Research

Publications

Beliefs About the Economy are Excessively Sensitive to Household-Level Shocks: Evidence from Linked Survey and Administrative Data
(with Luigi Butera, Chen Lian, and Dmitry Taubinsky)
Quarterly Journal of Economics, forthcoming

Abstract [PDF] We study how people's beliefs about the economy covary with household-level events, utilizing a unique link between Danish administrative data and a large-scale survey of consumer expectations. We find that compared to actual inflation, people's inflation forecasts covary much more strongly (and negatively) with both recently realized household income changes and measures of expected future household income changes. We formally establish that these findings are stark deviations from the Bayesian rational expectations benchmark. Similar results hold for perceptions of past inflation ("backcasts"), suggesting that imperfect recall is a key mechanism for biased forecasts. Building on this, a series of additional tests, some of which utilize data on adverse health events, suggests that the forecast biases are at least partly due to affect-cued recall. That is, negative (positive) household-level events cue negative (positive) recollections, which lead to pessimistic (optimistic) forecasts.


Working Papers

Geographic Price Extrapolation, Learning, and Housing Search: Evidence from Danish Movers
2026 American Real Estate and Urban Economics Association Best Junior Paper Prize

Abstract [PDF] I show that homebuyers who move across cities extrapolate house price levels from their origin markets to their destination markets. Using population-wide Danish administrative registers on housing transactions, I document an asymmetric, hockey-stick relationship between origin prices and overpayment for comparable homes: moving one standard deviation down in the housing price distribution (i.e., from a more expensive to a cheaper area) yields a 3.1% quality-adjusted overpayment relative to local homebuyers; by contrast, among movers into more expensive markets, overpayment is small and unrelated to origin prices. I interpret these facts with a housing search model in which buyers arrive with origin-based price beliefs and learn at a common rate during search. Despite symmetric learning, endogenous stopping creates asymmetry at the time of purchase: buyers whose beliefs imply willingness to overpay are quickly accepted by sellers and transact before fully learning the local price level, whereas buyers whose beliefs imply underpaying face more rejections, search longer, and therefore converge toward local prices. The model delivers additional predictions that I test in the administrative data and in a survey. The evidence favors origin-price extrapolation with subsequent learning over preference-based explanations such as reference points.


The Intergenerational Effects of Health Shocks: Location Choice, Homeownership, and Family Formation
(with Elin Colmsjö and Francesco Ruggieri)

Abstract We leverage Danish administrative data to study intra-household responses to unanticipated health shocks affecting the parents of working-age adults. Using a research design that compares similarly aged individuals whose parents experience a stroke at different times, we find that parental health shocks lead to reductions in adult children's income, lower rates of homeownership, increased geographic proximity to parents, and decreased likelihood of marriage. Heterogeneity analyses show that the non-pecuniary consequences are more pronounced among women. We then focus on the location margin and develop a model of residential location choice that features distance from parents and health shocks. By linking our reduced-form estimates to the model, we recover policy-relevant parameters that allow us to quantify the intergenerational consequences of parental health shocks operating through residential adjustments.


In Progress

Beliefs, Misperceptions, and Household Balance Sheets: Evidence from Surveys and Administrative Data
(with Luigi Butera, Benjamin Lockwood, and Dmitry Taubinsky)

The Price of Simplicity: Measuring the Willingness to Pay to Simplify Taxes
(with Dominic Kassirra)



Pre-Doctoral Work

Socioeconomic Network Heterogeneity and Pandemic Policy Response
(with Mohammad Akbarpour, Cody Cook, Aude Marzuoli, Simon Mongey, Abhishek Nagaraj, Pietro Tebaldi, Shoshana Vasserman & Hanbin Yang)

Abstract [PDF] We develop a heterogeneous-agents network-based model to analyze alternative policies during a pandemic outbreak, accounting for health and economic trade-offs within the same empirical framework. We leverage a variety of data sources, including data on individuals' mobility and encounters across metropolitan areas, health records, and measures of the possibility to be productively working from home. This combination of data sources allows us to build a framework in which the severity of a disease outbreak varies across locations and industries, and across individuals who differ by age, occupation, and preexisting health conditions. We use this framework to analyze the impact of different social distancing policies in the context of the COVID-19 outbreaks across US metropolitan areas. Our results highlight how outcomes vary across areas in relation to the underlying heterogeneity in population density, social network structures, population health, and employment characteristics. We find that policies by which individuals who can work from home continue to do so, or in which schools and firms alternate schedules across different groups of students and employees, can be effective in limiting the health and healthcare costs of the pandemic outbreak while also reducing employment losses.