<p>Economic inequality is a critical issue in elections and legislating, so having an informed electorate is vital to sensible policymaking. Unfortunately, misperceptions about the true extent of inequality abound. Here, we demonstrate that the most prevalent formats for representing economic distributions tend to dampen viewer impressions of inequality. We begin by showing that the most popular newspaper portrayals of inequality contain potentially biasing features. Next, in nine experiments (<i>N</i> = 3599 U.S. adults), we explore how these common representations of inequality evoke biased impressions and&#xa0;we test methods to mitigate these biases. Specifically, we document two biases in how people evaluate economic distributions. First, people are under-sensitive to differences in the size of identified population groups (e.g., top 1% vs. top 10%) such that their judgments become distorted by arbitrary ways in which a population is divided (<i>partition dependence</i>). Second, people’s judgments under-weight information about intermediate groups relative to the most- and least-wealthy groups (<i>middle neglect</i>). We test ways to mitigate these biases and conclude by proposing presentation guidelines that promote more accurate impressions.</p>

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How common depictions of wealth distributions can bias people to underestimate inequality

  • Jonathan E. Bogard,
  • Colin West,
  • Craig R. Fox

摘要

Economic inequality is a critical issue in elections and legislating, so having an informed electorate is vital to sensible policymaking. Unfortunately, misperceptions about the true extent of inequality abound. Here, we demonstrate that the most prevalent formats for representing economic distributions tend to dampen viewer impressions of inequality. We begin by showing that the most popular newspaper portrayals of inequality contain potentially biasing features. Next, in nine experiments (N = 3599 U.S. adults), we explore how these common representations of inequality evoke biased impressions and we test methods to mitigate these biases. Specifically, we document two biases in how people evaluate economic distributions. First, people are under-sensitive to differences in the size of identified population groups (e.g., top 1% vs. top 10%) such that their judgments become distorted by arbitrary ways in which a population is divided (partition dependence). Second, people’s judgments under-weight information about intermediate groups relative to the most- and least-wealthy groups (middle neglect). We test ways to mitigate these biases and conclude by proposing presentation guidelines that promote more accurate impressions.