Events and Meetings of Italian Statistical Society, Advances in Latent Variables - Methods, Models and Applications

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Gaussian state-space models of housing prices in the US
Eugenia Nissi, Agnese Rapposelli, Pasquale Valentini

Last modified: 2013-06-16

Abstract


The state of the current economy and recent events in the housing sector have lead to increased attention on the role of the housing sector in the economy as a whole. Hence, modeling the spatio-temporal variability of housing prices has enjoyed widespread popularity in the last years. In order to obtain a high degree of accuracy in the results, the analysis of housing prices across US States requires the definition of a general and flexible econometric model where the temporal and cross-sectional dependencies must be accommodated. In the present paper we discuss the modeling of spatio-temporal multivariate processes observed on a lattice by means of the Gaussian state-space model. The model has been applied in order to study the impact that the real per capita personal income and the unemployment rate may have on the real housing prices in the USA using State level data.

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