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indicator

Retirement Income & Social Security by Race

Retirement Income & Social Security by Race

Description

Share of Adults Age 65 or Older with Retirement and/or Social Security Income, by Race & Ethnicity, 2024

Data Source

American Community Survey (ACS)

Demographics
Housing
Community Infrastructure

Calculation Methodology

  1. 1
    Filter the dataset to include individuals aged 65 or older using the column AGEP.
  2. 2
    Derive race and ethnicity categories from the columns RAC1P and HISP based on specified conditions to classify groups such as Asian Only, Black or African American Only, Hispanic or Latino (Any Race), White Only, Other Single Race, and Multiple Races.
  3. 3
    Derive income groups from the columns RETP and SSP to classify individuals into Retirement Income Only, Social Security Income Only, Both Retirement and Social Security Income, and Neither Retirement nor Social Security Income.
  4. 4
    Apply the weight column PWGTP to all records to ensure representative estimates.
  5. 5
    Aggregate weighted counts by STATE and by the derived race and income group categories.
  6. 6
    Calculate the share of adults aged 65 or older within each race category who have retirement and/or social security income, presented as a stacked bar chart.

Source Variables using this Indicator (18)

Visuals Using This Indicator (1)

Visual for Indicator Retirement Income & Social Security by Race for 2024

Share of Adults Age 65 or Older with Retirement and/or Social Security Income, by Race & Ethnicity, 2024

View visualization

Why This Matters

Transparent methodology ensures every insight can be traced, verified, and built upon.

Reproducible Research

Every calculation can be traced back to its source. Our methodology documentation enables researchers to replicate findings and build upon our work.

Accountability

Clear attribution and citation requirements ensure proper credit to data providers and maintain research integrity.

Continuous Improvement

Transparent documentation allows for peer review, feedback, and iterative improvements to our analytical approaches.