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How a wage increase becomes a price increase.

The Atlas shows one face of the labor-supply problem: how many workers the U.S. is short at a given tolerance for wage growth. This page shows the other face. When wages rise to clear a labor shortage, prices follow. The pass-through is partial, and it depends on what share of the industry's wage bill the occupation accounts for, how labor-intensive the industry is, and how much foreign competition or market power dampens the firm's ability to mark prices up.

Below, the literature anchors and the per-occupation calibration we use on the Atlas banner. Pass-through bands are reduced-form estimates; they do not come from the general-equilibrium model that produces the shortage numbers. Phase 2 of this page will swap the eyeball industry shares for BEA Input-Output Use Table calculations.

Wage-to-price pass-through, by sector

How a sustained 1% rise in an industry's wages typically translates to that industry's prices over ~10 years. Ranges reflect the published span across major studies; tradable sectors sit lower because foreign competition limits firms' ability to pass costs through.

Nontradable services (healthcare, education)

0.40–0.60

Nontradable goods & construction

0.30–0.50

Transportation & freight

0.20–0.40

Retail & personal services

0.20–0.40

Tradable services (software, finance)

0.10–0.25

Tradable manufacturing

0.10–0.20

Reduced-form pass-through elasticity, 10-yr horizon · scale 0–0.65

Per-occupation pass-through

For each of the 18 occupation groups in the Atlas top-shortage list, our pass-through band combines three ingredients: the occupation's share of the industry's wage bill, the industry's labor share of output, and the industry's typical price-cost pass-through (from the literature in Figure 1). For each row, hovering shows the implied prices and CPI contribution at a 10% wage rise.

Occupation Primary industry Band @10%: industry @10%: headline CPI
15-1 software developers and other computer workers U.S. software and tech services 0.048–0.096 +0.5–1.0% +0.02–0.05 pp
13-1 business analysts, project managers, and other business-operations workers U.S. business services 0.054–0.090 +0.5–0.9% +0.01–0.02 pp
29-1 doctors, nurses, and other licensed healthcare practitioners hospital and clinical services 0.182–0.242 +1.8–2.4% +0.13–0.17 pp
29-2 medical technicians and lab technologists diagnostic and clinical laboratory services 0.028–0.039 +0.3–0.4% +0.02–0.03 pp
31-1 home health aides and nursing assistants home health and long-term care services 0.176–0.234 +1.8–2.3% +0.02–0.02 pp
25-2 K-12 and preschool teachers K-12 education 0.193–0.270 +1.9–2.7% +0.06–0.09 pp
39-9 childcare workers and personal-care workers childcare and personal-care services 0.245–0.315 +2.5–3.1% +0.02–0.03 pp
45-2 farm laborers and other agricultural workers food and agricultural production 0.036–0.060 +0.4–0.6% +0.03–0.05 pp
47-2 construction-trades workers (carpenters, plumbers, electricians) residential construction and home repair 0.049–0.073 +0.5–0.7% +0.04–0.06 pp
49-3 auto mechanics and equipment repair technicians auto repair and maintenance services 0.124–0.173 +1.2–1.7% +0.01–0.02 pp
51-2 assemblers and fabricators durable goods manufacturing 0.007–0.015 +0.1–0.1% +0.00–0.01 pp
51-4 machinists and other metal workers metalworking and machine-tool industries 0.006–0.013 +0.1–0.1% +0.00–0.01 pp
51-9 production workers (factory operators) U.S. manufacturing 0.010–0.020 +0.1–0.2% +0.00–0.01 pp
53-3 truck drivers and other vehicle operators freight trucking 0.042–0.070 +0.4–0.7% +0.03–0.04 pp
53-7 warehouse workers and material movers warehousing and logistics 0.060–0.100 +0.6–1.0% +0.06–0.10 pp
35-3 food service workers restaurants and food services 0.070–0.105 +0.7–1.1% +0.04–0.06 pp
41-2 retail sales workers and cashiers retail trade 0.021–0.035 +0.2–0.4% +0.03–0.05 pp
17-2 engineers engineering-intensive manufacturing and design services 0.004–0.008 +0.0–0.1% +0.00–0.00 pp

Methodology

For each occupation, the pass-through band is decomposed as: band = occupation_share_of_industry_wages × industry_labor_share × industry_price_to_cost_passthrough . The first two factors come from BLS Occupational Employment and Wage Statistics (OEWS) and a representative slice of the BEA Use Table; the third is calibrated from the studies in Figure 1.

To go from an industry-price change to a headline-CPI change, we weight by the industry's share of the CPI basket (BLS Relative Importance, December 2024). This gives a partial-equilibrium estimate of the contribution one occupation's wage path makes to overall inflation. It does not account for general-equilibrium effects, real exchange rate adjustments, or monetary policy responses.

A planned Phase 2 will replace the eyeball industry shares with a full BEA Input-Output Use Table calculation, propagated through the Leontief inverse to capture indirect effects (e.g., how higher construction wages raise input costs for industries that buy construction services).

Sources