Daniela Arlia*, Elie Vidal-Naquet**
AMU - AMSE
5-9 boulevard Maurice Bourdet
Camille Hainnaux: camille.hainnaux[at]univ-amu.fr
Daniela Horta Saenz: daniela.horta-saenz[at]univ-amu.fr
Jade Ponsard: jade.ponsard[at]univ-amu.fr
Nathan Vieira: nathan.vieira[at]univ-amu.fr
*Using a large listing dataset, I empirically show that the housing prices and rents evolved differently across and within sub-markets over nationwide housing cycles in Germany, providing evidence of the segmentation of the housing markets. In particular, I show two relevant empirical facts: 1) the price-to-rent ratio is highly heterogeneous across cities; 2) the return differentials between different housing quality tiers are lower in big cities compared to the rest of the country. The first fact contradicts the standard economic theory for which rental values should reflect the discounted prices. The second fact shows that shifts in the housing price distributions are not always homothetic. In order to explain these facts, I build up on the assignment model framework in which housing is segmented by various quality tiers and demand-driven shocks could generate spillovers both up and down, depending for the composition of the demand and the supply constraints of the local housing market. Combining the housing data with administrative panel data on the labor market, I exploit the cross-sectional variation in the exposure to technological change to build a quasi-experimental design for studying how demand-driven shocks that affect the local skills composition induce changes in the prices of both high-end and low-end housings. I finally discuss the implications for the welfare conditions of different types of workers across and within locations.
**We investigate how firm market power affects the French labor market. We distinguish between market power in product markets, measured by markups, and labor markets, measured by markdowns. The former expresses the price to marginal cost ratio, and the latter is defined as the marginal revenue product of labor over wages paid. To measure markups and markdowns on the firm level, we exploit exhaustive production data, which we augment with employer-employee data information over the period 1996-2020. We examine the impact of firm market power on wages, employment, sorting, and wage inequality.