Abstract
Social Scientists and policy makers need precise data on market rents. Yet, while housing prices are systematically recorded, few accurate data sets on rents are available. In this paper, we present a new data set describing local rental markets in France based on online ads collected through to webscraping. Comparison with alternate sources reveals that online ads provide a non biased picture of rental markets and allow coverage of the whole territory. We then estimate hedonic models for prices and rents and document the spatial variations in rent-price ratios. We show that rents do not increase as much as prices in the tightest housing markets. We use our dataset to estimate the market rent of each transaction and of social dwellings. In the latter case,this allows us to estimate the in-kind benefit received by social tenants which is mainly driven by the level of private rent in their municipality.
Highlights
Having precise knowledge of local rental markets has been a growing interest for policy makers and researchers
We show that rents does not increase as much as prices in the tightest housing markets
They cannot be used to monitor the rental dynamics of a city or an urban area. They do not allow monitoring of the market of new leases, but are representative of the whole rental sector where rent revision is regulated. Another dataset exists at the family branch of Social Security, which is collecting information provided by recipients of housing allowances
Summary
Having precise knowledge of local rental markets has been a growing interest for policy makers and researchers. In France, local taxes such as housing or property taxes should be based on the rental value of dwellings. The 2020 Finance Law provides that rental values have to be reviewed before 2026, requiring the collection of additional data for this purpose. Between December 2015 and January 2018, we periodically collected, cleaned and analyzed housing rental ads from the two largest French real estate websites. These two websites were the leaders in the market with a monthly stock of ads on the rental market oscillating between 500,000 and 750,000 [5,6,7]. We use our dataset to estimate the market rent of each transaction and social dwellings. Market rent can be used to measure the in-kind benefit received by social tenants which is mainly driven by the level of private rent in the municipality
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