Social Housing in Transition Countries by József Hegedüs Martin Lux Nóra Teller

Author:József Hegedüs, Martin Lux, Nóra Teller [József Hegedüs, Martin Lux, Nóra Teller]
Language: eng
Format: epub
Tags: Nonfiction, Social & Cultural Studies, Political Science, Politics, Social Services & Welfare, Government, Social Policy
ISBN: 9781136216220
Publisher: Taylor and Francis
Published: 2012-11-12T05:00:00+00:00

SPATIAL DISTRIBUTION AND THE CONDITIONS OF SOCIAL HOUSING

Methodology

To examine analytical questions of the physical patterns of social housing distribution, we used mainly Census 2000 data (next to the SMH 2005 data described in the preceding). The year 2000 is a good year for analyses because by that time the new housing construction programs had not yet been launched and the pattern in evidence is the one most directly resulting from housing privatization and the Soviet housing construction/allocation policy. We used aggregated data to analyze the spatial distribution of ‘old’ social housing (residual public housing after privatization), where data on dwellings is aggregated by 0.25 km2 spatial units (cells). Census data on ‘old’ social housing are complemented by data on new social housing built in Tallinn between 2000 and 2011 under programs described in the preceding.

Our hypothesis was that significant intraurban differences in spatial distribution of social housing existed in following building-related variables: (a) type of building (categories: single-family/apartment) and (b) time of building construction (categories: before 1946 and after 1946). We also aimed to study other spatial regularities outside the spatial distribution of these variables, including whether a higher concentration of social dwellings can be found in large housing estates. We used the socioeconomic variables of different city subdistricts and other local characteristics identified in previous studies as background variables to explain spatial variations in social housing.

To study the regularities of spatial patterns, we applied a statistical general linear model (Model 1), with binary coding 0:1 of the dependent variable: social dwellings not available/available in the subarea. The independent variables were the following: (a) dwelling type and (b) the age structure of dwellings by spatial units. The respective types were classified into 2-by-3 classes (e.g., prevailingly single-family areas/mixed type areas/apartment-dominated areas). But we also used a visual comparison of maps to explore regularities in social housing distribution in 2000 and the locations of new social dwellings in relation to the existing social housing pattern.

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