Investors’ return expectations are pivotal in stock markets, but the reasoning behind these expectations is not well understood. This paper explores economic agents’ mental models of what drives returns. We survey the general population, retail investors, financial professionals, and academic experts to investigate how they forecast and explain future returns in scenarios with stale news about future company earnings. We find that investors strongly disagree in their forecasts and reasoning. Most academic experts view markets as efficient. By contrast, most households express a perspective we call “expected earnings reasoning”: they directly equate higher expected earnings with higher expected returns. Professionals are split between market efficiency, mispricing, and expected earnings reasoning. In detailed experiments, we dissect why households adopt expected earnings reasoning. We show that it arises from inattention to how stock-price changes affect investor costs — that is, how much investors must pay to acquire a claim to future cash flows — because the typical format and context of investment problems obscure these cost implications. Our results help connect a series of previously documented anomalies in expectation and trading data and highlight the importance of selective attention and context in shaping reasoning and belief formation.

Using a representative online panel from the United States, we examine how individuals' macroeconomic expectations causally affect their personal economic prospects and their behavior. To exogenously vary respondents' expectations, we provide them with different professional forecasts about the likelihood of a recession. Respondents update their macroeconomic outlook in response to the forecasts, extrapolate to expectations about their personal economic circumstances, and adjust their consumption plans and stock purchases. Extrapolation to expectations about personal unemployment is driven by individuals with higher exposure to macroeconomic risk, consistent with macroeconomic models of imperfect information in which people are inattentive but understand how the economy works.

Information provision experiments allow researchers to test economic theories and answer policy-relevant questions by varying the information set available to respondents. We survey the emerging literature using information provision experiments in economics and discuss applications in macroeconomics, finance, political economy, public economics, labor economics, and health economics. We also discuss design considerations and provide best-practice recommendations on how to (i) measure beliefs; (ii) design the information intervention; (iii) measure belief updating; (iv) deal with potential confounds, such as experimenter demand effects; and (v) recruit respondents using online panels. We finally discuss typical effect sizes and provide sample size recommendations.

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 survey a representative sample of U.S. households to study how exposure to the COVID-19 stock market crash affects expectations and planned behavior. Wealth shocks are associated with upward adjustments of expectations about retirement age, desired working hours, and household debt but have only small effects on expected spending. We provide correlational and experimental evidence that beliefs about the duration of the stock market recovery shape households' expectations about their own wealth and their planned investment decisions and labor market activity. Our findings shed light on the implications of household exposure to stock market crashes for expectation formation.

We conduct a field experiment with US households to study how expectations about long-run home price growth shape spending decisions. We exogenously vary survey respondents' expectations by providing different expert forecasts. Homeowners' spending, measured using rich home-scanner data, is inelastic to home price expectations. By contrast, renters reduce their spending when expecting higher home price growth. These patterns reflect positive wealth effects for owners from higher future wealth and negative income effects for both groups due to higher future housing costs. Our study highlights consequences of asset price growth and long-term expectations about the economy for household behavior.

We study people’s subjective models of the macroeconomy and shed light on their attentional foundations. To do so, we measure beliefs about the effects of macroeconomic shocks on unemployment and inflation, providing respondents with identical information about the parameters of the shocks and previous realizations of macroeconomic variables. Within samples of 6, 500 US households and 1, 500 experts, beliefs are widely dispersed, even about the directional effects of shocks, and there are large differences in average beliefs between households and experts. Part of this disagreement seems to arise because respondents think of different propagation channels of the shocks, in particular demand- vs. supply-side mechanisms. We provide evidence on the role of associative memory in driving heterogeneity in thoughts and forecasts: contextual cues and prior experiences shape which propagation channels individuals retrieve and thereby which forecasts they make. Our findings offer a new perspective on the widely documented disagreement in macroeconomic expectations.

We examine how adverse local experiences that are uninformative of future returns affect households’ investment behavior in the short term. Using data from a German online brokerage and a survey, we show that retail investors sharply reduce risk taking in response to nearby firm bankruptcies. Adjustments in risk taking occur through immediate and transitory increases in trading, and work through more pessimistic expectations about aggregate stock returns and increased risk aversion. Changes in background risks or wealth effects cannot explain our findings. Extrapolation from local experiences to aggregate expectations is inconsistent with optimal use of full or limited information.

We survey retail investors at an online bank to study how beliefs about the autocorrelation of aggregate stock returns shape investment decisions measured in administrative account data. Individuals’ beliefs exhibit substantial heterogeneity and predict trading responses to market movements. We inform half of our respondents that, historically, the autocorrelation was close to zero, which causes them to update their perceived current autocorrelation and return expectations. The treatment shifts respondents’ equity purchases during the COVID-19 crash months later in the direction implied by the intervention. Our results provide causal evidence about the drivers of disagreement and trade in asset markets.