aceThe Health-Wealth Gradient in Labor Markets: Integrating Health, Insurance, and Social Metrics to Predict Employment Density
Labor market forecasting relies heavily on economic time-series data, often overlooking the “health–wealth” gradient that links population health to workforce participation. This study develops a machine learning framework integrating non-traditional health and social metrics to predict state-level employment density. Methods: We constructed a multi-source longitudinal dataset (2014–2024) by aggregating county-level Quarterly Census of Employment and Wages (QCEW) data with County Health Rankings to the state lev…
Integrating County Health Rankings and social metrics with QCEW data in a regularized XGBoost framework improved out-of-sample prediction of state-level employment density.
Evidence
- Peer-reviewedComputation2026-01-15
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Truvace Impact Record TRV-2026-0470, v1: “The Health-Wealth Gradient in Labor Markets: Integrating Health, Insurance, and Social Metrics to Predict Employment Density.” Truvace, 2026-07-22. /record/TRV-2026-0470 (accessed at citation time). sha256 4979bf16116f34f5…
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