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Construction of a Spatial Housing Price Index by Estimating an Almost Ideal Demand System

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  • Víctor Iturra
  • Dusan Paredes

Abstract

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

Suggested Citation

  • Víctor Iturra & Dusan Paredes, 2014. "Construction of a Spatial Housing Price Index by Estimating an Almost Ideal Demand System," Tijdschrift voor Economische en Sociale Geografie, Royal Dutch Geographical Society KNAG, vol. 105(3), pages 301-314, July.
  • Handle: RePEc:bla:tvecsg:v:105:y:2014:i:3:p:301-314
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    File URL: http://hdl.handle.net/10.1111/tesg.12067
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    Cited by:

    1. Dusan Paredes, 2012. "Alternative theories for explaining the spatial wage inequality: a multilevel competition among human capital, NEG and amenities," Documentos de Trabajo en Economia y Ciencia Regional 20, Universidad Catolica del Norte, Chile, Department of Economics, revised Apr 2012.
    2. Dusan Paredes, 2013. "The Role of Human Capital, Market Potential and Natural Amenities in Understanding Spatial Wage Disparities in Chile," Spatial Economic Analysis, Taylor & Francis Journals, vol. 8(2), pages 154-175, June.

    More about this item

    JEL classification:

    • C34 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Truncated and Censored Models; Switching Regression Models
    • R21 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Household Analysis - - - Housing Demand

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