Measuring Youth Living Conditions in Europe: A Multidimensional Cross-Country Approach

Abstract

Since the onset of the Great Recession, it could be argued that it is the young who have been hardest hit in their living conditions. This paper offers a comprehensive description of youth living conditions and how they evolved during the recession period. To do so, we develop a synthetic index combining the indicators proposed by experts in the dimensions of Education and Training, Employment and Entrepreneurship, and Social Inclusion, through a multi-criteria approach based on the double reference point method. This technique enriches the debate by shifting the focus to acceptable and desirable thresholds for each indicator and by overcoming limitations inherent in previous youth indexes that allow for total compensation between the indicators, whilst ignoring potential imbalances. Results show that, in a context of convergence in policy instruments across countries during the Great Recession, there was an improvement in education performance, whereas cross-country divergences in terms of youth labour market prospects and social inclusion increased. This evolution has led to a more complex picture which is characterized by greater polarization in the spatial distribution of youth living conditions, with two noticeable poles: north-central Europe as opposed to the south and east of Europe. Differences in institutional configurations in the fields of education and training, active labour market policies, employment protection legislation and welfare provision together with macroeconomic trends, particularly levels of demand for youth labour and fiscal resources, have played an important role in shaping European youth living conditions.

This is a preview of subscription content, access via your institution.

Fig. 1

Source: Own elaboration

Fig. 2

Source: Own elaboration

Fig. 3

Source: Own elaboration

Notes

  1. 1.

    Youth is defined as a period of transition between childhood and adulthood. The length of this period varies hugely across socio-economic and political contexts. Any attempt to delimit it proves a difficult task, since a young person may be regarded as an adult in one domain but as a minor in others.

  2. 2.

    We would like to remind that the aim of the group of experts was to provide a dashboard of indicators to monitor young people living conditions. The aim of the dashboard is not therefore to build a composite indicator.

  3. 3.

    In very few cases, the indicator for a specific country in a particular year was not available. As usual in these circumstances, an imputation method is applied. When there is information for another different year, the gap was filled using the most recent prior value for the indicator (cold deck imputation).

  4. 4.

    This means that two countries with a difference in the share of young people in education will display different youth unemployment rates if they have equal numbers of unemployed youth. To solve this problem, Hill (2012) suggested the use of ratios, as they provide a more accurate measure because those not looking for full-time work, in other words full-time students, are included in the denominator.

  5. 5.

    As already mentioned, data from the Eurobarometer are only available for 2011.

  6. 6.

    Classical manuals on methods used to build synthetic indicators are Nardo et al. (2005) and OECD (2008). A more recent review of the methods can be found in Greco et al. (2019).

  7. 7.

    The approach relies on the assumptions of optimising behaviour (Luque et al. 2012).

  8. 8.

    It will be assumed that all indicators are of the ‘the more, the better’ type. Thus, we have transformed indicators of the type ‘the less, the better’ to the ‘the more, the better’ by computing 100 minus the indicator.

  9. 9.

    It must be borne in mind that the effect of the weights is the opposite for positive and negative values of the achievement functions. For negative achievement values, a greater weight produces a worse strong indicator value, and for positive achievement values, a greater weight produces a better value of the strong indicator. Thus, in order to avoid this bias we need to correct weights and the values of the achievements function.

  10. 10.

    A weighted geometric mean, as an aggregation method, is a partial solution for compensability. While linear aggregation offers constant compensation, geometric aggregation offers inferior compensability for indicators with lower values (dismissing returns). In both linear and geometric aggregation, weights express trade-offs between indicators, with the idea being that deficits in one indicator or dimension can be offset by surplus in another. However, when different goals are legitimate and important, non-compensatory logic is necessary (Nardo et al. 2005).

  11. 11.

    We have also carried out all the calculations applying the min–max approach as a standardization criterion. The country’s ranking obtained from both criterions are not very different, thus confirming the robustness of our results (the Spearman rank correlation is 0.96). In the same vein, we have also carried out all the calculations using the geometric mean as an aggregation method. As expected, the Spearman rank correlation between the weak index and that obtained with the geometric mean is only 0.41, whereas the rank correlation with the strong index is close to 0 (−0.04). Table 8 of the Appendix show the country final ranks. The results reinforce the favourability of non-compensatory aggregation techniques derived from the multi-criteria approach (Castellano and Rocca 2014 and 2015). Detailed results are available from the authors upon request.

  12. 12.

    By definition, it is not possible to have a positive value in the strong index and a negative value in the weak index. Thus, there cannot be countries in the upper-left quadrant.

  13. 13.

    A simple comparison of the index computed in 2007 and 2016 does not necessarily indicate any real change in the situation of youth, but only reflects changes in the place each country occupies within an international ranking. A country might improve its position in the ranking merely because other countries do worse in terms of youth living condition indicators.

References

  1. Ayres-Wearne, V. (2001). A national youth policy: Achieving sustainable living conditions for all young people. Growth, 49, 7–15.

    Google Scholar 

  2. Bell, D. N. F., & Blanchflower, D. G. (2011). Young people and the Great Recession. Oxford Review of Economic Policy, 27(2), 241–267. https://doi.org/10.1093/oxrep/grr011.

    Article  Google Scholar 

  3. Benedicto, J. (2008). Young people and politics: Disconnected, sceptical, alternative or all of it at the same time? Revista de Estudios de Juventud [online], 81, 13–27.

    Google Scholar 

  4. Bessant, J., Farthing, R., & Watts, R. (2017). The precarious generation. A political economy of young people. Abingdon: Routledge, Taylor & Francis Group.

    Google Scholar 

  5. Blossfeld, H.-P., Klijzing, E., Mills, M., & Kurz, K. (Eds.). (2005). Globalization, uncertainty and youth in society. London: Routledge.

    Google Scholar 

  6. Boccuzzo, G., & Gianecchini, M. (2015). Measuring young graduates’ job quality through a composite indicator. Social Indicators Research, 122, 453–478.

    Article  Google Scholar 

  7. Castellano, R., & Rocca, A. (2014). Gender gap and labour market participation. A composite indicator for the ranking of European countries. International Journal of Manpower, 35(3), 345–367.

    Article  Google Scholar 

  8. Castellano, R., & Rocca, A. (2015). Assessing the gender gap in labour market index: Volatility of results and reliability. International Journal of Social Economics, 42(8), 749–772.

    Article  Google Scholar 

  9. Chaaban, J. M. (2009). Measuring youth development: A nonparametric cross-country ‘Youth Welfare Index’. Social Indicators Research, 93, 351–358.

    Article  Google Scholar 

  10. Chevalier, T. (2016). Varieties of youth welfare citizenship: Towards a two-dimension typology. Journal of European Social Policy, 26, 1–17.

    Article  Google Scholar 

  11. Commonwealth Secretariat. (2016). Global youth development index and report. London: Commonwealth Secretariat.

    Google Scholar 

  12. Côté, J. (2014). Towards a new political economy of youth. Journal of Youth Studies, 17, 527–543.

    Article  Google Scholar 

  13. Council of Europe. (2003). Experts on youth policy indicators. Strasbourg: Council of Europe.

    Google Scholar 

  14. Dvouletý, O., Mühlböck, M., Warmuth, J., & Kittel, B. (2018). ‘Scarred’ young entrepreneurs. Exploring young adults’ transition from former unemployment to self-employment. Journal of Youth Studies, 21, 1159–1181.

    Article  Google Scholar 

  15. Ecorys. (2011). Assessing practices for using indicators in fields related to youth. Final Report for the European Commission. DG Education and Culture. Birmingham: Ecorys.

  16. Eichhorst, W. (2015). Does vocational training help young people find a (Good) Job? IZA World of Labor. https://wol.iza.org/articles/does-vocational-training-help-young-people-find-good-job/long.

  17. Eichhorst, W., Marx, P., & Wehner, C. (2016). Labor market reforms in Europe: Towards more flexicure labor markets? IZA Discussion Paper 9863. Bonn: Institute for the Study of Labor.

    Google Scholar 

  18. Eichhorst, W., & Rinne, U. (2014). Promoting youth employment through activation strategies. ILO employment working paper 163. Geneva: International Labour Office.

    Google Scholar 

  19. Eichhorst, W., & Rinne, U. (2017). The European Youth Guarantee: A Preliminary Assessment and Broader Conceptual Implications. IZA Policy Paper 128. Bonn: Institute for the Study of Labor.

    Google Scholar 

  20. Eurofound. (2014a). Social situation of young people in Europe. Luxembourg: Publications Office of the European Union.

    Google Scholar 

  21. Eurofound. (2014b). Mapping youth transitions in Europe. Luxembourg: Publications Office of the European Union.

    Google Scholar 

  22. European Central Bank. (2014). The impact of the economic crisis on Euro area labour markets. ECB Monthly Bulletin, 49–64.

  23. European Commission. (2011). Commission Staff Working Document: On EU indicators in the field of youth. Brussels, 25.03.2011, SEC (2011) 401 final. Available online at: http://ec.europa.eu/youth/library/publications/indicatordashboard_en.pdf.

  24. European Commission. (2015). Education and Training Monitor. Luxembourg: European Union.

    Google Scholar 

  25. European Commission. (2016). The Youth Guarantee Country by Country. Brussels: European Commission. Available online at: http://ec.europa.eu/social/main.jsp?catId=1161.

  26. European Commission. (2018). European Youth Report. Flash Eurobarometer 455. Retrieved February 15, 2018, from http://ec.europa.eu/commfrontoffice/publicopinion

  27. Furlong, A. (2010). Transitions from education to work: New perspectives from Europe and beyond. British Journal of Sociology of Education, 31(4), 515–518. https://doi.org/10.1080/01425692.2010.484926.

    Article  Google Scholar 

  28. Giambona, F., & Vassallo, E. (2014). Composite indicator for social inclusion for European countries. Social Indicators Research, 116, 269–293.

    Article  Google Scholar 

  29. Goldin, N., Patel, P., & Perry, K. (2014). The global youth wellbeing index. Washington, DC: Center for Strategic and International Studies.

    Google Scholar 

  30. Greco, S., Ishizaka, A., Tasiou, M., & Torris, G. G. (2019). On the methodological framework of composite indices: A review of the issues of weighting, aggregation, and robustness. Social Indicators Research, 141, 61–94.

    Article  Google Scholar 

  31. Green, A. (2017). The crisis for young people. Generational inequalities in education, work, housing and welfare. London: Palgrave.

    Google Scholar 

  32. Green, A., & Nicola, P. (2017). Comparative perspectives: education and training system effects on youth transitions and opportunities. In I. Schoon & B. John (Eds.), Young people’s development and the great recession: Uncertain transitions and precarious futures (pp. 75–100). Cambridge: Cambridge University Press.

    Google Scholar 

  33. Groh-Samberg, O., & Voges, W. (2014). Precursors and consequences of youth poverty in Germany. Longitudinal and Life Course Studies, 5, 151–172.

    Article  Google Scholar 

  34. Hadjivassiliou, K. (2017). Introduction to comparing country performance. In J. O’Reilly, et al. (Eds.), Youth employment: STYLE Handbook. Bristol. UK.

  35. Hadjivassiliou, K., Kirchner Sala, L., & Speckesser, S. (2015). Key indicators and drivers of youth unemployment, STYLE Working Papers, WP3.1. CROME, University of Brighton, Brighton. Available at http://www.style-research.eu/publications/working-papers.

  36. Hadjivassiliou, K., Tassinari, A., Eichhorst, W., & Wozny, F., et al. (2019). How does the performance of school-to-work transition regimes vary in the European Union? In J. O’Reilly (Ed.), Youth labor in transition. Inequalities, mobility, and policies in Europe (pp. 71–103). New York: Oxford University Press.

    Google Scholar 

  37. Hadju, G., & Sik, E. (2017). Are young people’s work values changing? In J. O’Reilly, et al. (Eds.), Youth employment: STYLE Handbook. Bristol. UK.

  38. Hancock, L., Howe, B., Frere, M., & O’Donnell, A. (2001). Future directions in Australian social policy: New ways of preventing risk. CEDA.

  39. International Labour Organization. (2013). Global trends for youth 2013: A generation at risk. Geneva: ILO.

    Google Scholar 

  40. International Labour Organization. (2015a). Global employment trends for youth 2015: Scaling up investments in decent jobs for youth. Geneva: ILO.

    Google Scholar 

  41. International Labour Organization. (2015b). The youth guarantee program in Europe: Features, implementation and challenges. Working paper 4. Geneva: ILO Research Department.

    Google Scholar 

  42. Khan, L. B. (2010). The long-term labour market consequences of graduating from college in a bad economy. Labour Economics, 17(2), 303–316.

    Article  Google Scholar 

  43. Leccardi, C. (2017). The recession, young people, and their relationship with the future. In I. Schoon & J. Bynner (Eds.), Young people’s development and the Great Recession: Uncertain transitions and precarious futures (pp. 348–371). Cambridge: Cambridge University Press.

    Google Scholar 

  44. Leschke, J., & Mairéad, F., et al. (2019). Labour market flexibility and income security: changes for European youth during the Great Recession. In J. O’Reilly (Ed.), Youth labor in transition. Inequalities, mobility and policies in Europe (pp. 132–162). New York: Oxford University Press.

    Google Scholar 

  45. Luque, M., Miettinen, K., Eskelinen, P., & Ruiz, F. (2009). Incorporating preference information in interactive reference point methods for multiobjective optimization. Omega International Journal of Management Science, 37(2), 450–462.

    Article  Google Scholar 

  46. Luque, M., Miettinen, K., Ruiz, A. B., & Ruiz, F. (2012). A two-slope achievement scalarizing function for interactive multiobjective optimization. Computers & Operations Research, 39, 1673–1681.

    Article  Google Scholar 

  47. Luque, M., Pérez-Moreno, S., & Rodríguez, B. (2016). Measurement human development: A multi-criteria approach. Social Indicators Research, 125, 713–733.

    Article  Google Scholar 

  48. Macdonald, F., & Holm, S. (2001). Employment for 25- to 34- year-olds in the flexible labour market: A generation excluded? Growth, 49, 16–24.

    Google Scholar 

  49. Mazzotta, F., & Lavinia, P., et al. (2019). Stuck in the parental nest? The effect of the economic crisis on young Europeans’ living arrangements. In J. O’Reilly (Ed.), Youth labor in transition. Inequalities, mobility and policies in Europe (pp. 334–357). Oxford: Oxford University Press.

    Google Scholar 

  50. Mont’alvao, A., Mortimer, J. T., & Johnson, M. K. (2017). The great recession and youth labor market outcomes in international perspective. In I. Schoon & J. Bynner (Eds.), Young people’s development and the Great Recession: Uncertain transitions and precarious futures (pp. 52–75). Cambridge: Cambridge University Press.

    Google Scholar 

  51. Moreno Mínguez, A., & Crespi, I. (2017). Future perspectives on work and family dynamics in Southern Europe: The importance of culture and regional contexts. International Review of Sociology, 27(3), 389–393.

    Google Scholar 

  52. Nardo, M., Saisana, M., Saltelli, A., & Tarantola, S. (2005). Tools for composite indicators building, institute for the protection and security of the citizen, European Commission. EUR 21682 EN, European Communities.

  53. Navarro Jurado, E., Tejada Tejada, M., Almeida García, F., Cabello González, J., Cortés Macías, R., Delgado Peña, J., et al. (2012). Carrying capacity assessment for tourist destinations. Methodology for the creation of synthetic indicators applied in a coastal area. Tourism Management, 33(6), 1337–1346.

    Article  Google Scholar 

  54. Nico, M. (2009). Youth lifestyles and living conditions policy framework, youth policy topics, European Knowledge Centre for Youth Policy EKCYP of the partnership programme between the Council and the European Commission in the field of youth.

  55. OECD. (2008). Handbook on constructing composite indicators. Methodology and user guide. Paris: OECD.

    Google Scholar 

  56. O’Reilly, J., Eichhorst, W., Gábos, A., Hadjivassiliou, K., Lain, D., Leschke, J., et al. (2015). Five characteristics of youth unemployment in Europe: Flexibility, education, migration, family legacies, and EU policy. SAGE Open. https://doi.org/10.1177/2158244015574962.

    Article  Google Scholar 

  57. O’Reilly, J., Moyart, C., Nazio, T., & Smith, M. (2017). Youth employment: STYLE handbook. Bristol, UK: STYLE.

    Google Scholar 

  58. O’Reilly, J., Leschke, J., Ortlieb, R., Seeleib-Kaiser, M., & Villa, P. (Eds.). (2019). Youth labor in transition. Inequalities, mobility and policies in Europe. New York: Oxford University Press.

    Google Scholar 

  59. Renate, O., Sheehan, M., & Masso, J., et al. (2019). Do business start-ups create high-quality jobs for young people? In J. O’Reilly (Ed.), Youth labor in transition: Inequalities, mobility and policies in Europe (pp. 597–625). New York: Oxford University Press.

    Google Scholar 

  60. Pérez-Moreno, S., Rodríguez, B., & Luque, M. (2016). Assessing global competitiveness under multi-criteria perspective. Economic Modelling, 53, 398–408.

    Article  Google Scholar 

  61. Axel, P., & Walther, A. (2007). Activating the disadvantaged variations in addressing youth transitions across Europe. International Journal of Lifelong Education, 26(5), 533–53.

    Article  Google Scholar 

  62. Pulido-Fernández, J. I., & Rodríguez-Díaz, B. (2016). Reinterpreting the world economic forum’s global competitiveness index. Tourism Management Perspectives, 20, 131–140.

    Article  Google Scholar 

  63. Ruiz, F., Cabello, J. M., & Luque, M. (2011). An application of reference point techniques to the calculation of synthetic sustainability indicators. Journal of the Operational Research Society, 62, 189–197.

    Article  Google Scholar 

  64. Saisana, M., Tarantola, S., & Saltelli, A. (2005). Uncertainty and sensitivity techniques as tools for the analysis and validation of composite indicators. Journal of the Royal Statistical Society A, 168(2), 1–17.

    Article  Google Scholar 

  65. Schoon, I., & Bynner, J. (Eds.). (2017). Young people’s development and the Great Recession: Uncertain transitions and precarious futures. Cambridge: Cambridge University Press.

    Google Scholar 

  66. Schoon, I., & Bynner, J. (2019). Young people and the great recession: Variations in the school-to-work transition in Europe and the United States. Longitudinal and Life Course Studies, 10(2), 153–173.

    Article  Google Scholar 

  67. Serrano Pascual, A. S., & Martín Martín, P. M. (2017). From ‘employab-ility’ to ‘entrepreneurial-ity’ in Spain: youth in the spotlight in times of crisis. Journal of Youth Studies, 20, 798–821.

    Article  Google Scholar 

  68. Smith, M., & Villa, P. (2017). Flexicurity policies to integrate youth before and after the crisis. In J. O’Reilly, et al. (Eds.), Youth employment: STYLE Handbook: Bristol. UK.

  69. Smith, M., Leschke, J., Russell, H., & Villa, P. (2019). Stressed economies, distressed policies, and distraught young people: European policies and outcomes from a youth perspective. In J. O’Reilly (Ed.), Youth labor in transition. Inequalities, mobility, and policies in Europe (pp. 104–131). New York: Oxford University Press.

    Google Scholar 

  70. Sukarieh, M., & Tannock, S. (2016). On the political economy of youth: A comment. Journal of Youth Studies, 19, 1281–1289.

    Article  Google Scholar 

  71. Wierzbicki, A. P. (1980). The use of reference objectives in multiobjective optimization. In G. Fandel & T. Gal (Eds.), Multiple criteria decision making theory and application (pp. 468–486). Berlin: Springer.

    Google Scholar 

  72. Wierzbicki, A. P., Makowski, M., & Wessels, J. (Eds.). (2000). Model-based decision support methodology with environmental applications. Dordrecht: Kluwer Academic Publishers.

    Google Scholar 

  73. Wolbers, M. H. J. (2016). A generation lost?: Prolonged effects of labour market entry in times of high unemployment in the Netherlands. Research in Social Stratification and Mobility, Part A, 46, 51–59.

    Article  Google Scholar 

  74. Woodman, D., & Wyn, J. (2014). Youth and generation: Rethinking change and inequality in the lives of young people. London: Sage.

    Google Scholar 

  75. Wyn, J., & Woodman, D. (2006). Generation, youth and social change in Australia. Journal of Youth Studies, 9(5), 495–514.

    Article  Google Scholar 

Download references

Acknowledgements

We would like to thank the referee team for their valuable comments which helped to improve the paper significantly.

Author information

Affiliations

Authors

Corresponding author

Correspondence to Beatriz Rodriguez-Prado.

Additional information

Publisher's Note

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

Appendix

Appendix

See in Tables 8, 9, 10, 11 and 12.

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Corrales-Herrero, H., Rodriguez-Prado, B. Measuring Youth Living Conditions in Europe: A Multidimensional Cross-Country Approach. Soc Indic Res (2021). https://doi.org/10.1007/s11205-021-02608-8

Download citation

Keywords

  • Youth
  • Living conditions
  • Multi-criteria approach
  • Double reference point method
  • EU countries

JEL Classification

  • C43
  • J13