats' files
inverse_average_rate Inverse average tax rate
new_sapto SAPTO with user-defined thresholds
newstart_allowance Newstart allowance
differentially_uprate_wage Differential uprating
aus_pop_qtr_age Australian estimated resident population by age and date
prohibit_length0_vectors Prohibit zero lengths
carer_payment Carer Payment
carers_allowance Carers allowance
disability_pension Disability support pension
generic_inflator Generic inflator
gni Gross National Income, Australia
cpi_inflator CPI inflator
cpi_inflator_general_date CPI for general dates
energy_supplement Energy supplement
prohibit_unequal_length_vectors Prohibit unequal length vectors
income_tax_sapto Income tax payable as a function of SAPTO
residential_property_prices Residential property prices in Australia
child_care_subsidy Child Care Subsidy paid per child.
compare_avg_tax_rates Compare average tax rates by percentile
grattan-package The grattan package.
family_tax_benefit Family tax benefit
inverse_income Inverse income tax functions
revenue_foregone Revenue foregone from a modelled sample file
is.fy Convenience functions for dealing with financial years
inflator Inflate using a general index
model_child_care_subsidy Model Child Care Subsidy
gdp Gross Domestic Product, Australia
validate_fys_permitted Verifying validity of financial years
model_income_tax Modelled Income Tax
validate_per Validate per
income_tax Income tax payable
max_super_contr_base Maximum superannuation contribution base
lf_inflator Labour force inflators
pmax3 Threeway parallel maximum
pmaxC Parallel maximum
model_new_caps_and_div293 Modelling superannuation changes
new_medicare_levy New medicare levy
lito Low Income Tax Offset
medicare_levy Medicare levy
new_income_tax New income tax payable Income tax payable with new tax brackets, tax rates etc
rebate_income Rebate income
project Simple projections of the annual 2% samples of Australian Taxation Office tax returns.
sapto Seniors and Pensioner Tax Offset
reexports Objects exported from other packages
project_to Simple projections of the annual 2% samples of Australian Taxation Office tax returns.
sapto_rcpp SAPTO done in Rcpp
npv Financial functions
model_rent_assistance Model Rent Assistance
pminV Parallel maximum
progressivity Compute the progressivity
small_business_tax_offset Small Business Tax Offset
pension_supplement Pension Supplement
student_repayment HELP / HECS repayment amounts
pmaxV Parallel maximum
pminC Parallel maximum
sapto_rcpp_singleton SAPTO singleton
wage_inflator Inflation using the Wage Price Index.
rent_assistance Rent assistance
sapto_rcpp_yr SAPTO for specific years in C++
require_taxstats Attach a 'taxstats' package
youth_allowance Youth allowance
youth_unemployment Youth unemployment
unemployment_benefit Unemployment benefit
validate_date Verifying validity of dates
anyGeq Any without logical creation
apply_super_caps_and_div293 Superannuation caps and Division 293 calculations
IncomeTax IncomeTax
MedicareLevy Medicare levy in C++
AnyWhich Quickly verify (and locate) the existence of a breach.
CG_population_inflator Forecasting capital gains
age_pension Age pension
Offset General offset in C++
age_grouper Age grouper
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