Climate change drives up the cost of flood insurance coverage for homeowners. To mitigate these costs, many governments have opted to subsidize insurance. At the same time, reducing the cost of insurance in flood risk areas gives incentives for inefficient housing development in these places. In this paper, I recover the set of welfare weights that justify implementing the French subsidized insurance system. Leveraging unique fine-grain data in France for the universe of dwellings and households, I provide new stylized facts on exposure to flood risk by occupancy status, including owner-occupied, rental and second homes. I use these findings to simulate a quantitative spatial model with heterogeneous households, characterized by their income and dwelling's occupancy type. Results suggest that if barriers to mobility are high for low-income homeowners, a standard utilitarian welfare function may already justify subsidizing insurance. This paper offers policymakers insights on the benefits and costs of subsidizing insurance and highlights the need to address inequalities in flood insurance design.
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.