Forward to the Past: Short-Term Effects of the Rent Freeze in Berlin

Anja Hahn, Konstantin A. Kholodilin, Sofie Waltl*, Marco Fongoni

*Korrespondierende*r Autor*in für diese Arbeit

Publikation: Wissenschaftliche FachzeitschriftOriginalbeitrag in FachzeitschriftBegutachtung


In 2020, Berlin introduced a rigorous rent-control policy responding to soaring prices by capping rents: the Mietendeckel (rent freeze). The German Constitutional Court revoked the policy only one year later. Although successful in lowering rents during its duration, the consequences for Berlin’s rental market and close-by markets are per se not clear. This article evaluates the short-term causal supply-side effects in terms of prices, quantities, and landlords’ strategic behavior. We develop a theoretical framework capturing the key features of first-generation rent control policies and Berlin-specific aspects. Using a rich pool of detailed rent advertisements, predictions are tested, and further empirical causal inference techniques are applied for comparing price trajectories of dwellings inside and outside the policy’s scope. Mechanically, advertised rents drop significantly upon the policy’s enactment. A substantial rent gap along Berlin’s administrative border emerges, and rapidly growing rents in Berlin’s (unregulated) adjacent municipalities are observed. Landlords started adopting a hedging strategy insuring themselves against the risk of contractually long-term fixed low rents following a potentially unconstitutional law. Whereas this hedge was beneficial for landlords, the risk was completely borne by tenants. Moreover, the number of available properties for rent dropped significantly, a share of which appears to be permanently lost for the rental sector. This hampers a successful housing search for first-time renters and people moving within the city. Overall, negative consequences for renters appear to outweigh positive ones.
FachzeitschriftManagement Science
PublikationsstatusElektronische Veröffentlichung vor Drucklegung - Mai 2023