L'impact de Politiques Publiques sur le marché du logement

par Mariona Segú

Projet de thèse en Sciences économiques

Sous la direction de Miren Lafourcade et de Gabrielle Fack.

Thèses en préparation à Paris Saclay , dans le cadre de Sciences de l'Homme et de la Société , en partenariat avec Réseaux Innovation Territoires et Mondialisation (laboratoire) et de Université Paris-Sud (établissement de préparation de la thèse) depuis le 01-09-2015 .

  • Titre traduit

    Impact of Public Policies in the Housing Market


  • Résumé

    Abstract of first chapter: “Taxing Vacant Apartments: can fiscal policy reduce vacancy?” We provide the first evaluation of a tax on vacant housing. This instrument has increasingly been used by governments to reduce vacancy in large and dense cities with tight housing markets. We use the quasi-experimental setting of the implementation of a tax on vacancy in France in 1999 to identify the direct causal effect of the tax on the vacancy rate. Exploiting an exhaustive fiscal data set, which contains information on every dwelling in France from 1995 to 2013, we implement a Difference-in-Difference approach combined with a Propensity Score Matching strategy. Our results suggest that the tax was responsible for a 13% decrease in vacancy rates between 1997 and 2001. This impact is twice as high for municipalities with an initially high vacancy level. Our results also suggest that most of the vacant dwellings became primary residences. Research proposal for the second chapter: “Do short-term rent platforms affect rents? Evidence from Airbnb in Barcelona “ Recent technology improvements and the widespread use of Internet have made sharing assets cheaper and easier than ever. Physical assets can now be disaggregated and consumed as services thanks to the reduction of transaction cost enabled by the Internet. Users of the net are able of browsing, choosing and renting a room, a car lift or even a surfboard from another private user. In the case of housing, Airbnb has become a fierce competitor for the hotel industry with more than 2 million room's listing in 190 countries. In the same time, it has also became an attractive alternative for multiple-house owners who prefer renting their dwelling for shorter periods in Airbnb rather than for a longer period to a stable tenant. Therefore, some of the supply of the house renting market has shift to the tourism sector. In this context, it is crucial to assess to what extent the volume of supply shifting from housing to the tourism sector has had an impact on renting prices. The case of the city of Barcelona appears to be particularly convenient for this analysis. Tourism in Barcelona hasn't ceased to increase; in 2015 it was the 3rd most visited city in Europe and the 20th in the world, receiving up to 8.3 million people in 2015, more than 5 times its population. At the same time, while rents were on a decreasing pattern following the financial crisis, they have started to scale back up in 2015. Media and politicians have started to blame the illegal tourist apartments as the cause of the rise in rents but no causality has been identified so far. I propose to assess the impact of the apparition of airbnb on house rents and prices through an instrumental variable strategy in the context of Barcelona. Broadly speaking, I propose to use distance to important landmarks as an instrument to predict airbnb density. Given that being close to a landmark is likely to impact house prices and rents as well as airbnb density, I will first estimate this impact in the period before airbnb and then work with the first difference of the variables. Hence, for the instrument to be exogenous I need to assume that even if house prices are affected by the proximity to landmarks, this impact is constant over time. The exclusivity assumption is then relaxed thanks to the use of the time dimension. Therefore, any change in the price caused by the proximity to a landmark would be the impact of being in an area with a higher airbnb density. I plan to apply this strategy in the context of Barcelona using data on rents at the neighbourhood level (73 neighbourhoods) and combining it with data from the Inside airbnb, an online site collecting data on airbnb listing and host since 2015. The pass-through of property taxes into housing prices and rents. Evidence from Spanish Big Municipalities (with Clara Martínez-Toledano (PSE)) The local property tax on housing is a major component of local government revenues and of consumers' housing costs in developed countries. Yet, there is still neither an empirical nor a theoretical consensus on the incidence of local property taxes. We analyse empirically the incidence of local property taxes on housing prices and rents using a panel of administrative data at the municipal level from Spanish cities larger than 25,000 inhabitants for the period 2006-2017. We exploit the exogeneity of the updates of the cadastral value in order to look at the incidence of this fiscal instrument on housing prices and rents. More specifically, we implement an IV strategy and instrument the change in the tax liability by the timing of the update. We add to the literature by focusing on both the impact of housing prices and rents and through the use of a novel identification strategy to analyse the incidence of large property tax changes on housing prices and rents.