Skip to main content
Log in

European Regional Welfare Attitudes: a Sub-National Multi-Dimensional Analysis

  • Published:
Applied Spatial Analysis and Policy Aims and scope Submit manuscript

Abstract

Public attitudes to welfare are key issues in social policy research and practice given their important roles in shaping demands for different types of welfare policies as well as the political parameters within which those welfare decisions are made by governments. Research into headline trends has shown important hardenings in public attitudes to welfare cross-nationally. However, more detailed geographical analysis of these patterns of welfare attitudes sub-nationally remains an important and surprisingly neglected area of understanding, in part due to the lack of suitable survey datasets with which to create sufficiently reliable direct sub-national comparative estimates. Responding to these gaps, this article employs small area estimation techniques to present reliable sub-national estimates and analyses of distinct economic, moral and social welfare attitudes across European regions for the first time in the literature. Compared to previous national analyses the richer spatial understanding enabled in these original analyses reveals previously neglected variation in welfare attitudes within as well as across national boundaries. Five geodemographic ‘families’ of regional welfare attitudes are found across Europe’s regions – from strong welfare supporters to consistent welfare sceptics – with their regional memberships cutting across national boundaries and current welfare typologies.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9

Similar content being viewed by others

Notes

  1. http://ec.europa.eu/eurostat/web/population-and-housing-census/census-data/2011-census

  2. http://ec.europa.eu/eurostat/web/regions/data/database

  3. Full details from the diagnostic checks are available upon request from the authors.

References

  • Arts, W and Gelisson, J. 2010. Models of the welfare state in castles, F., Leibried, S., Lewis, J., Obinger, H. and Pierson, C. (eds) the Oxford handbook of the welfare state. Oxford: Oxford University press.

  • Bartholomew, D. J., Steele, F., Moustaki, I. and Galbraith, J. I. (2008) Analysis of multivariate social science data. CRC.

  • Baumberg Geiger, B. 2017. Sharp softening of attitudes to benefit claimants, reveals new data. Retrieved from https://inequalitiesblog.wordpress.com/2017/06/28/sharp-softening-of-attitudes-to-benefit-claimants-reveals-new-data/. Accessed 14 June 2018.

  • Baumberg Geiger, B. and Meueleman, B (2016) Beyond ‘mythbusting’: How to respond to myths and perceived undeservingness in the British benefits system, Journal of Poverty and Social Justice, 24(3), pp291–306.

  • Beresford, P. 2013. Why welfare literacy is vital. The Guardian, 30/1/2013.

  • Blekesaune, M., & Quadagno, J. (2003). Public attitudes toward welfare state policies: A comparative analysis of 24 nations. European Sociological Review, 19, 415–427.

    Article  Google Scholar 

  • Breznau, N (2017) Positive returns and equilibrium: Simulataneous feedback between public opinion and social policy. The Policy Studies Journal, 45(4), pp583–612, 583.

  • Brown, G., Chambers, R., Heady, P. and Heasman, D. 2001. Evaluation of small area estimation methods an application to the unemployment estimates from the UK LFS. Statistics Canada symposium Ottawa, October 2001.

  • Buil-Gil, D., Moretti, A., Shlomo, N., & Medina, J. (2019a). Worry about crime in Europe: A model-based small area estimation from the European Social Survey. European Journal of Criminology.

  • Buil-Gil, D., Medina, J., and Shlomo, N. 2019b. The geographies of perceived neighbourhood disorder. A small area estimation approach. Applied Geography, 10, (109). https://www.sciencedirect.com/science/article/pii/S0143622818310646

  • DiStefano, C., Zhu, M. and Mindrila, D. 2009. Understanding and using factor scores: Considerations for the applied researcher. Practical assessment, research and evaluation, 14(20).

  • Esping-Andersen, G. (1990). Three worlds of welfare capitalism. Princeton: Princeton University Press.

    Google Scholar 

  • European Social Survey. 2018. ESS8–2016 Documentation Report – The ESS Data Archive Edition 2.1. Retried from https://www.europeansocialsurvey.org/docs/round8/survey/ESS8_data_documentation_report_e02_1.pdf. Accessed 14 May 2019.

  • Eurostat (2019) Population on 1stJanuary by NUTS2 region. https://ec.europa.eu/eurostat/web/products-datasets/product?code=tgs00096. Accessed 1 June 2019.

  • Fay, R. E., & Herriot, R. A. (1979). Estimates of income for small places: An application of James–stein procedures to census data. Journal of the American Statistical Association, 74, 269–277.

    Article  Google Scholar 

  • Ghosh, M., & Rao, J. (1994). Small area estimation: an appraisal. Statisical Science, 9(1), 55–76.

    Article  Google Scholar 

  • González-Manteiga, W., Lombardía, M. J., Molina, I., Morales, D., & Santamaría, L. (2008). Bootstrap mean squared error of a small-area EBLUP. Journal of Statistical Computation and Simulation, 78, 443–462.

    Article  Google Scholar 

  • Hansen, T., & Klausen, J. E. (2010). Between the welfare state and local government autonomy. Local Government Studies, 28(4), 47–66.

    Article  Google Scholar 

  • Hershberger, S. L. (2005). Factor scores. In B. S. Everitt & D. C. Howell (Eds.), Encyclopedia of statistics in behavioral science (pp. 636–644). New York: John Wiley.

    Google Scholar 

  • Horvitz, D. G., & Thompson, D. J. (1952). A generalization of sampling without replacement from finite universe. Journal of the American Statistical Association, 47, 663–685.

    Article  Google Scholar 

  • Hu, L., & Bentler, P. M. (1999). Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives. Structural Equation Modeling, 6(1), 1–55.

    Article  Google Scholar 

  • Jakobsen, T (2011) ‘Welfare attitudes and social expenditure: Do regimes shape public opinion?’ Social Indicators Research, 101, pp323–340, 323.

  • Laenen, T. (2018). Do institutions matter? The interplay between income benefit design, popular perceptions, and the social legitimacy of targeted welfare. Journal of European Social Policy, 28(1), 4–17.

    Article  Google Scholar 

  • Marshall, A. 2010. Small area estimation using ESDS government surveys – An introductory guide economic and social data service.

  • Moretti, A and Whitworth, A (2019) Evaluations of small area composite estimators based on the iterative proportional fitting algorithm. Communications in Statistics – Simulation and Computation.

  • Moretti, A., Shlomo, N., & Sakshaug, J. (2019). Small area estimation of latent economic wellbeing. Sociological Methods & Research, 004912411982616.

  • OECD-JRC. 2008. Handbook on constructing composite indicators: methodology and user guide. OECD Statistics report. (Available from http://www.oecd.org/std/42495745.pdf. Accessed 19 Dec 2018.

  • Pratesi, M. (Ed.). (2016). Analysis of poverty data by small area estimation. Wiley.

  • Rahman, A. 2008. A review of small area estimation problems and methodological developments. University of Canberra: NATSEM discussion paper issue 66.

  • Rao, J. N. K., & Molina, I. (2015). Small Area Estimation. Wiley.

  • Roller, E. (1995). The welfare state: The equality dimension. In O. Borre & E. Scarbrough (Eds.), The scope of government (pp. 165–197). Oxford: Oxford University Press.

    Google Scholar 

  • Roosma, F., van Oorschot, W., & Gelissen, J. (2014). The preferred role and perfceived performance of the welfare state: European welfare attitudes from a multidimensional perspective. Social Science Research, 44, 200–210.

    Article  Google Scholar 

  • Roosma, F., Gelissen, J. and Van Oorschot, W. 2013. The multidimensionality of welfare state attitudes: A European cross-national study. Social indicators research, 113(1), 235 255.

  • Scarborough, P., Allender, S., Rayner, M., & Goldacre, M. (2009). Validation of model-based estimates (synthetic estimates) of the prevalence of risk factors for coronary heart disease for wards in England. Health & Place, 15(2), 596–605.

    Article  Google Scholar 

  • Slater, T. (2012). The myth of “broken Britain”: Welfare reform and the production of ignorance. Antipode, 46(4), 948–969.

    Article  Google Scholar 

  • Svallfors, S. (2004). Class, attitudes and the welfare state: Sweden in comparative perspective. Social Policy & Administration, 38(2), 119–138.

    Article  Google Scholar 

  • Svallfors, S. 2012. (ed.) Contested welfare states: welfare attitudes in Europe and beyond. Stanford, CA: Stanford University press.

  • Svallfors, S., & Taylor-Gooby, P. (2012). The end of the welfare state? Responses to state retrenchment. London: Routledge.

    Book  Google Scholar 

  • Taylor-Gooby, P. 2011. ‘Security, equality and opportunity: Attitudes and the sustainability of social protection’. Journal of European Social Policy, 21(2), pp150–163.

  • Taylor-Gooby, P and Leruth, B. 2018. (eds.) Attitudes, aspirations and welfare: Social policy directions in uncertain times. Oxford: Palgrave Macmillan.

  • Toikko, T. and Rantanen, T (2017) How does the welfare state model influence social political attitudes? An analysis of citizens’ concrete and abstract attitudes towards poverty. Journal of International and Comparative Social Policy, 33(3), pp201-224

  • Van Oorschot, W. (2010). Public perceptions of the economic, moral, social and migration consequences of the welfare state: An empirical analysis of welfare state legitimacy. Journal of European Social Policy, 20(1), 19–31.

    Article  Google Scholar 

  • Van Oorschot, W., Reeskens, T., & Meuleman, B. (2012). Popular perceptions of welfare state consequences: A multilevel, cross-national analysis of 25 European countries. Journal of European Social Policy, 22(2), 181–197.

    Article  Google Scholar 

  • Whitworth, A. 2013. (ed.) evaluations and improvements in small area estimation methodologies. National Centre for research methods methodological review paper.

  • Wiggan, J. (2012). Telling stories of 21st century welfare: The UK coalition government and the neo-liberal discourse of worklessness and dependency. Critical Social Policy, 32(3), 383–405.

    Article  Google Scholar 

Download references

Funding

This research has been funded by the UK Economic and Social Research Council (ESRC) National Centre for Research Methods (NCRM) grant number ES/N011619/1.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Angelo Moretti.

Ethics declarations

Conflict of Interest

The authors declare that they have no conflict of interest.

Additional information

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Appendix: Confidence Intervals Plots Section 3

Appendix: Confidence Intervals Plots Section 3

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Moretti, A., Whitworth, A. European Regional Welfare Attitudes: a Sub-National Multi-Dimensional Analysis. Appl. Spatial Analysis 13, 393–410 (2020). https://doi.org/10.1007/s12061-019-09309-3

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s12061-019-09309-3

Keywords

Navigation