Can Big Data Increase Our Knowledge of Local Rental Markets?
Download Document| Date Published | 2017 |
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| Primary Author | Guillaume Chapelle and Jean-Benoît Eyméoud |
| Other Authors | |
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| Country | France |
Abstract
The French rental market is largely unknown despite its considerable weight in public spendings. In this paper we develop a new method based on web scraping to observe the rental market from web activity. We present a new database based on adds posted on the two main French real estate websites between December 2015 and June 2017. After discussing the potential bias caused by the method, we argue that web activity is a faithful way to observe market rent levels and, on the long run, to follow the dynamics of the rental market. We provide estimates of the level of rent of a representative good in the main French urban areas. Finally, we illustrate one possible use for our database by estimating the distribution of the implicit subsidy related with the access to a social housing unit.