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People differ in their lay theories about how and why the financial well-being of individuals changes over time or varies between individuals. We introduce a measure of Causal Attributions of Financial Uncertainty—the CAFU scale—and find that such attributions can be reliably described along three distinct dimensions, respectively capturing the extent to which changes in financial well-being are perceived to be: (1) knowable and within individuals’ control due to individual factors such as effort (“Rewarding”); (2) knowable and outside of individuals’ control due to systemic factors such as favoritism and discrimination (“Rigged”); and (3) inherently unpredictable and determined by chance events (“Random”). In a sample representative of the U.S. population on various demographic characteristics (N = 1,102), we find that differences in these beliefs are associated with political ideology, revealing a predicted pattern: conservatives scored higher on the Rewarding subscale and liberals scored higher on the Rigged and Random subscales, even when controlling for key demographics. Moreover, we find that these three dimensions predict responses to different policy messages when controlling for political ideology. In three preregistered experiments (combined N = 2,560), we observe increased support for various social welfare policies when we highlighted aspects of these policies that are compatible with people’s beliefs about financial well-being. Likewise, we observe increased support for political candidates when they expressed their positions in a way that is compatible with people’s beliefs. Thus, this work can help better understand drivers of political attitudes and guide in crafting more persuasive policy messages.

Most people want to save more money. Yet, they are often unsure how much they can or should allocate towards savings at any given time. In order to simplify these types of financial decisions, people often create a budget, organizing their finances into meaningful categories and earmarking money. Across eight pre-registered experiments (N = 4,860), we investigate how the configuration of household budgets can shape consumers’ decisions to allocate their income towards savings versus spending decisions. In Studies 1-4, we show that people often rely on a 1/n heuristic to guide their financial allocations, which can lead to systematic biases depending on how their budget is partitioned. Furthermore, we find that people use different heuristics, depending on how their budget is configured. In Studies 5-8, we identify the specific conditions under which people use therely on a 1/n heuristic in household budgeting decisions. We conclude by discussing implications for household savings decisions and other resource allocations decisions.

We provide evidence that investor behavior is sensitive to two dimensions of subjective uncertainty concerning future asset values. Investors vary in the extent to which they attribute market uncertainty to: (1) missing knowledge, skill, or information (epistemic uncertainty), and (2) chance or stochastic processes (aleatory uncertainty). Investors who view stock market uncertainty as higher in epistemicness (knowability) are more likely to reduce uncertainty by seeking guidance from experts and are more responsive to available information when choosing whether or not to invest. In contrast, investors who view stock market uncertainty as higher in aleatoriness (randomness) are more likely to reduce uncertainty through diversification and their risk preferences better predict whether or not they choose to invest. We show, further, that attributions of uncertainty can be perturbed by the format in which historical information is presented: charts displaying absolute stock prices promote perceptions of epistemicness and greater willingness to pay for financial advice, whereas charts displaying the change in stock prices from one period to the next promote perceptions of aleatoriness and a greater tendency to diversify.

People are routinely judged based on the outcomes of their predictions. In this paper we argue that the perceived nature of uncertainty critically influences ascription of credit, blame, and luck to forecasters. In one archival study and five lab studies, we demonstrate that epistemic (knowable) uncertainty is associated with attributions of credit for correct predictions and blame for incorrect predictions, whereas aleatory (random) uncertainty is associated with attributions of good luck for correct predictions and bad luck for incorrect predictions.

In this project, I explore the effect of category width on consumers’ confidence in, and extremity of their attitudes. I show that participants who have been primed with narrow (vs. broad) categories exhibit less overconfidence when asked to evaluate their performance on a trivia quiz. They also have less extreme opinions on current issues related to brands, products, and politics, and they become more tolerant to opposing viewpoints (e.g., taxation, gun control).