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Is Education No Longer the 'Great Equalizer'?

Income Gap Analysis Among Black and White Americans

Project Overview

This project explores the relationship between educational attainment and income inequality in the United States, focusing on racial disparities between Black and White Americans. Using data from the American Community Survey (ACS), the study evaluates whether higher education levels correspond to greater earning potential and how these relationships differ by race.

Objectives

  1. Analyze the correlation between income and education across racial groups.
  2. Identify disparities in the correlation between income and higher education for Black and White Americans.
  3. Examine spatial patterns of income and educational disparities across U.S. states.

Data

  • Sources: American Community Survey (ACS)
  • Data Focus:
    • Annual income per capita
    • Percentage of college degree holders
  • Time Frame: 2005–2013
  • Racial/Ethnic Groups Analyzed: Black, White, Hispanic, Asian

Tools and Technologies

  • Languages: R
  • Libraries: ggplot2, dplyr, tidyr, sf, leaflet
  • Methods:
    • Correlation analysis
    • Geographic mapping of income and education data
    • Temporal trends and spatial visualization

Key Findings

  1. White Americans exhibit the highest correlation between income and education (0.94), while Black Americans show the lowest (0.42).
  2. Coastal states display stronger correlations for White Americans, while correlations for Black Americans are weaker or even negative in several states.
  3. Maps of income per capita reveal stark disparities between Black and White Americans, with the largest gaps observed in the Midwest and Northeast.

Outcomes

  • Spatial visualizations of income and education correlations by race.
  • Identification of regions with the highest racial disparities in education-income relationships.
  • Insights into the systemic barriers faced by Black Americans in leveraging higher education for increased income.

Future Work

  • Analyze income and education correlations at the county level.
  • Investigate additional factors influencing disparities, such as occupational segregation and access to education.
  • Examine trends over time to identify areas of improvement or stagnation.