Abstract We use a revealed-preference approach to estimate investor expectations of stock market returns. Using data on demand for index funds that follow the S&P 500, we develop and estimate a model of investor choice to flexibly recover the time-varying distribution of expected future returns across investors. Our analysis is facilitated by the prevalence of leveraged funds that track the same underlying asset: by choosing between higher and lower leverage, investors trade off higher return against less risk. Our estimates indicate that investor expectations are heterogeneous, extrapolative, and persistent. Following a downturn, investors become more pessimistic on average, but there is also an increase in disagreement among participating investors due to the presence of contrarian investors.

Abstract We present a portfolio choice demand model that allows for the nonparametric estimation of investors’ (subjective) expectations and risk preferences. Using comprehensive 401(k)-plan-level data from 2009 through 2019, we explore heterogeneity in asset allocations using our empirical framework. We recover investors’ beliefs about each asset and examine the implications and potential sources of those beliefs. Heterogeneity in expectations across investors accounts for twice as much variation in portfolio holdings as heterogeneity in risk aversion. Belief heterogeneity is partly driven by investors’ characteristics and experiences, reflecting local sources of information such as county-level GDP and employers’ past performance.

We develop a new nonparametric approach for discrete choice and use it to analyze the demand for health insurance in the California Affordable Care Act marketplace. The model allows for endogenous prices and instrumental variables, while avoiding parametric functional form assumptions about the unobserved components of utility. We use the approach to estimate bounds on the effects of changing premiums or subsidies on coverage choices, consumer surplus, and government spending on subsidies. We find that a $10 decrease in monthly premium subsidies would cause a decline of between 1.8% and 6.7% in the proportion of subsidized adults with coverage. The reduction in total annual consumer surplus would be between $62 and $74 million, while the savings in yearly subsidy outlays would be between $207 and $602 million. We estimate the demand impacts of linking subsidies to age, finding that shifting subsidies from older to younger buyers would increase average consumer surplus, with potentially large impacts on enrollment. We also estimate the consumer surplus impact of removing the highly‐subsidized plans in the Silver metal tier, where we find that a nonparametric model is consistent with a wide range of possibilities. We find that comparable mixed logit models tend to yield price sensitivity estimates toward the lower end of the nonparametric bounds, while producing consumer surplus impacts that can be both higher and lower than the nonparametric bounds depending on the specification of random coefficients.

We use credit report data to study consumer financial distress in America. We report large, persistent disparities in financial distress across regions. To understand these patterns, we conduct a “movers” analysis. For collections and default, there is only weak convergence following a move, suggesting these types of distress are not primarily caused by place-based factors (e.g., local economic conditions and state laws) but instead reflect person-based characteristics (e.g., financial literacy and risk preferences). In contrast, for personal bankruptcy, we find a sizable place-based effect, which is consistent with anecdotal evidence on how local legal factors influence personal bankruptcy.Authors have furnished an Internet Appendix, which is available on the Oxford University Press Web site next to the link to the final published paper online.