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Youth Labor in TransitionInequalities, Mobility, and Policies in Europe$

Jacqueline O'Reilly, Janine Leschke, Renate Ortlieb, Martin Seeleib-Kaiser, and Paola Villa

Print publication date: 2018

Print ISBN-13: 9780190864798

Published to Oxford Scholarship Online: January 2019

DOI: 10.1093/oso/9780190864798.001.0001

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Stuck in the parental nest?

Stuck in the parental nest?

The effect of the economic crisis on young Europeans’ living arrangements

Chapter:
(p.334) 11 Stuck in the parental nest?
Source:
Youth Labor in Transition
Author(s):

Fernanda Mazzotta

Lavinia Parisi

Publisher:
Oxford University Press
DOI:10.1093/oso/9780190864798.003.0011

Abstract and Keywords

This chapter provides an extensive analysis of leaving and returning home by young people in 14 European countries. It analyzes the effect of the Great Recession, considering a period from 2005 to 2013 and controlling for two key determinants of living arrangements: employment and partnership. The main result is that the Great Recession has reduced the probability of leaving home and increased the probability of returning home, with differences across country groups. In particular, the probability of leaving home in Southern and Eastern European countries slightly declines during the period of analysis, whereas a sharp decrease is recorded in Continental countries at the beginning of the Great Recession. Southern European countries show an increase in home-returning throughout the entire period. Finally, both leaving and returning home seem more closely linked to partnership than to employment.

Keywords:   young people, leaving home, returning home, Great Recession, employment, partnership

11.1. Introduction

The Great Recession has had a profound impact on the process of young people’s transitions into adulthood. In particular, youth unemployment has increased disproportionately during the economic crisis, often leading young people to remain living with their parents. In fact, a number of studies have found that the share of young people living with their parents increased in many European countries in the early years of the crisis (Aassve, Cottini, and Vitali 2013). This chapter aims to expand on previous studies by providing a comparative analysis of home-leaving and home-returning by young people in 14 European countries during the period 2005–2013, which covers the years prior to, during, and after the recession of 2008–2009.1 Drawing on the European Union Statistics on Income and Living Conditions (EU-SILC), the chapter analyzes, first, the probability of youth (aged 18–34 years) leaving home and, second, the probability of youth (aged 20–36 years) returning home (i.e., “boomeranging”).

Exploiting the nature of EU-SILC’s longitudinal data, we consider the two phenomena—leaving home and returning home—in a dynamic way; in other words, the same individual is observed in two consecutive years by living arrangement (i.e., living in the parental home or independently in the first year and living independently or returning to the parental home in the subsequent (p.335) year). Living arrangements are strongly linked to employment and partnership.2 For this reason, we simultaneously model these three outcomes: living independently, finding employment, and being in a partnership (either married or cohabiting with the partner). Our main hypothesis regarding the effects of the Great Recession is that it reduces the probability of leaving home and increases the probability of returning home.

Three main research questions are investigated in this chapter: Is there a negative (positive) effect of the Great Recession on leaving (returning) home? Does the effect persist after considering the two main drivers of leaving and returning home (i.e., employment and partnership)? Are there significant differences across country groups?

The chapter is organized as follows. Section 11.2 provides a literature review, and Section 11.3 discusses the data used and the research design. In Section 11.4, we present descriptive statistics with regard to the effect of the crisis on leaving and returning home. We present our econometric model in Section 11.5 and discuss the empirical results in Section 11.6.

11.2. Literature review

The literature analyzing the decision of young adults to live with their parents (or, conversely, to leave the parental home) identifies four different sets of determinants: (1) age-related events (in particular, employment and partnership), (2) institutional and cultural factors (labor market regulations, welfare provisions, and social norms), (3) macrostructural factors (i.e., labor market characteristics, economic cycles, and housing market conditions), and (4) rational choice/exchange perspectives and preferences of children and parents.

The first group of determinants deals with young adults’ involvement in age-related events such as completing school, getting a job, starting a career, forming a family, or bearing children. Any of these events can lead to a decision to leave the parental home (Berngruber 2015). Among these events, partnership and employment are found to play a crucial role. Indeed, partnership is the most widely reported factor behind young adults’ decisions to leave home: Adult children in partnerships are more likely to leave the parental home than are their unpartnered peers (O’Higgins 2006; Hank 2007; Lei and South 2016). Getting a job is widely reported as another crucial event. For instance, Jacob and Kleinert (2008) find that, in Germany, nonemployment delays household formation and that the longer young adults have been unemployed, the less likely they are to leave home. Ayllón (2015) finds that employment and leaving home are two closely linked phenomena in Southern Europe but that the same is not true in Nordic countries. Mazzotta and Parisi (2015a) provide evidence that employed young people in Italy are more likely to leave the family of origin than are jobless youth, after controlling for parental background.

(p.336) The second group of determinants concerns institutional and cultural factors such as labor market regulations, welfare provisions (unemployment benefits and social assistance), and social norms (Billari 2004; Chiuri and Del Boca 2010; Settersten and Ray 2010). Labor market regulations (e.g., employment protection legislation or active labor market policies) and the generosity of the welfare state (i.e., social assistance and unemployment benefits)—both of which differ across countries—affect both the economic independence of young people and access to affordable accommodation. It has been shown that leaving the parental home is closely linked to the probability of young people receiving social assistance in the Nordic countries (Ayllón 2015). Social norms and culture differ significantly by country (as discussed later in this section) and by gender, albeit with some similarities across countries (related to gender roles in paid and unpaid work), which explains some differences between women and men in the decision to leave home. Women have a lower threshold for economic independence and are more likely to start a family during unemployment than are men (Ermisch 1999).

The third group of determinants concerns macrostructural factors, such as labor market characteristics (youth/prime-age unemployment rate and labor market segmentation), the economic cycle (i.e., economic growth and downturn), and housing conditions. In particular, the prices and the scarcity of rented housing are acknowledged in the literature as reasons that explain young people delaying leaving the parental home (Aassve et al. 2002; Iacovou 2002; Gökşen et al. 2016). Martins and Villanueva (2006) show that differences in mortgage markets across Europe can explain up to 20% of the cross-country variance in establishment of new households. Given that comparable data on housing market conditions are not available for a large number of EU countries or over time (2005–2013), we limit the focus of our empirical analysis to the other two key determinants of leaving and returning home, namely employment and partnership.

Finally, the fourth set of determinants considered in the literature concerns rational choice/exchange perspectives and preferences. Children are assumed to compare the costs and benefits of living with their parents with alternative living arrangements and to then choose the arrangement that offers the most highly valued net benefits. This could depend on the intra-household transfer of time and money, the personal income of young adult children, family income, or the health of parents (Ermisch 1999; Manacorda and Moretti 2006; Mazzotta and Parisi 2015b). Medgyesi and Nagy (this volume) study the extent to which young adults living with their parents contribute to household expenses. They find that the majority of young adults benefit from intra-household sharing of resources within the family. However, a small group of young adults living at home (mainly in Eastern European countries) tend to support their parents: Their contribution to the household budget is higher than that of their parents.

(p.337) Differences across countries in the share of young people living at home are explained in the literature mainly on the basis of both institutional/cultural factors and macrostructural determinants. Jones (1995) and Reher (1998) identify Southern and Eastern European cultural roots as reasons for late home-leaving and also for the strong synchronization between leaving and first marriage. Others emphasize the poor economic conditions (related to labor market conditions) for young adults in Southern countries (Saraceno 2015). Esping-Andersen (1999) focuses on the peculiarities of the Southern European welfare system, which is characterized by a lack of support for young unemployed people and by the crucial role played by the family in helping them. Reher argues that Northern countries, characterized by early home-leaving, have “weak” family ties and a sense of “social,” rather than familial, solidarity with elderly or frail members of society. In Nordic and Continental countries, parents with high incomes help their children leave home, whereas in Southern and some Eastern European countries, parents seem to use their high incomes to delay the departure of children (Iacovou 2010). The decision to co-reside could also depend on parents’ economic needs (Medgyesi and Nagy, this volume).

Studies on young people returning home are scarce and mainly focus on returning migrants (see Le Mare, Promphaking, and Rigg 2015; Masso et al., this volume).3

The four groups of determinants outlined previously for the analysis of young people’s reasons for leaving the parental home can also apply to their reasons for returning home. For instance, young people are more likely to return to the parental home at the end of formal education. Stone, Berrington, and Falkingham (2014) indicate the awarding of a final degree as a key turning point for students deciding to return home.4 Several other studies highlight the importance of a change in economic activity status (i.e., becoming unemployed) in fostering a potential return to the parental home. Separation and divorce increase the likelihood of returning to live with one’s parents (DaVanzo and Goldscheider 1990; Mitchell, Wister, and Gee 2000); however, the association between partnership dissolution and returning home is moderated by gender and parenthood (Stone et al. 2014). Overall, men are more likely than women to return to the parental home following the dissolution of marriage or cohabitation (Ongaro, Mazzuco, and Meggiolaro 2009). Studies have also found that returning home is related to institutional factors, such as welfare provisions (Berrington, Stone, and Falkingham 2013) and cultural norms (Boyd and Pryor 1989). Returns to the parental home at the end of formal education are likely to increase as a result of rising levels of student debt and a weaker graduate jobs market (Andrew 2010; Clapham et al. 2012); economic status and employment conditions can also increase the likelihood of returning home (Goldscheider and Goldscheider 1999). Finally, with regard to the economic crisis, together with later home-leaving, studies have found evidence of a “boomerang” phenomenon in France, Spain, and the United Kingdom, with increasing numbers of young people returning (p.338) to their parents’ home after having lived independently (Plantenga, Remery, and Samek Lodovici 2013).

11.3. Research design

In order to examine the phenomena of both leaving and returning home in 14 EU countries (AT, BE, CY, CZ, EE, ES, FR, IT, LT, LU, LV, PL, PT, and SI),5 we used EU-SILC longitudinal data. We considered eight panels covering the period from 2005 to 2013.6 For each panel, we considered periods of 2 years each (e.g., for the panel from 2005 to 2008, there are three 2-year periods: 2005–2006, 2006–2007, and 2007–2008), and for each 2-year period we considered the change (or not) in living arrangements between the two points in time (i.e., the beginning, time t, and the end, time t + 1). Thus, the first dependent variable is the observed transition of leaving the parental home (L). L describes whether young people who were living in the family of origin at time t are still living with their parents at t + 1 or have left.7 The second dependent variable is the observed transition of returning to the parental 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 or have returned to live with at least one of them.8

We constructed two samples—one for those leaving and one for those returning. The leaving-home sample consists of young people aged 18–34 years the first time they are observed. The returning-home sample consists of young people aged 20–36 years the first time they are observed. We excluded students from both samples so as to make the results comparable across countries.9 In order to improve the interpretation of the results, we grouped countries in four classes: Continental, Southern, Eastern, and Baltic countries. Both the descriptive and the econometric analyses are carried out separately for the four groups of countries. The small sample size at the single-country level (above all for the sample of returning home) makes it necessary to group countries.

Given the great heterogeneity of European labor market institutions and welfare systems, to group countries we follow the classification developed by the European Commission (2006, 2007). Using a principal component analysis, the European Commission groups 18 European countries according to three dimensions of labor market/flexicurity systems: income/employment security, numerical external flexibility/employability, and tax distortions.

The Continental group of countries (AT, BE, FR, and LU) is characterized by (1) intermediate to high security, (2) intermediate to low flexibility, and (3) intermediate to high taxation. In this group, social benefits are targeted at individuals who belong to specific categories, such as a specific type of family or a specific type of worker. In the Southern group of countries (CY, ES, IT, and PT), welfare coverage tends to be “residual” and largely left to the family. It tends to be characterized by (1) relatively low security, (2) low flexibility, and (3) no clear (p.339) pattern on taxation. The Eastern group (CZ, PL, and SI) is characterized by (1) insecurity, (2) intermediate to high flexibility, and (3) intermediate to high taxation. Finally, we distinguish the Baltic group of countries (EE, LT, and LV) from the Eastern European group because the Baltic countries are more similar to the Continental countries with regard to family formation (Eurofound 2014) and implemented flexibility/protection patterns (Anca 2012).

11.4. Descriptive statistics

In this section, we provide descriptive statistics on key variables, focusing on the role of the economic crisis across the four groups of countries. Table 11.1 shows the share of young people (aged 18–34 years) leaving home during the period under consideration (2005–2013). The lowest percentage of youth leaving the parental home is found in the Eastern, Baltic, and Southern European countries (on average, 3.0%, 4.5%, and 5.9%, respectively, over the entire period). The highest percentage is found in the Continental countries (13.6%, on average, over the entire period). Except for the Eastern countries, where the exit rate is very low for all the years considered, descriptive statistics show that the other three groups of countries register a decrease in the share of young people leaving home between 2005 and 2013.10 However, whereas for the Continental countries we detect two decreases—one just after the onset of the crisis (2009–2010), from (p.340) 15.3% to 10.8%, and another (in 2011) from 14.3% to 12.5%—the effect in the Southern countries is postponed to 2011 (with a decline from 7.3% to 4.8%).

Table 11.1 Observed rate of home-leaving at time t + 1 for young people (aged 18–34 years) living with their parents at time t (students are excluded) by group of countries, 2005–2013 (%)

Year

Continental

Southern

Eastern

Baltic

Total

2005–2006

15.5

6.3

3.3

6.9

9.4

2006–2007

15.6

5.8

3.3

5.5

8.8

2007–2008

12.8

7.0

3.1

3.7

8.3

2008–2009

15.3

6.2

3.3

3.4

9.1

2009–2010

10.8

5.0

2.7

4.9

6.7

2010–2011

14.3

7.3

2.7

4.5

9.2

2011–2012

12.5

4.8

3.4

3.4

7.4

2012–2013

9.8

4.1

2.2

3.9

5.5

Total

13.6

5.9

3.0

4.5

8.2

Sample size

2,890

4,492

1,640

1,021

10,043

Notes: Percentages are calculated each year as the number of young people who have left home at time t + 1 divided by the total number of young people (excluding students) living in the parental home at time t. Continental countries: Austria, Belgium, France, and Luxembourg; Southern countries: Cyprus, Italy, Portugal, and Spain; Eastern countries: Czech Republic, Poland, and Slovenia; Baltic countries: Estonia, Latvia, and Lithuania.

With regard to returning to the parental home (Table 11.2), all four groups of countries show very low rates (less than 1% on average). However, we do find differences during the economic crisis. Whereas in Continental countries we observe an increase from 0.4% to 1.2% at the beginning of the recession (2008–2009), in Southern countries the increase does not occur until 2011–2012. Overall, the rate of home-returning decreases for all groups of countries in 2012–2013 (see Table 11.2).11

Table 11.2 Observed rate of home-returning at time t + 1 for young people (aged 20–36 years) living away from parents at time t (students are excluded) by group of countries, 2005–2013 (%)

Year

Continental

Southern

Eastern

Baltic

Total

2005–2006

0.5

0.9

1.1

0.6

0.6

2006–2007

0.6

0.7

0.4

0.6

0.6

2007–2008

0.6

1.0

0.5

0.6

0.7

2008–2009

0.4

1.1

0.4

1.4

0.6

2009–2010

1.2

1.2

0.5

1.4

1.1

2010–2011

0.5

1.0

0.7

1.0

0.6

2011–2012

0.8

1.4

0.4

0.4

0.9

2012–2013

0.3

1.1

0.3

0.4

0.5

Total

0.6

1.0

0.5

0.8

0.7

Sample size

543

803

378

262

1,986

Notes: Percentages are calculated each year as the number of young people who returned home at time t + 1 divided by the total number of young people (excluding students) living independently at time t. Continental countries: Austria, Belgium, France, and Luxembourg; Southern countries: Cyprus, Italy, Portugal, and Spain; Eastern countries: Czech Republic, Poland, and Slovenia; Baltic countries: Estonia, Latvia, and Lithuania.

When studying the effect of the economic crisis on leaving and returning home, we should consider, separately, the probability of finding a job and the decision to form a family. Figure 11.1a presents the percentage of employed among young people who are still living with their parents at time t + 1, compared to those who have left home at time t + 1. Figure 11.1b presents the percentage of individuals in partnerships among young people who are still living with their parents at time t + 1, compared to those who have left home to live independently.

Stuck in the parental nest?The effect of the economic crisis on young Europeans’ living arrangementsStuck in the parental nest?The effect of the economic crisis on young Europeans’ living arrangements

Figure 11.1 (a) Share of young people employed at time t + 1 by group of countries, distinguishing between those who stayed at home (stayers) and those who left home (leavers) in the period under consideration (confidence interval at 95% level). (b) Share of young people in a partnership at time t + 1 by group of countries, distinguishing between those who stayed at home (stayers) and those who left home (leavers) in the period under consideration (confidence interval at 95% level).

Young people who have left home are more likely to be employed than those who are still living with their parents (83% vs. 70%, on average),12 and this difference is higher for Continental countries, suggesting that young people decide to leave the parental home once they have found a job (see Figure 11.1a). The same pattern is found for partnerships:13 Young people who have left home are more likely to be in a partnership than those who are still living with their parents. On average, 55% of those leaving home are in a partnership at t + 1 (for Eastern (p.341) (p.342) countries, the percentage is particularly high at approximately 70%), compared to approximately 4% for those who stayed at home (17% and 12%, respectively, for the Eastern and Baltic countries; see Figure 11.1b). The Baltic and Eastern European countries have particularly high shares of people in a partnership and living with their parents. In general, for all groups of countries, partnership seems to be more important than employment in explaining home-leaving (there are statistically significant differences in the percentages of partnership among leavers and stayers).

As a result of the depth and duration of the economic crisis, young people are less likely to be in employment in Continental, Southern, and Baltic countries (see Figure 11.1a).14 Whereas the differences are statistically significant for those who remained in the parental home, there are no statistically significant differences for those who left. Our results are in line with those found by the European Commission (2014, 32, Table 15) and are consistent with the hypothesis that during the economic crisis, young people have a greater need to find a job as a precondition for leaving home. Finally, we do not find statistically significant differences for the share of young people in a partnership across time periods among stayers, whereas the changes found for leavers do not follow a precise trend (see Figure 11.1b). In summary, young people who leave home are likely to be working or in a partnership, especially in the Southern countries.

In Continental countries, being employed is the main factor associated with leaving the parental home, given that in these countries young people also leave when they are single.15 Thus, we find different cultural patterns (in accordance with the literature), with (single) young people in Continental countries becoming independent (much earlier), whereas in Southern and Eastern countries they mainly leave home in order to start a family (and/or a relationship). Moreover, in Continental countries, employment status is more important than partnership status in explaining the decision to leave home, whereas the opposite is true for the other country groups. This finding does not change as a result of the economic crisis; in fact, in Southern countries, the crisis has worsened the employment conditions of young individuals who remain in the parental home.

Figures 11.2a and 11.2b show the patterns for employment and partnership, distinguishing between those who had not returned home (labeled as alone or living independently) and those who had returned home at time t + 1. Figure 11.2a shows that even though individuals who return home are on average more likely not to be employed than those who continue to live independently,16 we find the most important differences across time periods. There is a very low proportion of not employed at the beginning of the period in the sample of youth living independently, with no differences in the Southern and Baltic countries between not employed as a share of those who returned home and not employed as a share of those who did not return home. For the Southern countries, we observe an increase in the share of people who are not employed (p.343) (p.344) across all the periods, with sharper differences among those who return home (see Figure 11.2a). Moreover, there is a large proportion of people not employed in the very last period for all the countries, above all for those who return home in the Eastern, Baltic, and Southern countries (approximately 26% for Eastern and Baltic countries and approximately 60% for Southern countries). For Continental countries, the percentages of not employed among the young people living independently (defined as stayers in Figure 11.2a) are very low and stable across all periods observed, whereas the shares of not employed among those who return home (defined as returned in Figure 11.2a) show a decrease in 2010 (stable across the years for stayers, decreasing in 2010 for returners).

Stuck in the parental nest?The effect of the economic crisis on young Europeans’ living arrangementsStuck in the parental nest?The effect of the economic crisis on young Europeans’ living arrangements

Figure 11.2 (a) Share of young people not employed at time t + 1 by group of countries, distinguishing between those who lived independently (stayers) and those who returned home (returned) in the period under consideration (confidence interval at 95% level). (b) Share of young people not in a partnership at time t + 1 by group of countries, distinguishing between those who lived independently (stayers) and those who returned home (returned) in the period under consideration (confidence interval at 95% level).

The effect of partnership dissolution is statistically significant for almost all countries (Eastern Europe being the exception): Young people without a partner return home more often than do young people with a partner, and the proportion is quite high (approximately 90% in some countries). This pattern is less strong for Eastern countries, where (in line with Iacovou 2010) young people are often found living with a partner in the same house as their parents. In short, partnership status does not appear to influence the decision to return home.

The difference in the percentage of not employed young people among those who return home and those who do not return home is lower than the difference in the percentage of returners and non-returners who are not in a partnership. With regard to leaving home, it seems that partnership is more important than not having a job in predicting the probability of returning home. Across subperiods, there are neither clear nor significant patterns in the Continental or Baltic countries, whereas in the Southern countries the percentage of partnership breakups increases among those who return home, and the opposite is true in Eastern countries (these effects are statistically significant).

11.5. Econometric analysis: Methodology

The aim of the econometric analysis is to disentangle the effect of the economic crisis on the probability of leaving (returning) home after controlling for employment and the partnership status of young people.17 The method used to estimate the two probabilities is a trivariate probit model. This is a simulation method for maximum likelihood estimation of a multivariate probit regression model. The model controls for unobservable factors that influence the probability of leaving (returning) home, of being employed (not employed), and of being in a couple (not in a couple). It is necessary to consider the mutual correlation between the three outcomes in order to avoid biased results.18 Moreover, this is a type of first-order Markov approach. It takes into account pairs of observations in two consecutive years, namely t and t + 1 for each individual. In year t, the young person lives with his or her parents (or independently), and in year t + 1 he or she has (p.345) left (returned) home. This strategy improves the existing models in the literature by controlling for feedback effects; unobserved heterogeneity; nonrandom selection of the sample; and unobserved cross-process correlations between living arrangement, employment, and partnership.

The model for leaving home considers three dependent variables: the probability of leaving home (Lt+1), the probability of being employed (Et+1), and the probability of having a partner (Pt+1). The model can be identified by functional form, but we also include the following variables (in only one equation at a time): the household crowding index at time t in equation Lt+1, the employment status at time t in equation Et+1, and whether or not the person is living not just with one but with both parents at time t in equation Pt+1. To examine the effect of employment and partnership on the probability of leaving home, we also include, in equation Lt+1, the probability of being employed and of being in a relationship at time t + 1. Other control variables (i.e., gender—male or not; age and age squared; education—two dummies for secondary education and tertiary education, with compulsory education as the reference category; and general health status—good health or not) have been chosen in accordance with the literature. We further include in equation Lt+1 parents’ income at time t (expressed as the logarithm of the sum of the income of both parents) and personal income of the young person at time t (expressed as the logarithm of his or her personal income).

The model for returning home simultaneously estimates the probability of returning home (Rt+1), the probability of not being in partnership (UPt+1), and the probability of not being employed (NEt+1). We include the following variables to identify the model: the crowding index and whether the person has children at time t + 1 in equation Rt+1, whether the person has children and whether the person is not employed at t + 1 in equation UPt+1, and whether the person is not employed at time t in equation NEt+1. We also include, in Rt+1, the probability of not being employed at t + 1 and the probability of not being in a relationship at t + 1. Other control variables (i.e., gender, age and age squared, education, general health status, and personal income at time t + 1) are included as described for the home-leaving model.

The three outcomes (for the models for both leaving and returning home) can be correlated independently. The correlations relate to unobservable traits such as ability, intelligence, personality traits, ambition, quality of the relationship with parents, family background, and so forth. We estimate the correlation among the three error terms as follows: whether positive, unobservable individual factors determining the outcome of primary interest (i.e., leaving or returning) are also positively associated with the other two outcomes (being employed and having a partner for leaving, and not being employed and not being in a partnership for returning).

We claim that only by acknowledging correlation effects between the three processes can we properly deal with endogeneity problems that may arise when (p.346) studying life transitions that possibly take place in a sequential manner and/or simultaneously (Siegers, de Jong-Gierveld, and van Imhoff 1991; Mulder and Wagner 1993; Billari, Philipov, and Baizán 2001).

Together with the estimated coefficients (provided in Tables 11.3 and 11.4), we also calculate predicted probabilities (Figures 11.3 and 11.4) and their confidence intervals so as to analyze whether there is evidence of a time trend or not across groups of countries.

Table 11.3 Trivariate probit model for probability of leaving home by group of countries

Probability of leaving home

Continental

Southern

Eastern

Baltic

Log parents’ income at t

–0.027**

–0.017***

0.008

–0.028***

Log personal income at t

0.065***

0.027***

0.046***

0.040***

2005–2006

0.170**

0.109**

0.061

0.111

2006–2007

0.150**

0.055

0.09

0.030

2007–2008

0.019

0.116***

0.057

–0.151**

2008–2009

0.220***

0.122***

0.119*

–0.249***

2010–2011

0.152**

0.245***

–0.059

–0.063

2011–2012

0.142*

0.000

0.081

–0.186**

2012–2013

–0.100

–0.085

–0.111

–0.131

Male

–0.080*

–0.036

–0.094**

–0.174***

Age

0.093

0.117***

–0.027

0.208***

Age squared

–0.003**

–0.002***

0.000

–0.004***

Tertiary education

0.789***

0.175***

–0.05

–0.077

Secondary education

0.394***

0.059**

–0.119**

–0.002

Good health at t

0.120*

0.089**

–0.041

–0.179***

House crowded at t

0.217***

0.231***

0.031

0.095*

In a partnership at t + 1

2.169***

1.644***

1.458***

0.975***

Employed at t + 1

0.215***

0.199***

–0.062

0.000

Country dummies

Yes

Yes

Yes

Yes

Constant

–4.015***

–4.413***

–1.525**

–4.178***

No. of observations

27,386

75,774

44,544

21,445

Log likelihood

–2.74E + 08

–2.51E + 08

–1.30E + 08

–1.40E + 07

Notes: Continental countries: Austria, Belgium, France, and Luxembourg; Southern countries: Cyprus, Italy, Portugal, and Spain; Eastern countries: Czech Republic, Poland, and Slovenia; Baltic countries: Estonia, Latvia, and Lithuania. The likelihood ratio test for the hypothesis ρ‎21 = ρ‎31 = ρ‎32 = 0 is statistically different from zero at the 1% level. Estimates do not consider students. Estimates are clustered at the individual level.

(*) p < .10.

(**) p < .05.

(***) p < .01.

Table 11.4 Trivariate probit model for probability of returning home by group of countries

Probability of returning home

Continental

Southern

Eastern

Baltic

Log personal income at t + 1

0.013

0.000

0.008

–0.008

2005–2006

–0.408***

–0.012

0.256***

–0.241**

2006–2007

–0.335***

–0.145*

–0.059

–0.235**

2007–2008

–0.372***

0.006

0.001

–0.244*

2008–2009

–0.485***

0.005

–0.05

0.082

2010–2011

–0.437***

–0.081

0.166

–0.097

2011–2012

–0.138

0.058

–0.068

–0.371***

2012–2013

–0.594***

–0.027

–0.151

–0.396***

Male

0.078

0.055

–0.041

0.218***

Age

–0.177**

–0.247***

–0.151**

–0.162*

Age squared

0.002

0.003***

0.003**

0.003

Tertiary education

–0.482***

–0.119**

–0.530***

–0.300***

Secondary education

–0.165**

–0.05

–0.272***

–0.002

Is a parent

–0.196**

–0.351***

–0.167**

–0.173**

Good health at t

–0.049

–0.072

–0.047

0.111

House crowded at t

–0.092***

–0.237***

–0.155***

–0.119**

Not in a partnership at t + 1

1.021***

1.138***

0.506***

0.796***

Not employed at t + 1

0.238***

0.222***

0.105

0.189**

Country dummies

Yes

Yes

Yes

Yes

Constant

0.835

2.869***

0.585

0.738

No. of observations

97,157

74,607

63,122

28,931

Log likelihood

–7.91E + 08

–2.92E + 08

–1.14E + 08

–2.17E + 07

Notes: See notes to Table 11.3.

(p.347) 11.6. Results and discussion

This section presents and discusses estimates for both models regarding the probability of leaving and returning home. The models are estimated separately for the four groups of countries. We present estimates that include country dummies (within each country group—not reported) and year dummies. Table 11.3 shows estimates for the probability of leaving home.19 To disentangle the effect of the economic crisis, we include year dummies, excluding the period 2009–2010, and we calculate predicted probabilities for each year plotted in Figure 11.3.

Stuck in the parental nest?The effect of the economic crisis on young Europeans’ living arrangements

Figure 11.3 Marginal predicted probabilities of leaving home by group of countries and across time periods with 95% confidence interval bands.

The correlation between the error terms (ρ‎) is significantly different from zero.20 Thus, the three equations are strongly related: The same unobservable factors positively affect the probability of leaving, of being employed, and of (p.348) being in a relationship. This indicates that a trivariate probit technique is appropriate in this context.

Looking at the coefficients of the time dummies, we can see that young people are more likely to leave home before and after 2009–2010; in other words, there is a crisis effect, given that the probability of leaving is lower just after the onset of the Great Recession compared to the other periods (i.e., the coefficients of all time dummies are positive compared to 2009–2010; see Table 11.3). And the effect also holds after including employment and partnership. Figure 11.3 plots the marginal predicted probabilities of leaving home. The results confirm the descriptive statistics, showing that in Southern, Baltic, and Eastern European countries, the probability of leaving home is lower compared to that in Continental countries (approximately 3%–6% and 12%–15%, respectively). There are no striking differences over time with the exception of the Continental countries, where we observe a decrease in the probability of leaving (in particular, there are two declines: one in 2009–2010 and another in 2012–2013).

Thus, the probability of leaving home in Southern and Eastern European countries (the lowest in comparative terms) turns out to be rather stable in the period considered (2005–2013), whereas a decrease is recorded in Continental countries. The crisis has therefore reduced the probability of leaving home in those countries that were both less affected by the economic downturn and (p.349) where young people were used to living independently at a relatively young age. In the Southern and Eastern countries, by contrast, where young people were hit hardest by the economic crisis, we do not observe the sharp decrease in the probability of home-leaving one might have expected (Aassve et al. 2013). This may be due to the fact that these countries already recorded the highest percentage of young adults living in the parental home at the beginning of the observed period (i.e., before the Great Recession). This implies that the economic crisis hit a large share of those young individuals (aged 18–34 years) who were already somehow “protected” by their family of origin (i.e., living with their parents). Therefore, the change observed in the probability of youth leaving home during the Great Recession is smaller in these two groups of countries (Southern and Eastern) than in the others. Moreover, in these countries, cultural factors (which tend to be relatively stable over time) may play a stronger role than economic conditions (which fluctuate with the economic cycle) in explaining living arrangements.

As already seen in the descriptive statistics (see Section 11.4), leaving home is strongly connected to partnership, and indeed it seems to be more closely linked to partnership than to employment: In all groups of countries considered, the coefficient of partnership is positive and strongly significant compared to that of employment, which is smaller and not significant in the Eastern and Baltic countries. Partnership thus has a strong effect on leaving home: The more young people enter a partnership (including marriage), the more likely they are to leave home. Employment is a good predictor of leaving home in Continental and Southern countries: Being employed positively affects the probability of leaving. However, employment has an indirect effect through partnership in those countries (Baltic and Eastern) where we do not find a direct effect.

With regard to demographic variables, the results are in line with the literature. Women have a lower income threshold for independence: They leave the parental home more often than men in all countries except the Southern countries. The difference observed between men and women may be due to the fact that the impact of unemployment differs by gender: Women may be more inclined to start a family, whereas men try to find a more stable job first (Plantenga et al. 2013); also, women enter partnerships at a lower age (Eurostat 2009).

High parental income (in Southern, Continental, and Baltic countries) is associated with a lower probability of leaving home. Higher personal education and good health unambiguously increase the probability of leaving home in Continental and Southern countries. A downward correlation exists between age and leaving, such that the most likely to leave are individuals aged approximately 29 and 26 years, respectively, for the Baltic and Southern countries.

Table 11.4 presents estimates for a trivariate probit model for the probability of returning home, and Figure 11.4 plots the marginal predicted probabilities across time periods. Looking at the dummies that explain the difference between time periods, we find that there is a time effect only in the Continental and Baltic countries, where the probability of returning home is always lower compared (p.350) to 2009. In contrast with Stone, Berrington, and Falkingham’s results (2012), the period is still statistically significant when we include what they call turning points (e.g., separation or unemployment). This result implies that the economic crisis has a direct effect on returning home, given that it produces uncertainty about the future. However, when we plot the predicted marginal probability of returning home (see Figure 11.4), we observe that, also in Southern countries, the probability of returning home constantly increases for all the periods considered. This increase—observed already in 2007 (before the crisis) in the Southern countries—may be due to structural or cultural factors, but it has been exacerbated by the Great Recession.

Stuck in the parental nest?The effect of the economic crisis on young Europeans’ living arrangements

Figure 11.4 Predicted probabilities of returning home by group of countries and across time periods with 95% confidence interval bands.

Continental and Eastern countries have the lowest percentage of individuals returning home, with a jump just after the onset of the crisis (2009–2010), whereas in Eastern countries the effect does not appear until 2011 (but the difference is not significant). In Baltic countries, we record an increase that lasts longer—from 2008–2009 until 2010–2011. The predicted probability of returning to the parental home for countries in these three groups becomes stable at approximately 0.5%. This low rate (especially in the Continental countries) has been related to relatively generous welfare-state benefits and to cultural factors, given that both young people and their parents greatly value independence compared to their Southern counterparts (Iacovou 2010). For the Eastern and Baltic countries, this (p.351) result may depend on emigration—that is, on the necessity for young people to leave their country of origin.

Thus, the result that merits highlighting is that Southern European countries show an increase in boomeranging throughout the entire period considered (beginning in 2005), which may indicate a long-term as opposed to a cyclical trend. This finding differs from that for the Continental countries, where the increase starts just after the onset of the crisis (2009–2010), whereas in the Baltic countries we record an increase that lasts longer—from 2008–2009 until 2010–2011.

Again, we confirm the hypothesis already observed for leaving: Just as partnership had a strong effect on leaving home, being single has a very strong effect on returning home. In fact, union dissolution is a key determinant of returning home. Similarly, not being employed increases the probability of returning home in the Continental, Southern, and Baltic countries (the result also holds if we exclude inactives).

With regard to the other control variables, the most important result is that being alone increases the likelihood of returning to the parental home. In fact, young parents (both mothers and fathers) are less likely to return to the parental home than are individuals without children, just as individuals living in crowded families (usually with more than one child or other relatives) are less likely to return to living with their parents. Higher education decreases the probability of returning home, whereas health does not have any effect. Men are more likely to return home only in the Baltic countries.

11.7. Conclusions

This chapter has examined the influence of the Great Recession on the probability of leaving or returning to the parental home in Europe. The transition into adulthood in the form of leaving the parental home to establish an autonomous household is highly variable across European countries. Our findings reveal that Southern, Baltic, and Eastern European countries have lower leaving rates compared to Continental countries and that the crisis has not exacerbated this difference. In the former groups of countries, leaving the family of origin is not as highly valued as in Continental countries. Also, before the Great Recession, a high share of young adults were living in the family of origin in Southern, Baltic, and Eastern European countries. Thus, in these countries, cultural factors (which tend to be relatively stable over time) may play a stronger role than economic conditions in decisions to leave home. So when youth unemployment started to increase dramatically, many young adults in these countries were still living at home. In short, these youth were caught by the crisis and by its effects, but they were already under the protection of the family of origin.

What is striking are the changes observed in Continental countries. We observe a decrease in the probability of leaving home during the crisis (in (p.352) particular, the percentage of home-leavers rises and falls between 2009 and 2011). Continental countries are still characterized by higher levels of home-leaving compared to the other groups of countries, but the deterioration in labor market conditions for young people (i.e., difficult school-to-work transitions, youth unemployment, and economic hardship) increased the uncertainty of youth integration into secure employment, thus lowering the probability of leaving home in 2009.

All country groups experience an increase in the percentage of people returning home, with the exception of the Eastern countries. There are also noticeable differences across countries regarding timing: Southern European countries register an increase throughout the entire period; Continental countries show an increase in the very first period, after the onset of the crisis; and in the Baltic countries, the effect occurs earlier (in 2008–2009) and lasts longer. However, for the latter group of countries, the returning rate stabilizes at its lowest percentage toward the end of the period considered. Previous studies analyzing home-leaving have shown that in Southern European countries, late home-leaving contributes to a lower probability of returning (Iacovou and Parisi 2009). We find instead that returning home has increased in Southern countries and that this trend has been exacerbated by the Great Recession. In these countries, young people are less likely to be entitled to welfare benefits/assistance compared to their Continental counterparts; moreover, living with parents is more socially acceptable in Southern countries so that they are more likely to return home during a long-term economic downturn.

The results regarding the effect of the Great Recession also hold after controlling for partnership and employment. Partnership has a strong effect on the probability of both leaving and returning home. Young people in a partnership are more likely to leave, just as young people not (or no longer) in a partnership are more likely to return home. Employment is a good predictor of leaving home in Continental and Southern countries, but it has an indirect effect through partnership on leaving home in the Baltic and Eastern European countries. Similarly, losing one’s job increases the probability of returning home in Continental, Southern, and Baltic countries (the result also holds if we exclude inactives).

Our findings support the hypothesis that parental monetary resources play a crucial role in adulthood transitions. More than in previous recessions, the family plays a protective role, allowing their adult children to stay longer at home—that is, allowing young adults to overcome the economic difficulties faced during the Great Recession. This is noticeable especially in those countries (i.e., Continental countries, in our study) where economic independence is highly valued (both by parents and by children) and school-to-work transitions tend to be smoother. In these countries, it is relatively uncommon for older youth to live with their parents; therefore, staying at home longer might imply a higher psychological cost for both parents and adult children. Conversely, in those countries where cultural norms render it socially acceptable for older youth to live with their (p.353) parents, the psychological costs of postponing home-leaving because of the difficulties faced by young people in the labor market might be lower.

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Notes:

(1) Four Continental countries (AT, BE, FR, and LU), four Southern countries (CY, ES, IT, and PT), three Eastern countries (CZ, PL, and SI), and three Baltic countries (EE, LT, and LV).

(2) Individuals in a partnership are defined here as people who are either married or cohabiting.

(3) See, for instance, for Europe: Iacovou and Parisi (2009); and for the United States: DaVanzo and Goldscheider (1990), Goldscheider and Goldscheider (1999), Kaplan (2009), Dettling and Hsu (2014), and Lei and South (2016). For specific European countries, see Konietzka and Huinink (2003); Konietzka (2010); Stone, Berrington, and Falkingham (2012, 2014); and Berngruber (2015).

(4) The “turning point” is a key concept in life course theory, referring to an event, an experience, or a change in circumstances that significantly alters the individual’s subsequent life course trajectory (Stone et al. 2012).

(5) We selected 14 countries because of data restrictions. We excluded countries that are not included in all the waves from 2005 to 2013 (BG, CH, HR, IE, MT, RO, and TR). Greece had to be excluded because of missing information for some key variables. The Nordic countries (DK, FI, IS, NO, and SE) were excluded because of their sampling design strategy, which is not suitable for our dynamic approach. Another four countries (HU, NL, SK, and UK) were excluded because they do not collect net personal income for all the waves, and this is one of the key variables in the empirical analysis.

(6) For each panel, the same individuals were tracked for a maximum of 4 years.

(7) The nature of the data does not permit a distinction between those who have left home for the first time and those who had previously left, subsequently returned, and then left a second time.

(8) Because of the relatively short observation period, we do not know when exactly the young people in this sample left the parental home; we only know that they left home some time previously and have now returned.

(9) Students may bias the results because their attitude toward living arrangements is different across countries. In some countries, it is common for students to leave home and then return after getting a degree. In other countries, young people stay at home to complete their tertiary education, which increases the share of individuals living in the parental home only for education purposes. We are not interested here in leaving and/or returning for educational reasons.

(10) The differences between the two percentages at the beginning and at the end of the period (2005–2006 and 2012–2013) are statistically significant at the (p.354) 1% level—except for the Eastern countries, for which the statistical significance is at the 5% level.

(11) Between 2011 and 2012, the decrease is significant at the 1% level for both Continental and Southern countries, and for the entire sample.

(12) The mean differences are statistically significant in almost all the periods for the Continental and the Southern countries. There are significant differences only in some years in the Eastern and in the Baltic countries.

(13) The differences are all statistically significant at the 1% level.

(14) In the Eastern countries, the differences are not statistically significant for either leavers or stayers across the period observed.

(15) See Mazzotta and Parisi (2016) for descriptive statistics on different destinations after leaving.

(16) The differences are statistically significant at the 1% level.

(17) As argued in Section 11.2, it is not possible to control for housing conditions given that data on housing markets are not easily available for a large number of EU countries or over time.

(18) The maximum likelihood estimates of the implied trinomial probit model differ sharply from those obtained when either being employed or household membership is taken as exogenous (McElroy 1985).

(19) Estimates for the probability of being employed and being in a partnership are available from the authors on request.

(20) Accordingly, the overall likelihood ratio test of ρ‎21 = ρ‎31 = ρ‎32 = 0 is always not accepted with Prob > χ‎2 = 0.0000.