Publications

This paper shows that real estate wealth inequality affects vulnerability to environmental risks. I measure the heterogeneity in vulnerability to risks using dwelling-level French data for the universe of owner-occupied, rental, second, and vacant dwellings, linking these properties to the disposable income and real estate wealth of their owners. Homeowners owning only their primary residence are highly vulnerable to risk due to limited real estate wealth, whereas most owners of rental, second and vacant homes diversify their assets, exposing only a fraction of their real estate wealth to environmental risks. I show that these findings matter for adaptation policies. Place-based policies such as building infrastructures may fail to target the most vulnerable places if local ownership structures are not taken into account. In addition, a subsidized natural disaster insurance that would not target the most vulnerable households could benefit substantially the wealthy and well-diversified ones.

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.

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 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.

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.