Pay gaps within occupations
This chart tracks how the gap between high- and low-paid workers has changed within selected occupations. It uses weighted Census ACS microdata for full-time, year-round workers and reports percentile ratios, which describe dispersion without identifying differences in experience, geography, hours, or job specialization.
What does it show?
Pay inequality is widening inside several professions, not only between different occupations.
Methodology
Six-profession view. Weighted 90th/10th percentile ratio of annual wage income (WAGP) per occupation, ACS 1-year PUMS person records, person weights (PWGTP). Universe: full-time (35+ usual hours) year-round (50+ weeks) workers with positive wage income. Occupations matched to OCCP codes via each vintage's data dictionary labels across all three coding eras (2000-, 2010-, 2018-based; physicians combine the post-2018 physician/surgeon codes; PUMS lumps judges with lawyers under 2100). Known breaks: 'Designers' includes all designers through the 2017 vintage, graphic designers only after; 'Marketing and sales managers' includes sales managers through the 2017 vintage. ADJINC omitted (cancels within-year in a ratio). WAGP top-coding compresses the far right tail, so high-wage occupations' p90 (notably physicians) is conservative; wage income only — partnership/self-employment income (e.g. law-firm partners) is excluded and unvested equity never appears, so measured spread is a floor. Underlying percentile levels (p10-p95) in data/wagespread-levels.json. Annual, ~1-year lag; no 2020 1-year release. Directional, not a precise continuous series.