I’m Thomas Bézy, second 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 a research fellow at the Social Economics Lab and at the World Inequality Lab.
I am visiting the London School of Economics until June 2024.
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.
Who is exposed to flood risk? This paper documents the vulnerability and exposure to flood risk with fine-grain data for the universe of homeowners, landlords and tenants in France. I measure vulnerability to floods, diversification strategies and sorting over flood risk across the income and wealth distributions. I find evidence of a two-dimensionnal inequality. Low-income households are both more vulnerable and more exposed to flood risk. I derive the implications of these findings for adaptation policies. (1) The cost buying back homes at risk could be divided by five if it focused on low-income homeowners. (2) A subsidized flood insurance policy funded by insurance premiums would make low-income households transfer 3% of annual flood losses to high-income households through regressive premiums.
Alleviating unpaid rent risk can influence landlords’ willingness to supply housing, and, in turn, the access of constrained tenants to high-opportunity neighborhoods. To examine the consequences of insuring landlords against unpaid rent, we study the implementation of Visale, a publicly funded insurance covering unpaid rent risk in France, free of charge for eligible landlords and tenants. We show that the guarantee improved access to rental housing for eligible tenants. Administrative registry and income tax information on all French households as well as confidential data on Visale beneficiaries show that the scheme increased the directed migration of treated low-income renters towards high-opportunity, high-rent neighbourhoods. It led them to form new households and substitute out of public housing, but potentially displaced some untreated households in the “housing rat race”.
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 study investigates the factors that contribute to difficulties that firms face when trying to recruit new employees. We match firm surveys to firm’s tax records and administrative data to see how factors such as industry, location, company size, and employment characteristics affect recruitment difficulties. Our results show that about 10% of the variance in recruitment difficulties can be explained by these observable factors, and up to 14% when considering difficulties from the previous year. However, most of the difficulties encountered by companies are due to factors not captured by our data, which may be related to internal characteristics of the company such as management quality and the recruitment process.
Applied Econometrics for Master students, Fall 2023
Undergraduate Econometrics, Spring 2023
Undergraduate Mathematics, Fall 2022
Undergraduate Mathematics, Spring 2021