We present a self- and social-signaling model formalizing findings in political psychology that moral and political judgments stem primarily from intuition and emotion, while reasoning serves to rationalize these intuitions to maintain an image of impartiality. In social interactions, agents’ rationalizations are strategic complements: others’ rationalizations weaken their ability to judge critically and make their actions less revealing of (inconvenient) truths. When agents are naive about their own rationalizations, our model predicts ideological and affective polarization, with each side assigning inappropriate motives to the other. Cross-partisan exchanges of narratives reduce polarization but are avoided by the agents. In within-group exchanges agents favor skilled speakers, whose narratives worsen polarization. Our model explains partisan disagreements over policy consequences, aligns with empirical polarization trends, and offers insights into efforts to disrupt echo chambers.

Social preferences depend on emotional states like compassion and anger. Since emotions are fleeting and subject to manipulation, they may generate demand for commitment. We investigate the use of commitment strategies in an online experiment (n = 1,400), where subjects decide to watch or avoid videos before engaging in a charitable giving task. We find that a video with emotional content increases giving, but is also avoided more than non-emotional videos. We estimate a structural model of state-dependent social preferences, and show evidence for sophisticated commitment to selfishness and altruism. We argue that giving can be fruitfully analyzed as a self-control problem.

In most countries, wealth inequality is much higher than income inequality, spurring debates about wealth taxation. However, it is unclear if voters are aware of these differences. In a large- scale survey experiment among a representative Dutch population (N=4,501), we study voters’ perceptions of income and wealth distributions, and connect their views to administrative data about their own income and wealth. Despite a primer on the definition of income and wealth, respondents underestimate the difference between the top 10% share of income and wealth by a factor of 10. Moreover, they use information about the income distribution to make predictions about the wealth distribution and vice versa, even when information about both is provided, further demonstrating confusion about the two types of inequality. An information intervention about actual inequality levels and personal ranks in the income/wealth distribution has an impact on the perceived inequality and perceived fairness of inequality, but little effect on policy preferences. We discuss implications for political debates about inequality and wealth taxation.

Inequality statistics highlight specific aspects of economic reality: economists traditionally rely on technical indices like the Gini coefficient, while recent scholarship emphasizes measures like the Top 10% income share, which more directly evoke political conflict. We investigate how inequality metrics are used in the media, and whether they shape public perceptions and support for redistribution. Across 39 prominent newspapers in eight Western countries, left-wing media are more likely than right-wing media to report top-share metrics, and less likely to report the Gini coefficient. To assess the behavioral consequences of this asymmetry, we conduct an online experiment (N = 1,246), showing that “political” measures reduce acceptance of inequality relative to the Gini coefficient, with an effect equivalent to a 0.12-0.17 point increase in the underlying Gini. Experts are less susceptible, but not immune, and overestimate the effect on the public. Thus, inequality statistics do not merely describe economic reality, but shape normative assessments of the income distribution — implying that their asymmetric use in the media amplifies political divisions.