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The aim of this paper is to build, for the first time, a spatial housing price index for the Chilean communities. The first step is to recover hedonic prices of three housing attributes by estimating a mixed index model using a generalised method of moments ( GMM) procedure. Second, a censored almost ideal demand system is estimated to build expenditures for every community and to compare them among different spatial units, while maintaining a constant utility level. Using micro data from the 2009 CASEN survey, we show that there are important differences in the expenditure of a consumer in Santiago to access the same level of welfare in another community in the country and there are important differences in housing prices among Chilean communities [ABSTRACT FROM AUTHOR]

This paper proposes a methodology for a spatial cost index of housing that considers spatial heterogeneity in properties across regions. The index is built by combining three different techniques to reduce the spatial heterogeneity in housing: Quasi-experimental methods, hedonic prices and Fisher spatial price index. Using microdata from the Chilean survey CASEN 2006, it is shown that the quasi-experimental method called Mahalanobis metric within propensity score calipers (MMWPS) leads to a significant reduction in the potential bias. The technique matches dwellings of a particular region with other properties of similar characteristics in the benchmark region (Metropolitan region). Once the houses are matched, a hedonic price model is computed, and a regional housing price matrix is created using Fisher spatial price indices. The paper concludes the existence of price differentials for homogeneous houses across regions in Chile. [ABSTRACT FROM AUTHOR]

The aim of this article is to develop a methodology for a spatial or regional cost index of housing that considers spatial differentials across regions. Using microdata from the Chilean survey CASEN 2003, it is showed that a spatial or regional housing price index based on the weighted mean or the estimators of hedonic price equations might lead to biased results due to spatial heterogeneity. The potential bias is reduced by matching the houses in a region with a clone in the Metropolitan Region, according to own and neighbors' characteristics using propensity scores. As a result a very different pattern of spatial cost of housing arises. Finally, using a Fisher ideal price index, the paper proposes a spatial or regional cost index of housing that shows price differences for homogeneous houses across regions. [ABSTRACT FROM AUTHOR]