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Single Access Neighbourhoods and Neighbourhood Cohesion

This paper compares the level of neighbourhood cohesion of two single access neighbourhoods in Calgary, Alberta. The two neighbourhoods had a high sense of neighbourhood cohesion. It is argued that the single access to the neighbourhood has contributed to a high sense of neighbourhood cohesion. One neighbourhood outperformed the other on all three subscales of cohesion due to a stronger sense of seclusion for the neighbourhood. Establishing a sense of identity, a focus, and a clear boundary for a neighbourhood is paramount. Meanwhile, visionary planning for the future of neighbourhood design in terms of ease and flexibility of redevelopment for the open grid model seems to dominate the mindset of municipal planners raising the banner of sustainability.
21.12.2015 | Karim Youssef | Volume: 2 | Issue: 2 | Pages: 1-10 | 10.13060/23362839.2015.3.2.236

Effects of Housing Prices on Income Inequality in Urban China

This paper explored the effects of housing prices on income inequality in China. By using China''s inter-provincial panel data from 1995 to 2011, we find that both housing prices and long-term mortgage rates are associated with the Gini coefficient of the income of urban residents, and the coefficients of correlation are significant positive. Moreover, a series of housing price control policies promulgated by the Chinese government has worsened the situation and has caused considerable interaction effects on long-term mortgage rates since 2003.
21.12.2015 | Chuanyong Zhang, Fang Zhang | Volume: 2 | Issue: 2 | Pages: 11-18 | 10.13060/23362839.2015.3.2.237
Briefing paper: What are the strengths and weaknesses of pan-European data sets, EU-SILC and EQLS? Specifically, should we trust them when making international housing comparisons?

EU-SILC: Should We Make Do with What We Have?

In this Briefing Paper the focus is on the EU-SILC based on the question: What are the strengths and weakness of the pan-European data set EU-SILC which stands for ‘European Union Statistics of Income and Living Conditions’? How useful is this database when making international housing comparisons? The examples in this paper are based on my experience with the EU-SILC and illustrate a number of themes as setting norms for all countries and differences between housing and poverty research. My conclusion is that some of these measures transcend the database evaluation and are concerned with the definition of concepts. As long as there are no ‘better’ data alternatives, we should make do with what we have, but carefully and transparently.
21.12.2015 | Marietta Haffner | Volume: 2 | Issue: 2 | Pages: 27-34 | 10.13060/23362839.2015.3.2.239
Briefing paper: What are the strengths and weaknesses of pan-European data sets, EU-SILC and EQLS? Specifically, should we trust them when making international housing comparisons?

What Have ECHP and EU-SILC to Contribute to the Comparative Study of Housing?

This paper discusses the strengths and weaknesses of pan-European datasets, in particular ECHP and EU-SILC, for research in housing. Although ‘housing’ is a complex topic when studied from a European comparative perspective, I argue that there is no inherent reason why housing should be less amenable to cross-national research than other equally complex topics in comparative social science research, such as research into family change and stability, or the impact of educational systems on social stratification. Given appropriate theory, conceptualisation and contextualisation, along with strong methodologies, meaningful and informative research in housing with ECHP and EU-SILC are possible. There are however a number of limitations, which are mainly related to the fact that both datasets are geared towards the ‘production’ of a ‘system of social indicators’ informing European and national governments. Because of these limitations, ECHP and in particular EU-SILC are less attractive and less useful for academic research then they could potentially be.

21.12.2015 | Caroline Dewilde | Volume: 2 | Issue: 2 | Pages: 19-26 | 10.13060/23362839.2015.3.3.238
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