Exploratory Analyses of the U.S. Housing Bubble with Kolmogorov Entropy and Principal Component Analysis (PCA)
18 Pages Posted: 17 Apr 2010 Last revised: 7 May 2015
Date Written: April 15, 2010
In this paper we develop an exploratory non-parametric clustering model of spatial and/or spatio-temporal phenomena based on Kolmogorov entropy. The methodology will be tested using quarterly HPI (Housing Price Index) data for 350 plus cities in the US from the Federal Financing and Housing Administration (FHFA), an agency of HUD (US Dept of Housing and Urban Development). This multivariate data will be also analyzed with Principal Component Analysis (PCA) techniques to identify key regions involved in creating the housing bubble and its spread to the rest of cities.
Keywords: Kolmogorov Entropy, K-Means Clustering, Principal Component Analysis
JEL Classification: R12, R2, R32, A, C
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