I am Thomas Bézy, third year PhD candidate at the Paris School of Economics under the supervision of Katrin Millock and Lucas Chancel. My research is centered on inequalities on the housing market, with a particular focus on adaptation to climate change. I am also a research fellow at the World Inequality Lab.
I am currently visiting UC Berkeley Haas under the supervision of Antoine Levy at the Fisher Center for Real Estate.
You can find my CV here, contact me using this email address: thomas.bezy[at]psemail.eu and find my publications and working papers below.
To make flood insurance affordable, several countries subsidize premiums in high-risk areas. This paper examines the effects of the French flood insurance policy, one of the most heavily subsidized systems, which mandates coverage and requires all households to pay premiums not indexed to risk exposure. Using fine-grained data on dwellings along the French-Belgian border, I analyze the 1982 implementation of this system and find a large increase in new construction in flood-prone areas, raising total flood costs by 1.5% since 1982. Despite these behavioral responses, subsidies may still benefit mobility-constrained households in high-risk areas. Using the reduced-form estimates, I calibrate a location choice model along with a social insurance framework to recover optimal subsidies. I also simulate how complementing subsidies with policies like land-use regulation and taxes on new constructions in flood-prone areas could enhance welfare. This study provides policymakers with new estimates and counterfactual policy options for offering flood insurance coverage.
This paper quantifies how natural disaster risks are distributed across tenants, homeowners and multi-property owners. I measure the heterogeneity in exposure to risks using dwelling-level French data for the universe of dwellings, linking these properties to the disposable income and real estate wealth of their owners. Renters and homeowners owning only their primary residence are highly exposed to natural disasters; whereas multi-property owners expose only a fraction of their real estate wealth to environmental risks. Using Storm Alex as a case study, I find that these disparities in exposure lead to pronounced differences in post-disaster recovery. Lastly, I draw implications for policy: place-based interventions, such as resilient infrastructure projects, may fail to target the most exposed households if ownership and occupancy patterns are ignored; and untargeted subsidized natural disaster insurance could disproportionately benefit multi-property owners.
This paper demonstrates that unpaid rent risk makes landlords reluctant to supply housing services to fragile tenants; and that insuring owners against it improves the access of renters to high-opportunity neighborhoods. We study the implementation of Visale, a publicly funded rent guarantee insurance policy in France, free of charge to eligible tenants and landlords. We demonstrate that the non-payment guarantee increased access to private-sector rental housing for eligible tenants. The scheme eased the spatial mobility of low-income renters towards higher-wage, higher-rent locations. It led to new household formation, some reallocation of the vacant housing stock, and substitution out of public housing, but may have displaced ineligible households in tighter housing markets.
Landlords and tenants, on average, have opposite characteristics; but they display positive assortative matching within rental markets. In a nationwide data set containing administrative information on linked renter-occupiers and owners of investment properties in France, we document assortative matching by income level and composition, wealth, age, marital status and family structure, both across and within fine geographic segments. Consistent with a novel theory of rental housing assignment, the income correlation is only partially explained by observable characteristics such as location, size, or investment timing. This pattern has substantial implications for returns to wealth, and the incidence of housing market policies.
This article examines the difficulties anticipated by companies in France when it comes to recruiting staff. We match several data sources to examine how recruitment difficulties are distributed by sector, location and size of the establishment and employment area characteristics. Together, these factors explain around 6% of the total variation in recruitment challenges, increasing to 14% when incorporating recruitment difficulties reported in the previous year. Most of the recruitment difficulties anticipated thus result from factors not observed in the data used in this article, potentially linked to the internal characteristics of each establishment, such as the quality of management and specific recruitment processes.
Applied Econometrics for Master students, Fall 2023
Undergraduate Econometrics, Spring 2023
Undergraduate Mathematics, Fall 2022
Undergraduate Mathematics, Spring 2021