<abstract xmlns="http://www.w3.org/1999/xhtml">

<p>It is essential to measure within-country differences in housing costs in order to evaluate costs of living, assessing and comparing poverty levels, quantifying salaries and disposable income of families and finally for designing housing policies at local level. To the authors knowledge, no studies have yet been carried out on the computation of Space Price Indexes for Housing Rents (SPIHRs). In this article we computed preliminary estimates of sub-national SPIHRs by using hedonic regression model, which is an extension of the Country Product Dummy method, for all the Italian regions. The hedonic regression is generally used to obtain multilateral spatial indexes, thus allowing us to obtain multilateral SPIHRs for the Italian regions. The estimates have been done using 2017 data from the Real Estate Market Observatory which is a part of the Italian Agency of Revenue and Tax. This data source is the most comprehensive source of information on Italian houses price rents with a wide geographical coverage, including data for each Italian municipality. The obtained results show significant differences across the Italian regions, thus highlighting the importance of calculating SPIHR in Italy on a regular basis and the need to continue researches in this field.</p>
</abstract>

It is essential to measure within-country differences in housing costs in order to evaluate costs of living, assessing and comparing poverty levels, quantifying salaries and disposable income of families and finally for designing housing policies at local level. To the authors knowledge, no studies have yet been carried out on the computation of Space Price Indexes for Housing Rents (SPIHRs). In this article we computed preliminary estimates of sub-national SPIHRs by using hedonic regression model, which is an extension of the Country Product Dummy method, for all the Italian regions. The hedonic regression is generally used to obtain multilateral spatial indexes, thus allowing us to obtain multilateral SPIHRs for the Italian regions. The estimates have been done using 2017 data from the Real Estate Market Observatory which is a part of the Italian Agency of Revenue and Tax. This data source is the most comprehensive source of information on Italian houses price rents with a wide geographical coverage, including data for each Italian municipality. The obtained results show significant differences across the Italian regions, thus highlighting the importance of calculating SPIHR in Italy on a regular basis and the need to continue researches in this field.

Sub-National Spatial Price Indexes for Housing: Methodological Issues and Computation for Italy

Journal of Official Statistics

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

It is essential to measure within-country differences in housing costs in order to evaluate costs of living, assessing and comparing poverty levels,...

Sub-National Spatial Price Indexes for Housing: Methodological Issues and Computation for Italy

Publicado en línea: 29 mar 2022

Páginas: 57 - 82

Recibido: 01 ago 2020

Aceptado: 01 abr 2021

DOI: https://doi.org/10.2478/jos-2022-0004

Palabras clave
Spatial rental price indexes, hedonic regression, country product dummy method, symbolic data analysis

© 2022 Ilaria Benedetti et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Sub-National Spatial Price Indexes for Housing: Methodological Issues and Computation for Italy

Publicado en línea: 29 mar 2022

Páginas: 57 - 82

Recibido: 01 ago 2020

Aceptado: 01 abr 2021

DOI: https://doi.org/10.2478/jos-2022-0004

Palabras claveSpatial rental price indexes, hedonic regression, country product dummy method, symbolic data analysis

© 2022 Ilaria Benedetti et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Palabras clave
Spatial rental price indexes, hedonic regression, country product dummy method, symbolic data analysis