Housing and discrimination in economics : an empirical approach using Big Data and natural experiments[Logement et discrimination en économie : une approche empirique mêlant expérience naturelle et Big Data]

The first chapter documents a key parameter to understand the housing market: the elasticity of housing supply in French urban areas. We show that this elasticity can be apprehended in two ways by considering the intensive and extensive supply of housing. Thanks to a large amount of new data collected and an original estimation strategy, this first chapter estimates and decomposes the two elasticities. The second chapter is devoted to the possibilities offered by Big Data for studying the French rental housing market. By using online data from December 2015 to June 2017 and comparing this data with traditional administrative data, we find that the Internet provides data to accurately track local real estate markets.The third chapter deals with the discrimination of women in politics. It exploits a natural experiment, the French departmental elections of 2015 during which, for the first time in the history of the French elections, the candidates had to present themselves in pairs of candidates necessarily mixed. Using the fact that the order of appearance of the candidates on a ballot was determined by the alphabetical order and showing that this rule does not seem to have been used strategically by the parties, we show, first, that the position of women on the ballot is random, and second, that the right-hand pairs for whom the name of the female candidate is in first position on the ballot receive on average 1.5 percentage points less than votes.