Rental Housing Market and Directed Search
This paper introduces new empirical findings concerning the rental housing market in the Paris metropolitan area. Combining a new dataset gathered from online advertisements for Parisian rentals with a hedonic model that incorporates both apartment features and property-specific photographs, two main stylized facts are established. First, with comparable property features, landlords who ask for lower rent attract a greater number of applicants, consistent with predictions from standard directed search models. Second, many landlords employ a two-stage pricing approach, initially advertising a high rent and then reducing it after a “wait-and-see” period. This previously unreported feature is consistent with the slow Dutch auction mecha-nism studied in the auction literature and observed in the property sales market.
Keywords: Rental Housing Market; Hedonic Model; Directed Search Models; Landlords’ Pricing Strategies; Machine Learning
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