D 8.3 Leaving and returning to the parental home during the economic crisis

Fatoş Gökşen, Deniz Yükseker, Alpay Filiztekin, İbrahim Öker, Sinem Kuz, Fernanda Mazzotta and Lavinia Parisi

Koç University Social Policy Center & University of Salerno

STYLE-WP8: Family and Cultural Drivers of Youth Unemployment and Adulthood Transitions

Version - Final Submission date - Planned: 31/12/2015 Actual: 04/01/2016

This project has received funding from the European Union’s Seventh Framework Programme for research, technological development and demonstration under Grant Agreement no. 613256.

2 Gökşen, Yükseker, Filiztekin, Öker, Kuz, Mazotta & Parisi

STYLE Working Papers are peer-reviewed outputs from the www.style-research.eu project. The series is edited by the project coordinator Professor Jacqueline O’Reilly. These working papers are intended to meet the European Commission’s expected impact from the project:

i) to ‘advance the knowledge base that underpins the formulation and implementation of relevant policies in Europe with the aim of enhancing the employment of young people and their transition to economic and social independence’, and

ii) to engage with ‘relevant communities, stakeholders and practitioners in the research with a view to supporting employment policies in Europe.’ Contributions to a dialogue about these results can be made through the project website www.style-research.eu, or by following us on Twitter @STYLEEU.

To cite this report:

Reference: Gökşen, F., Yükseker, D.,Filiztekin A., Öker, I., Kuz, S., Mazzotta, F. & Parisi L. (2016), Leaving and returning to the parental home during the economic crisis. STYLE Working Papers WP8.3, CROME, University of Brighton, Brighton. http://www.style-research.eu/publications

© Copyright is held by the authors

About the authors Fatoş Gökşen – http://www.style-research.eu/team/fatos-goksen Deniz Yükseker _ http://www.style-research.eu/team/deniz-yukseker Alpay Filiztekin – http://myweb.sabanciuniv.edu/alpayf İbrahim Öker – http://www.style-research.eu/team/ibrahim-oker Sinem Kuz – http://www.style-research.eu/team/sinem-kuz/ Fernanda Mazzotta – http://www.style-research.eu/team/fernanda-mazzotta/ Lavinia Parisi – http://www.unisa.it/docenti/laviniaparisi/index

Acknowledgements

The research leading to these results has received funding from the European Union’s Seventh Framework Programme for research, technological development and demonstration under grant agreement no. 613256.

D 8.3 - Leaving and returning to the parental home during the economic crisis 3

Executive Summary

This report describes and comparatively identifies the possible economic, institutional and cultural factors that take part in the process of transition to adulthood. The report particularly focuses on the interrelationships of youth unemployment and decisions to leave and return to the parental home. Entering the labour market and residential autonomy are key events in the adulthood transition of young people, with significant consequences on their economic and social well-being. The nexus of leaving and returning to the parental home; parental resources used to facilitate adulthood transitions; the consequences of unemployment and precarious work on the opportunity for young people to establish their own families, and economic independence are critical to understand the barriers encountered in the transition to independent adulthood. Transition to adulthood is shaped by interactions between labour markets, the family (household structure) and public policies.

The report, firstly, outlines the effects of leaving and returning to parental home on the household structure; secondly, it examines the role of economic factors in determining leaving and returning to the parental home in Europe during the crisis; thirdly, it presents an overview of the EU housing policies and discusses how leaving and returning to parental home connect with European housing policies.

The analyses in this report are based on European Union Surveys of Income and Living Standards (EU-SILC) and SILC data from Turkey. The data set covers 28 European countries with the addition of Turkey. The longitudinal part of the SILC data follows individuals/households that are selected from larger cross-sectional data for four consecutive years. In this report, we use waves 7 through 12 which correspond to panels between the years of 2004 and 2012).

Most of the analysis in this report is carried out at the single country level, presenting figures separately for each country. However, for the purposes of discussion and synthesis it becomes useful to think in terms of clusters of countries. We take as our starting point Esping-Andersen’s (1990) three European models of welfare capitalism: social democratic or universalist; liberal; and employment centred models with the additions of dualistic welfare regimes of Southern countries; a post-socialist countries, a cluster for Baltic countries.

When we look at the characteristics of young people who live with their parents the results exhibit two distinct characteristics. First, in all country groups the percentage of young individuals that live with their parents has increased over time. The increase accelerates after the 2008 crisis, particularly in Northern and Continental European countries. Second, there are significant differences across 4 Gökşen, Yükseker, Filiztekin, Öker, Kuz, Mazotta & Parisi

country groups. While this share is below 50% in Northern and Continental countries, it is higher in Mediterranean, Eastern European and Baltic countries. It should also be noted that there is a variation within country groups. In all countries, males are more likely to co-reside with their parents and the gender difference is larger in the Northern and Continental countries. The level of completed education turns out to be an important characteristic to explain young peoples’ living arrangements. More educated individuals are more likely to live independently. However, even the most educated individuals in southern and eastern European countries stay with their parents, whereas the difference between the least educated groups across countries is less pronounced. As for income, we found that before the crisis, in the northern and Western Europe, young people living with their parents were earning significantly less than those who live independently. The highest difference is observed in Turkey where the ones who live with parents were considerably poorer. In the southern and eastern Europe, the difference was significantly less, but incomes earned by those who co-reside with their parents were still substantially lower. After the crisis, there is a tendency towards increasing inequality between those living in parental homes and those who have moved out. This trend is present in all country groups, except the UK and Turkey where there is a tendency of incomes to equalize.

As for youth leaving the parental home, the lowest percentage is found in the Eastern, Baltic, Southern European countries, and in Turkey. The highest is in the UK, followed by Continental and Nordic countries. All welfare regimes registered a decrease in the leaving home decision between 2005 and 2012, with the UK experiencing the highest decrease. With regard to returning to the parental home all countries show very low rates of returning to the parental home. In Turkey, on the other hand, returning to the parental home is slightly higher than the European countries. All the countries show a higher percentage of young people returning home after the economic crisis, however a more substantial increase is found in Southern European countries.

Gender has a significant discriminating influence on the rate of leaving parental home. In line with the literature, we found that gender affects the incidence of leaving and returning to the parental home, but this effect varies across welfare regimes and over time. Leaving parental home is more common among women. Immediately after the onset of the economic crisis, the gap tends to decline despite some differences across groups of countries. In Anglo-Saxon countries, for example, the rate of exit among males was higher than females after the crisis, suggesting that males’ response to the economic crisis was leaving the parental home. In Eastern Europe, on the other hand, males were more likely to stay at home during the years of crisis.

Another factor shaping the decision to leave or return is age. The decision to return is more common among young individuals aged between 25 and 34, compared to the 18-24 age group. Results D 8.3 - Leaving and returning to the parental home during the economic crisis 5

indicate that leaving home among the young is the highest in Nordic countries. In addition to gender and age, employment conditions, marriage, and income have substantial effects on leaving the parental home. Young people leaving home are more likely to be employed. The same pattern is observed for marital status: more than half of those leaving home are married. Looking at the household income, we can see that in the Nordic and Anglo-Saxon countries home leavers have worse economic condition. On the contrary, in Southern, Continental and Eastern countries, richer families foster the exit of their children and this pattern increases with the crisis.

Regarding returning home, while there is considerable variance between the leaving parental home and gender, this difference vanishes when the return patterns are considered. Except for the Eastern European countries, there is almost no difference in the return rates by gender even in the time of economic crisis. For all countries, lower ages indicate more likelihood to come back to the parental home. The rate of return is the highest in Turkey and it is followed by the Anglo-Saxon countries regardless of the economic crisis. Returning home is strictly connected to unemployment; in fact, the percentage of young people employed is higher for the ones living on their own than for those returning home. Particularly strong is the effect of marital or partnership status. Young people without a partner return home more often in all the countries apart from the Eastern bloc countries, where they often return with a partner.

When we analyse the probability of leaving home across income and employment conditions we find that for the southern, eastern and continental European countries, relative higher parental income increases the chances of co-residence, i.e. decreases leaving parental home. Wealthy families can support young people also outside the parental home and so they can foster the exit. On the contrary, poorer parents have no way of controlling the household living arrangement decisions of their child. Income does not have such a big effect on the probability of returning home. However, marital status has a strong effect on both the probability of leaving and returning home. Finally, employment is a good predictor of leaving\returning home but only by an indirect effect that works through marital status.

The housing market and housing policies, in addition to demographic factors and labour market dynamics affect young people’s possibilities of becoming independent and are related to differences in transition regimes. Main axis of divergence is between Anglo-Saxon countries (the UK in this case) and continental Europe. The former is recognizable for the preference for owner occupation of dwellings whereas the latter can be identified with very high levels of renting. In this report, we used housing tenure, housing allowances, and rent control as proxies for housing policies to identify their impact on leaving and returning decisions of the youth. Public housing policies such as housing allowances and rent-controlled or free (social) housing, have a considerable impact on the decision to 6 Gökşen, Yükseker, Filiztekin, Öker, Kuz, Mazotta & Parisi

leave/return to parental home. This impact is more apparent for leave decisions. With the exception of Eastern European countries, the marginal effect of benefiting from housing allowances on the probability of leaving the parental home is positive across welfare regimes. Lack of housing allowance seems to affect the rate of return to parental home, though the effect is marginal. As for the impact of rent-controlled housing on the decision to return, returners are mostly the ones who did not benefit from rent-control. Housing allowance receivers are less likely to come back to the parental home, and those who benefit from rent-control (social tenants) are less likely to return to their parental home. However, divergences from this trend in some regime types point at the role of other housing policies such as massive housing privatization since 1990, mortgage and tax policies, or decreasing overall housing expenditures.

While many of the findings in this report have significant implications for youth policies it is beyond the scope of this report to fully discuss these policy issues. Yet, findings of this report underscore the importance of a holistic approach to understanding the complexity of the extended transitions to adulthood in Europe. The comparative, macro-social tendencies presented in this study require further national and regional analysis as patterns of transitions vary according to the particular institutional contexts of the countries. Typologies used in this report capture some of the variation in individual countries, but leave substantial variation unaccounted for. The country specific differences can only be grasped adequately in their “totality as country specific institutional packages”. Transition to adulthood takes place within a complex framework of structural, institutional, economic, and cultural determinants that differ among countries and this report addresses only a limited number of these determinants. Regional and national divergences can only be understood and interpreted within a historical perspective that includes the cultural differences underlying various life course events over time (Giuliano, 2007; Manacorda and Moretti, 2007).

Key words: Youth unemployment, leaving and returning to parental home, EU housing policies

D 8.3 - Leaving and returning to the parental home during the economic crisis 7

Table of Contents 1. Introduction ...... 10 2. Patterns of living with or apart from parents: Static analysis ...... 13 2.1 Variable selection and limitations ...... 13

2.2 Characteristics of young people living with parents ...... 15

2.3 Gender, age and living with parents ...... 17

2.4 Education and living with parents ...... 20

2.5 Work status and living with parents ...... 24

2.6 Youth income and living with parents ...... 25

3. Patterns of leaving and returning to the parental home and the effect of the economic crisis: Dynamic analysis ...... 31 3.1 Patterns of leaving and returning to parental home ...... 32

3.2 Econometric analysis: Method and results...... 43

4. Housing policies and leaving and returning to the parental home ...... 55 4.1 Overview of the EU housing policies ...... 56

4.2 Housing polices and living with parents: static analysis ...... 59

4.3 Housing Policies and Leaving Parental Home: Dynamic Analysis ...... 64

4.4 Housing Policies and Returning to the Parental Home: Dynamic Analysis ...... 70

5. Conclusion ...... 76 6. Bibliography ...... 80 7. Appendix ...... 84 8. Recent titles in this series ...... 92 9. Research Partners ...... 97 10. Advisory Groups ...... 98

8 Gökşen, Yükseker, Filiztekin, Öker, Kuz, Mazotta & Parisi

Abbreviations

AT Austria BE Belgium BG Bulgaria BME Black and Minority Ethnic CH Switzerland CY Cyprus CZ Czech Republic DE Germany DK Denmark EC European Commission EE Estonia EPL Employment Protection Legislation ES Spain ESF European Social Fund EU European Union EU-LFS European Union- Labour Force Survey EU-SILC European Union Survey on Income and Living Conditions FI Finland FR France GR Greece HU Hungary IE Ireland ILO International Labour Office IS Iceland ISCED International Standard Classification of Education IT Italy LFS Labour Force Survey LT Lithuania LU Luxembourg LV Latvia MT Malta NEET Not in Employment, Education or Training NGO Non-Governmental Organisation NL Netherlands NO Norway OECD Organisation for Economic Cooperation and Development OLS Ordinary Least Squares ONS Office for National Statistics PL Poland PT Portugal RO Romania D 8.3 - Leaving and returning to the parental home during the economic crisis 9

SE Sweden SHARE Survey of Health, Ageing and Retirement in Europe SI Slovenia SK Slovakia SOC Standard Occupational Classification STW School to Work UK United Kingdom VET Vocational Education and Training

10 Gökşen, Yükseker, Filiztekin, Öker, Kuz, Mazotta & Parisi

1. Introduction

This report describes and comparatively identifies the possible economic, institutional and cultural factors that take part in the process of transition to adulthood. The report particularly focuses on the interrelationships of youth unemployment and decisions to leave and return to the parental home. Entering the labour market and residential autonomy are key events in the adulthood transition of young people, with significant consequences on their economic and social well-being. The nexus of leaving and returning to the parental home; parental resources used to facilitate adulthood transitions; the consequences of unemployment and precarious work on the opportunity for young people to establish their own families and economic independence are critical to understand the barriers encountered in the transition to independent adulthood.

Around the world, young people are delaying taking what is commonly regarded as the first step in an independent adult life – moving out of their parents’ home. Recently a number of comparative studies focusing on this issue gained more visibility as the patterns of nest leaving showed significant variations across the countries depending on several labour market dynamics (Billari et. al., 2001). Differences in the pattern of leaving home across European countries reflect institutional, economic, as well as conjunctural factors (Aassve et al., 2002; Billari et al., 2001; Corijn and Klijzing, 2001).

Decision to leave home is expected to be associated with both welfare policies and the household structure of the young adults. It may have significant consequences for important areas of policy, such as the demand for housing (Ermisch & Di Salvo, 1997) and the risk of poverty among young people (Iacovou, Aassve, & Davia, 2007). Furthermore, a significant number of studies have demonstrated that the family structure has a significant influence on the propensity of young adults to leave home (Mitchell et al., 1989; Aquilino, 1991; Mitchell, 1994; Goldscheider & Goldscheider, 1998). There is some evidence that gender has a significant discriminating influence on the departure from the parental home (Thomsin et al., 2004). Given that leaving home requires at least a minimum amount of financial resources, economic independence is a significant prerequisite for moving out of the parental home (Nilsson & Strandh, 1999; Aassve, Billari, & Ongaro, 2001; Jacob & Kleinert, 2008; Couppié & Gasquet, 2009).

Leaving home, however, is not necessarily a simple or unidirectional process (Erscmich, 1999; Iacovou, 2010). Young people retain close links with their parents even after leaving home and, for some, those links are manifested by returning to live at the parental home. Jones (1995) notes that returns to the parental home are less common in the Southern European countries, where home- D 8.3 - Leaving and returning to the parental home during the economic crisis 11

leaving is late. Variations among Northern European countries related to other factors, such as job security and the welfare system, are also likely to have a relevant effect (Iacovou, 2010).

The aim of this report is to analyse the impact of youth unemployment on the decision to leave and return to the parental home in countries with different welfare regimes. This decision is shaped by the interplay between labour markets, the family (household structure) and public policies. Faced with increasing levels of unemployment young people in many EU countries are confronted with more difficulties to start their housing plans compared to former generations. The combination of different elements such as little availability of rental housing, decreased social housing production and increasing youth unemployment, cause many young people to rely more heavily on the family to meet their housing needs.

Most of the analysis in this report is carried out at the single country level, presenting figures separately for each country. However, for the purposes of discussion and synthesis it becomes useful to think in terms of clusters of countries. We take as our starting point Esping-Andersen’s (1990) three European models of welfare capitalism: social democratic or universalistic model which aims to promote equality and provide universal benefits (Nordic countries); a conservative or employment cantered model which reproduces a highly regulated employment regime with a structure of social security which distinguishes between a high level of compensation of those included standard work arrangements and a residual social assistance system (Continental European countries); a liberal model with means-tested benefits and limited social insurance where the labour market is characterized by a high degree of flexibility while the level of qualifications of the work force is rather low (Anglo-Saxon countries). These models have been refined and revised over the years; several researchers have added a family-oriented model which is characterized by low percentage of standard work arrangements and high rate of unprotected living conditions creating a dualistic welfare regime in which family and informal work play and important role (Southern countries); a post-socialist category which is characterized by a moderate degree of employment protection (Eastern countries) (Blossfeld et al., 2005; Iannelli and Smith, 2008); and a cluster for Baltic countries (Gabos, et al., 2015). In addition to providing a theoretically-informed means of simplifying the interpretation of our results, this type of welfare regime typology helps us to consider the links between the welfare state and youth transitions. However, working with clusters such as these carries the risk of reproducing structures of transition to adulthood in a static way, and neglects unique processes of globalization and individualization in specific countries. Thus, the interpretative value of discussing transitions through welfare models should be understood as a “heuristic compromise of medium range validity” (Walther, 2002). Typologies capture some of the variation in individual countries, but leave substantial variation unaccounted for. Transition to adulthood takes place within a complex framework of structural, institutional, economic, and cultural determinants that differ among countries and this 12 Gökşen, Yükseker, Filiztekin, Öker, Kuz, Mazotta & Parisi

report addresses only a limited number of these determinants. Regional and national divergences can only be understood and interpreted within a historical perspective that includes the cultural differences underlying various life course events over time (Giuliano, 2007; Manacorda and Moretti, 2006).

With a view to understanding the interactions between family, labour markets and housing policies this report is organized as follows: the following section outlines the patterns of leaving and returning to parental home and its effects on the household structure; next section examines the role of economic factors in determining leaving and returning to the parental home in Europe during the crisis; the final section presents an overview of the EU housing policies and discusses how leaving and returning to the parental home connect with European housing policies.

D 8.3 - Leaving and returning to the parental home during the economic crisis 13

2. Patterns of living with or apart from parents: Static analysis

2.1 Variable selection and limitations

Our analysis is based on European Union Surveys of Income and Living Standards (EU-SILC) and SILC data from Turkey. The data set covers 28 European countries (with lack of data for Germany) and Turkey. The longitudinal part of the SILC data follows individuals/households that are selected from larger cross-sectional data for four consecutive years. We use waves 7 through 12 (that is, the panel starts in 2004 and ends in 2012). Total number of individuals is 939,131, however, we have a total of 2,956,325 observations due to attrition of individuals or households (a more detailed description of the dataset is provided in the Appendix A- Table 1).

The group we focus on is young population defined as individuals between ages of 16 and 34. According to the 2011 Population and Housing Census in the EU and EFTA countries, the share of this group in the population ranges between 20% and 30% among EU countries, with an overall average of 24.4%. The country with the lowest share of young population in Europe is Italy (20.4%) and the highest share is observed for Cyprus (30.4%). Turkey differs from the rest of Europe markedly, with a younger age profile. The share of young population in Turkey is 33.9% and the share of adult population (those older than 34,) is 49% as opposed to European average of 57%.

In our data set, the share of young population is slightly lower than the number the Census suggests, regardless of any weights. This is mostly due to non-response (attrition) rate in the SILC data (details can be found in Appendix A-Table A.2).

There are a couple of concerns regarding the dataset. First, a quick look at the data reveals that there are many instances when an individual identifies a person as his/her parent in a given year, yet has a missing value in another year even when the parent is present in the household (in wave 10, for example, there are 1446 such cases). Therefore, we identified the parents (and spouses) of each individual1 throughout the panel and then checked whether the parent is present in the year of survey.

1 We have also found that individuals may have identified more than one person as their father/mother/spouse. These cases always refer to incidence of re-marriage. The presence of a step-parent is treated as biological parent. 14 Gökşen, Yükseker, Filiztekin, Öker, Kuz, Mazotta & Parisi

Second, the person may not live with his/her parents, yet may cohabitate with his/her parents-in-law. Identifying the parents of spouses’, we treated such individuals also as ‘living with parents’2. The dynamics of the analysis, changing household status with respect to the presence of parents, involves nine different possibilities (Table2.1):

Table 2.1: Structure of transition matrix Time t+1 Does not live Lives Missing w/ parents w/ parents Obs. Does not live I II A w/ parents Lives

III IV B

t w/ parents Missing C D E Obs. Time Time

The cases I-IV are unambiguously defined moves, and case E refers to a non-response in two consecutive years. In cases A and B, either the individuals grows out of the young population, i.e., turns 35 in year t+1, or is a non-response person who is likely to have moved to a different household with or without parents. Similarly, in cases C and D, either the individual grew into the young population, that is, turns 16 in year t+1, or moves into the panel from a non-panel household with or without parents. As we have missing information on some cases of exit and return, our analysis can only provide a lower bound, that is, reported incidences are possibly smaller number of than actual, for the dynamics of household structure.

There are a few important variables in our analysis that require a clear definition. One such variable is ‘marital status of the individual’. The SILC database contains two variables, ‘marital status’ and ‘consensual union’, though with some inconsistencies. Moreover, as it is the case with parent id variables, we found instances where the spouse id variable has a missing value when the spouse identified in a different year still lives in the household. Thus, our definition of ‘married’ is a variable which takes the value one if the spouse/partner of the individual resides in the same household.

The moves in and out of the parental home are also related to whether the individual is a student or not. We use self-reported economic status variable to identify whether the person is a student in any given year. We use the same variable to construct employment status of the individuals. Any

2 It is also likely that a young individual may live in a household where his/her parents are absent but grandparents are present. Unfortunately, there is no variable in the longitudinal dataset that identifies the relation of each individual to other members of the household. Our incursion into the Turkish data when such identification is possible yields that these are rather rare cases. D 8.3 - Leaving and returning to the parental home during the economic crisis 15

individual, who declares to be employed or self-employed, both full- or part-time, is defined as ‘employed’; those who are currently not employed, but looking for a job and are available for work are defined as ‘unemployed’ and those who are neither employed nor unemployed and nor student are not in the labour force or `inactive’.

Individuals’ income variables in the SILC database do not provide sufficient information about specific individual's income. The dataset also provides information on total household income. However, we have no information as to who owns assets that generate part of the household income. Therefore, we chose to generate a parental income (obtained from employment or through social transfers) variable for each individual. In the case of living with a partner, we also have generated a variable for the partner’s income.

In the following section characteristics such as education, gender, age, income, and working status of young people who co-reside with parents are analysed. We split the whole sample into three sub- periods: pre-crisis, years before 2009; crisis, 2009 and 2010; and post-crisis 2011 and 2012. In addition, we computed and organised the output in different clusters of countries following a welfare regime typology mentioned above Nordic countries (Denmark, Finland, Norway, Sweden, and Ireland and Iceland), Anglo-Saxon (United Kingdom), Continental (Austria, Belgium, France and Luxembourg and Netherlands), Southern countries(Cyprus, Spain, Italy and Portugal, Greece, and Malta), Eastern bloc (Czech Republic, Poland and Slovenia, Slovakia, Bulgaria, and Romania) and finally Baltic countries (Estonia, Latvia and Lithuania).

2.2 Characteristics of young people living with parents

In this section, we analyse the pattern of co-residence with parents across countries over time and discuss possible determinants of household formation in Europe. The shares of young population that live with their parents (Figure 2.1) exhibit two distinct characteristics. First, in all country groups the percentages of young individuals that live with their parents have increased over time. The increase accelerates after the 2008 crisis, particularly in Northern and Continental European countries, albeit form lower levels. Second, there are significant differences across country groups. While this share is below 50% in Northern and Continental countries, it is above 65% in Mediterranean and over 70% in Eastern European and Baltic countries. It should also be noted that there is a variation within country groups (Table 2.2). For example, Ireland is closer to Southern countries, whereas the UK exhibits similar pattern as Continental countries, as does the Czech Republic. Interestingly, despite the hardship observed in Greece after the crisis, the share of young people living with their parents continues to be the lowest among all Mediterranean countries. This may be due to the less 16 Gökşen, Yükseker, Filiztekin, Öker, Kuz, Mazotta & Parisi

pronounced importance of family solidarity in Greece compared to other Southern countries as a strategy for accumulating educational and financial capital (Moreno, 2012).

Similarly, in Turkey the share of young individuals living with their parents is not only lower than the overall average, but also lower than that of the Mediterranean group. This finding can be explained by the relatively early marriage age in Turkey both for females and males compared to other countries in the analysis (average marriage age for women is 23.7 and 26.9 for men (TURKSTAT, 2014)

Figure 2.1: Share of young population (ages 16-34) that live with their parents by clusters of countries (2004-2012) (%) 80 75 70 65 60 55 50 45 40 35 30 2004 2005 2006 2007 2008 2009 2010 2011 2012

Nordic Anglo-Saxon Countries Continental European Countries Mediterranean Countries Baltic States Eastern European Countries Turkey

Source: Authors’ own calculations on EU-SILC Longitudinal data 2005-2012.

Table 2.2: Share of young population (ages 16-34) that live with their parents (2004-2012)3 2004 2005 2006 2007 2008 2009 2010 2011 2012 Nordic Countries 44.2 42.5 41.8 42.9 42.1 43.8 45.1 46.2 48.0 DK 41.6 38.6 38.6 44.1 43.8 48.8 52.7 52.0 57.6 FI 45.5 44.4 44.3 45.3 45.8 43.2 42.4 41.9 44.9 NO 45.2 41.7 39.4 39.8 36.5 38.1 39.8 41.5 44.7 SE 38.9 39.5 40.5 40.6 42.4 46.5 47.0 47.9 44.5 IS 54.6 52.5 52.5 53.0 55.7 55.5 57.0 59.8 59.8 Anglo-Saxon Countries 59.2 47.9 49.6 51.7 51.7 52.0 53.1 55.1 52.6 UK 40.2 43.0 47.3 48.7 50.8 53.1 55.1 52.6 IE 59.2 68.1 72.8 76.0 81.4 80.6

3 Total number of cases by subpopulations and by clusters of countries are presented in the Appendix D 8.3 - Leaving and returning to the parental home during the economic crisis 17

Continental European Countries 42.8 43.1 44.3 45.1 44.2 44.9 46.8 47.8 50.7 AT 51.1 52.4 55.1 53.3 50.8 48.9 48.9 47.7 46.3 BE 41.9 45.7 46.3 48.0 49.0 47.3 47.4 47.5 54.4 LU 28.0 22.6 20.4 22.4 21.4 38.3 43.0 45.2 57.4 FR 42.6 45.3 46.3 47.3 46.1 45.7 48.3 49.9 48.2 NL 38.0 39.7 40.9 42.3 42.3 44.8 47.4 50.3 Mediterranean Countries 65.6 65.5 65.8 66.9 67.0 67.6 69.3 70.7 71.4 IT 63.3 64.0 65.3 66.4 66.3 66.4 68.8 68.8 70.5 ES 68.1 67.4 66.1 66.9 65.5 66.2 67.7 70.3 71.4 PT 69.3 70.9 72.1 73.1 74.7 73.8 75.6 74.8 73.4 GR 63.4 61.5 62.2 63.0 63.1 63.1 64.6 66.8 66.1 CY 65.4 65.5 67.5 69.3 72.3 74.2 75.3 74.9 MT 66.2 68.1 72.2 73.7 72.9 75.6 74.3 Baltic States 73.7 68.7 69.6 69.7 69.7 70.1 70.5 71.1 71.7 EE 73.7 71.1 70.9 70.3 67.9 68.0 66.7 68.8 69.1 LT 69.8 72.6 72.7 73.9 77.5 78.0 76.7 78.2 LV 62.8 64.4 65.7 68.4 66.6 68.5 69.3 69.0 Eastern European Countries 69.0 69.9 71.2 72.7 72.9 74.9 77.1 77.9 CZ 50.4 52.5 55.1 58.5 58.8 61.0 63.6 64.7 HU 60.3 60.8 61.1 66.1 66.4 68.9 72.0 74.8 PL 70.6 71.0 72.5 72.2 72.0 74.1 75.9 75.7 SI 84.4 83.9 84.6 83.6 82.2 83.0 83.5 83.9 SK 79.3 80.2 82.0 82.2 82.1 83.6 86.7 87.8 BG 74.4 78.6 78.7 79.8 81.3 82.4 83.6 RO 61.5 63.6 65.5 70.0 73.4 76.5 TR 59.4 61.7 59.8 60.0 60.7 61.0 64.3 Total 54.6 56.6 58.6 60.3 61.5 62.4 64.3 65.8 67.2 Total Non-TR 54.6 56.6 58.5 60.3 61.6 62.6 64.7 66.4 67.7 Source: Authors’ own calculations on EU-SILC Longitudinal data 2005-2012. (Population weighted shares)

2.3 Gender, age and living with parents A growing literature on living arrangements points at significant differences across genders (Iacovou, 2002; Saraceno & Olagnero, 2004) and age groups (Feijten & Mulder, 2002; Fransson et al., 1998; Goldscheider & DaVanzo, 1985; Mulder & Hooimeijer, 2002; Saraceno & Olagnero, 2004). Figure 2.2 illustrates the difference between males' and females' share of youth that are living with their parents) for groups of countries. In all countries, males are more likely to co-reside with their parents and the gender differences is larger in the Northern and Continental countries, despite the fact that their overall rates are much lower than those of Southern and Eastern European countries. The gap rises rapidly in Anglo-Saxon (UK) countries over time, particularly in the UK where it has doubled after the crisis, as the increase in the share of males living with their parents increases much faster than the share of females. This finding may indicate a more likely association between females’ higher rate of leaving the parental home and family life cycle than with employment cycles. 18 Gökşen, Yükseker, Filiztekin, Öker, Kuz, Mazotta & Parisi

Figure 2.2: Share of males and females who are living with their parents 20

18

16

14

12

10

8

6

4

2

0 2004 2005 2006 2007 2008 2009 2010 2011 2012

Nordic Anglo-Saxon Countries Continental European Countries Mediterranean Countries Baltic States Eastern European Countries Turkey

Source: Authors’ own calculations on EU-SILC Longitudinal data 2005-2012.

Whether a person lives with his/her parents or not also changes with age (Figure 2.3). In all countries more than seventy percent of the 16-24 age group co-resides with their parents and there is little variation across countries (Figure 2.3). In Continental Europe and the UK the share of 25-34 age group living with their parents is between 10% and 20%, the share is even lower in Northern countries while in the south and east of Europe the rate is higher than 40%. These shares seem to be quite stable over the recent economic crisis.

The last panel (Figure 2.3) shows the share of adult population (aged 35 and more) that lives with parents. The share of adult population that shares house with their parents is quite stable over time (over the recent crisis), with the exception of Eastern European countries and Turkey where the shares increase slightly. As it is with young population, there are significant differences across country groups; in the south and east of Europe, multi-generational households are more likely to be formed. This figure suggests that the difference of living arrangements in these countries is not unique to young population; either preferences or social and economic conditions in the latter group of countries are significantly different and living in larger households is a more likely outcome.

D 8.3 - Leaving and returning to the parental home during the economic crisis 19

Figure 2.3: Living with the parents by age across clusters of countries Panel a: Ages 16-24 100.0

50.0

0.0 2005 2008 2012

Nordic Anglo-Saxon Countries Continental European Countries Mediterranean Countries Baltic States Eastern European Countries Turkey

Panel b: Ages 25-34 80.0

60.0

40.0

20.0

0.0 2005 2008 2012

Nordic Anglo-Saxon Countries Continental European Countries Mediterranean Countries Baltic States Eastern European Countries Turkey

Panel c: Ages 35 and more

15.0

10.0

5.0

0.0 2005 2008 2012

Nordic Anglo-Saxon Countries

Continental European Countries Mediterranean Countries Baltic States Eastern European Countries Turkey

Source: Authors’ own calculations on EU-SILC Longitudinal data 2005-2012. 20 Gökşen, Yükseker, Filiztekin, Öker, Kuz, Mazotta & Parisi

2.4 Education and living with parents

The discussion of age groups regarding whether they live in or out of the parental home needs to address the schooling/education status of young individuals (Feijten & Mulder, 2005; Breen & Buchman, 2002). In our sample an overwhelming majority of individuals younger than 19 is student, and between one third and one half aged between 20 and 22 reported that they are continuing with their education4. The decision to stay in school depends on the ease of access to education, available financial opportunities and existence of widespread education facilities. Another potential explanation for the decision to continue education is labour market conditions. In regions with stronger labour demand young individuals choose to move into the labour market, whereas when demand for labour is limited they opt to live with their parents and stay in school.5 The important point is, however, that the share of students increases in most countries during the crisis and continues to stay at a higher level than the pre-crisis values. The negative shock to the European economies had a positive impact on schooling and once the level has increased there seems to be some persistence.6

4 It is very difficult in these surveys to capture the residence choice of university students. In some countries students more often than not prefer to live with their parents while in university, in others they choose to move to other cities. 5 See Table A.4 in the Appendix for differences in the share of students across countries. 6 As the supply of educated individuals increase in the labour market, their relative wages are expected to decline if there is substitution between skilled and unskilled workers. Therefore the persistence can be explained either the labour market conditions have not improved right after the crisis years or substitution is limited or external economies are at work. It is not possible to demonstrate which of these factors are more probable within the short time span here. D 8.3 - Leaving and returning to the parental home during the economic crisis 21

Table 2.3: Share of non-student young (ages 16-34) population that live with their parents across clusters of countries (2004-2012) 2004 2005 2006 2007 2008 2009 2010 2011 2012 Nordic Countries 28.1 26.6 25.8 26.1 25.8 30.1 26.6 28.2 30.7 DK 25.7 22.0 23.3 26.2 28.6 34.7 30.5 29.3 32.8 FI 26.1 26.0 24.3 25.4 27.1 30.6 23.5 24.1 27.3 NO 25.4 24.4 25.7 24.3 20.9 25.6 22.2 23.1 27.7 SE 23.0 24.0 25.4 25.9 27.4 31.7 31.9 34.4 34.4 IS 46.0 44.5 35.0 35.2 38.6 40.4 34.6 40.2 39.0 Anglo-Saxon Countries 46.9 40.2 42.1 44.2 44.7 43.1 43.2 45.2 41.2 UK 34.9 36.9 41.0 42.5 42.1 43.2 45.2 41.2 IE 46.9 57.3 63.9 66.4 73.2 72.0 Continental Countries 27.0 28.5 28.7 28.4 27.3 30.8 29.1 31.1 33.1 AT 43.2 43.8 45.8 44.2 41.1 39.0 39.6 39.5 37.0 BE 26.4 30.6 30.3 29.1 29.7 34.7 27.8 30.3 34.7 LU 19.8 13.5 10.8 11.6 11.3 25.5 24.8 26.8 36.7 FR 22.0 25.3 26.6 26.7 27.0 32.7 28.9 31.6 31.4 NL 26.2 23.1 22.7 22.8 22.1 23.8 26.1 27.5

Mediterranean Countries 58.3 56.2 56.3 57.3 57.3 59.7 59.0 60.0 60.6 IT 54.4 54.3 55.3 56.1 55.4 58.2 56.6 56.2 56.8 ES 62.5 58.3 56.3 57.1 55.5 55.6 56.5 57.7 58.9 PT 60.5 61.6 63.5 64.7 67.3 67.6 66.9 65.6 64.2 GR 57.9 55.5 56.4 57.0 57.4 58.7 59.0 61.3 60.7 CY 50.8 50.5 51.7 52.8 61.5 59.2 60.3 60.6 MT 58.4 61.2 66.9 69.6 67.5 70.8 69.2

Baltic States 60.7 55.1 54.9 56.3 56.2 61.9 57.9 59.4 60.5 EE 60.7 56.3 55.2 55.6 51.4 58.6 51.0 55.5 56.5 LT 56.5 56.1 58.2 60.1 69.3 65.4 64.2 67.6 LV 51.9 53.4 55.8 58.5 60.3 59.2 59.9 59.1 Eastern European Countries 56.8 58.3 59.9 61.8 64.5 64.4 67.0 68.0 CZ 36.4 37.4 39.3 43.2 49.8 45.0 47.5 49.3 HU 50.3 49.7 48.9 53.6 52.6 56.0 58.7 61.0 PL 60.3 62.0 64.0 63.5 66.3 66.0 68.0 68.4 SI 75.0 73.8 74.7 73.2 73.5 71.3 73.0 72.8 SK 68.3 70.3 72.3 73.5 74.9 74.5 78.5 80.8 BG 70.1 74.8 74.9 76.7 77.8 78.2 78.7 RO 53.4 54.1 55.9 60.5 63.8 69.3 TR 56.1 58.0 56.7 56.0 56.3 55.7 59.0 Total 43.1 44.3 46.6 48.4 50.0 53.3 52.7 54.4 56.0 Total Non-TR 43.1 44.3 46.1 47.7 49.3 53.0 52.2 54.2 55.5 Source: Authors’ own calculations on EU-SILC Longitudinal data 2005-2012. (Population weighted averages)

22 Gökşen, Yükseker, Filiztekin, Öker, Kuz, Mazotta & Parisi

Recalculated proportion of young individuals who live with their parents (after students are excluded7) are given in Table 2.3 for all countries and plotted for country groups in Figure 4. As expected smaller share of young individuals choose to live with their parents when students are excluded compared to that when students are included. The variation across countries has not changed significantly when students are excluded; in Northern and Continental countries the shares are significantly lower than remaining countries, with the share in the UK staying in between.

Figure 2.4: Share of non-student young population (ages 16-34) that live with their parents by clusters of countries (2004-2012) 80 70 60 50 40 30 20 2004 2005 2006 2007 2008 2009 2010 2011 2012

Nordic Anglo-Saxon Countries Continental European Countries Mediterranean Countries Baltic States Eastern European Countries Turkey

Source: Authors’ own calculations on EU-SILC Longitudinal data 2005-2012.

The level of completed education turns out to be an important characteristic to explain peoples’ choice of living arrangements. The figures refer to those who have currently completed/not continuing their education. If age is a determinant of living arrangements , then in countries where school leaving age is high (e.g. some Nordic countries) the observed differences may reflect the differences in age as much as completed education. While more educated individuals are more likely to live independently, there are variations across countries. In Figure 2.5, the shares of young non-student population who co-resides with their parents are given for each completed level of education and for three different sub-periods. The proportion of individuals who have at least a university degree and live with their parents is lower than those of other groups. However, even the most educated individuals in southern and eastern European countries stay with their parents, whereas the difference between the least educated groups across countries is less pronounced. The figure also

7 We analysed young people aged 18-34 years old the first time they are observed. Given this age range we decided to exclude students. Students, in fact, could bias results as young people aged 18-34 are quite likely to be in further education and so they may have remained at home just for this reason. In fact, in Nordic and Continental countries, more than 50% of those living with their parents are students. D 8.3 - Leaving and returning to the parental home during the economic crisis 23

reveals that in all categories the share of co-residence increases with the crisis and declines afterwards but remains above the pre-crisis levels with less educated individuals affected more than the others.

Figure 2.5: Share of non-student young population (ages 16-34) that live with their parents by completed education level across clusters of countries

Panel a: 2005-2008 90.0 80.0 70.0 60.0 50.0 40.0 30.0 20.0 10.0 0.0 Nordic Ang-Sax Cont. Med. Baltic EEC Turkey

LT Secondary Secondary Tertiary

Panel b: 2008-2010 80.0

60.0

40.0

20.0

0.0 Nordic Ang-Sax Cont. Med. Baltic EEC Turkey

LT Secondary Secondary Tertiary

Panel c: 2010-2012 90.0 80.0 70.0 60.0 50.0 40.0 30.0 20.0 10.0 0.0 Nordic Ang-Sax Cont. Med. Baltic EEC Turkey

LT Secondary Secondary Tertiary

Source: Authors’ own calculations on EU-SILC and Turkey-SILC Longitudinal data 2005-2012. 24 Gökşen, Yükseker, Filiztekin, Öker, Kuz, Mazotta & Parisi

2.5 Work status and living with parents With the exception of the UK, the effect of crisis is also observed as an increasing rate of inactive population and unemployment rate with the exception of the UK (Appendix-Table A.4). An individual is defined to be ‘employed’ if he/she works either full or part time; is designated to be ‘unemployed’ if not employed, looking for a job and ready to work; and called ‘inactive’ if not part of the labour force excluding students. Different working statuses are found to effect living with one’s parents. Figure 2.6 provides the share of young individuals by his / her employment status that co-reside with their parents in each country group. Interestingly, inactive individuals started to live more with their parents before the crisis which may be the indication of a response to the early signals of the recession in the European labour markets.8

Figure 2.6: Share of young adult (ages 16-34) population living with their parents by working status across clusters of countries (2005-2012) a. Nordic countries b. Anglo-Saxon countries (UK)

80 80 60 60 40 40 20 20 0 0 2005 2006 2007 2008 2009 2010 2011 2012 2005 2006 2007 2008 2009 2010 2011 2012

Employed Unemployed Inactive Employed Unemployed Inactive

c. Continental European countries d. Mediterranean countries

80 80 60 60 40 40 20 20 0 0 2005 2006 2007 2008 2009 2010 2011 2012 2005 2006 2007 2008 2009 2010 2011 2012

Employed Unemployed Inactive Employed Unemployed Inactive

8 Data were cross-checked for any inconsistencies which would lead to these significant increases in this particular time frame. D 8.3 - Leaving and returning to the parental home during the economic crisis 25

Figure 2.6: Share of young people (ages 16-34) living with parents by work status (Continued) e. Baltic states f. Eastern European countries

80 80 60 60 40 40 20 20 0 0 2005 2006 2007 2008 2009 2010 2011 2012 2005 2006 2007 2008 2009 2010 2011 2012

Employed Unemployed Inactive Employed Unemployed Inactive

g. Turkey

80 60

40 20 0

2005 2006 2007 2008 2009 2010 2011 2012

Employed Unemployed Inactive

Source: Authors’ own calculations on EU-SILC Longitudinal data 2005-2012.

2.6 Youth income and living with parents An important determinant of the decision on leaving parental home is expected to be income, be it the child’s or parents’. Le Blanc and Wolff (2006) show that children with more income of their own tend to live independently, yet they found little influence of parents’ income on decision to leave parental home, suggesting that the altruistic models’ (Ermisch, 1999; Manacorda and Moretti, 2007) predictions are, at best, questionable. This section provides a descriptive analysis of individual income and co-residing with parents.

Table 2.4 provides the ratio of incomes who live with their parents to income of those who live independently. For married couples, income variable is the sum of both partners’ income9. Before the

9 We are considering married couples as one unit, upon the assumption that their decision to live with or without parents depends on their total income. The comparison group is, then, married couples who live independent of their parents. 26 Gökşen, Yükseker, Filiztekin, Öker, Kuz, Mazotta & Parisi

crisis, in the northern and western Europe, singles living with their parents were earning significantly less than those who live independently. The highest difference is observed in Turkey where the ones who live with parents were considerably poorer. In the southern and eastern Europe, the difference was significantly less, but incomes earned by those who co-reside with their parents were still substantially lower. After the crisis, there is a tendency towards increasing inequality between those living in parental homes and those who have moved out. This trend is present in all country groups, except the UK and Turkey where there is a tendency of incomes to equalize.

For couples, however, the ratio, while still below unity, was substantially higher in the western and northern Europe and not much different in the remaining countries before crisis. Again, there is a decline in the ratio; average income of those living with parents decreases relative to those who are not. This could be either due to declining incomes of those who live with their parents, or that individuals move in with their parents as they get poorer, leading to an overall decline in the average income of those living with their parents.

The EU-SILC data also provide information on the income distribution in each country and classify households based on equivalised disposable income in quintiles.10 In Figure 2.7, the percentage of those who live with their parents in top and bottom quintiles are plotted by country group.11 In the Nordic countries, higher share of young individuals of the lowest and top quintiles are living with their parents, whereas in the UK, to stay at parents’ home is observed at a higher rate in the middle income groups. Higher rates of living with the parents among low-income groups in the Nordic countries can be explained that the Nordic countries provide universal and non-taxable monetary child benefits paid to families with children up until the age 20 (age limit differs in different Nordic countries).12 In the Continental Europe, staying with parents increases with household income level. In Baltic States and Eastern European countries, the trend is similar to the UK, and the shape of at- risk-income curve is closer to the Continental countries. After the crisis, the shapes stay similar, except in Nordic countries where middle income group now hosts more children in parents’ home.

10 The equivalised disposable income is the total income of a household, after tax and other deductions, that is available for spending or saving, divided by the number of household members converted into equalised adults; household members are equalised or made equivalent by weighting each according to their age, using the so-called modified OECD equivalence scale (http://ec.europa.eu/eurostat/statistics-explained/index.php/Glossary:Equivalised_disposable_income). 11 There is no information in Turkish data on income quintiles of households. 12 We are a bit reluctant to speculate too much on the findings where we do not have data. Data and the analysis we undertook cannot address the causality problem. There is a considerable identification problem which cannot address the question of whether decision to live with parents is dependent on the income, or whether income is dependent on the decision to live with the parents. D 8.3 - Leaving and returning to the parental home during the economic crisis 27

Table 2.4: Income of youth (ages 16-34) living with parents relative to income of youth living independently (%) Singles Married Couples Pre- Post- Pre- Post- Crisis Crisis Crisis Crisis Nordic 50.6 42.6 71.0 51.3 DK 37.2 42.4 81.6 32.2 FI 48.4 56.3 86.2 99.6 NO 41.2 43.0 71.3 45.8 SE 45.7 36.9 66.5 47.5 IS 56.6 61.6 55.8 57.9 Anglo-Saxon Countries 58.3 68.0 65.7 74.1 UK 58.3 68.0 65.7 74.1 IE 79.2 92.1 Continental European Countries 61.7 60.2 71.7 63.3 AT 75.4 73.0 80.9 74.9 BE 59.8 74.3 80.3 46.6 LU 44.6 64.6 69.7 61.2 FR 46.8 48.7 70.8 51.6 NL 43.8 46.8 66.5 54.9 Mediterranean Countries 67.6 63.4 68.0 65.9 IT 63.7 59.9 80.5 76.8 ES 61.8 63.7 65.7 59.2 PT 71.8 78.2 63.5 73.4 GR 64.2 54.5 58.5 70.3 CY 63.0 87.5 69.9 68.4 MT 196.4 138.1 85.7 59.8 Baltic States 73.4 63.8 77.7 74.3 EE 60.0 55.5 75.7 76.8 LT 63.1 76.8 79.8 73.9 LV 68.2 64.5 79.5 82.5 Eastern European Countries 82.0 78.7 69.7 65.2 CZ 73.7 81.4 79.5 75.8 HU 60.2 49.7 73.3 58.8 PL 52.2 63.3 64.5 73.0 SI 85.0 80.4 76.9 82.8 SK 67.6 78.9 76.6 74.9 BG 76.6 91.7 66.9 56.4 RO 45.2 67.0 58.4 75.4 TR 37.7 52.3 31.1 53.8

Source: Authors’ own calculations on EU-SILC Longitudinal data 2005-2012. (Population weighted shares)

28 Gökşen, Yükseker, Filiztekin, Öker, Kuz, Mazotta & Parisi

Figure 2.7: Staying at home by income quintiles

a. Before 2009

0.5 0.7 0.4 0.65 0.3 0.6 0.2 0.1 0.55 0 0.5 Lowest Sec. Third Fourth Top 20% Lowest Sec. Third Fourth Top 20% 20% Quint. Quint. Quint. 20% Quint. Quint. Quint.

Nordic Anglo Continent Med. Baltic Eastern

b. 2009 and after

0.5 0.7

0.4 0.65 0.3 0.6 0.2 0.1 0.55 0 0.5 Lowest Sec. Third Fourth Top 20% Lowest Sec. Quint. Third Fourth Top 20% 20% Quint. Quint. Quint. 20% Quint. Quint.

Nordic Anglo Continent Med. Baltic Eastern

Source: Authors’ own calculations on EU-SILC Longitudinal data 2005-2012.

Lastly, there is the question, as Kahn et al. (2013) put it, “who supports whom?” To that end, first an indicator variable is generated that takes a value of one if the income of an individual (or sum of partners) is less than 40% of parents’ (or parent-in-laws’ income) and zero otherwise.13 First two columns of Table 2.5 show the percentage of those with an income less than the assigned threshold of parents’ income. In the Nordic countries and the UK, parental support (income differential which is taken as a proxy for parental support), whether the relative income ratio is above the threshold or whether the parents provide accommodation, is higher than in other countries. This may be an effect

13 Kahn et al. (2013) uses this threshold for the US and report that subsequent tests with different threshold values do not make any significant difference. D 8.3 - Leaving and returning to the parental home during the economic crisis 29

of a higher share of double breadwinning parents and/or higher share of working students both in the UK and Nordic countries (Sainsbury, 2003). The parental income support declines after the crisis in all countries except Turkey.

The second variable is about the first two persons who provide accommodation. We have generated a variable that takes the value of one if exclusive responsibility for housing is on parents and zero otherwise. The table shows that the nature of parental support for those who are living with parents is most likely to be through providing free accommodation. In most countries, parental accommodation support is above 75%, with the lowest figure observed for Bulgaria.

Table 2.5: Parental income and accommodation support (pre and post Crisis) Income Support Accommodation Support Pre-Crisis Post-Crisis Pre-Crisis Post-Crisis Nordic Countries 40.3 25.0 89.7 82.6 DK 42.3 26.2 89.7 92.6 FI 43.1 22.3 92.4 93.9 NO 38.6 22.5 90.1 95.8 SE 39.5 31.4 92.5 48.6 IS 40.1 22.8 80.6 85.9 Anglo-Saxon Countries 63.3 58.2 96.5 86.9 UK 63.3 58.2 96.4 86.7 IE 22.3 96.8 95.8 Continental European Countries 34.9 23.0 85.8 91.2 AT 21.9 24.5 86.9 87.8 BE 35.8 16.4 90.2 89.7 LU 25.2 20.6 77.3 87.7 FR 38.5 22.8 74.3 91.2 NL 46.4 29.8 98.8 98.9 Mediterranean Countries 35.1 23.2 88.5 88.2 IT 36.7 24.2 89.2 89.2 ES 30.9 22.7 87.7 84.3 PT 32.7 20.3 86.2 86.9 GR 38.7 27.8 89.4 89.6 CY 48.8 24.4 86.8 90.5 MT 26.7 17.2 92.7 92.9 Baltic States 34.0 21.7 72.7 79.7 EE 34.2 20.4 68.8 82.7 LT 37.0 22.5 79.9 81.2 LV 31.2 22.2 72.4 75.9 Eastern European Countries 34.6 20.2 79.6 77.6 CZ 28.3 14.0 91.2 92.9 HU 35.1 32.5 78.1 79.8 PL 35.1 20.6 76.7 78.4 SI 31.0 13.7 81.6 76.8 SK 38.0 16.3 82.2 74.5 BG 36.6 20.6 62.9 66.6 RO 56.7 23.1 71.8 75.7 TR 13.7 26.8 n.a. n.a. Source: Authors’ own calculations on EU-SILC Longitudinal data 2005-2012. (Population weighted averages) 30 Gökşen, Yükseker, Filiztekin, Öker, Kuz, Mazotta & Parisi

To conclude this section, in all country groups the share of young individuals that live with their parents have increased over time. The increase accelerates after the 2008 crisis, particularly in Northern and Continental European countries. In all countries, males are more likely to co-reside with their parents and the gender differences is larger in the Northern and Continental countries, despite the fact that their overall rates are much lower than those of Mediterranean and Eastern European countries. The share of adult population that shares house with their parents is quite stable over time (over the recent crisis), with the exception of Eastern European countries and Turkey, where the shares increase slightly. In the south and east of Europe, multi-generational households are more likely to be formed. This finding suggests that the difference of living arrangements in these countries is not unique to young population; either preferences or social and economic conditions in the latter group of countries are significantly different and living in larger households is a more likely outcome. Sub-protective welfare structure in the Southern European countries which are characterized by low percentage of standard work arrangements and high rate of unprotected living conditions has created a “dualistic” welfare regime in which family plays a significant role. This state-family dependence (Moreno, 2012) may have contributed to the pattern of familialism that would explain the late transitions to adulthood in the Southern European countries. Unlike Southern countries, state is present throughout the entire life-cycle of its citizens in the Nordic countries by providing support for individual autonomy. Young people receive universal allowances regardless of their economic situation or the support they receive from their families (Moreno, 2012) which may speed up the transitions to residential autonomy.

The level of completed education turns out to be an important characteristic to explain young peoples’ residential patterns. More educated individuals are more likely to live independently. Results reveal that the share of co-residence increases with the crisis and declines afterwards but remains above the pre-crisis levels with less educated individuals affected more than the others. Before the crisis, in the northern and western Europe, singles living with their parents were earning significantly less than those who lived independently. After the crisis there is a tendency towards increasing this inequality between those living in parental homes and those who have moved out in all country groups, except the UK and Turkey where there is a tendency of incomes to equalize.

D 8.3 - Leaving and returning to the parental home during the economic crisis 31

3. Patterns of leaving and returning to the parental home and the effect of the economic crisis: Dynamic analysis

The transition of young adults from their parents’ homes to other living arrangements is linked to many economic and social outcomes such as completing schooling, beginning a job, forming a family, living with a partner and perhaps having children. In this section, we analysed the patterns of leaving and returning to parental home and the role of economic factors in determining leaving and returning to the parental home in Europe (and in Turkey) considering three important steps to adulthood all together (namely, completing schooling, the transition to work, and forming a family). In particular, we examined the leaving home decision of young Europeans (aged 18-34) considering simultaneously both the employment and the marital status (or in partnership) of young people after leaving. At the same time, we need to examine the returning home decision of young Europeans (aged 18-34) considering simultaneously both their employment and their marital status after returning home.14 Secondly, we analysed whether the economic crisis has affected the emancipation model as well as the patterns of leaving and returning home.

The wide-spread economic recession that followed the financial crisis of 2007–08 had wide-ranging and long-lasting impacts on household incomes. Living in the family home may provide an important support during unemployment spells or job search. In particular, young people are expected to be more likely to return to the parental home (the so called boomerang generation) during the economic crisis in countries (i.e. UK) where the average age of leaving is low (Iacovou & Parisi, 2009).

Research suggests that individual-level factors (including marital status and economic activity), parental-level factors (including economic background), and contextual factors (such as house prices and share of social housing, tax breaks, share of rental sector, see later section) can all affect the likelihood of leaving/returning to parental home (Ermisch, 1999; Mazzotta & Parisi, 2015; Vanzo & Goldscheider, 2010).

14 We excluded 16-17 year olds because they have not yet reached full 'adulthood' and hence in some countries face some legal restrictions in leaving home and/or in forming a family - for example in some countries, until age 18 a person may not marry without parental consent. However, in practical terms, it makes virtually no difference to either the descriptive statistics or the econometric analysis since 16-17 year olds make up only 1-3% of the 16-34 year old sample. 32 Gökşen, Yükseker, Filiztekin, Öker, Kuz, Mazotta & Parisi

Following Billari and Tabellini (2010) we consider that the pattern of transition to adulthood is due to two different explanations: one emphasises culture or cultural change, and the other focuses on economic and institutional factors. We argue that the decision of leaving\returning to the parental home is driven by the economic status (income) before the transition, as well as the employment and marital status or forming a partnership during the transition. We also consider the effect of culture, social policy, or in general institutional differences, looking at different countries in different welfare regimes.

3.1 Patterns of leaving and returning to parental home The data used in this section are drawn from EU-SILC survey. We analysed young people aged 18- 34 years old the first time they are observed. Given this age range we also decided to exclude students. Students, in fact, could bias results as young people aged 18-34 are quite likely to be in further education and so they may have remained at home just for this reason. Indeed, in Nordic and Continental countries, more than 50% of those living with their parents are students.15 Moreover unemployed, student and inactive would all be included in the same reference category (as they are all not employed) and it could also be a problem to distinguish between them. We considered the panel structure of EU-SILC for the period 2005-2012, and for each panel we considered a couple of years. The selection of the period enabled us to use three dummy periods to disentangle the effect of the two important economic crises that Europe faced, i.e. the economic crisis of 2009 and the sovereign debt crisis of 2010.16

The first variable we consider is the observed probability of Leaving Home (L). L describes whether young Europeans, who were living in the family of origin at time t, are still living with their parents at t+1. If the individual is not in the family of origin at t+1 we can observe his/her transition: whether he/she has left home alone, whether he/she has left home to live with a partner and whether he/she is not in the panel anymore (attrition). However, we do include in the category of leaving also young people that were living with their parents at t and not living with their parents at t+1 because their parents have left home.

15 The situation is very different in the UK where we find the lowest percentage of students among individuals living at home; English students are more likely to stay in college accommodation during their university education. 16 The starting point of the financial crisis was the 2008 subprime crisis in the US. European countries faced a major economic recession in 2009 following the US crisis and a second crisis due to the current sovereign debt in 2010. Given the data available of the data we can consider the years before 2008 as a period before the economic crisis, the years 2008 and 2009 as the period where the economic crisis start so we can see its first effect, and finally the years 2010 and 2011 as a period where for some countries (i.e. Mediterranean) took place the current sovereign debt crisis while for some other (i.e. Continental and Nordic) a period of recover start.

D 8.3 - Leaving and returning to the parental home during the economic crisis 33

The second variable of interest is the probability of Returning Home (R). R describes whether young Europeans, who were living on their own at time t, are still living without their parents at t+1. If the individual is living with their parents at time t+1, we know his/her transition: whether he/she has returned to the parental home or his\her parents have returned home; whether he/she has returned to parental home with a partner or not.

Figure 3.1 shows the share of young people leaving home aged 18-34 during the period under consideration (2005–2012). The lowest percentage of youth leaving the parental home is found in the Eastern, Baltic, Southern European countries and in Turkey (respectively 3.08%, 4.65%, 6.09% and 7.22%). The highest is in the UK precisely 14.01%, followed by Continental and Nordic. Except for the Nordic and Eastern Countries, descriptive statistics 17 show that all welfare regimes registered a decrease in the leaving home decision between 2005 and 2012, with the UK experiencing the highest decrease (from 14% in 2005 to 7% in 2012). In the total sample, the rate of leaving home decreased by two percentage points (p.p.) during the same period (Table 3.1).

Figure 3.1: Observed rate of leaving home for children aged 18-34 living with their parents at time t (students excluded) 18% 16% 14% 12% 10% 8% 6% 4% 2% 0% 2005- 2006 2006-2007 2007-2008 2008-2009 2009-2010 2010-2011 2011-2012

Nordic Anglo-Saxon Continental Mediterranean Eastern European Baltic Turkey

Source: Authors’ own calculations on EU-SILC Longitudinal data 2005-2012.

With regard to returning to the parental home (Figure 3.2) all the European Countries show very low rates of returning to the parental home (from 0.46% of Nordic to 1.27% of Southern Countries). In Turkey, on the other hand, returning to the parental home is slightly higher than the European countries (around 3%). There is no regularity in the patterns observed, all the countries show a higher percentage of young people returning home during the economic crisis (2008-2009), however the

17 We test whether the differences between the two percentages and the beginning and at the end of the period (2005-2006 and 2011-2012) are statistical significant and they are statistically different from zero at 1% level. 34 Gökşen, Yükseker, Filiztekin, Öker, Kuz, Mazotta & Parisi

deepest increase is found in Southern European countries (one p.p.). In the total sample of 18 to 34 year olds (excluding students), between 2005 and 2012 the retuning rate increase of 0.47 p.p. (Table 3.1).

Figure 3.2: Observed rate of returning home for young people aged 18-34 living without parents at time t (students excluded) 4.0% 3.5% 3.0% 2.5% 2.0% 1.5% 1.0% 0.5% 0.0% 2005- 20062006-2007 2007-2008 2008-2009 2009-2010 2010-2011 2011-2012

Nordic Anglo-Saxon Continental Mediterranean Eastern European Baltic Turkey

Source: Authors’ own calculations on EU-SILC Longitudinal data 2005-2012.

As discussed in the literature and recalled in section one, gender has a significant discriminating influence on the decision of exit and return decisions of the young individuals (Thomsin et al., 2004; Billari, Philipov and Baizán, 2001). In line with the literature, we found that gender affects the decision to leave/return to parental home, but this effect varies across welfare regimes and over time. Figure 3.3 shows how leaving parental home is more common among women. Note that in 2009, immediately after the onset of the economic crisis, the gap tends to decline despite some differences across groups of countries. In Anglo-Saxon countries (UK), for example, the rate of exit among males was higher than females during the crisis, suggesting that males’ response to the economic crisis was leaving the parental home. In Eastern Europe, on the other hand, males were more likely to stay at home during the years of crisis.

D 8.3 - Leaving and returning to the parental home during the economic crisis 35

Table 3.1: Number of observations for the sample of young people (18-34) leaving and returning home (excludes students) Nordic Anglo-Saxon Continental Mediterranean Eastern European Baltic Turkey Total Living Living Living Living Living Living Living Leaving Leaving Leaving Leaving Leaving with Leaving Weighted with Weighted with Leaving Weighted with Weighted with Weighted with Weighted with Weighted Living with Leaving home a home a home a home a home a Weighted % parent at home a t+1 % parent at % parent at home a t+1 % parent at % parent at % parent at % parent at % parent at t home a t+1 t+1 t+1 t+1 t+1 t+1 t t t t t t t 2005- 2006 293 34 7.73% 372 56 14.19% 2,720 276 16.15% 6,169 411 6.27% 4,082 157 3.35% 1,551 87 7.09% 15,187 1,021 9.54% 2006-2007 517 54 9.57% 649 64 9.66% 4,882 499 15.83% 11,463 636 5.78% 8,080 318 3.33% 3,437 177 5.60% 1459 105 6.71% 30,487 1,853 8.92% 2007-2008 488 55 8.91% 581 75 12.41% 4,390 450 12.84% 11,268 731 7.04% 7,679 289 3.16% 3,632 157 3.75% 2861 206 6.72% 30,899 1,963 8.34% 2008-2009 552 51 6.68% 696 44 6.07% 4,001 442 15.22% 11,489 662 6.24% 6,271 233 3.28% 3,160 143 3.45% 3970 402 9.19% 30,139 1,977 9.11% 2009-2010 497 48 16.57% 661 71 9.70% 4,292 387 10.82% 10,943 574 5.04% 5,805 220 2.68% 3,145 174 5.00% 4048 285 6.58% 29,391 1,759 6.77% 2010-2011 402 31 11.67% 537 36 7.10% 3,427 398 15.04% 7,869 543 7.17% 4,624 159 2.62% 2,510 109 4.55% 2675 193 6.73% 22,044 1,469 9.19% 2011-2012 258 20 7.95% 393 26 6.62% 1,952 183 13.05% 4,597 230 4.62% 2,718 92 3.37% 1,406 54 3.18% 1422 87 5.77% 12,746 692 7.48% Total 3,007 293 10.13% 3,889 372 8.99% 25,664 2,635 14.01% 63,798 3,787 6.09% 39,259 1,468 3.08% 18,841 901 4.65% 16,435 1,278 7.22% 170,893 10,734 8.45% Not Not Not Not Not Not Not living living Returnin living living Returnin living Returnin living Returnin living Returnin Not living Returning Weighted Weighted Returning Weighted Weighted Weighted Weighted Weighted Returning with with g home with with g home with g home with g home with g home with parent Weighted % home at t+1 % % home at t+1 % % % % % home at t+1 parent at parent at at t+1 parent at parent at at t+1 parent at at t+1 parent at at t+1 parent at at t+1 at t t t t t t t t 2005- 2006 1,364 17 0.47% 1,791 9 0.59% 7,894 55 0.49% 5,084 61 1.09% 4,879 63 1.16% 1,676 23 1.16% 22,688 228 0.68% 2006-2007 2,510 15 0.30% 2,722 10 0.37% 13,751 84 0.78% 8,898 83 0.81% 9,754 55 0.45% 3,671 29 0.74% 1036 25 2.36% 42,342 301 0.75% 2007-2008 2,315 22 0.53% 2,302 4 0.14% 13,886 76 0.78% 9,020 103 1.21% 9,183 61 0.52% 3,919 25 0.56% 2010 52 2.52% 42,635 343 0.84% 2008-2009 1,771 17 0.27% 1,781 14 0.65% 9,815 58 0.52% 7,531 110 1.33% 6,440 33 0.39% 3,062 52 1.55% 3165 116 3.54% 33,565 400 0.72% 2009-2010 1,272 10 0.10% 1,335 12 1.10% 9,420 91 1.61% 6,071 94 1.59% 4,880 28 0.45% 2,467 34 1.60% 3188 92 2.80% 28,633 361 1.47% 2010-2011 545 7 1.82% 683 3 0.51% 4,676 23 0.57% 2,778 44 1.10% 2,585 19 0.87% 1,250 14 1.10% 2210 71 3.11% 14,727 181 0.73% 2011-2012 814 6 0.60% 965 6 0.75% 5418 42 0.95% 3538 57 2.12% 3394 14 0.50% 1724 14 0.52% 977 23 2.30% 16,830 162 1.15% Total 10,591 94 0.46% 11,579 58 0.54% 64,860 429 0.82% 42,920 552 1.27% 41,115 273 0.56% 17,769 191 1.00% 12,586 379 2.92% 201,420 1,976 0.89% Authors’ own calculations on EU-SILC Longitudinal data 2005-2012.

36 Gökşen, Filiztekin, Öker, Kuz, Mazotta & Parisi

Figure 3.3: Gender differences in leaving parental home 4.00

2.00

0.00 2005 2006 2007 2008 2009 2010 2011 2012

-2.00

-4.00

-6.00 Nordic Anglo-Saxon Countries Continental European Countries Mediterranean Countries -8.00 Baltic States Eastern European Countries Turkey

Source: Authors’ own calculations on EU-SILC Longitudinal data 2005-2012.

Another factor shaping the decision to leave or return is age (Billari, Philipov and Baizán, 2001). Based on the results given in Figure 3.4, the decision to return is more common among young individuals aged between 25 and 34, when it is compared to age brackets of 18-24. A quick look at the results indicates that the exit rate among the young (25-34) is the highest in Northern European countries. Turkey is ranked second in terms of the exit rate in both age brackets. Furthermore, other than Nordic countries and Turkey, there is almost no difference between the stated age brackets when the exit decisions of young individuals are considered.

There are several reasons why young people may leave\return home in the period under consideration. We focus the attention on employment conditions, marriage (partnership) and the household income prior the transition. In addition to the individual demographic characteristics, employment conditions, partnership, and household income prior the transition might have a significant impact on the transitions of young adults. Figures 3.5a, 3.5b, and 3.5c present the percentage of married, employed people and the equivalent income of the family of origin distinguishing between individuals who have left home at t+1 and those who have stayed at home.

D 8.3 - Leaving and returning to the parental home during the economic crisis 37

Figure 3.4: Parental home living rates by age groups and by country groups (%) 20.00

15.00

10.00

5.00

0.00 18-2425-3418-2425-3418-2425-3418-2425-3418-2425-3418-2425-3418-2425-3418-2425-34 2005 2006 2007 2008 2009 2010 2011 2012

Nordic Anglo-Saxon Countries Continental European Countries Mediterranean Countries Baltic States Eastern European Countries Turkey

Source: Authors’ own calculations on EU-SILC Longitudinal data 2005-2012.

Young people leaving home are more likely to be employed18 and this indicates that individuals may leave the parental home after they have found a job (Figure 3.5a). The same pattern is clear and even strongest for marital status19: 50% of those leaving home are married at t +1 (for Eastern countries the percentage is even higher, around 70%), the corresponding figure for those who stayed at home is around 3% (12 and 16% for Eastern and Baltic countries respectively).

Not surprisingly, during the economic crisis, overall young people were less likely to be employed in Anglo-Saxon (UK only) and Continental countries (Figure 3.5b). Southern countries registered a decrease of employment during all the periods, differences are statistical significant for those who remain at parental home, while there are no statistically differences for those who leave parental home. For Eastern countries, differences are not statistically significant. For Continental countries, the employment decreases among leavers while for Southern countries it decrease for stayers and finally for Baltic employment decreases for both leavers and stayers.

Looking at the household income20, we can see that in the Nordic and Anglo-Saxon countries home leavers have worse economic condition at time t, so they may exit in order to be better off (Figure

18 The mean differences are statistically significant for almost the periods for Continental, Southern and Baltic Countries. Not significant different from zero in the Eastern countries. 19 The differences are always statistically significant at 1% level. 20 The household income is equivalized with OECD equivalence scale and corrected for Purchasing Power Parity. 38 Gökşen, Filiztekin, Öker Kuz,, Mazzotta & Parisi

3.5c). On the contrary in Southern, Continental and also Eastern countries, richer families foster the exit of their children and this pattern increases with the crisis.21

Figure 3.5a: Percentage of children employed at time t+1 distinguishing between those who stayed at home (0) and those who have left home (1) in 2005-2006, 2009-2010 and 2011-2012

Employed

Nordic Anglo-Saxon Continental

2005 2005 2005 0 2009 0 2009 0 2009 2011 2011 2011

2005 2005 2005 1 2009 1 2009 1 2009 2011 2011 2011

Southern Eastern Baltic

2005 2005 2005 0 2009 0 2009 0 2009 2011 2011 2011

2005 2005 2005 1 2009 1 2009 1 2009 2011 2011 2011

0 .2 .4 .6 .8 1 0 .2 .4 .6 .8 1 0 .2 .4 .6 .8 1 Graphs by welfare

Source: Authors’ own calculations on EU-SILC Longitudinal data 2005-2012.

21 All these differences are statistically significant at 5% level. D 8.3 - Leaving and returning to the parental home during the economic crisis 39

Figure 3.5b: Percentage of children married at time t+1 distinguishing between those who stayed at home (0) and those who have left home (1) in 2005-2006, 2009-2010 and 2011-2012.

Married

Nordic Anglo-Saxon Continental

2005 2005 2005 0 2009 0 2009 0 2009 2011 2011 2011

2005 2005 2005 1 2009 1 2009 1 2009 2011 2011 2011

Southern Eastern Baltic

2005 2005 2005 0 2009 0 2009 0 2009 2011 2011 2011

2005 2005 2005 1 2009 1 2009 1 2009 2011 2011 2011

0 .2 .4 .6 .8 0 .2 .4 .6 .8 0 .2 .4 .6 .8

Figure 3.5c: Average Income at time t distinguishing between those who stayed at home (0) and those who have left home (1) in 2005-2006, 2009-2010 and 2011-2012.

Income

Nordic Anglo-Saxon Continental

2005 2005 2005 0 2009 0 2009 0 2009 2011 2011 2011

2005 2005 2005 1 2009 1 2009 1 2009 2011 2011 2011

Southern Eastern Baltic

2005 2005 2005 0 2009 0 2009 0 2009 2011 2011 2011

2005 2005 2005 1 2009 1 2009 1 2009 2011 2011 2011

0 0 0 5,000 5,000 5,000 10,00015,00020,00025,000 10,00015,00020,00025,000 10,00015,00020,00025,000 Sour ce: Authors’ own calculations on EU-SILC Longitudinal data 2005-2012

40 Gökşen, Filiztekin, Öker Kuz,, Mazzotta & Parisi

Above stated factors influencing the leaving home decisions of the young adults are likely to have significant effect on the returning decisions of the individuals as well. Regarding gender, while there is considerable variance between the leaving parental home patterns of the genders, this difference vanishes when the return patterns are considered. As given in Figure 3.6, except the Eastern European countries, there is almost no difference in the return rates by gender even in the time of economic crisis. In the Eastern European countries, on the other hand, the difference by gender increases in 2009: the return rate among males is lower than that of females.

Figure 3.6: Gender differences in returning parental home 6.00

5.00

4.00

3.00

2.00

1.00

0.00 2005 2006 2007 2008 2009 2010 2011 2012 -1.00

-2.00

-3.00 Nordic Anglo-Saxon Countries Continental European Countries Mediterranean Countries -4.00 Baltic States Eastern European Countries Turkey

Source: Authors’ own calculations on EU-SILC Longitudinal data 2005-2012.

When it comes to the relationship between age and returning to the parental home the difference between age brackets flourishes in all over the welfare regimes (Figure 3.7). For all countries, lower ages indicate more likelihood to come back to the parental home. The rate of return is the highest in Turkey and it is followed by the Anglo-Saxon countries in almost each of the considered years. For all the country groupings, it should be noted that the return rates have increased after the crisis, especially for those aged between 18 and 24.

D 8.3 - Leaving and returning to the parental home during the economic crisis 41

Figure 3.7: Returning to parental home rates by age groups and by country clusters (%) 12.00

10.00

8.00

6.00

4.00

2.00

0.00 18-24 25-34 18-24 25-34 18-24 25-34 18-24 25-34 18-24 25-34 18-24 25-34 18-24 25-34 18-24 25-34 2005 2006 2007 2008 2009 2010 2011 2012

Scandinavian Anglo-Saxon Countries Continental European Countries Mediterranean Countries Baltic States Eastern European Countries Turkey

Source: Authors’ own calculations on EU-SILC Longitudinal data 2005-2012.

Figure 3.8a, 3.8b, and 3.8c reveal the patterns of employment, marital status and (own) income distinguished between those who did not return (that we labelled alone or live independently) and those who have returned home. Returning home is associated to unemployment; in fact, the percentage of young people employed is higher for the sample living on their own than for those returning home for Southern and Nordic countries. 22 For Continental countries there is no such evidence, however, if we look at the equivalent income at time t of households of young people living without parents, those who come back home, in particular in the Continental countries are in a worse initial condition. Particularly, statistical significant is the effect of marital or partnership status. Young people without a partner return home more often in all the countries apart from the Eastern bloc countries, where they often return also with a partner.

22 Differences statistically significant at 1% level. 42 Gökşen, Filiztekin, Öker Kuz,, Mazzotta & Parisi

Figure 3.8a: Percentage of young people employed at time t+1 distinguishing between those who lived independently (0) and those who have returned home (1) in 2005-2006, 2009-2010 and 2011-2012.

Employed

Nordic Anglo-Saxon Continental

2005 2005 2005 0 2009 0 2009 0 2009 2011 2011 2011

2005 2005 2005 1 2009 1 2009 1 2009 2011 2011 2011

Southern Eastern Baltic

2005 2005 2005 0 2009 0 2009 0 2009 2011 2011 2011

2005 2005 2005 1 2009 1 2009 1 2009 2011 2011 2011

0 .2 .4 .6 .8 1 0 .2 .4 .6 .8 1 0 .2 .4 .6 .8 1

Figure 3.8b: Percentage of young people married at time t+1 distinguishing between those who lived independently (0) and those who have returned home (1) in 2005-2006, 2009-2010 and 2011-2012.

Married

Nordic Anglo-Saxon Continental

2005 2005 2005 0 2009 0 2009 0 2009 2011 2011 2011

2005 2005 2005 1 2009 1 2009 1 2009 2011 2011 2011

Southern Eastern Baltic

2005 2005 2005 0 2009 0 2009 0 2009 2011 2011 2011

2005 2005 2005 1 2009 1 2009 1 2009 2011 2011 2011

0 .2 .4 .6 .8 1 0 .2 .4 .6 .8 1 0 .2 .4 .6 .8 1

D 8.3 - Leaving and returning to the parental home during the economic crisis 43

Figure 3.8c: Average Income at time t distinguishing between those who lived independently (0) and those who have returned home (1) in 2005-2006, 2009-2010 and 2011-2012.

Income

Nordic Anglo-Saxon Continental

2005 2005 2005 0 2009 0 2009 0 2009 2011 2011 2011

2005 2005 2005 1 2009 1 2009 1 2009 2011 2011 2011

Southern Eastern Baltic

2005 2005 2005 0 2009 0 2009 0 2009 2011 2011 2011

2005 2005 2005 1 2009 1 2009 1 2009 2011 2011 2011

0 0 0

10,00020,00030,00040,00050,000 10,00020,00030,00040,00050,000 10,00020,00030,00040,00050,000

Source: Authors’ own calculations on EU-SILC Longitudinal data 2005-2012.

3.2 Econometric analysis: Method and results To estimate both the probability of leaving home and the probability of returning home, we use a trivariate probit model.23 In the first model the dependent variables are the probability of Leaving Home (Lt+1), the probability of being Employed (Et+1) and the probability of being Married (Mt+1). In the second the dependent variables are the probability of Returning Home (Rt+1), the probability of being Unmarried (UMt+1), and the probability of being Employed (Et+1).

The explanatory variables of main interest are the economic status at time t (that is, the income in the family of origin) employment and marital status. To disentangle the effect of marital status and employment, we distinguish between what happened in the last year before the transition and at time

23 This is a simulation method for maximum likelihood estimation of the multivariate probit regression model. 44 Gökşen, Filiztekin, Öker Kuz,, Mazzotta & Parisi

t+1. We then include two dummies: whether the person get married/employed in the last year or is married/employed at time t+1.24

One of the main aims of our work is to disentangle the effect of the economic crisis. We include two dummies to capture this effect and we calculate predicted probabilities separate for the three periods. Other control variables for both models are chosen according to the literature; these are gender, age, education, general health, area of residence, share of youth labour income in the total household labour income. The model controls for unobservable factors that influence the three dependent variables. Correlations relate unobservables such as ability, intelligence, personality traits, ambition, and relationship with parents, family background and so on. Table 3.2 presents the coefficient of estimates for the probability of leaving home25.

With regard to the main variable of interest (i.e. parental income) the theoretical model (see for instance Angelini-Laferrere (2012) allows for both a positive and a negative effect of parental income on nest leaving depending on the means by which the parents express their altruism when their child co-resides and when he or she lives independently. They define a standard altruism case where a positive parental income effect on leaving is found, on the contrary the proximity altruists allow for a negative parental income effect.

Results on income variables have to be interpreted looking simultaneously at the household income variable26 as well as the fraction of youth income on household income. Total household income includes not-working income, while the fraction of youth income is the ratio between youth labour income and household labour income. This variable takes into account the fact that the youth can contribute to household income at time t if he\she is working.

Our results report a negative relation between household income and leaving home in Nordic and Anglo-Saxon countries. For those countries we do not include a fraction of youth income because we do not have personal income, so household income includes youth income. Moreover, excluding students from our sample could have the effect of excluding better off families (the ones that are able

24 Both models are estimated separately for six different welfare regimes and Turkey. Country dummies in each estimation should capture cross-country cultural differences (i.e., differences in preferences about co-residence, family ties, attitudes regarding partnership formation, costs of moving out, etc.) to the extent that these aspects have remained constant over time. 25 Unobservable factors that influence the probability of leaving, being employed and married are statistically different from zero, which indicates that a trivariate probit technique is appropriate in this context. 26 Prevalently parental income. D 8.3 - Leaving and returning to the parental home during the economic crisis 45

to finance higher education) above all in Nordic countries where students live in the parental home.27 Thus, the remaining sample could consist of medium-income families where the proximity altruism holds: the higher the income the higher would be the cohabitation to foster transfers inside the parental home, hence the lower is the probability of leaving home. Moreover, it can also be a matter of preference: young people compare the utility of living apart relative to the utility of living with their parents (Ermisch, 1999) and they are happy to stay at home in countries where the average household income is higher compared to the rest of Europe.

However, in other countries (such as Southern, Continental, Eastern countries and Turkey) higher total household income is associated with higher probability of leaving (Mazzotta & Parisi, 2015; in line with Parisi, 2008). In those countries, we include the fraction of youth income (expressed as the ratio between the personal income from labour and pension and the total household income from labour and pension) and we find a strong positive effect of personal income on leaving home: the higher (the lower) the youth (parents) income compared to family (youth) income, the more likely is the youth to leave. This result could be counterintuitive given that leaving home is positively correlated with the total equivalized income (which include not working income: capital assets and real estate), while is negative correlated with the labour and pension family income. We could explain these puzzling result as follows: the effect of total equivalized household income can be interpreted as a wealth effect due to not working income, thus wealthier families (with more capital assets and property income) can support young people also outside the parental home, while poorer parents have no way of controlling the household living arrangement decisions of their children. Moreover, in the richest countries (Nordic and Anglo-Saxon28) children of a poorer family could expect to improve their personal condition leaving the parental home. On the contrary, in poorer and less intergenerationally mobile societies (as in Southern countries), children of a poorer family have less chance of improving their condition by leaving the parental home.

Marital status has a strong effect on leaving home: the more likely young people are to be married, the more likely they are to leave home. The effect is stronger if the marriage has occurred in the very last year. Employment is a good predictor of leaving home only in Continental countries, it seems that

27 The percentage of student is quite big in Nordic and Continental countries where more than 50% of young people living with their parent are students (see Mazzotta, F. Parisi, L (2016). The role of economic factors in determining leaving and returning to the parental home in Europe during the crisis. http://www.style-research.eu/publications/working-papers/).

28 Note that Nordic (Denmark and Iceland) and Anglo-Saxon (United Kingdom) countries do not record in the survey personal income as well as individual health, as a consequence we cannot include those variable (namely Health and Fraction of youth personal income on household income) in the estimates. Of course we have consider the negative results of total household income with caution, in fact, this negative effect of the total equivalized family income can include the negative effect of the labour family income. 46 Gökşen, Filiztekin, Öker Kuz,, Mazzotta & Parisi

being employed in almost all the countries does not affect the probability of leaving directly. However, employment has an indirect effect through marriage.

As expected, young people from better off families may have a higher probability of being employed, also controlling for the unobservables that link leaving home, marriage and employment. Children from wealthier families have an increased probability of being employed maybe because they are able to afford a high-quality school and university and also may have better information and search strategies (Farace, Mazzotta, & Parisi, 2014). There is a strong state dependence regarding the probability of employment and previous employment conditions; the lagged employment variables are positive and significant. Increases in education unambiguously decrease the probability that young people live at home (increase leaving home) and do not work (increase the probability to be employed) for all countries except for the Eastern bloc. On the contrary, having a health limitation increases the probability that a son lives at home and does not work. Women have a lower income threshold for independence and they leave the parental home more than men in Continental, Southern, Eastern and Baltic countries. In Turkey, on the other hand, men are more likely to leave home.

As expected, after 2008 young people were less likely to leave home, to get married and above all to be employed. The effect of the crisis is strongest regarding the probability of employment so we can argue that the effect of the crisis works through employment. Looking at the figures of the marginal predicted probabilities (Figure 3.9a), results confirm descriptive statistics showing that in Southern and Eastern Europeans countries and in Turkey the probability of leaving home is lower compared to Northern Europe. There are no striking differences across the analysis period apart from the Anglo- Saxon and Turkish case where we observe a decrease in the probability of leaving after 2008. When we consider the joint predicted probability to leave home, to be employed and to get married (Figure 3.9b) we can see that the percentage of people that have left home, are employed and married decreases during the period under consideration for all the welfare regimes and Turkey except for Eastern countries and the sharpest decrease is in Northern European countries.

D 8.3 - Leaving and returning to the parental home during the economic crisis 47

Table 3.2: Trivariate probit model for probability of leaving home, being employed and being married, with country dummies and distinguishing before married/employed last year or before

Nordic Anglo_saxon Continental Southern Eastern Baltic Turkey 1)Probability of Leaving Home Log of eq.income at t -0.31*** -0.12*** 0.21*** 0.15*** 0.19*** -0.03 -0.14* 2009-2010 -0.06 -0.24** 0.05 0.06* -0.11** -0.03 0.23 2011 0.32** -0.14* -0.03 -0.02 -0.04 -0.04 0.25 Male -0.19 -0.12 -0.08* -0.08*** -0.18*** -0.18*** -0.14 Age 0.49** 0.03 0.12* 0.10** -0.02 0.16** 0.14 Age squared -0.01** 0.00 -0.00** -0.00** 0.00 -0.00** 0 Tertiary education 0.66** 0.21 0.68*** 0.07** -0.15* -0.06 -0.65*** Secondary education 0.02 -0.03 0.34*** 0.04 -0.14** 0.03 -0.14 House crowded at t 0.41** 0.07 0.05 0.06* -0.22*** -0.11* 0.04 Employed last year 0.29 0.29 0.29*** 0.08 0.02 0.13 0.63*** Employed before 0.03 0.12 0.13* 0.04 -0.01 0.04 0.00* Married last year 1.89*** 2.61*** 2.86*** 2.76*** 1.93*** 2.01*** -0.13 Married before 1.98*** 0.95*** 1.48*** 1.04*** 0.92*** 0.55*** -0.09 Good health at t -0.20* 0.15** 0.05 0.01 -0.19*** Fraction of youth Income 0.56*** 0.58*** 0.29*** 0.49*** 1.08*** Constant -4.83* -1.02 -5.79*** -5.00*** -3.09*** -3.47*** -7.34** 2)Probability of forming a couple Log of eq.income at t -0.13* -0.10*** -0.06 -0.12*** -0.11*** 0.00 -0.44*** 2009-2010 -0.11 0.01 -0.05 -0.06** 0.05 0.00 -0.59*** 2011 -0.40** -0.12 -0.07 -0.08*** -0.06** 0.04 -0.16*** Male -0.27 -0.42*** -0.32*** -0.36*** -0.47*** -0.35*** -0.18*** Age 0.48** 0.35*** 0.05 0.35*** 0.31*** 0.31*** -0.18* Age squared -0.01* -0.01*** 0.00 -0.01*** -0.00*** -0.00*** 0.00* Tertiary education 0.06 0.13 0.30*** -0.27*** 0.06 -0.13* -0.04 Secondary education 0.24 0.32** 0.28*** -0.14*** 0.16*** 0.04 -0.15 Living with both parents -0.22 -0.08 -0.05 -0.25*** -0.13*** -0.16*** -0.27*** Good health at t 0.07 -0.01 0.19*** 0.25*** 0.16*** Employed -0.09 0.35*** 0.26*** 0.07** 0.13*** 0.14*** -0.20** Fraction of youth Income 0.25** -0.06 -0.21** -0.49*** 3.36*** Constant -6.42** -5.52*** -1.49* -5.25*** -5.63*** -6.07*** 7.75*** 3)Probability of being employed Log of eq.income at t 0.14** 0.15*** 0.48*** 0.52*** 0.29*** 0.48*** 0.15*** 2009-2010 -0.52*** -0.20** -0.21*** -0.38*** -0.21*** -0.26*** -0.59*** 2011 -0.46*** -0.33*** -0.17*** -0.26*** -0.19*** -0.45*** -0.16*** Male 0.05 -0.04 -0.07* 0.02 0.26*** 0.01 0.22** Age -0.30* 0.09 0.08 0.08*** -0.01 -0.06 0.40*** Age squared 0.01* 0.00 -0.00* -0.00*** 0.00 0.00 -0.01*** Tertiary education 1.07*** 1.02*** 0.46*** 0.23*** 0.53*** 0.48*** 1.40*** Secondary education 0.38*** 0.74*** 0.30*** 0.20*** 0.33*** 0.24*** 0.51*** Good health at t 0.46*** 0.28*** 0.27*** 0.52*** 0.23*** Fraction of youth Income 1.46*** 1.59*** 1.69*** 1.58*** 0.24*** Employed 1.16*** 1.57*** 1.27*** 1.23*** 1.42*** 0.93*** 1.01*** Constant 2.64 -3.73*** -6.27*** -5.77*** -3.23*** -4.12*** -6.29***

48 Gökşen, Filiztekin, Öker Kuz,, Mazzotta & Parisi

Figure 3.9a: Marginal predicted probabilities of leaving home, being employed and being married by time periods

Leaving .14 .12 .1 .08 .06 .04

2005-2008 2008-2010 2010-2012 period

UB/LB Nordic UB/LB Anglo-Saxon UB/LB Continental UB/LB

Southern UB/LB Eastern UB/LB Baltic UB/LB Turkey

with 95% confidence interval

Married .2 .15 .1 .05

2005-2008 2008-2010 2010-2012 period

UB/LB Nordic UB/LB Anglo-Saxon UB/LB Continental UB/LB

Southern UB/LB Eastern UB/LB Baltic UB/LB Turkey

with 95% confidence interval

Source: Authors’ own calculations on EU-SILC Longitudinal data 2005-2012.

D 8.3 - Leaving and returning to the parental home during the economic crisis 49

Employment 1 .9 .8 .7 .6

2005-2008 2008-2010 2010-2012 period

UB/LB Nordic UB/LB Anglo-Saxon UB/LB Continental UB/LB

Southern UB/LB Eastern UB/LB Baltic UB/LB Turkey

with 95% confidence interval

Figure 3.9b: Joint predicted probabilities of leaving home, being employed and being married by time periods .02 .015 .01 .005 0

2005-2008 2008-2010 2010-2012 period

UB/LB Nordic UB/LB Anglo-Saxon UB/LB Continental UB/LB

Southern UB/LB Eastern UB/LB Baltic UB/LB Turkey

with 95% confidence interval

Source: Authors’ own calculations on EU-SILC Longitudinal data 2005-2012.

50 Gökşen, Filiztekin, Öker Kuz,, Mazzotta & Parisi

Table 3.3 presents estimates for the trivariate probit model for the probability of returning home and Figure 3.10a shows the marginal predicted probabilities. Income at time t positively affects the decision to return to the parental home in Nordic countries, while it effects negatively the decision to return in Baltic and Continental countries. The first result (i.e. young people with high income at t are more likely to return to the parental home) seems counterintuitive, however for Nordic countries we cannot control for personal income so we are not able to disentangle the effect of youth income relative to their parents’ income. On the contrary, for Baltic and Continental countries and for Turkey young people returned home if their income before the transition was lower and also their income relative to family income was lower (both income at t and fraction of youth income at time t+1 are negative).

Looking at the dummies that explain the difference among time periods, we find that there is a time effect: the probability of returning home is higher in the periods after 2008 (during the economic crisis). Differently from Stone et al. (2012) the period is still statistically significant when we include what they call the turning points i.e. an event, experience or change in circumstances that significantly alters the individual’s subsequent life-course trajectory (such as divorce or unemployment). For Continental countries being unemployed the last year increase the probability to return, the same is true for Southern but considering unemployment since the beginning of the spell.

With regard to the marginal predicted probabilities, we observe that returning home is higher for Baltic and Southern countries, while the lowest for the UK, which registered an increase only during 2008- 2009. In the same period, also Baltic and Continental countries registered an increase in the probability of returning home. For Southern countries, the probability of returning home increased for all the periods. The likelihood of returning declines with age and men are significantly more likely to return than women.

D 8.3 - Leaving and returning to the parental home during the economic crisis 51

Table 3.3: Trivariate probit model for probability of returning home, being employed and being unmarried, with country dummies and distinguishing before married/employed last year or before (surprising insignificant direct effects of employment on propbability of return) Nordic Anglo_saxon Continental Southern Eastern Baltic Turkey

1)Probability of Returning Home Log of eq.income at t 0.70** 0.06 -0.11** 0.01 0 -0.10** -0.14* 2009-2010 0.33 0.33** 0.17* 0.07 0.09 -0.07 0.23 2011 -0.35** 0.43*** 0.27*** 0.03 -0.08 0.28*** 0.25 Male -0.21 0.09 0.21*** 0.13** 0.15** 0.47*** -0.14 Age 0.17 -0.31* -0.40*** -0.13 -0.22** -0.23* 0.14 Age squared 0 0 0.01*** 0 0.00* 0.00* 0 Fraction of youth Income at t+1 -0.32** -0.49*** -0.52*** -0.88*** -0.65*** Tertiary education -1.35*** 0.64** -0.31*** -0.09 -0.46*** -0.21 -0.14 Secondary education -0.76*** 0.61** -0.04 0.03 -0.09 0.01 0.04 Good health at t -0.15 -0.11 -0.11 -0.11 0.12 House crowded at t -0.14 0.07 0.05 -0.15*** -0.08 -0.02 0.00* Unemployed last year 0.48 -0.09 0.46*** 0.11 -0.02 -0.07 -0.13 Unemployed before 0 -5.48*** 0.06 0.28** -0.45** -0.12 -0.09 Divorced last year 0.91** 1.48*** 1.59*** 1.45*** 1.14*** 1.38*** 1.63*** Divorced\not married before 0.34 0.99*** 0.94*** 1.30*** 0.75*** 1.16*** 1.08*** Constant -9.75* 0.34 4.69*** 0.16 1.27 1.39 -7.34** 2)Probability of not being

married Log of eq.income at t -0.60*** -0.11*** 0.26*** 0.11*** 0.13*** -0.01 -0.44*** 2009-2010 0.07 -0.05 -0.01 0.15*** -0.04 0.12** -0.59*** 2011 0.22*** 0.01 0.04 0.07*** -0.06** 0.02 -0.16*** Male 0.24*** 0.10** -0.46*** -0.06** -0.48*** -0.60*** -0.18*** Age -0.50*** -0.14** -0.23*** -0.46*** -0.52*** -0.61*** -0.18* Age squared 0.01*** 0 0.00*** 0.01*** 0.01*** 0.01*** 0.00* Fraction of youth Income at t+1 3.58*** 2.05*** 2.55*** 2.81*** 3.36*** Tertiary education 0.04 -0.09 -0.13** 0.21*** 0.05 -0.22*** -0.04 Secondary education -0.13 -0.20*** -0.06 0.20*** -0.05 -0.1 -0.15 Good health at t -0.37*** -0.12*** -0.11*** -0.19*** 0.03 Employed -0.09 -0.18*** -0.53*** -0.27*** -0.58*** -0.36*** -0.20** Constant 12.82*** 3.39*** -0.91 5.49*** 5.93*** 7.55*** 7.75*** 3)Probability of being employed Log of eq.income at t 0.05 0.14*** 0.44*** 0.35*** 0.27*** 0.36*** 0.15*** 2009-2010 -0.41*** -0.12** -0.02 -0.30*** -0.18*** -0.18*** -0.59*** 2011 -0.04 -0.10** -0.15*** -0.26*** -0.08*** -0.34*** -0.16*** Male 0.46*** 0.55*** 0.25*** 0.29*** 0.48*** 0.07* 0.22** Age 0.1 0.05 -0.04 0.04 0.06 0.07 0.40*** Age squared 0 0 0 0 0 0 -0.01*** Fraction of youth Income at t+1 0.74*** 1.08*** 1.26*** 1.01*** 1.40*** Tertiary education 0.52*** 0.47*** 0.31*** 0.32*** 0.39*** 0.24*** 0.51*** Secondary education 0.37*** 0.23*** 0.20*** 0.18*** 0.27*** 0.14*** 0.24*** Good health at t 0.42*** 0.25*** 0.15*** 0.25*** 0.21*** Employed 1.40*** 1.89*** 1.61*** 1.45*** 1.47*** 1.11*** 1.01*** Constant -2.76 -3.27*** -5.06*** -4.45*** -4.39*** -5.22*** -6.29***

52 Gökşen, Filiztekin, Öker Kuz,, Mazzotta & Parisi

Figure 3.10a: Predicted probabilities of returning home, being employed and not being married by time periods

Returning

.03 .02 .01 0

2005-2008 2008-2010 2010-2012 period

UB/LB Nordic UB/LB Anglo-Saxon UB/LB Continental UB/LB

Southern UB/LB Eastern UB/LB Baltic UB/LB Turkey

with 95% confidence interval

Not married .35 .3 .25 .2 .15 .1

2005-2008 2008-2010 2010-2012 period

UB/LB Nordic UB/LB Anglo-Saxon UB/LB Continental UB/LB

Southern UB/LB Eastern UB/LB Baltic UB/LB Turkey

with 95% confidence interval

D 8.3 - Leaving and returning to the parental home during the economic crisis 53

Employed .9 .85 .8 .75 .7

2005-2008 2008-2010 2010-2012 period

UB/LB Nordic UB/LB Anglo-Saxon UB/LB Continental UB/LB

Southern UB/LB Eastern UB/LB Baltic UB/LB Turkey

with 95% confidence interval

Figure 3.10b: Joint predicted probabilities of returning home, not being employed and not being married by time periods .008 .006 .004 .002 0

2005-2008 2008-2010 2010-2012 period

UB/LB Nordic UB/LB Anglo-Saxon UB/LB Continental UB/LB

Southern UB/LB Eastern UB/LB Baltic UB/LB Turkey

with 95% confidence interval

Source: Authors’ own calculations on EU-SILC Longitudinal data 2005-2012.

54 Gökşen, Filiztekin, Öker Kuz,, Mazzotta & Parisi

It would be interesting to draw conclusions on the trends on leaving and returning altogether, however, it is difficult to connect them. There are two main reasons for that: first the two samples are different, the first one (leaving) consists of young people living with their parents the first year observed in the panel that are likely to leave home or staying; the second sample (returning) consists of young people that are not living with their parents the first time they are observed and they are likely to return home or to stay independently. The second reasons rely on the fact that the panel is too short to observe the two transitions for the same person. However, we can find some trend: men in almost all welfare regimes are less likely to leave home but more likely to return. This result could be driven by the fact that usually men are the principal earner in the family, so they leave home only if they have an economic status that allows them to be economically independent. Secondly, young people with higher education in almost all welfare regimes are more likely to leave as well as less likely to return home. On the contrary, in the Eastern countries higher educated people are less likely to leave and also to return home.

In some countries, young people are less likely to leave as well as to return home: for instance Denmark with respect to Island, Italy with respect to Cyprus and Spain, Czech Rep. and Poland with respect to Slovenia. On the other hand, some countries are characterized by a higher probability to leave parental home as well as to return: for instance France.

To conclude this section, the Southern, the Eastern European and the Baltic countries as well as Turkey show lower leaving rates compared to the other countries, and the crisis did not exacerbate this difference. During the financial crisis (2008-2009), the sharpest decrease of leaving home is observed in Northern countries. All countries experienced an increase of the percentage of people returning home, except the Eastern European countries. Southern European countries registered an increase of returning home throughout the period. With regard to income we have seen that for the Southern, Eastern and Continental European countries, relative higher family labour and pension income increases the chances of co-residence, i.e. decreases leaving parental home (as in Angelini & Laferrère, 2012; Iacovou, 2010; Manacorda & Moretti, 2006). Instead, wealthy families (considering all the household income including the not working income) can support young people also outside the parental home and so they can foster the exit (in line with Mazzotta & Parisi, 2015; Parisi, 2008). On the contrary, poorer parents have no way of controlling the household living arrangement decisions of their child. Income does not have such a big effect on the probability of returning home. However, marital status has a strong effect on both the probability of leaving and returning home. Finally, employment is a good predictor of leaving home but only by an indirect effect that works through marital status. With regards to returning home, losing a job increases the probability of returning home only for Continental and Southern Countries, but the positive effect of the divorce on the provability of returning home is stronger (the results hold also if we exclude inactive). D 8.3 - Leaving and returning to the parental home during the economic crisis 55

4. Housing policies and leaving and returning to the parental home

Availability of housing and housing market circumstances are widely recognised as influencing the opportunities for young adults to leave their parents’ homes (Aassve et al., 2002; Feijten & Mulder, 2002; Iacovou, 2002; Mulder et al., 2002; Roberts, 2003). Particularly young adults are the most vulnerable to the pricing of rented housing, since rented accommodation is the most typical first step in the autonomous housing career (Kendig, 1990). Scarcity of rented housing or housing suitable for single people are often given as reasons why young people in Southern Europe delay leaving home (Aassve et al., 2002; Iacovou, 2002). As found by Mulder (2006) for Italy, Spain and Greece, “a combination of high-level of home-ownership, difficult access to mortgages, and high house prices seems to make it particularly difficult for young people to form their own households” (p. 4).

Owner occupied dwellings today still represent by far the most widespread form of occupation in the EU (Housing Europe, 2015). Nevertheless, in many countries recent policies have started to favour an increase in rental housing compared to the past. However, data form EU-SILC show that the distribution of population across tenures saw an increase in tenants and decrease in ownership since 2007 (Housing Europe, 2015). Combination of different elements such as little availability of rental housing, decreased social housing production and increasing youth unemployment cause many young people to rely more heavily on the family to meet their housing needs. This trend is more visible in Southern Europe and CEE countries, but recently in UK as well (Housing Europe, 2015).

Household formation depends heavily on the ownership of a house. The state of both mortgage and rental market plays an important role for the youth to leave their parents’ home. In regions where there is a developed mortgage market, young households can have easier access to home ownership. On the other hand, for those who are at the beginning of their adult life and unable to come up with a down payment, a rental market plays an important interim role (Le Blanc and Wolff, 2006). A small rental market reduces their chance to leave their home to form an independent life until an age they could afford. However, it is difficult to provide entirely consistent comparative figures for the stock of housing policies, both because different countries define the tenure in different ways and because of data availability. However, it is probably true to say that there has been an upward pressure in most countries as governments look to the sector to become more self-sufficient and 56 Gökşen, Filiztekin, Öker Kuz,, Mazzotta & Parisi

income related subsidies to support poorer households have become more generally available (Scanlon, Arrigoitta, and Whitehead, 2015).

In the following section we provide an overview of the EU housing policies. In Section 4.2 we go on to incorporate variables related to housing policies into the regression analysis of Section 3 that studied the determinants of leave/return to parental home decisions of young adults.

4.1 Overview of the EU housing policies Housing policies are related to how housing finance markets operate, whether and to what extent the state finances, builds or regulates social housing, policies on rental housing, and the supply of housing units. Defined as such, EU members do not have a single set of policies on housing (Boccadoro 2008).

Housing Finance before and after the Global Financial Crisis

Housing policies in various countries as well as within the EU have been impacted by processes of globalization in recent decades and the global financial crisis in 2007-2008 (Guerra 2008). Borrowing opportunities and borrowing costs (e.g. down payment requirements) for buying homes were reduced as a result of the abundant availability of mortgage loans. Taxation policies also made it more financially attractive to buy than rent. Concomitantly homeownership and owner-occupancy increased among indebted households (OECD 2011).

A consequence of the easy availability of credit has been a rise in the demand for home ownership, and hence an increase in real house prices (OECD 2011). This trend can be observed for various EU countries: among the countries analysed in this report, between 1980 and 2008 real house prices rose by more than 90 percent in Belgium, Spain and the UK, and between 20% and 90% in Austria, Denmark, France, Italy and Slovenia, whereas in Portugal real house prices remained stable (OECD 2011).

Across the EU, owner occupied homes represent the most widespread form of occupation (the average is about 60%). During the 1990s and most of the 2000s, home ownership increased steadily, but since 2007 there is a decrease in owner occupiers and an increase in renters in the EU 15; whereas the share of owner occupiers has continued to increase in new member states (Housing Europe 2015).

D 8.3 - Leaving and returning to the parental home during the economic crisis 57

The global financial crisis exposed some of the weaknesses of a housing market and housing policy based on easy credit (Guerra 2008). Defaulting mortgages and over-indebted households were two problem areas for some EU countries that have triggered policy responses in recent years. For instance, Italy and Spain set up solidarity funds to help vulnerable defaulting households, whereas Hungary and Ireland created mortgage to let programs. Renegotiation of mortgage debt (the Netherlands and Denmark) and moratoria on repossessions (Ireland, Portugal, Greece and Spain) were among other policies. Tax policies favouring indebtedness for home ownership were scaled down in the Baltic countries, the Netherlands and Belgium.

Divergent Rent Policies Rent policies in EU countries exhibit a variety that includes rent controls, laws encouraging or discouraging the for profit rental market, dual rental markets and housing allowances. In the aftermath of the global financial crisis, some countries have undertaken policy changes in the rental sector. Spain and Portugal have changed their tenancy laws in order to foster investment in the rental sector whereas the Netherlands seeks to create a regulated social sector and a non-regulated rental sector by reforming its rent setting system. Germany, on the other hand, is currently bolstering its rent control system (Housing Europe 2015).

Social Housing before and after the Financial Crisis There is no common definition of social housing and no common social housing policy in the EU 27. But in recent years, housing has been recognised as a significant dimension of social exclusion by the EU and is taken into account in policy coordination. And, despite the lack of a common social housing policy, EU competition law has an impact on social housing policies in individual member states (Boccadoro 2008). Regardless of how EU law views it, it has been argued that there are common elements in social housing across the Union: the goal of supplying affordable housing by constructing, managing or purchasing social housing and the identification of target populations in terms of socio-economic status or vulnerabilities (European Parliament 2013). EU 27 countries nevertheless diverge from each other widely in terms of the share of social housing. While the EU average is 8.3%, the Netherlands leads with 32%, followed by Austria with 23%, whereas Mediterranean and Eastern countries have social housing stocks of less than 5%.

Two main social housing models have been identified across the EU 27 along four dimensions; the tenure, the provider of the service, the beneficiaries and the funding arrangements. Tenure is mostly based on social renting and is present in all EU countries except Greece; the sale of low cost housing is available in Cyprus, Greece and Spain, and intermediate tenure is available in several countries, for instance in the UK. Provision of social housing may be through local governments, public companies, non-profit associations, cooperatives and even for-profit developers. In the past decade, private and 58 Gökşen, Filiztekin, Öker Kuz,, Mazzotta & Parisi

for-profit organizations have taken an increasingly larger role. Currently in many EU countries, while local public authorities manage and regulate the sector, development of new housings usually falls on the private sector. However, Central and Eastern European countries display a different pattern due to large-scale privatisations of social housing since the 1990s whereby the public’s role has diminished (European Parliament 2013). In terms of beneficiaries, too, there is large variation among the EU 27. Whereas countries including Germany, Austria and France set income ceilings high in order to ensure that there is an income mix among social housing beneficiaries, other countries determine beneficiaries in terms of low income, vulnerabilities or household needs. Funding of social housing provision may rely on mortgages, public loans and public grants, municipal funds and land grants and tenants’ contributions.

Based on these four dimensions, two main social housing models have been identified: universalistic and targeted, with the latter having two sub-models, the generalist and residual. In the universalistic model, the public sector’s responsibility is viewed as providing decent and affordable housing to the whole population. In this model, through rent control, housing allowances and rent guarantees, the public sector regulates the housing market. In the targeted model, the supply of housing is left to the market, while the public provides social housing for only those who cannot afford decent housing. In the generalist sub-model, the main allocation criterion is income level, whereas in the residual, only the most vulnerable groups are entitled to social housing (Ghekiere 2011, cited in European Parliament 2013).

Accordingly, the Netherlands, Denmark and Sweden, with 20 percent or more of housing in the social sector, are considered to fall into the universalistic model. Whereas Austria, Czech Republic, France, Finland, Poland (between 11% and 19%), Belgium, Germany, Italy (between 5 and 10%), Slovenia, Luxemburg and Greece (0-5%) belong in the generalist model. The UK, with more than 20%, has the largest residual social housing sector (Treanor, 2015). And France (11-19%), Belgium, Estonia, Germany, Ireland, Malta (5-10%), Bulgaria, Cyprus, Hungary, Latvia, Lithuania, Spain and Portugal (0-5%) also belong in the residual model (European Parliament 2013).

The financial crisis has led to increasing demand for social housing in the EU with the result that social housing expenditure as a percentage of the GDP has been on the rise since 2007. Rent benefits as a percentage of GDP has also registered an increase in the same period (European Parliament 2013).

D 8.3 - Leaving and returning to the parental home during the economic crisis 59

Convergence or Divergence of Housing Policies in the EU?

Based on the foregoing discussion, can we talk about a convergence or divergence in housing policies in the EU? One argument is that, despite the diversity in housing markets, there is a convergence along some dimensions, namely decrease in direct housing provision by the public, decentralization of policy implementation, the increasing role played by private partners and increasing importance of and attention paid to the private housing market (Forrest and Lee 2003; Bramley, Munroi and Pawson 2004; both cited in Guerra 2008).

The divergence thesis builds on the notion of a correspondence between welfare regime types (a la Esping-Andersen) and housing policies in the EU. Barlow and Duncan (1994, cited in Guerra 2008) have argued that there is a relation between different levels of social housing construction by the public sector and welfare regime types. Kemeny (2005 and 2006, cited in Malpass 2008) extends the concept of welfare regimes to include housing and posits the main axis of divergence to be between Anglo-Saxon countries (the UK in this case) and continental Europe. The former is recognizable for the preference for owner occupation of dwellings whereas the latter can be identified with very high levels of renting. The key in this typology is dual rental markets (for profit rental tenancy versus rent- control in a small sector of social housing) in the Anglo-Saxon model versus unitary rental markets (where states regulate rents even in the private housing sector) in Continental Europe.

4.2 Housing polices and living with parents: static analysis

In this section we incorporate variables involving housing policies into the econometric models estimated in Section 3 to see how leaving/returning to parental home decisions of young adults are affected by their housing status.

The data set used in this study contains information on the tenancy status of household and whether they have a mortgage plan. Using these variables, we have constructed a modified tenancy status. The share of households who own a house with or without mortgage, and the share of households that rent at market or a reduced rate is provided in Figure 4.1 by country groups.29 These figures are broadly in line with the figures cited in the overview of EU housing policy provided in Section 4.1.

29 A detailed table is provided in the Appendix-Table A.5.

60 Gökşen, Filiztekin, Öker Kuz,, Mazzotta & Parisi

Home ownership ratio is above 60% in most countries and shows an increasing trend. The mortgage market, or the use of mortgages, is very limited in the Baltic States and eastern European countries. On the other hand, ownership in the north, the west and the continental European countries benefits from a significant mortgage market. We do not have information on mortgage usage in Turkish SILC data.

In the continental European countries there is larger rental market than other country groups; however, the size of this market is declining. In fact, rental market is declining everywhere. In the UK more individuals enjoy tenancy at reduced rental rates, with the share of tenants benefitting from controlled or free rent being around 20%. In other country groups, share of tenancy at reduced rental rates is much smaller, and in the east Europe it is declining.

Figure 4.1: Housing tenure across clusters of countries a. Nordic countries b. Anglo-Saxon countries (UK)

100% 100% 90% 90% 80% 80% 70% 70% 60% 60% 50% 50% 40% 40% 30% 30% 20% 20% 10% 10% 0% 0% 2005 2006 2007 2008 2009 2010 2011 2012 2005 2006 2007 2008 2009 2010 2011 2012

Owner w/o Mortgage Owner w/ Mortgage Owner w/o Mortgage Owner w/ Mortgage Tenant at Market Rate Tenant at Controlled Rent or Free Tenant at Market Rate Tenant at Controlled Rent or Free c. Continental European countries d. Mediterranean countries

100% 100% 90% 90% 80% 80% 70% 70% 60% 60% 50% 50% 40% 40% 30% 30% 20% 20% 10% 10% 0% 0% 2005 2006 2007 2008 2009 2010 2011 2012 2005 2006 2007 2008 2009 2010 2011 2012

Owner w/o Mortgage Owner w/ Mortgage Owner w/o Mortgage Owner w/ Mortgage Tenant at Market Rate Tenant at Controlled Rent or Free Tenant at Market Rate Tenant at Controlled Rent or Free

D 8.3 - Leaving and returning to the parental home during the economic crisis 61

Figure 4.1: Housing tenure across clusters of countries (continued) e. Baltic states f. Eastern European countries

100% 100% 90% 90% 80% 80% 70% 70% 60% 60% 50% 50% 40% 40% 30% 30% 20% 20% 10% 10% 0% 0% 2005 2006 2007 2008 2009 2010 2011 2012 2005 2006 2007 2008 2009 2010 2011 2012

Owner w/o Mortgage Owner w/ Mortgage Owner w/o Mortgage Owner w/ Mortgage Tenant at Market Rate Tenant at Controlled Rent or Free Tenant at Market Rate Tenant at Controlled Rent or Free g. Turkey

100% 90% 80% 70% 60% 50% 40% 30% 20% 10% 0% 2006 2007 2008 2009 2010 2011 2012

Owner w/o Mortgage Owner w/ Mortgage Tenant at Market Rate Tenant at Controlled Rent or Free Source: Authors’ own calculations on EU-SILC Longitudinal data 2005-2012.

Another important policy variable is housing allowances by the government either as rent benefits or benefits to owner-occupiers. The share of households that benefit from these allowances in all households is given in Figure 4.2. In Nordic and Continental countries, around 10% of households use these benefits. In the UK, the benefits are more widespread. In other country groups, only five percent enjoy housing benefits. While this share has increased after the crisis in Mediterranean countries and Baltic States, there are fewer households that enjoy household allowances in the eastern European countries in the latter years.

62 Gökşen, Filiztekin, Öker Kuz,, Mazzotta & Parisi

Figure 4.2: Share of households that benefit from housing allowances (%) 0.16

0.14

0.12

0.1

0.08

0.06

0.04

0.02

0 2005 2006 2007 2008 2009 2010 2011 2012

Nordic Anglo Continent Med. Baltic Eastern Turkey

Source: Authors’ own calculations on EU-SILC Longitudinal data 2005-2012.

In Table 4.1, we present the share of young people who live independently and their housing tenure status. As expected very few of these individuals own a house without a mortgage, except in Baltic States and East European countries where relatively higher share of young independent individuals own a house. Also, in countries where a developed mortgage market exist, ownership based on a mortgage is observed at a higher proportion among independent young people compared to all households, with more than half of the independent young people owning a house through the mortgage system. While in the southern and eastern European countries the share of young people owning a house through mortgage is relatively lower, there are significant differences when compared to the share of mortgage in home ownership for all households.

D 8.3 - Leaving and returning to the parental home during the economic crisis 63

Table 4.1: Tenure status and housing allowance of those who do not co-reside with parents Tenant Owner w/o Owner w/ Tenant at reduced rent or Housing mortgage mortgage Market Rate free Allowance Pre- Post- Pre- Post- Pre- Post- Pre- Post- Pre- Post- Crisis Crisis Crisis Crisis Crisis Crisis Crisis Crisis Crisis Crisis Nordic Countries 8.1 5.1 56.5 61.4 25.3 22.7 10.2 10.8 23.7 35.0 DK 7.3 6.1 61.8 59.8 30.9 34.1 0.0 0.0 19.7 26.8 FI 11.9 5.2 36.8 52.7 25.0 20.5 26.3 21.6 26.1 32.9 NO 3.6 7.8 69.5 66.5 19.0 16.8 7.8 8.9 24.1 41.6 SE 13.5 0.7 44.9 61.7 40.3 37.3 1.3 0.3 23.2 25.0 IS 4.4 2.0 74.0 66.4 9.7 16.8 11.9 14.8 24.0 39.3 Anglo-Saxon Countries 3.4 4.0 55.7 50.3 23.7 26.0 17.2 20.2 20.5 38.9 UK 2.5 3.9 55.9 49.9 24.3 26.0 17.3 20.2 20.5 38.9 IE 8.9 54.5 19.8 16.8 Continental European Countries 6.3 4.5 38.8 46.8 39.0 34.9 16.0 13.9 23.4 32.9 AT 5.9 9.4 15.6 24.5 58.8 41.6 19.8 24.5 25.8 42.3 BE 7.0 4.9 47.7 52.5 35.8 32.0 9.4 10.6 26.0 37.8 LU 2.2 2.0 19.7 41.8 66.8 48.8 11.3 7.4 17.7 53.8 FR 8.7 3.4 30.1 38.5 31.8 33.1 29.4 25.0 19.5 28.8 NL 4.2 2.2 70.4 70.7 25.3 26.9 0.1 0.2 25.6 36.8 Mediterranean Countries 22.7 19.3 31.9 42.6 24.6 22.8 20.9 15.3 25.9 43.9 IT 31.1 28.0 23.5 25.4 20.8 23.8 24.6 22.8 22.8 47.2 ES 9.6 9.1 47.5 57.2 26.5 22.3 16.4 11.5 26.2 51.1 PT 21.3 13.2 42.6 46.1 17.7 23.7 18.4 17.0 30.4 31.6 GR 23.4 34.1 8.8 14.3 47.5 36.9 20.3 14.8 26.5 29.0 CY 23.4 32.9 28.5 27.4 26.0 18.1 22.2 21.6 26.3 44.8 MT 34.6 30.8 39.9 52.4 6.0 3.2 19.4 13.5 40.8 48.9 Baltic States 46.7 51.6 17.2 20.7 12.7 9.7 23.4 18.0 30.7 55.1 EE 45.9 39.6 22.9 27.5 10.9 7.9 20.2 25.1 28.3 38.8 LT 52.7 60.6 14.7 18.0 7.5 4.8 25.1 16.6 30.6 43.4 LV 41.8 53.8 8.2 18.1 21.9 13.5 28.1 14.6 33.9 74.3 Eastern European Countries 45.6 49.4 14.8 20.0 9.8 9.1 29.8 21.5 30.6 36.8 CZ 42.5 43.6 20.2 24.5 10.8 13.3 26.5 18.7 22.7 20.9 HU 49.5 38.9 27.2 38.3 8.6 6.8 14.7 16.0 30.7 50.8 PL 42.5 47.4 4.1 16.0 7.9 7.5 45.5 29.1 28.6 32.0 SI 49.8 37.1 8.0 17.1 5.9 6.5 36.3 39.4 31.4 26.7 SK 58.9 54.3 13.4 23.9 20.4 16.3 7.3 5.5 32.6 55.0 BG 48.5 56.4 10.5 3.9 12.6 9.3 28.4 30.4 47.5 60.0 RO 86.8 1.8 4.5 6.9 54.2 TR 32.9 30.1 0.0 0.0 40.9 41.7 26.1 28.2 50.0 42.4 Source: Authors’ own calculations on EU-SILC Longitudinal data 2005-2012. (Population weighted shares)

64 Gökşen, Filiztekin, Öker Kuz,, Mazzotta & Parisi

4.3 Housing Policies and Leaving Parental Home: Dynamic Analysis In line with the discussion above, we construct three variables to assess the effect of housing policies on household formation. The first variable is a direct measure of housing policies, indicating whether the household receives any support (housing allowance) for housing. The second variable tracks whether the household rents at a reduced rate (including free, "social", housing). The third variable we construct tracks who provides or pays for accommodation in the parental household. We analyzed the leaving patterns in the cases where child is responsible for the provision of housing, in the case where parent is responsible; and in the case of joint provision.30

It has been shown that the housing policies are influential on leaving the parental home decisions of the young individuals (Aassve et al., 2002; Feijten & Mulder, 2002; Iacovou, 2002; Mulder et al., 2002; Roberts, 2003). As seen in Figure 4.3 (panel a/b/c), leaving home is more common in the households where the housing is provided by the parents. Young individuals are less likely to leave home when they are responsible for the accommodation costs and when this cost is undertaken jointly31. This finding is in line with the above discussion that higher parental income is associated with higher probability of leaving home. However, it is a somewhat problematic interpretation and should be approached cautiously as our analysis cannot capture the “who supports whom?” question. The underlying assumption of the model is that it is the parents who are providing the support. If a young person is entirely responsible for the accommodation costs, then it’s questionable how far they are still living “at home” in the sense that most young adults live at home, or what would be meant by them “leaving home”.

The analysis provided in the previous sections revealed that the UK exhibited considerable differences from other countries across welfare regimes in terms of the decision of leaving/returning to the parental home. They continue to exhibit significant differences when the nature of provision for housing is included in the analysis. The exit rate has significantly increased in the post-crises period for youth who provided/paid for accommodation in the parental home. This is likely to be due to improvement in the economic conditions of parents coupled with the youth's ability to pay for independent living.

In all other countries, across different welfare regimes, the rate of departure follows almost identical trends. One exception is the sharp decrease of exit rate in Baltic countries in the case of joint

30 Mortgage variables were not used in the dynamic model due to the small number of observations (especially for returning to the parental home variable) in the dataset. 31 In the case of partial responsibility, since there is space for only two names, that this is much more common where the young adult lives with a single parent. So it may be that the full sample are too heterogeneous to be meaningful D 8.3 - Leaving and returning to the parental home during the economic crisis 65

provision of accommodation. This is likely to be due to the high rate of owner-occupancy, together with limited provision of subsidized or free social housing, which targets only low-income groups (Treanor, 2015; Housing Europe, 2015).

Figure 4.3: Sharing of Accommodation Costs (% of Leavers)

Panel a: Child is Responsible (%) b: Parent is Responsible (%)

30.0 100.0 25.0 80.0 20.0 60.0 15.0 40.0 10.0 20.0 5.0 0.0 0.0 2005-2008 2008-2009 2010-2012 2005-2008 2008-2009 2010-2012

Nordic Anglo Continent Nordic Anglo Continent Med. Baltic Eastern Med. Baltic Eastern

Panel c: Joint Provision (%) 60.0 50.0 40.0 30.0 20.0 10.0 0.0 2005-2008 2008-2009 2010-2012

Nordic Anglo Continent Med. Baltic Eastern

Source: Authors’ own calculations on EU-SILC Longitudinal data 2005-2012.

As discussed in Aassve et al. (2002), government provided housing allowances might be a significant determinant of the decision to leave the parental home. The distribution of the housing allowances among those who left the parental home is seen in Figure 4.4. Before the crisis, around 30% of the young who left home in Continental Europe used to receive housing allowance. In Nordic countries this ratio was 26% and in the UK about 10%, while in the rest of the countries it was not very significant (between 0% and 5%).32

32 Since there is no policy similar to housing allowances in effect in Turkey we could not observe any individual benefitting from this policy.

66 Gökşen, Filiztekin, Öker Kuz,, Mazzotta & Parisi

Figure 4.4: Percentage of leavers with housing allowances (%)

35.0

30.0

25.0

20.0

15.0

10.0

5.0

0.0 2005-2008 2008-2009 2010-2012

Nordic Anglo Continent Med. Baltic Eastern

Source: Authors’ own calculations on EU-SILC Longitudinal data 2005-2012.

As Ermisch (1999) has shown, living in a parent-owned house, or as a tenant in a rent-controlled housing ("social tenant"), or as a private tenant has the potential to affect when young adults leave their parental home. In our sample, the percentage of social tenants differs across the welfare regimes, with Nordic and Continental European countries providing more social housing (around 18 and 20%, respectively) than others. In all other country groups, including Turkey, the percentage or social tenants is around 6% before the crisis, and from 1% to 5% after the crisis (Panel c of Figure 4.5). In line with the other findings (higher income is associated with higher rate of departure) most of the young who left home are residing either in their own houses or they are private tenants (Panel a/b). In all country groups, rent control (social tenants) housing is negatively associated with nest- leaving.

D 8.3 - Leaving and returning to the parental home during the economic crisis 67

Figure 4.5: Housing tenure of leavers (%)

Panel a: Owners Panel b: Private tenants 60.0 60.0 40.0 40.0

20.0 20.0 0.0 2005-2008 2008-2009 2010-2012 0.0 2005-2008 2008-2009 2010-2012 Nordic Anglo Continent Nordic Anglo Continent Med. Baltic Eastern Med. Baltic Eastern Turkey Turkey

Panel c: Social tenants 30.0

20.0

10.0

0.0 2005-2008 2008-2009 2010-2012

Nordic Anglo Continent Med. Baltic Eastern Turkey

Source: Authors’ own calculations on EU-SILC Longitudinal data 2005-2012.

To estimate the effect of housing policies on the decision to leave the parental home, we turn to the econometric model used in Section 3. We reestimate the probability of leaving home with housing policy variables. The individual level housing variables used in the analysis are as follows: 1) a dummy variable that takes the value of 1 if the individual receives housing allowance; zero otherwise; 2) a dummy variable for home ownership; 3) a dummy variable for being a social tenant; and 4) a dummy variable for being a private tenant. To highlight the impact of individual level housing variables, below we report only the (marginal) effect of housing policy variables.33

33 Full regression results (as STATA output) are available upon request. 68 Gökşen, Filiztekin, Öker Kuz,, Mazzotta & Parisi

The results (Figure 4.6) show that with one exception, the marginal effect of receiving housing allowances on the probability of leaving the parental home is positive across welfare regimes.34 As expected, the effect of this policy is the highest in the Nordic countries, where housing allowances increase the percentage of leavers by around 3%. It should be noted that the marginal impact of housing allowance on the decision to leave parental home increases over time and through the economic crisis of 2008 in the UK, Baltic, and eastern European countries, while in others there is a slight decrease.

Figure 4.6: Marginal effect of receiving housing allowance on leaving the parental home

Source: Authors’ own calculations on EU-SILC Longitudinal data 2005-2012.

Figure 4.7 below shows the marginal effect of rent control on the decision of young adults to leave parental home. Except for the Mediterranean countries the marginal effect of rent control is positive, although the magnitude of the effect is different. Compared to those living in self-owned households, in the Nordic countries living in rent-controlled ("social") housing is associated with around 8% higher probability of leaving the parental home for young adults. Nordic countries are followed by the UK, Baltic and eastern European countries in terms of the magnitude of the marginal effect of rent control. This rate does not vary during and after the crisis in Nordic countries, while it has different effect in other country groups throughout the period under consideration, with the economic crisis of 2008 having a significant impact on its magnitude. In the UK, the impact of rent control increases all

34 The negative effect of receiving housing allowance on the probability of leaving the parental home in eastern European countries begs an explanation. It may be that housing allowance means better housing and, together with the rate of joint provision of accommodation costs being high in eastern European countries (Figure 4.3, Panel c), this may result in young adults finding it less desirable and more costly to leave their parental homes. D 8.3 - Leaving and returning to the parental home during the economic crisis 69

throughout the period under consideration, including the crisis period, possibly due to decreasing share of social housing over time in overall housing, and the effect of other variables on the decision to leave being depressed during the economic recession. The same explanation may hold for Baltic countries as well. In all other country groups, the marginal effect of rent control either goes down all throughout the period or after the onset of economic crisis in 2008. There does not seem to be a difference between living in a household as social tenant or private tenant with regard to the marginal impact of rent control on the decision to leave the parental home.

Figure 4.7: Marginal effect of tenure status on probability of leaving home

Nordic Countries Anglo-Saxon Countries .22 .04 .2 .03 .18 .02 Effects on Pr(Exit) Effects on Pr(Exit) .16 .01

.14 2005-2008 2008-2009 2005-2008 2008-2009 2010-2012 Year Year tenure2 tenure3 tenure2 tenure3

Continental Eur. Countries Meditarrenean Countries .015 .022 .0215 .01 .021 .005 .0205 Effects on Pr(Exit) 0 Effects on Pr(Exit) .02 -.005

.0195 2005-2008 2008-2009 2010-2012 2005-2008 2008-2009 Year Year tenure2 tenure3 tenure2 tenure3

Baltic Countries Eastern Eur. Countries

.05 .04

.04 .03

.03 .02

Effects on Pr(Exit) Effects on Pr(Exit) .02 .01 0 .01 2005-2008 2008-2009 2010-2012 2005-2008 2008-2009 2010-2012 Year Year

tenure2 tenure3 tenure2 tenure3 70 Gökşen, Filiztekin, Öker Kuz,, Mazzotta & Parisi

Figure 4.7: Marginal effect of tenure status on probability of leaving home (continued)

Turkey .2 .15 .1 Effects on Pr(Exit) .05 2005-2008 2008-2009 2010-2012 Year

tenure2 tenure3

Notes: 1) tenure3 refers to the social tenants (rent controlled housing). 2) tenure2 refers to private tenants. 3) Base category is home ownership Source: Authors’ own calculations on EU-SILC Longitudinal data 2005-2012.

4.4 Housing Policies and Returning to the Parental Home: Dynamic Analysis

It is not surprising to observe that in most, if not all, of the countries the cost of accommodation is provided mostly by the parents or, to a lesser extent, it is jointly provided after young individuals return to the parental home (Figure 4.8). In Anglo-Saxon countries, parental provision of accommodation reaches to 88% during the crisis. On the other hand, in the eastern European countries the share of returners who undertook the accommodation costs increased after the crisis. In contrast, in Mediterranean countries, while around 43% of the returnees were responsible for the provision of the accommodation before the crisis, their ratio dropped to 30%, which is likely due to high youth unemployment coupled with his incidence of home ownership in these countries.

D 8.3 - Leaving and returning to the parental home during the economic crisis 71

Figure 4.8: Sharing of accommodation costs (% of returners)

Panel a: Child is responsible Panel b: Parent is responsible

50.0 100.0 40.0 80.0 30.0 60.0 20.0 40.0 10.0 20.0 0.0 0.0 2005-2008 2008-2009 2010-2012 2005-2008 2008-2009 2010-2012

Nordic Anglo Continent Nordic Anglo Continent Med. Baltic Eastern Med. Baltic Eastern

Panel c: Joint provision 50.0 40.0 30.0 20.0 10.0 0.0 2005-2008 2008-2009 2010-2012

Nordic Anglo Continent Med. Baltic Eastern

Source: Authors’ own calculations on EU-SILC Longitudinal data 2005-2012.

In accordance with what is observed in the case of leaving the parental home, lack of housing allowance seems to be an important determinant of the decision to return to the parental home. As seen in the Figure 4.9, except for Nordic and Continental European countries, in line with the general trends described earlier, the percentage of those receiving housing allowance among the young individuals before they returned to the parental home is very low (less than 10%). The effect of this policy is the highest in the Nordic countries, where housing allowances increase the percentage of leavers by around 3%.

72 Gökşen, Filiztekin, Öker Kuz,, Mazzotta & Parisi

Figure 4.9: Rate of housing allowance receivers before returning (%) 30.0

25.0

20.0

15.0

10.0

5.0

0.0 2005-2008 2008-2009 2010-2012

Nordic Anglo Continent Med. Baltic Eastern

Source: Authors’ own calculations on EU-SILC Longitudinal data 2005-2012.

Figure 4.10 below shows the rate of those who benefit from the policy of rent control among the returners across welfare regimes. Returners are mostly the ones who were owners of a house or private tenant. When the change during and after the economic crisis is considered, while the rate of return for those that enjoyed rent-controlled (social) housing decreased, rate of return for those who owned their houses or rented at market rental rates increased.

Figure 4.10: Housing tenure status of young individuals before returning (%)

Panel a: Owners Panel b: Private Tenants 80.0 60.0 60.0 40.0 40.0 20.0 20.0 0.0 0.0 2005-2008 2008-2009 2010-2012 2005-2008 2008-2009 2010-2012

Nordic Anglo Continent Nordic Anglo Continent Med. Baltic Eastern Med. Baltic Eastern Turkey Turkey

D 8.3 - Leaving and returning to the parental home during the economic crisis 73

Figure 4.10: Housing tenure status of young Individuals before returning (%) (continued)

Panel c: Social Tenants 20.0 15.0 10.0 5.0 0.0 2005-2008 2008-2009 2010-2012

Nordic Anglo Continent Med. Baltic Eastern Turkey

Source: Authors’ own calculations on EU-SILC Longitudinal data 2005-2012.

Figure 4.11 shows the marginal effect of receiving housing allowances on the probability of returning to the parental home. The results reveal that the marginal effect of receiving housing allowance before returning to the parental home is negative, with the implication that housing allowance receivers are less likely to come back to the parental home. Although this negative association is recorded, it should be noted that the magnitude of this impact is very low. The highest marginal impact is in eastern European countries, where it is only 8‰.

Figure 4.11: Marginal effect of receiving housing allowance on returning to parental home (%)

Source: Authors’ own calculations on EU-SILC Longitudinal data 2005-2012.

74 Gökşen, Filiztekin, Öker Kuz,, Mazzotta & Parisi

As for the impact of rent control on the probability of returning home, Figure 4.12 reveals that, with the exception of the UK and Mediterranean countries, the marginal effect of rent control is negative. That is, those who benefit from rent-control (social tenants) are less likely to return to their parental home. The magnitude of this effect seems highest in the case of Turkey (about 1%). It should again be noted that, as in the case of housing allowance, the magnitude of the effect of rent control impact is very low. Figure 4.12: Marginal effect of housing tenure on the probability of returning to parental home

Nordic Countries Anglo-Saxon Countries 0 .08 .06 -.001 .04 -.002 Effects on Pr(Return) Effects on Pr(Return) .02 0 -.003 2005-2008 2008-2009 2010-2012 2005-2008 2008-2009 2010-2012 Year Year

tenuret1 tenuret3 tenuret1 tenuret3

Continental Eur. Countries Meditarrenean Countries 0 .002 -.001 0 -.002 -.002 Effects on Pr(Return) Effects on Pr(Return) -.003 -.004 -.004 2005-2008 2008-2009 2010-2012 2005-2008 2008-2009 2010-2012 Year Year

tenuret1 tenuret3 tenuret1 tenuret3

Baltic Countries Eastern Eur. Countries 0 -.0025 -.003 -.001 -.0035 -.002 -.004 Effects on Pr(Return) Effects on Pr(Return) -.003 -.0045 -.004 -.005 2005-2008 2008-2009 2010-2012 2005-2008 2008-2009 2010-2012 Year Year

tenuret1 tenuret3 tenuret1 tenuret3

D 8.3 - Leaving and returning to the parental home during the economic crisis 75

Figure 4.12: Marginal effect of housing tenure on the probability of returning to parental home (continued)

Turkey .04 .03 .02 Effects on Pr(Return) .01 0

2005-2008 2008-2009 2010-2012 Year

tenuret1 tenuret3

Notes: 1) tenure3 refers to the social tenants (rent controlled housing). 2) tenure1 refers to private tenants. 3) Base category is home ownership. Source: Authors’ own calculations on EU-SILC Longitudinal data 2005-2012.

Our findings are broadly in line with the EU housing polices outlined above. To summarize this section, we note that who pays for the cost of housing, together with public housing policies such as housing allowances and rent-controlled or free (social) housing, has a considerable impact on the decision to leave/return to parental home. This impact is more apparent on the decision to leave. Econometric estimations show that, with the exception of eastern European countries, the marginal effect of benefitting from housing allowances on the probability of leaving the parental home is positive across welfare regimes. As for the marginal effect of rent control on the decision of young adults to leave parental home it is positive, except for the Mediterranean countries. Lack of housing allowance seems to be one of the important determinants of returning to the parental home. Returners are mostly the ones who were owners of a dwelling or who are private tenants. This rate is observed to decrease further during the crisis as well. Housing allowance receivers are less likely to come back to the parental home, as well as those who benefit from rent-control (social tenants) (although in both cases the magnitude of the impact is very low).

76 Gökşen, Filiztekin, Öker Kuz,, Mazzotta & Parisi

5. Conclusion

This report describes and comparatively identifies the possible economic, institutional and cultural factors that take part in the process of transition to adulthood. The report particularly focuses on the interrelationships of youth unemployment and decisions to leave and return to the parental home. The nexus of leaving and returning to the parental home; parental resources used to facilitate adulthood transitions; the consequences of unemployment and precarious work on the opportunity for young people to establish their own families, and economic independence are critical to understand the barriers encountered in the transition to independent adulthood. Transition to adulthood is shaped by interactions between labour markets, the family (household structure) and public policies.

The shares of young people that live with their parents exhibit two distinct characteristics. First, in all country groups share of young individuals that live with their parents have increased over time. The increase accelerates after the 2008 crisis, particularly in Northern and Continental European countries, although from sensible lower levels. Second, there are significant differences across country groups. While this share is below 50% in Northern and Continental countries, it is above 65% in Mediterranean and over 70% in Eastern European and Baltic countries.

The share of the population aged 35 and more that shares house with their parents is quite stable over time (over the recent crisis), with the exception of Eastern European countries and Turkey, where the shares increase slightly. In the south and east of Europe, multi-generational households are more likely to be formed. This suggests that the difference of living arrangements in these countries is not unique to young population; either preferences or social and economic conditions in the latter group of countries are significantly different, and living in larger households is a more likely outcome.

As for gender differences, in all countries males are more likely to co-reside with their parents and the gender difference is larger in the Northern and Continental countries, despite the fact that their overall rates are much lower than those of Mediterranean and Eastern European countries. The level of completed education turns out to be an important characteristic to explain peoples’ choice of living arrangements. While more educated individuals are more likely to live independently, there are variations across countries. Even the most educated individuals in southern and eastern European countries are found to stay with their parents, whereas the difference between the least educated groups across countries is less pronounced. Across all welfare regimes, the share of co-residence D 8.3 - Leaving and returning to the parental home during the economic crisis 77

increases with the crisis and declines afterwards, but remains above the pre-crisis levels, with the less educated individuals affected more than the others.

With the exception of the UK, the effect of the crisis is also observed through an increasing rate of inactivity among young people and increasing unemployment rate. Different labour market status has also an impact on the decision to live with one’s parents. An interesting result regarding this is that inactive individuals had started to live more with their parents than before the crisis.

Before the crisis, in the northern and western Europe, singles living with their parents were earning significantly less than those who lived independently. After the crisis, there is a tendency towards increasing inequality between those living in parental homes and those who have moved out in all country groups, except the UK and Turkey where there is a tendency of incomes to equalize. Average income of those living with parents decreases relative to those living independently. This could be either due to declining incomes of those who live with their parents, or that individuals moving back with their parents as they get poorer, leading to an overall decline in the average income of those living with their parents.

Adulthood transitions in the form of leaving the parental home to establish an autonomous household is highly variable among European countries. Our findings reveal that the Southern, Eastern Baltic countries and Turkey show lower leaving rates compared to the other countries, and the crisis did not change this difference. After the financial crisis (2008-2009), the sharpest decrease in the rate of leaving home is observed in Nordic countries. All countries experienced an increase in the percentage of people returning home, except the eastern European countries. Southern European countries registered an increase of returning home throughout the period.

With regard to income we have seen that for the Southern, Eastern and Continental European countries, relative higher family labour and pension income increases the chances of co-residence, i.e. decreases leaving parental home (as in Angelini & Laferrère, 2012; Iacovou, 2010; Manacorda & Moretti, 2006). Instead, wealthy families (considering all the household income including the not working income) can support young people also outside the parental home and so they can foster the exit (in line with Mazzotta & Parisi, 2015; Parisi, 2008). On the contrary, poorer parents have no way of controlling the household living arrangement decisions of their child. Income does not have such a big effect on the probability of returning home. However, marital status has a strong effect on both the probability of leaving and returning home. Finally, employment is a good predictor of leaving home but only by an indirect effect that works through marital status. With regards to returning home, losing a job increases the probability of returning home only for Continental and Southern Countries, but the 78 Gökşen, Filiztekin, Öker Kuz,, Mazzotta & Parisi

positive effect of the divorce on the provability of returning home is stronger (the results hold also if we exclude inactive).

Besides these factors, availability of housing and housing market circumstances are widely recognised as influencing the opportunities for young adults to leave their parents’ homes. A combination of high-levels of home-ownership, difficult access to mortgages, and high house prices seems to make it particularly difficult for young people to form their own households. There is no common housing policy in the EU 27, but in recent years, housing has been recognised as a significant dimension of social exclusion by the EU. There are common elements in social housing across the Union: the goal of supplying affordable housing and the identification of target populations in terms of socio-economic status or vulnerabilities. Policies converge also along the dimensions of decrease in direct housing provision by the public, the increasing role played by private partners and increasing importance of the private housing market. The main axis of divergence seems between the UK and continental Europe. The former is recognizable for the preference for owner occupation of dwellings whereas the latter can be identified with high levels of renting.

Our findings are broadly in line with the EU housing polices outlined above. Public housing policies such as housing allowances and rent-controlled or free (social) housing have a considerable impact on the decision to leave/return to parental home. This impact is more apparent for leave decisions. With the exception of eastern European countries, the marginal effect of benefitting from housing allowances on the probability of leaving the parental home is positive across welfare regimes. The effect of this policy is the highest in the Nordic countries, where housing allowances increase the percentage of leavers by around 3%. As for the effect of rent control on the decision of young adults to leave parental home is positive, with the exception of the Mediterranean countries. Lack of housing allowance seems to be an important determinant of the decision to return to the parental home. Returners are mostly the ones who were owners of a house or who are private tenants. This rate is observed to decrease further during the crisis as well. As for the impact of rent-controlled housing and housing allowances on the decision to return, returners are mostly the ones who did not benefit from rent-control and housing allowances. However, divergences from this trend in some regime types point at the role of other housing policies such as massive housing privatization since 1990, mortgage and tax policies, or decreasing overall housing expenditures.

These findings once more reinforce the argument that the nexus of leaving and returning to the parental home; parental resources used to facilitate adulthood transitions; the consequences of unemployment and precarious work on the opportunity for young people to establish their own families, and economic independence is critical to understand the barriers encountered in the transition to independent adulthood. D 8.3 - Leaving and returning to the parental home during the economic crisis 79

Finally, while many of the findings in this report have significant implications for youth policies it is beyond the scope of this report to fully discuss these policy issues. Yet, findings of this report underscore the importance of a holistic approach to understanding the complexity of the extended transitions to adulthood in Europe. The comparative, macro-social tendencies presented in this study require further national and regional analysis as patterns of transitions vary according to the particular institutional contexts of the countries. Typologies used in this report capture some of the variation in individual countries, but leave substantial variation unaccounted for. As argued by Bucholtz et al., (2009, p.67) the country specific differences can be understood in that institutions and social structures are interwoven with a high degree of internal complementarity. They can only be grasped adequately in their “totality as country specific institutional packages”. Transition to adulthood takes place within a complex framework of structural, institutional, economic, and cultural determinants that differ among countries and this report addresses only a limited number of these determinants. Regional and national divergences can only be understood and interpreted within a historical perspective that includes the cultural differences underlying various life course events over time (Giuliano, 2007; Manacorda and Moretti, 2007).

80 Gökşen, Filiztekin, Öker Kuz,, Mazzotta & Parisi

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Angelini, V., & Laferrère, A. (2012). Parental altruism and nest leaving in Europe: evidence from a retrospective survey. Review of Economics of the Household, 11(3), 393–420. doi:10.1007/s11150- 012-9170-9.

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84 Gökşen, Filiztekin, Öker Kuz,, Mazzotta & Parisi

7. Appendix

Table A.1: Total number of observations by country and year in the SILC dataset 2004 2005 2006 2007 2008 2009 2010 2011 2012

Nordic. 29,788 52,135 69,475 77,386 81,087 77,373 54,086 32,897 15,658 DK 7,099 9,817 12,092 10,638 9,816 9,284 6,910 4,452 2,190 FI 5,136 9,569 13,443 17,051 16,505 15,671 10,615 6,625 3,097 NO 11,004 20,284 27,249 27,259 32,152 30,068 20,585 12,302 5,905 SE 4,563 8,673 11,500 15,685 15,739 15,397 10,891 6,293 2,960 IS 1,986 3,792 5,191 6,753 6,875 6,953 5,085 3,225 1,506 Anglo- Saxon 1,952 11,816 18,635 22,004 23,726 20,470 11,758 6,731 3,005 UK 0 8,047 13,683 17,822 20,989 19,360 11,758 6,731 3,005 IE 1,952 3,769 4,952 4,182 2,737 1,110 0 0 0 Cont. Euro. 35,233 55,952 71,349 82,930 73,872 73,334 51,228 31,812 15,502 AT 5,816 8,879 12,941 16,680 13,622 13,594 9,618 6,114 3,116 BE 3,280 7,728 11,490 14,831 14,314 14,255 9,742 5,920 2,889 LU 9,629 9,637 10,125 4,753 4,240 5,729 3,626 2,494 1,631 FR 16,508 19,147 22,629 25,840 16,248 16,069 11,549 7,370 3,537 NL 0 10,561 14,164 20,826 25,448 23,687 16,693 9,914 4,329 Med. Count. 39,189 69,491 101,725 128,074 134,931 138,515 97,047 60,767 28,817 IT 15,822 29,411 41,929 52,737 52,408 51,123 34,434 21,206 9,354 ES 11,316 19,374 26,588 34,619 35,955 36,857 26,606 16,396 7,653 PT 3,540 6,540 9,009 11,691 11,786 13,008 9,507 6,656 3,723 GR 8,511 11,301 15,188 14,793 16,868 18,034 12,919 7,746 3,472 CY 0 2,865 5,635 8,083 10,025 9,283 6,519 4,057 2,024 MT 0 0 3,376 6,151 7,889 10,210 7,062 4,706 2,591 Baltic States 5,809 13,359 24,242 33,885 38,292 40,780 29,353 18,656 9,002 EE 5,809 6,765 10,980 14,370 13,030 13,539 9,497 5,967 2,738 LT 0 2,923 6,706 10,231 12,150 12,845 9,310 5,677 2,930 LV 0 3,671 6,556 9,284 13,112 14,396 10,546 7,012 3,334 East. Euro. 0 40,827 79,803 118,039 152,258 158,979 116,395 74,350 36,508 CZ 0 10,333 17,830 23,029 26,787 23,239 15,158 9,238 5,051 HU 0 5,328 11,422 18,107 21,922 24,001 17,333 11,008 5,788 PL 0 12,117 23,268 32,483 41,088 38,541 27,028 16,908 7,992 SI 0 9,174 16,699 22,533 28,842 29,568 20,186 12,350 5,551 SK 0 3,875 7,505 11,127 15,132 15,672 11,555 7,331 3,640 BG 0 0 3,079 5,811 9,139 14,162 11,488 8,738 4,095 RO 0 0 0 4,949 9,348 13,796 13,647 8,777 4,391 Turkey 0 0 7,921 15,513 23,684 32,504 24,722 17,218 8,739 Total 111,971 243,580 373,150 477,831 527,850 541,955 384,589 242,431 117,231 Source: Authors’ own calculations on EU-SILC Longitudinal data 2005-2012.

D 8.3 - Leaving and returning to the parental home during the economic crisis 85

Table A.2: Shares of Age Groups in Total Population 2011 Population EU-SILC EU-SILC and Housing Census Unweighted Weighted Yng/Adlt Yng/Adlt Yng/Adlt Child Young Adult Ratio Ratio Ratio Nordic Countries 18.3 25.2 56.4 44.8 34.5 33.8 DK 19.2 22.9 57.9 39.7 24.4 25.8 FI 17.7 23.8 58.5 40.8 34.1 40.9 NO 19.9 24.8 55.3 44.8 35.3 32.1 SE 16.4 29.3 54.2 54.1 33.7 36.2 IS 22.2 27.1 50.6 53.6 51.8 44.3 Anglo-Saxon Countries 19.1 25.4 55.5 45.8 27.8 30.9 UK 18.8 25.2 56.0 45.1 27.8 30.9 IE 22.6 28.0 49.5 56.5 N/A N/A Continental European Countries 19.0 23.5 57.4 41.0 34.1 35.2 AT 15.7 24.0 60.3 39.8 32.6 36.1 BE 18.1 23.9 58.0 41.3 38.5 40.2 LU 18.5 25.2 56.3 44.8 49.2 41.4 FR 19.7 23.5 56.7 41.4 34.4 33.5 NL 18.6 23.1 58.2 39.7 29.1 38.2 Mediterranean Countries 15.5 22.6 61.9 36.5 33.3 38.2 IT 14.9 20.9 64.2 32.6 31.1 32.8 ES 16.0 24.1 59.9 40.2 35.0 46.9 PT 15.9 23.4 60.7 38.5 30.1 32.2 GR 15.5 24.2 60.3 40.2 31.2 41.9 CY 17.3 30.4 52.3 58.1 44.9 48.1 MT 16.0 26.6 57.4 46.4 37.6 40.1 Baltic States 15.9 25.6 58.5 43.8 37.7 43.3 EE 16.4 25.6 58.0 44.1 45.9 43.6 LT 16.1 25.4 58.5 43.5 31.0 40.8 LV 15.1 26.0 58.9 44.2 37.1 47.2 Eastern European Countries 16.2 26.6 57.2 46.5 39.7 46.1 CZ 15.3 26.2 58.4 44.9 35.8 40.7 HU 15.7 24.9 59.4 42.0 39.6 42.1 PL 16.3 28.8 54.9 52.5 42.5 46.7 SI 15.1 25.1 59.8 41.9 45.4 41.8 SK 17.8 24.5 57.7 42.4 54.8 52.3 BG 14.1 24.8 61.1 40.6 31.3 42.2 RO 16.9 25.3 57.8 43.7 29.7 50.1 TR 17.1 33.9 49.0 69.3 73.1 N/A Total 17.2 25.8 57.0 45.3 38.3 38.0 Total Non-TR 17.2 24.4 58.4 41.8 35.9 38.0 Source: Authors’ own calculations on EU-SILC Longitudinal data 2005-2012.

86 Gökşen, Filiztekin, Öker Kuz,, Mazzotta & Parisi

Table A.3: Marital Status and Consensual Union of Young Population Marital Consensual Union Status Yes, on a Yes, w/o a No Missing Total Status legal basis legal basis Never 2,777 72,908 427,114 13,474 516,273 married (Row %) (0.54) (14.12) (82.73) (2.61) (100.00) [Col.%] [1.61] [90.27] [96.62] [53.70] [71.64] Married 169,873 3,692 5,476 13 179,054 (Row %) (94.87) (2.06) (3.06) (0.01) (100.00) [Col.%] [98.32] [4.57] [1.24] [0.05] [24.84] Separated 19 881 2,856 59 3,815 (Row %) (0.50) (23.09) (74.86) (1.55) (100.00) [Col.%] [0.01] [1.09] [0.65] [0.24] [0.53] Widowed 3 129 587 417 1,136 (Row %) (0.26) (11.36) (51.67) (36.71) (100.00) [Col.%] [0.00] [0.16] [0.13] [1.66] [0.16] Divorced 77 2,765 5,739 10 8,591 (Row %) (0.90) (32.18) (66.80) (0.12) (100.00) [Col.%] [0.04] [3.42] [1.30] [0.04] [1.19] Missing 28 393 280 11,117 11,818 (Row %) (0.24) (3.33) (2.37) (94.07) (100.00) [Col.%] [0.02] [0.49] [0.06] [44.31] [1.64] Total 172,777 80,768 442,052 25,090 720,687 (Row %) (23.97) (11.21) (61.34) (3.48) (100.00) [Col.%] [100.00] [100.00] [100.00] [100.00] [100.00] Source: Authors’ own calculations on EU-SILC Longitudinal data 2005-2012.

D 8.3 - Leaving and returning to the parental home during the economic crisis 87

Table A.4: Share of students, inactivity and employment rate Inactivity Rate Employment Rate Unemployment rate In Education (excl. Students) (Employed/Pop excl. St.) (Unemp./Active) Pre- Post- Pre- Post- Pre- Post- Pre- Post- Crisis Crisis Crisis Crisis Crisis Crisis Crisis Crisis Crisis Crisis Crisis Crisis Nordi c 30.9 31.8 37.4 23.6 27.3 13.2 72.4 67.1 80.6 5.2 7.7 7.2 DK 31.1 33.6 41.7 12.7 17.5 5.0 54.0 45.0 48.5 2.2 4.0 4.8 FI 34.0 32.5 36.0 18.3 24.7 13.1 44.5 38.9 46.6 3.2 3.8 4.3 NO 29.1 28.4 37.9 18.8 21.1 6.5 49.9 47.9 53.5 2.2 2.6 2.0 SE 28.9 31.9 30.0 13.0 10.0 9.6 53.8 52.8 54.7 4.2 5.4 5.7 IS 34.4 40.5 46.0 13.8 16.5 6.2 49.9 37.9 42.4 1.8 5.1 5.4 Anglo Saxon 16.7 21.6 22.8 29.9 16.4 12.1 49.9 56.8 59.4 3.6 5.3 5.8 UK 13.9 21.1 22.8 33.4 16.4 12.1 49.6 57.3 59.4 3.1 5.2 5.8 IE 30.5 39.4 12.3 13.3 51.5 38.8 5.8 8.5 Cont. Euro. 24.6 26.2 29.4 14.0 14.8 9.0 56.6 54.2 56.9 4.7 4.9 4.7 AT 21.0 22.3 22.4 13.7 14.1 12.5 61.4 59.7 61.2 3.9 3.9 4.0 BE 25.0 25.0 29.6 15.4 21.7 10.5 53.3 47.1 54.7 6.3 6.3 5.3 LU 12.1 20.1 28.6 12.4 19.6 8.1 68.3 53.9 57.0 7.3 6.5 6.3 FR 30.0 26.4 30.1 13.4 19.8 10.1 50.5 46.0 52.2 6.1 7.8 7.6 NL 24.6 31.6 34.3 14.6 4.5 4.4 59.4 62.4 59.8 1.3 1.5 1.5 Med. Cntr. 23.8 25.1 30.0 18.1 18.8 12.1 51.0 45.7 45.1 7.1 10.4 12.9 IT 24.3 25.2 32.3 19.5 23.8 14.1 48.7 41.8 41.8 7.5 9.3 11.8 ES 22.6 26.4 31.3 15.8 8.5 8.9 54.0 50.3 42.6 7.5 14.8 17.1 PT 24.3 24.2 28.2 13.7 19.3 7.5 54.9 47.1 53.0 7.1 9.3 11.3 GR 23.1 24.2 26.6 20.1 21.9 15.2 48.9 44.0 40.4 7.8 9.9 17.8 CY 30.1 32.3 37.4 19.4 23.0 10.0 47.2 39.7 45.4 3.3 4.9 7.2 MT 16.3 15.4 16.7 21.6 24.3 18.0 57.3 54.2 61.0 4.8 6.1 4.4 Baltic States 31.4 29.4 34.1 19.8 20.9 9.6 44.7 37.1 44.2 4.1 12.6 12.1 EE 34.2 31.2 35.8 19.6 23.1 10.1 42.2 34.9 44.2 3.9 10.8 9.9 LT 33.9 35.1 38.5 19.0 17.3 6.4 43.3 36.6 44.6 3.8 11.0 10.5 LV 24.7 23.1 29.2 20.6 21.3 11.5 49.9 39.8 43.8 4.8 15.7 15.5 East. Euro. 28.3 28.2 33.7 21.4 23.6 12.1 45.1 42.1 46.9 5.1 6.1 7.3 CZ 25.9 24.2 33.1 15.5 28.0 9.7 53.9 42.5 51.3 4.7 5.3 6.0 HU 25.4 27.7 35.9 23.6 25.8 11.2 45.7 39.6 43.8 5.3 7.0 9.1 PL 26.4 22.2 26.9 25.9 33.5 21.7 41.5 38.2 44.9 6.1 6.1 6.5 SI 36.5 38.7 42.1 18.1 14.4 5.1 41.5 41.3 45.0 3.9 5.5 7.8 SK 30.7 32.7 39.6 17.7 17.0 5.6 46.3 42.8 46.6 5.3 7.4 8.2 BG 17.0 21.1 26.6 29.1 26.8 17.4 46.6 44.7 47.1 7.3 7.4 9.0 RO 20.1 28.3 31.7 30.9 12.0 10.0 45.8 55.9 54.2 3.2 3.8 4.1 Turkey 10.1 12.4 14.8 35.4 32.4 30.7 49.4 48.9 48.9 5.1 6.4 5.6 Total 25.9 26.0 30.2 19.5 21.3 13.4 49.5 45.5 48.3 5.1 7.1 8.0 Total Non- TR 26.7 27.5 32.5 18.7 20.1 11.0 49.5 45.2 48.2 5.1 7.2 8.3 Source: Authors’ own calculations on EU-SILC Longitudinal data 2005-2012.

88 Gökşen, Filiztekin, Öker Kuz,, Mazzotta & Parisi

Table A.5: Share of young population that live with their parents

2004 2005 2006 2007 2008 2009 2010 2011 2012

Nordic Countries 25.3 24.9 24.1 23.2 22.9 22.2 21.1 20.3 19.5

DK 23.2 21.4 21.0 18.1 17.7 17.2 16.1 15.9 15.7

FI 23.5 23.1 22.4 22.2 22.3 22.0 21.0 20.5 19.8 NO 29.3 26.9 25.3 24.2 23.4 22.3 20.8 20.3 20.0 SE 25.2 25.0 24.8 24.3 23.9 23.1 22.4 20.4 18.6

IS 29.3 28.5 27.9 27.2 27.2 26.5 26.0 26.2 24.8

Anglo-Saxon Countries 20.3 20.6 20.0 19.1 19.1 19.3 18.6 18.0 16.9 UK 21.9 21.1 20.0 19.6 19.6 18.6 18.0 16.9

IE 20.3 17.9 16.7 15.3 15.1 14.9 Continental European Countries 24.5 23.7 23.1 22.5 21.8 21.5 20.6 20.2 19.7 AT 23.5 22.8 22.3 21.9 21.2 21.2 20.6 20.2 19.3 BE 23.4 23.1 23.2 23.7 23.0 23.1 22.6 22.3 21.8

LU 37.7 37.2 35.6 34.4 35.0 28.5 27.0 25.3 22.4

FR 23.7 23.5 23.1 22.7 22.7 21.8 21.4 20.5 20.3 NL 21.3 20.0 19.1 18.6 18.9 17.5 17.4 16.9 Mediterranean Countries 24.7 24.2 23.7 23.3 22.8 22.3 22.0 21.2 20.7 IT 23.9 23.2 22.5 22.2 21.5 21.0 21.0 20.0 19.3 ES 26.1 25.4 24.9 24.4 23.8 23.3 23.1 21.8 21.2 PT 24.9 23.4 23.1 22.6 21.6 20.9 19.8 20.0 19.8

GR 24.0 24.3 23.8 23.2 22.9 22.2 21.3 20.2 18.8 CY 27.1 26.8 26.5 26.3 25.5 26.0 26.0 27.3

MT 25.1 25.2 23.9 24.1 23.4 23.1 22.7

Baltic States 27.6 26.3 24.9 24.9 24.2 24.0 24.0 23.3 23.2

EE 27.6 28.0 28.1 28.2 27.6 27.2 27.2 26.2 26.7

LT 24.0 20.0 21.2 20.5 20.4 21.4 20.7 20.4

LV 24.8 24.5 24.1 24.2 24.2 23.4 23.0 22.7 Eastern European Countries 28.1 27.7 27.3 26.5 26.0 25.2 24.5 23.7

CZ 25.9 25.5 25.1 24.3 23.8 23.2 22.7 21.7

HU 25.3 25.4 25.2 24.7 25.0 24.5 24.1 24.2

PL 28.5 28.3 27.7 26.9 26.2 25.4 24.8 24.6

SI 31.3 30.5 30.2 29.3 28.7 27.5 26.8 25.6

SK 29.4 29.8 30.7 31.5 31.6 32.1 31.2 31.2

BG 25.0 25.0 22.9 22.4 22.2 21.3 18.8

RO 24.0 22.3 21.9 21.4 20.5 19.9

TR 43.5 42.1 42.3 41.7 40.7 41.2 39.9

Total 24.9 24.8 24.9 24.7 24.6 24.4 23.9 23.4 22.9 Total Non-TR 24.9 24.8 24.5 24.1 23.7 23.3 22.8 22.1 21.5

D 8.3 - Leaving and returning to the parental home during the economic crisis 89

Table A.6: Tenure status and Housing Allowance (all households) Tenant Owner w/o Owner w/ Tenant at reduced rent Housing mortgage mortgage Market Rate or free Allowance Pre- Post- Pre- Post- Pre- Post- Pre- Post- Pre- Post- Crisis Crisis Crisis Crisis Crisis Crisis Crisis Crisis Crisis Crisis Nordic Countries 23.7 24.6 52.1 55.2 17.7 14.0 6.6 6.2 9.9 9.3 DK 15.2 17.6 58.9 59.7 25.9 22.6 0.0 0.1 10.2 8.2 FI 45.1 40.5 22.9 37.0 13.1 9.3 18.9 13.2 14.8 13.5 NO 13.0 26.1 70.7 60.0 11.1 9.0 5.3 4.9 2.4 2.4 SE 27.1 5.2 41.2 65.3 30.6 28.9 1.1 0.6 8.5 6.7 IS 18.0 18.3 69.6 68.0 5.1 6.6 7.2 7.1 33.7 41.1 Anglo-Saxon Countries 42.6 43.0 34.0 32.4 7.9 6.6 15.6 18.0 18.8 13.6 UK 34.4 39.8 38.6 34.3 10.0 7.2 17.0 18.6 12.5 12.6 IE 61.1 66.1 23.4 18.3 3.2 2.3 12.3 13.3 44.5 49.6 Continental European Countries 29.5 28.4 29.1 37.1 27.9 23.2 13.6 11.3 10.5 10.0 AT 16.4 31.8 10.9 22.8 49.2 24.8 23.5 20.6 4.1 4.8 BE 38.3 38.6 30.9 32.9 21.5 18.7 9.3 9.8 0.8 0.8 LU 5.5 21.9 16.9 33.5 64.6 38.6 12.9 6.0 5.0 12.0 FR 41.5 42.3 20.8 22.5 19.3 16.6 18.4 18.7 22.1 22.6 NL 8.8 9.5 61.4 63.3 29.5 26.9 0.2 0.3 9.3 9.4 Mediterranean Countries 56.4 59.4 13.7 19.9 13.3 9.0 16.5 11.8 2.1 3.1 IT 63.1 63.8 11.3 12.4 11.4 10.4 14.2 13.3 1.7 2.5 ES 43.4 55.0 20.9 28.1 15.5 7.8 20.2 9.2 1.0 1.4 PT 55.2 54.8 20.1 21.8 9.8 10.1 14.9 13.3 5.6 4.4 GR 45.5 67.6 6.4 11.4 32.2 14.5 15.9 6.5 1.1 0.9 CY 36.6 59.0 10.2 11.7 15.0 7.2 38.2 22.0 2.2 2.3 MT 61.9 64.5 12.5 11.5 2.1 1.6 23.4 22.4 10.1 16.0 Baltic States 76.5 83.9 5.2 4.8 4.8 3.5 13.5 7.8 3.5 4.0 EE 73.4 78.5 8.6 8.5 4.7 2.2 13.3 10.8 2.2 2.1 LT 89.3 92.1 2.7 2.7 0.8 0.8 7.1 4.4 4.2 3.9 LV 58.4 79.0 1.1 4.9 13.3 6.8 27.2 9.3 4.3 5.5 Eastern European Countries 70.6 76.8 4.9 6.5 4.3 3.5 20.2 13.3 3.8 2.6 CZ 63.9 68.5 8.3 8.1 4.6 6.1 23.2 17.2 4.1 2.1 HU 77.5 74.2 10.3 15.6 2.9 2.0 9.3 8.2 9.0 9.1 PL 58.9 70.9 0.8 4.3 3.3 2.1 37.1 22.8 5.0 3.0 SI 83.4 77.4 2.9 5.9 3.8 3.9 9.8 12.8 0.5 0.4 SK 85.2 85.4 2.8 5.1 10.0 7.9 2.1 1.6 0.3 0.3 BG 85.0 85.5 2.7 1.8 2.2 1.5 10.2 11.3 0.1 0.0 RO 97.2 0.4 0.7 1.7 TR 63.9 61.1 0.0 0.0 20.5 21.8 15.6 17.1 0.1 0.2 Source: Authors’ own calculations on EU-SILC Longitudinal data 2005-2012.

90 Gökşen, Filiztekin, Öker Kuz,, Mazzotta & Parisi

Table A7: Country dummies of Table 3.2 Nordic Anglo_saxon Continental Southern Eastern Baltic 1)Probability of Leaving Home danimark -0.25** austria -0.21*** france 0.26*** luxemb -0.36*** italy -0.29*** spain -0.06 portugal -0.40*** - czeckrep 0.37*** - poland 0.68*** - lettonia 0.16*** lituania -0.13** 2)Probability of forming a couple danimark -0.19 austria -0.02 france -0.06 luxemb -0.05 italy -0.41*** spain -0.34*** portugal -0.10* - czeckrep 0.19*** poland 0.45*** lettonia -0.11** lituania -0.06 3)Probability of being employed danimark 0.08 austria -0.01 france -0.19*** luxemb -0.07 italy -1.15*** spain -1.12*** portugal -0.56*** - czeckrep 0.46*** - poland 0.53*** lettonia 0.09*** lituania 0.23***

D 8.3 - Leaving and returning to the parental home during the economic crisis 91

Table A8: Country dummies of Table 3.3 Nordic Anglo_saxon Continental Southern Eastern Baltic 1)Probability of Returning Home danimark -0.25** austria -0.21*** france 0.26*** luxemb -0.36*** italy -0.29*** spain -0.06 portugal -0.40*** czeckrep -0.37*** poland -0.68*** lettonia -0.16*** lituania -0.13** 2)Probability of not being married danimark -0.19 austria -0.02 france -0.06 luxemb -0.05 italy -0.41*** spain -0.34*** portugal -0.10* czeckrep -0.19*** poland 0.45*** lettonia -0.11** lituania -0.06 3)Probability of being employed danimark 0.08 austria -0.01 france -0.19*** luxemb -0.07 italy -1.15*** spain -1.12*** portugal -0.56*** czeckrep -0.46*** poland -0.53*** lettonia 0.09*** lituania 0.23***

92 Gökşen, Filiztekin, Öker Kuz,, Mazzotta & Parisi

8. Recent titles in this series

Available at: http://www.style-research.eu/publications/working-papers

WP3 POLICY PERFORMANCE

Key Indicators and Drivers of Youth Unemployment Hadjivassiliou, Kirchner Sala and Speckesser (2015) STYLE Working Paper WP3.1 Indicators and Drivers of Youth Unemployment

The Effectiveness of Policies to combat Youth Unemployment Gonzalez Carreras, Kirchner Sala and Speckesser (2015) STYLE Working Paper WP3.2 Policies to combat Youth Unemployment

Policy Performance and Evaluation: Qualitative Country Case Studies Eichhorst, Hadjivassiliou and Wozny (eds.)(2015) STYLE Working Paper WP3.3 Policy Performance and Evaluation – Synthesis Report

Country Reports

Policy Performance and Evaluation: Germany Eichhorst, Wozny and Cox (2015) STYLE Working Paper WP3.3 Performance Germany

Policy Performance and Evaluation: Estonia Eamets and Humal (2015) STYLE Working Paper WP3.3 Performance Estonia

Policy Performance and Evaluation: Spain González-Menendez, Mato, Gutierrez, Guillen, Cueto and Tejero (2015) STYLE Working Paper WP3.3 Performance Spain

Policy Performance and Evaluation: Netherlands Bekker, van de Meer, Muffels and Wilthagen (2015) STYLE Working Paper WP3.3 Performance Netherlands

Policy Performance and Evaluation: Poland Ślezak and Szopa (2015) STYLE Working Paper WP3.3 Performance Poland

Policy Performance and Evaluation: Sweden Wadensjö (2015) STYLE Working Paper WP3.3 Performance Sweden D 8.3 - Leaving and returning to the parental home during the economic crisis 93

Policy Performance and Evaluation: Turkey Gökşen, Yükseker, Kuz and Öker (2015) STYLE Working Paper WP3.3 Performance Turkey

Policy Performance and Evaluation: United Kingdom Hadjivassiliou, Tassinari, Speckesser, Swift and Bertram (2015) STYLE Working Paper WP3.3 Performance UK

WP4 POLICY TRANSFER

Barriers to and triggers of innovation and knowledge transfer Petmesidou and González-Menéndez (eds.)(2015) STYLE Working Paper WP4.1 Barriers to and triggers of policy innovation and knowledge transfer

Country Reports

Barriers to and triggers for innovation and knowledge transfer in Belgium Martellucci and Marconi (2015) STYLE-D4.1 Country Report Belgium

Barriers to and triggers of policy innovation and knowledge transfer in Denmark Carstensen and Ibsen (2015) STYLE-D4.1 Country Report Denmark

Barriers to and triggers for innovation and knowledge transfer in Spain González-Menéndez, Guillén, Cueto, Gutiérrez, Mato and Tejero (2015) STYLE-D4.1 Country Report Spain

Barriers to and triggers for innovation and knowledge transfer in France Smith, Toraldo and Pasquier (2015) STYLE-D4.1 Country Report France

Barriers to and triggers for innovation and knowledge transfer in Greece Petmesidou and Polyzoidis (2015) STYLE-D4.1 Country Report Greece

Barriers to and triggers for innovation and knowledge transfer in the Netherlands Bekker, van der Meer and Muffels (2015) STYLE-D4.1 Country Report Netherlands Barriers to and triggers of policy innovation and knowledge transfer in Slovakia Veselkova (2015) STYLE-D4.1 Country Report Slovakia

94 Gökşen, Filiztekin, Öker Kuz,, Mazzotta & Parisi

Barriers to and Triggers for Innovation and Knowledge Transfer in Turkey Gökşen, Yükseker, Kuz and Öker (2015) STYLE-D4.1 Country Report Turkey

Barriers to and Triggers for Innovation and Knowledge Transfer in the UK Hadjivassiliou, Tassinari and Swift (2015) STYLE-D4.1 Country Report UK

WP5 MISMATCH: SKILLS AND EDUCATION

A Comparative Time Series Analysis of Overeducation in Europe: Is there a common policy approach? McGuinness, Bergin and Whelan (2015) STYLE Working Paper WP5.1 Overeducation in Europe

Are student workers crowding out low-skilled youth? Beblavý, Fabo, Mýtna Kureková, and Žilinčíková (2015) STYLE Working Paper WP5.3 Are student workers crowding out the low skilled youth

Recruitment Methods & Educational Provision effects on Graduate Over-Education and Over- Skilling McGuinness, Bergin and Whelan (2015) STYLE Working Paper WP 5.4 Report Recruitment Methods

WP6 MISMATCH: MIGRATION Re-emerging migration patterns: structures and policy lessons. Akgüç and Beblavý (2015) STYLE Working Papers, WP6.3

WP7 SELF-EMPLOYMENT AND BUSINESS START UPS

Business Start-Ups and Youth Self-Employment: A Policy Literature Overview Sheehan and McNamara (2015) STYLE Working Paper D7.1 Business Start-Ups Youth Self-Employment Policy Literature Review

Country Reports

Business Start-Ups and Youth Self-Employment in Germany Ortlieb and Weiss (2015) STYLE Working Paper WP7.1 Germany D 8.3 - Leaving and returning to the parental home during the economic crisis 95

Business Start-Ups and Youth Self-Employment in Estonia Masso and Paes (2015) STYLE Working Paper WP7.1 Estonia

Business Start-Ups and Youth Self-Employment in Spain González Menéndez and Cueto (2015) STYLE Working Paper WP7.1 Spain

Business Start-Ups and Youth Self-Employment in Ireland Sheehan and McNamara (2015) STYLE Working Paper WP7.1 Ireland

Business Start-Ups and Youth Self-Employment in Poland Pocztowski, Buchelt and Pauli (2015) STYLE Working Paper WP7.1 Poland

Business Start-Ups and Youth Self-Employment in the UK Hinks, Fohrbeck and Meager (2015) STYLE Working Paper WP7.1 UK

Mapping patterns of self-employment Masso et al. (2015) STYLE Working Papers, WP7.2

WP8 FAMILY DRIVERS

Work-poor and work-rich families: Influence on youth labour market outcomes Berloffa, Filandri, Matteazzi, Nazio, O’Reilly, Villa and Zuccotti (2015) STYLE Working Paper WP8.1 Work-poor and work-rich families

Leaving and returning to the parental home during the economic crisis (forthcoming) STYLE Working Papers, WP8.3

WP9 ATTITUDES AND VALUES

Value system shared by young generations towards work and family Hajdu and Sik (2015) STYLE Working Paper WP9.1 Searching for gaps: are work values of the younger generations changing?

96 Gökşen, Filiztekin, Öker Kuz,, Mazzotta & Parisi

The impact of youth unemployment on social capital (forthcoming) (2015) STYLE Working Paper WP9.2

Aspirations of vulnerable young people in foster care Hart, Stubbs, Plexousakis, Georgiadi and Kourkoutas (2015) STYLE Working Paper WP9.3 Aspirations of vulnerable youth in foster care

WP 10 FLEXICURITY

Mapping Flexicurity Performance in the Face of the Crisis: Key Indicators and Drivers of Youth Unemployment Eamets, Beblavý, Bheemaiah, Finn, Humal, Leschke, Maselli and Smith (2015) STYLE Working Paper WP10.1 Mapping flexibility and security performance in the face of the crisis

Youth School-To-Work Transitions: from Entry Jobs to Career Employment Berloffa, Matteazzi, Mazzolini, Sandor and Villa (2015) STYLE Working Paper WP10.2 Youth School-To-Work Transitions: from Entry Jobs to Career Employment

Flexicurity and Subjective Insecurity (forthcoming) STYLE Working Papers, WP10.3

D 8.3 - Leaving and returning to the parental home during the economic crisis 97

9. Research Partners

1. University of Brighton – BBS CROME – United Kingdom 2. Institute for Employment Studies – United Kingdom 3. Institute for the Study of Labor – Germany 4. Centre for European Policy Studies – Belgium 5. TARKI Social Research Institute – Hungary 6. University of Trento – Italy 7. National University of Ireland Galway – Republic of Ireland 8. Democritus University of Thrace – Greece 9. University of Oxford – United Kingdom 10. Economic & Social Research Institute – Republic of Ireland 11. University of Salerno – Italy 12. University of Oviedo – Spain 13. University of Tartu – Estonia 14. Cracow University of Economics – Poland 15. Slovak Governance Institute – Slovakia 16. Metropolitan University Prague – Czech Republic 17. Grenoble School of Management – France 18. University of Tilburg – Netherlands 19. University of Graz – Austria 20. Copenhagen Business School – Denmark 21. Norwegian Social Research – Norway 22. Swedish Institute for Social Research – Sweden 23. Koç University Social Policy Centre – Turkey 24. University of Turin – Italy 25. EurActiv – Belgium http://www.style-research.eu/research-organisations

98 Gökşen, Filiztekin, Öker Kuz,, Mazzotta & Parisi

10. Advisory Groups

Consortium Advisory Network Business Europe www.businesseurope.eu

ETUI: European Trade Union Institute www.etui.org

European Youth Forum www.youthforum.org

European Foundation for the Improvement of Living and Working Conditions www.eurofound.europa.eu

ILO: International Labour Office www.ilo.org

OECD: Organisation for Economic Cooperation and Development www.oecd.org

OSE: Observatoire Sociale Européen www.ose.be

SOLIDAR: European network of NGOs working to advance social justice in Europe www.solidar.org

EurActiv www.euractiv.com

European Commission, DG Employment, Social Affairs & Inclusion http://ec.europa.eu/social/main.jsp?langId=en&catId=1036

Local Advisory Boards including employers, unions, policy makers and non-government organisations www.style-research.eu/project-advisors/local-advisory-boards/