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

Author:

Benedetti Ilaria1,Biggeri Luigi2,Laureti Tiziana1

Affiliation:

1. University of Tuscia , Via del Paradiso 47, 01100 , Viterbo (VT), Italy .

2. The University of Florence , Viale Morgagni, 59, 50134 Firenze, 50134 , Italy .

Abstract

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.

Publisher

Walter de Gruyter GmbH

Reference62 articles.

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2. Aten, B. 2008. Estimates of State and Metropolitan Areas Price Parities for Consumption Goods and services in the United States, 2005’, U.S. Bureau of Economic Analysis. Available at: https://www.bea.gov/system/files/papers/P2008-1.pdf (accessed May 2020).

3. Aten, B.H. 2017. “Regional price parities and real regional income for the United States”, Social Indicators Research, 131(1): 123–143 DOI: https://doi.org/10.1007/s11205-015-1216-y.10.1007/s11205-015-1216-y

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