Market heterogeneity and the determinants of Paris apartment prices

A quantile regression approach

Dados Bibliográficos

ID10864751
AutoresCharles-Olivier Amédée-Manesme (0000-0002-9192-7228, Université Laval), Michel Baroni (0000-0001-7462-7584, École Supérieure des Sciences Économiques et Commerciales), Fabrice Barthélémy (0000-0002-3484-3116, CEMOTEV, Université de Versailles Saint-Quentin-en-Yvelines; THEMA, Université de Cergy-Pontoise, France), François Des Rosiers (0000-0002-3542-8504, Université Laval, autor correspondente)
Ano2017
Volume54
Fascículo14
Páginas3260-3280
Data de publicação2017-11-01
Peer ReviewedSim
Open AccessSim
TipoARTICLE
PeriódicoUrban Studies (JOURNAL)
Identificadores do periódicoISSN: 0042-0980 • E-ISSN: 1360-063X
EditoraSAGE Publications (PUBLISHER • US)
DOI10.1177/0042098016665955
OpenAlexW2203042035
IdiomaEN
Referências citadas32

In this paper, the heterogeneity of the Paris apartment market is addressed. For this purpose, quantile regression is applied – with market segmentation based on price deciles – and the hedonic price of housing attributes is computed for various price segments of the market. The approach is applied to a major data set managed by the Paris region notary office (Chambre des Notaires d’Île de France), which consists of approximately 156,000 transactions over the 2000–2006 period. Although spatial econometric methods could not be applied owing to the unavailability of geocodes, spatial dependence effects are shown to be adequately accounted for through an array of 80 location dummy variables. The findings suggest that the relative hedonic prices of several housing attributes differ significantly among deciles. In particular, the elasticity coefficient of the apartment size variable, which is 1.09 for the cheapest units, is down to 1.03 for the most expensive ones. The unit floor level, the number of indoor parking slots, as well as several neighbourhood attributes and location dummies all exhibit substantial implicit price fluctuations among deciles. Finally, the lower the apartment price, the higher the potential for price appreciation over time. While enhancing our understanding of the complex market dynamics that underlie residential choices in a major metropolis such as Paris, this research provides empirical evidence that the QR approach adequately captures heterogeneity among house price ranges, which simultaneously applies to housing stock, historical construct and social fabric

Apartment · Decile · Econometrics · Economics · Geography · Market segmentation · Microeconomics · Quantile regression · Statistics · Stock (firearms · Engineering · Housing Market and Economics · Mathematics · Regional Economics and Spatial Analysis · Spatial and Panel Data Analysis

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