We survey the recent literature in economics using open-ended survey data to uncover mechanisms behind economic beliefs and behaviors. We first provide an overview of different applications, including the measurement of motives, mental models, narratives, attention, information transmission, and recall. We next describe different ways of eliciting open-ended responses, including single-item open-ended questions, speech recordings, and artificial intelligence–powered qualitative interviews. Subsequently, we discuss methods to annotate and analyze such data with a focus on recent advances in large language models. Our review concludes with a discussion of promising avenues for future research.

We link survey data on Danish people’s perceived income positions and fairness views on inequality within various reference groups to administrative records on their reference groups, income histories, and life events. People are, on average, well-informed about the income levels of their reference groups. Yet, lower-ranked respondents in all groups tend to overestimate their own position among others because they believe others’ incomes are lower than they actually are, whereas the opposite holds true for higher-ranked respondents. Misperceptions of positions in reference groups relate to proximity to other individuals, transparency norms, and visible signals of income. People view inequalities within their co-workers and education groups as significantly more unfair than overall inequality, yet underestimate inequality the most exactly within these groups. Views on the fairness of inequalities are strongly correlated with an individual’s current position, move with shocks like unemployment or promotions, and change when experimentally informing people about their actual positions. However, the higher perceived unfairness of income differences within co-workers and education groups stays unchanged. The theoretical framework shows that this can have important implications for redistribution policy.

This article studies the effect of corporate and personal taxes on innovation in the United States over the twentieth century. We build a panel of the universe of inventors who patented since 1920, and a historical state-level corporate tax database with corporate tax rates and tax base information, which we link to existing data on state-level personal income taxes and other economic outcomes. Our analysis focuses on the effect of personal and corporate income taxes on individual inventors (the micro level) and on states (the macro level), considering the quantity and quality of innovation, its location, and the share produced by the corporate rather than the noncorporate sector. We propose several identification strategies, all of which yield consistent results. We find that higher taxes negatively affect the quantity and the location of innovation, but not average innovation quality. The state-level elasticities to taxes are large and consistent with the aggregation of the individual-level responses of innovation produced and cross-state mobility. Corporate taxes tend to especially affect corporate inventors’ innovation production and cross-state mobility. Personal income taxes significantly affect the quantity of innovation overall and the mobility of inventors.

We investigate the origins and implications of zero-sum thinking: the belief that gains for one individual or group tend to come at the cost of others. Using a new survey of 20,400 US residents, we measure zero-sum thinking, political preferences, policy views, and a rich array of ancestral information spanning four generations. We find that a more zero-sum mindset is strongly associated with more support for government redistribution, race- and gender-based affirmative action, and more restrictive immigration policies. Zero-sum thinking can be traced back to the experiences of both the individual and their ancestors, encompassing factors such as the degree of intergenerational upward mobility they experienced, whether they immigrated to the United States or lived in a location with more immigrants, and whether they were enslaved or lived in a location with more enslavement.

This paper explores global perceptions and understanding of climate change and policies, examining factors that influence support for climate action and the impact of different types of information. We conduct large-scale surveys with 40,000 respondents from 20 countries, providing new international data on attitudes toward climate change and respondents’ socioeconomic backgrounds and lifestyles. We identify three key perceptions affecting policy support: perceived effectiveness of policies in reducing emissions, their impact on low-income households, and their effect on respondents’ households (self-interest). Educational videos clarifying policy mechanisms increase support for climate policies; those merely highlighting climate change’s impacts do not.