SEGMENTED REAL-ESTATE MARKETS AND PRICE MECHANISMS - THE CASE OF PARIS

Statistical clustering methods can be powerful in reconstructing socia l segmentation patterns in a spatial setting. In this article, a segme ntation of the Paris real estate market is identified, and it is shown how price mechanisms differ from one segment to another. Market segme nts are determined by use of a neuronal technique. The application of Kohonen's algorithm in section 1, leads to the division of the Paris r egion into three housing market segments: superior housing, intermedia te housing and ordinary housing. A statistical analysis of each segmen t is provided in section 2. Prices and turn-over are analysed over tim e and boom-and-bust cycles are compared. In section 3, structurally di stinctive models of land, housing and office prices for each of the th ree segments are established. The characteristics of the models shed l ight on the real estate boom of the 1980s in the Paris agglomeration.