Carolina Workshed — Rural Labor Market Model

Unskilled & production-labor change across South Carolina communities · data vintage: Nov 2025 LAUS + 2024–25 WARN + QCEW

Map metric

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Layers

Communities (sized by est. labor pool) Job investments ▲ Closures & layoffs ▼ Material-change outlines

Legend

About

Click any county or community dot for a full readout. Verified events carry job counts; shaded county metrics marked “modeled” are estimates.

Sources: SC DEW Employment Situation (Nov 2025) · SC DEW QCEW county analyses (Q1–Q2 2025) · SC WARN Reports 2024 & 2025 (scworks.org) · SC DEW Economic Analysis Report · Company releases: Scout Motors, Redwood Materials, BMW, International Paper, Canfor, Tupperware. Manufacturing-share & blue-collar workforce figures are modeled estimates.

Methodology & material-change thresholds

What is real vs. modeled. County labor force and unemployment (Nov 2025 vs Nov 2024) are official LAUS estimates via SC DEW. Every marker labeled with a job count comes from a WARN notice or an official company/state announcement. County manufacturing share and production & logistics workforce are modeled estimates, calibrated to SC DEW QCEW statewide manufacturing employment (~263,000, −1.2% YoY mid-2025), regional industry mixes (e.g., Upstate manufacturing ≈79k jobs), and Census occupation profiles (e.g., Laurens County: ~23% of employed in production/transportation/material-moving).

Classification rules (2024–25 window):

Material expansion ≥ $500M verified capital investment in-county, or ≥ 5% YoY county employment growth (QCEW).
Material contraction ≥ 100 WARN-affected jobs, or ≥ 5% employment decline, or ≥ +1.2 pts YoY unemployment increase.
Mixed / transition Simultaneous material gains and losses.
Stable None of the above; some flagged “watch” where slack is building.

Rural definition. 23 counties flagged rural: all non-metropolitan counties plus MSA counties of predominantly rural character (Laurens, Darlington, Union).

Blue-collar estimate. Production + transportation/material-moving workforce ≈ labor force × (0.7 × manufacturing share + 4%), per modeled occupation mix.