Data Stories / Incarceration Economics

Incarceration Economics

Editorial note (2026-05-12): This data-journalism story is now published by Fivvix, DaedArch's content channel. The underlying data sources and methodology remain available via Trellison Institute's research services. Story production: Fivvix · Data + methodology: Trellison Institute · System: shared (V5 composer / Napoleon production suite)

Economic impact of incarceration on families and communities. County-level spending, employment loss, family disruption, and recidivism costs.

In Development Methodology Complete

Active Research Project

This data story is in active development. The methodology outline and visualization requirements are complete. Data collection from Pew Research and Urban Institute is in progress.

The Research Question

What is the true economic cost of incarceration — not to the state, but to the families and communities left behind? This story maps county-level data on incarceration rates against employment, income, education, and family stability metrics to show the cascading economic impact that traditional cost analyses miss.

Planned Data Sources
  • Pew Research Center: incarceration and family impact studies
  • Urban Institute: economic modeling of incarceration costs
  • Bureau of Justice Statistics: incarceration rates by county
  • Census Bureau ACS: employment, income, family composition data
  • State corrections department budgets and per-inmate costs
Production Status

Methodology: Outline complete with visualization requirements

Data Collection: In progress (Pew + Urban Institute)

Visualization: County-level economic impact mapping planned

Music: Not yet composed

Expected Completion: Q3 2026

Methodology

Economic impact analysis follows Urban Institute modeling frameworks. County-level data aggregated from BJS and Census ACS. Family impact metrics from Pew longitudinal studies. All correlational claims clearly distinguished from causal claims. Negative results reported — counties where incarceration rates do not correlate with expected economic indicators are as important as those that do.

Read our full methodology

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