PIT administration maturity

A continuous PIT administration maturity score is computed as a weighted composite of four PIT-admin pillars — Assessment & Filing, Enforcement, Digital Transformation and Registration. Within each pillar the standardised features are averaged; pillars are then combined using AHP-derived weights (Assessment & Filing 42% · Enforcement 28% · Digital Transformation 18% · Registration 12%). The composite is z-scored and regressed on log GDP per capita using Ordinary Least Squares (OLS) — the line minimises the sum of squared residuals and represents expected maturity for income level. Each jurisdiction’s residual — its vertical distance from the line, in σ (standard deviation) units of maturity — is its continuous over- or under-performance against peers at a similar income (R² = 0.25, σ residuals = 0.87). The shaded band marks ±1σ of residual error around the line of best fit; jurisdictions inside the band sit within typical scatter for their income level and are not flagged as outliers. Points above the band are punching above their weight, those below are punching below — the further from the line, the stronger the divergence.

AHP-derived weights. The Analytic Hierarchy Process (AHP) is a structured technique for deriving priority weights from pairwise comparisons — each pair of pillars is judged on relative importance, and the resulting comparison matrix is solved (via its principal eigenvector) to produce weights that sum to 100%. A consistency check flags whether the pairwise judgements hang together logically. The weights here give Assessment & Filing the largest share because it is the workload core of a tax administration, with Enforcement, Digital Transformation and Registration following in turn.

Each feature’s σ shift is the mean of its per-feature regression residual (σ vs income-expected — the deviation from what the jurisdiction’s income level would predict) across the cohort of jurisdictions sitting more than ±0.5σ off the maturity regression line. The eight features with the largest weighted contribution in each direction are plotted above.

Block-weighted contributions. Each feature’s σ shift is multiplied by its AHP per-feature weight — the pillar’s AHP weight divided by the number of features in the pillar, the same weight that determines the feature’s contribution to the maturity composite in Section 1. Each bar therefore shows the feature’s contribution to the maturity residual the regression is fitting, so features in heavily weighted pillars (Assessment & Filing, Enforcement) rise relative to lightly weighted ones (Registration), where the same raw σ shift counts for less in the composite. The hover shows the exact per-feature weight, the post-weighted contribution and the raw σ shift.

Caveat — audit-yield interpretation. The Audit yield / PIT revenue feature is structurally ambiguous: a high ratio can mean (a) the administration has effective audit-selection capability and recovers revenue productively, or (b) baseline voluntary compliance is weak, so a larger share of revenue has to be clawed back through audits. ISORA does not publish a PIT-specific audit hit rate, but the aggregate Audit hit rate (all tax types, indicator 337_173) is included in the Enforcement pillar as a triangulation signal — high audit yield combined with a high aggregate hit rate is more consistent with reading (a); high yield with a low hit rate points to (b). Country-by-country context still matters: Italy and Spain (high historical tax gap) sit closer to (b); Denmark and Norway (high baseline compliance) sit closer to (a).