To mitigate the rising costs of flood insurance, several high-income countries have implemented subsidies to lower premiums in high-risk areas. While helping mobility-constrained, low-income homeowners afford insurance, these policies come at the cost of distorting incentives to locate in flood-prone areas. In this paper, I measure the benefits and costs of subsidizing insurance. I conduct the analysis for France, one of the countries subsidizing flood insurance to the largest extent. First, leveraging unique fine-grain data for the universe of dwellings and households, I provide new stylized facts on flood risk exposure by occupancy status: owner-occupied, rental and second homes. Second, historical data at the French-German border allows me to identify the effects of the 1982 implementation of the French system on new construction projects. Third, I incorporate these mechanisms into a quantitative spatial model where households have heterogeneous income and occupancy status. I find that even with a utilitarian welfare function, subsidizing insurance may be justified if homeowners are not perfectly mobile. This paper offers policymakers a framework, as well as estimates, to think about the effects of subsidizing insurance.

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 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.