Teaching Income Inequality with Data-Driven Visualization

S. Truong, H. Barreto
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Abstract

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. JEL codes: A2, C1, D6, E6, I3
用数据驱动的可视化教学收入不平等
家庭收入分配是经济学关注的焦点,因为它对社会福祉和社会凝聚力有着强烈的影响。然而,非专家受众在理解传统的不平等衡量标准方面面临严重障碍。为了有效地传达美国收入不平等的程度,我们开发了一种新技术,通过使用当前人口调查中的美国家庭收入微观数据来可视化收入分配及其随时间的分散。其结果是,随着时间的推移,收入分配呈现出惊人的动态变化,引起了公众的关注,并鼓励对收入不平等进行进一步调查。详细实施可在github.com/sangttruong/incoevis上获得。我们项目的交互式演示可在research.depauw.edu/econ/incoevis.JEL代码:A2、C1、D6、E6、I3上获得
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