Matteo Saccarola

Matteo Saccarola

Economics PhD Candidate

Research

Job Market Paper

Geographic Price Extrapolation, Learning, and Housing Search: Evidence from Danish Movers

Abstract [PDF] Using population-wide Danish administrative registers on housing transactions, I document an asymmetric, hockey-stick relationship between origin market prices and overpayment for comparable homes. Quantitatively, the elasticity of overpayment with respect to the origin-destination price difference is 3.9 percent (p < 0.01) when movers relocate from more expensive to cheaper housing markets. In contrast, buyers moving to more expensive locations exhibit little systematic overpayment, and their purchase prices are unrelated to prices at origin. I interpret these patterns through a housing search model in which buyers enter with price beliefs anchored in their origin market and update those beliefs gradually during search. Despite homogeneous learning, endogenous stopping generates the observed asymmetry at purchase: buyers predisposed to overpay transact quickly before fully learning the local price level, while those predisposed to underpay search longer and converge toward local prices. The model yields additional predictions that I test using administrative and survey data. The evidence supports origin-based price extrapolation with subsequent learning rather than preference-based explanations such as reference dependence. A calibration illustrates that even a small inflow of misperceiving nonlocal buyers can raise equilibrium prices in destination markets



Working Papers

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)
Revise-and-resubmit (second round) at the Quarterly Journal of Economics

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.


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.