Teaching Income Inequality with Data-Driven Visualization
The distribution of household income is a central concern in economics due to its strong influence on society’s well-being and social cohesion. Yet, non-expert audiences face serious obstacles in understanding conventional measures of inequality. To effectively communicate the extent of income inequality in the United States, we have developed a novel technique for visualizing income distribution and its dispersion over time by using U.S. household income microdata from the Current Population Survey. The result is a striking dynamic animation of income distribution over time, drawing public attention, and encouraging further investigation of income inequality. Detailed implementation is available at github.com/sangttruong/incomevis. An interactive demonstration of our project is available at research.depauw.edu/econ/incomevis.
Sang Truong https://orcid.org/0000-0001-8069-9410
Humberto Barreto https://orcid.org/0000-0003-4822-038X
Truong, S. T., & Barreto, H. (2023). Teaching Income Inequality with Data-Driven Visualization. The American Economist, 68(1), 140–155. https://doi.org/10.1177/05694345221129022