This paper introduces new empirical findings concerning the functioning of the rental housing market. Utilizing a unique dataset gathered from online advertisements for Parisian rentals, along with a hedonic model that incorporates both apartment features and property-specific photographs, two main stylized facts are established. First, landlords who offer lower rent, while keeping property features constant, attract a greater number of applicants, consistent with predictions from standard directed search models. Second, a previously unreported trend in landlords’ pricing strategies is identified: a significant portion employ a two-stage pricing approach, initially setting a high advertised rent and subsequently reducing it after a “wait-and-see” period, consistent with the slow Dutch auction mechanism already studied in the auction literature and empirically observed in the property sales market.

Keywords: Rental Housing Market; Hedonic Model; Directed Search Models; Landlords’ Pricing Strategies; Machine Learning

JEL Classification: R31, R21, C21, D83, C45