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Changelog

Source: NEWS.md

inequality 0.2.0

This release responds to feedback from Frank Cowell and Emmanuel Flachaire (personal communication, 1 May 2026) on the v0.1.0 release. Two gaps were flagged: confidence intervals were available only for the Gini, and the package rejected non-positive values for the Gini and the top shares. A follow-up internal audit produced several smaller fixes that ship together.

Confidence intervals on every inequality measure

Bootstrap confidence intervals are now available on every inequality function via ci = TRUE. Each function gains ci, R, and level arguments matching the existing Gini API. Results are returned in ci_lower, ci_upper, and se fields on the output object and shown by the print method.

Functions extended: iq_theil(), iq_atkinson(), iq_sgini(), iq_palma(), iq_hoover(), iq_kolm(), iq_percentile_ratio(), iq_polarisation(), iq_shares(), iq_concentration(), iq_kakwani(), and iq_poverty().

The bootstrap uses probability-proportional resampling, so survey weights flow through to the variance, not just the point estimate.

iq_compare() runs one bootstrap loop, propagates CIs to every row

When ci = TRUE, iq_compare() now runs a single resample loop and attaches ci_lower and ci_upper columns to every row of the table. The old gini_ci field is removed. The table now also covers S-Gini, Kolm, and Wolfson (12 measures, up from 9).

Negative values are now supported via negatives = "keep"

Functions that are mathematically defined for distributions containing negative values now accept negatives = c("error", "keep"), with "error" as the default for back-compatibility. With negatives = "keep":

  • iq_gini() and iq_sgini() permit negatives; the index is still computed by the standard formula but is no longer bounded in [0, 1]. The print method emits a note when the input contains negatives.
  • iq_shares() permits negatives; segment shares may fall outside [0, 1] and a warning is issued. If total income is non-positive, the function returns NA shares with a warning.
  • iq_palma(), iq_hoover(), and iq_polarisation() similarly accept negatives.

iq_kolm() already worked for negative values and is unchanged.

iq_atkinson() and iq_theil() continue to require strictly positive values: they involve log(x) or x^(1 - epsilon) for which the formula is mathematically undefined at zero or below. The error message now documents this explicitly.

Bug fixes

  • iq_kakwani() no longer takes the absolute value of post-tax income before computing the post-tax Gini. Households whose post-tax income is negative are now reflected honestly in the Reynolds-Smolensky index.
  • iq_palma() and iq_polarisation() now warn rather than abort when the relevant denominator is non-positive (returning NA).
  • The standard Gini now returns NA (with a warning) when the population mean is non-positive. Previously the function returned 0 when mu == 0, which conflated “perfect equality” with “undefined”. With negatives = "keep" set, the user is pointed at normalised = TRUE for the Raffinetti et al. (2017) bounded variant.
  • The Watts poverty index drops observations with x = 0 from the Watts sum (since log(line / 0) diverges) and emits a one-time warning. FGT measures and the Sen index continue to include all poor observations.
  • iq_percentile_ratio() now warns when the lower percentile is negative, since the resulting ratio sign-flips and has no inequality interpretation.
  • The error message for measures that require strictly positive input (Theil, Atkinson, decompose, growth_incidence) no longer suggests setting negatives = "keep", which those wrappers do not expose. Instead the message points the user at measures that admit zero or negative support.

New features (audit follow-up)

  • iq_gini() gains a normalised flag implementing the Raffinetti, Siletti and Vernizzi (2017) Gini variant, which is bounded in [-1, 1] for distributions containing negative values.
  • iq_compare() gains a negatives argument. With negatives = "keep" it permits zero or negative input and returns NA for the Theil and Atkinson rows (which are mathematically undefined for non-positive values), while still computing Gini, S-Gini, Kolm, Wolfson, Hoover, Palma and percentile-ratio rows.
  • iq_concentration() gains a correction = "wagstaff" option for the Wagstaff (2005) normalised concentration index, alongside the existing Erreygers (2009) correction.
  • ?iq_theil now documents the convention difference vs the legacy ineq package (ineq::Theil(x, parameter = 0) corresponds to GE(1) / Theil T here, not to GE(0) / Theil L).
  • New tests/testthat/test-axioms.R locks in scale invariance, Kolm translation invariance, Pigou-Dalton transfer principle, anonymity, parameter monotonicity, decomposition exactness, the Erreygers and Wagstaff bounds, and bootstrap nominal coverage.
  • New tests/testthat/test-cross-package.R cross-checks Gini, Theil, and Atkinson values against the legacy ineq package on a fixed seed. Skipped when ineq is not installed and on CRAN.

Acknowledgements

Thanks to Frank Cowell and Emmanuel Flachaire for the careful read and the two-line list of gaps.

inequality 0.1.0

CRAN release: 2026-04-20

  • Initial release.

Inequality indices

  • Gini coefficient with bootstrap or asymptotic (jackknife) confidence intervals via iq_gini(), following Davidson (2009).
  • Extended S-Gini family with adjustable inequality aversion parameter via iq_sgini(), following Donaldson and Weymark (1980).
  • Theil T (GE(1)), mean log deviation (GE(0)), and general GE(alpha) via iq_theil(), following Theil (1967) and Shorrocks (1980).
  • Atkinson index with inequality aversion parameter via iq_atkinson().
  • Kolm absolute inequality index via iq_kolm().
  • Palma ratio (top 10% / bottom 40% income shares) via iq_palma().
  • Hoover index (Robin Hood / Pietra index) via iq_hoover().
  • Percentile ratios (P90/P10, P80/P20, custom) via iq_percentile_ratio().

Distribution and decomposition

  • Lorenz curve with base graphics plot method via iq_lorenz().
  • Between-within group decomposition for the generalised entropy family via iq_decompose(), following Bourguignon (1979).
  • Income share tabulation (bottom 50%, middle 40%, top 10%, top 1%) via iq_shares().
  • Concentration index for health inequality with optional Erreygers (2009) correction via iq_concentration().
  • Wolfson bipolarisation index via iq_polarisation().

Poverty

  • Foster-Greer-Thorbecke poverty measures (headcount, gap, severity), Sen index, and Watts index via iq_poverty().
  • Growth incidence curve with plot method via iq_growth_incidence(), following Ravallion and Chen (2003).

Fiscal

  • Kakwani progressivity index and Reynolds-Smolensky redistribution index via iq_kakwani().

Utilities

  • Side-by-side comparison of all major indices via iq_compare().
  • All functions accept optional survey weights.