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Clustering Methods for Italian Residential Real Estate Market

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  • Raffaella Pinto

Abstract

Until yet, few attention has been given to the description of the residential market and its relationship with other macroeconomic variables for Italian market. To go through this relation, we have collected a large number of demographic and economic data besides the residential one on the 8.101 Italian communes on a short period of time, 1999-2003. Then we have made some hypothesis on how these data influence the real estate market by building some indicators representing the demand and supply side of the residential market. On the first step we have applied a principal component analysis in order to show the significance of the correlation between some indicators and the real estate market and then we have applied a clustering algorithm to the first four principal components. The aim of the cluster is to identify homogeneous groups of Italian cities, where real estate market variables, from the demand and supply side, have performed in a similar way. The final result provides support to the empirical evidence that some communes are similar in their real estate behaviour for the period observed. While the analysis is limited to aggregate different variables in a static model with only descriptive purposes, the result provides a guideline for the further application of cluster analisys to other types of real estate and economic information.

Suggested Citation

  • Raffaella Pinto, 2005. "Clustering Methods for Italian Residential Real Estate Market," ERES eres2005_287, European Real Estate Society (ERES).
    • Handle: RePEc:arz:wpaper:eres2005_287
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    JEL classification:

    • R3 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Real Estate Markets, Spatial Production Analysis, and Firm Location

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