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Home ownership and support for government redistribution

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Comparative European Politics Aims and scope

Abstract

In this article, we investigate the relationship between home ownership and support for redistribution in 24 European countries, integrating research on housing regimes and welfare attitudes. We improve upon earlier research by taking into account within-group heterogeneity of owners and tenants, by elaborating on social mechanisms (self-interest and socio-spatial segregation), by researching a wide range of European (instead of Anglo-Saxon) countries and by recognizing differences in the meaning of tenure and home ownership across countries. We find that, while home owners are less supportive of redistribution, the effect of home ownership varies with age and income position. We furthermore find that housing regime characteristics matter, as owners and tenants have different welfare attitudes in different contexts. In settings where home ownership has become more financialized, support for redistribution is smaller, and more so among home owners. On the other hand, in settings where outright home ownership fills gaps in welfare provision, both owners and tenants prefer more redistribution.

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Notes

  1. Work on this article pre-dates publication of Ansell’s work, and hence developed independently. We added these references during the revision process, highlighting similarities and differences in our approach.

  2. Although we can only distinguish between home owners and non-owners in our sample, the theoretical argument concerns home owners and tenants.

  3. We tested whether the degree of urbanization has a different effect on support for redistribution for home owners and tenants: this is not the case.

  4. We tested whether the interaction of income with tenure affects the explanations at the macro-level, this was not the case. This was a test to check whether differences in selectivity of owners and tenants between countries impact on our finding. Results are available upon request.

  5. Ansell (2012) uses the 2009 ISSP module, however this module has many missing values for tenure, making the data less reliable compared with the ESS-data, and there are less European countries available. We ran our models on a small subsample of these 2009 data, for European countries with less than 15 per cent missing values and found quite similar results for 2009 as for 2004. Results are available upon request.

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Acknowledgements

This research was supported by the European Research Council [ERC Starting Grant HOWCOME, Grant Agreement No. 283615; PI: C. Dewilde], www.tilburguniversity.edu/howcome.

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Authors and Affiliations

  1. Department of Sociology, Tilburg University, The Netherlands

    Stéfanie André & Caroline Dewilde

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Appendix

Appendix

Operationalization of the variables

The income variable in the ESS is a variable with 12 crude monthly income groups. Since 23 per cent of the data are missing, we create a variable with five categories: low, low-middle, middle-high, high and missing. Age acts as proxy for the life-course stage, we therefore recode age in four dummies: youngest till 25 (saving for a deposit), 26–45 (young and paying off the mortgage), 46–60 (older and paying off the mortgage), 61 to oldest (mortgage-free and pensions). Degree of urbanization has the following categories: big city, suburbs, small city, country village or farm/countryside.

At the individual level, we control for gender, education, marital status, unemployment and religion. The first four variables indicate the risk people have of needing to depend on social transfers (Blekesaune and Quadagno, 2003; Meier Jaeger, 2006; Finseraas, 2009; Dallinger, 2010; Guillaud, 2013). Religion and especially religious institutions can act as a substitute for the welfare state. Therefore, we expect those who are a member of a religious institution to be less in favour of the welfare state, as found by Guillaud (2013). Religion is coded as (1) adherent of a religion. Educational level is recoded into five dummies based on ISCED5. Gender is coded as female (1). Marital status is coded as: married/living together, separated/divorced, widowed, single and missing. Unemployment is dummy coded (1) for those who are unemployed and actively looking for a job, since those are the people who might receive unemployment benefits. Religion is coded as (1) adherent of a religion.

Our macro-indicators for all countries refer to 2004, or the year closest to 2004. For an extensive overview of the sources of our data at the macro-level, we refer to the online appendix. Home ownership rates are measured as the percentage of home owners in a country. Data are from Housing Statistics in the EU and Hypostat. The correlation between the aggregated home ownership rates in the ESS and those reported in external sources is high (r=0.92). Outright home ownership rates are aggregated from the European Quality of Life Survey. There are no macro-indicators referring to the degree of ‘tenure neutrality’ – understood in terms of the availability to different social groups of similar tenure choices entailing comparable costs and benefits. We therefore take the percentage of social rental housing, indicating (limited) choice between social renting, private renting and home ownership. Social rental rates are from CECODHAS and EUROSTAT. Data on mortgage debt as percentage of GDP are from the 2004 and 2008 Hypostat reports. To take account of variation between welfare regimes, we include income inequality and two measures of social spending. Income inequality is measured by the GINI-coefficient, data are from LIS and the World Bank. For social spending as percentage of GDP, we used the SOCX database of the OECD and the World Bank. We also included the percentage of social spending financed through social contributions from EUROSTAT. Unemployment rates are from the Housing Statistics in the EU report (2005–2006) and The World Bank. Data on economic affluence, GDP per capita at current prices, are from EUROSTAT and IMF. We centred all continuous independent variables on their grand mean. Descriptives are presented in Table A1, revealing, among others, that 72 per cent of respondents across Europe are home owners.

Table A1 Descriptives of the variables (N=43602)
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Tables A2 and A3

Table A2 Multilevel analyses support for redistribution: the individual level (N=43602)
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Table A3 Multilevel analyses support for redistribution: relationships at the country-level (N=43 602)
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André, S., Dewilde, C. Home ownership and support for government redistribution. Comp Eur Polit 14, 319–348 (2016). https://doi.org/10.1057/cep.2014.31

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