Generation of Young Adults Living with Their Parents in European Union Countries

Abstract

Young adult Europeans today find it more and more difficult to leave their native nest. The article examines the changes in the percentage of nesters over time, considering their gender, age, and the form of professional activity and employment status. The article also measures the phenomenon of nesting using the linear ordering of countries. Eurostat data were used in the work. The period of the study covers the years 2011–2019, while the spatial scope relates to the 28 countries of the European Union. The results show that more and more young adults live with their parents, and the percentage of nesters varies across Europe. Young adults living with their parents are people with a different employment status and professional activity. Those are employed persons working full-time, employed persons working part-time, unemployed persons, students, employees with a permanent job, employees with a temporary job and other persons outside the labor force. We prove that the problem of nesting between European countries was varied. It is noticeable that this phenomenon is intensifying, especially among the unemployed and those without permanent employment.

1. Introduction

There are many changes taking place in the modern world. Rapid modernization, individualization, and the globalization processes bring about new phenomena in social life. These include different ways of realizing one’s personal life than in the previous periods. There are individuals that are characterized by an attitude towards their development and independence. On the other hand, there is another group of young adults who still stay in the family home and, despite the appropriate age, cannot leave it [1]. The changing social and economic environment has led to a massive increase in the number of adult children, who either did not leave their home or returned to their family home after moving out [2]. In the face of change and the accompanying uncertainty, the family plays a significant role in the lives of young adults. It is a potential factor in creating adaptive, harmonious, and sustainable communities. It is the family that protects, shelters, and nurtures the individual in the context of adversity affecting multiple domains of function (e.g., domestic, academic, and occupational, among others) and, most importantly, provides an essential link between the individual and the larger community [3].

The family helps young adult children cope with the many challenges of early adulthood [4], and enables young adults to develop the skills and experience needed to be successful in adult life independently [5]. For example, parents may advise on health insurance plans when a child obtains a new job or emotional support during a relationship breakup. Young adults reported feeling supported when their mothers just listened to them talk about their day [6]. These types of support can also have an impact on the well-being of young adult children [7]. Life events and the needs of young adult children greatly influence the willingness of parents to help them. When young people were moving toward socioeconomic attainment or when they had experienced a crisis, they were more likely to receive financial and housing assistance. In this way, parents served as collaborators in their children’s transition to adulthood, acting as scaffolding systems to help young people reach their goals and as safety nets to catch them before they fell too far. Thus, parental assistance in young adulthood promoted progress toward self-sufficiency under changed structural conditions [8]. Thanks to the family nest, young adults can maintain their current standard of living and not experience poverty [9,10]. Of the many events that take place in the lives of young adults, such as leaving school, entering the labor market, marrying, and having children, leaving home is by far the most important factor in driving poverty among young adults [11]. Living with parents provides various types of support for young adult children; however, it may interfere with the children’s sense of independence [2,12], and negatively affect the well-being of the family and individual development [13]. Frequent parental support may be associated with diminished efficacy and initiative if grown children who receive such support feel less competent than other adults. They may be overly dependent or suffer from little confidence in their own abilities [14]. As Iacovou [15] notes, if young adult children or their parents value the “community” of families more than intergenerational independence, they can devote their resources to extending cohabitation (for example, parents may provide cash benefits to cohabitants or provide benefits in kind, such as clothes, meals, or the use of from the car), at the expense of your own well-being. Deferring the access to independence of young adult children is also associated with the extension of education and the subsequent entry into professional life. This is sometimes seen as a period of gradual preparation for adult roles [16].

Leaving the family home is an important factor in the transition to adulthood. This usually coincides with taking on major adult roles such as running their own household, making their own financial and consumption decisions, and more generally taking responsibility for their own lives without parental supervision [17]. Compared with other demographic phenomena such as an aging population, more frequent family breakdowns and the rise in single households or the mass movement of people across international borders, young people’s living conditions remain a relatively poorly researched topic. Current trends leave no doubt that young people extend the period in which they stay at home. This phenomenon was already noted by Whittington and Peters [18], Schneider [19] and Weston et al. [20]. Adult children living under the same roof with their parents are a social group that exists all over the world. They are defined in various ways, for example bamboccioni or mammoniin Italy [21], nesthocker in Germany [22], kidults or boomerangkids in the UK [23], parasaito shinguruin in Japan [24,25], gniazdownicy in Poland [26], fledgling in Canada [27], kippers in the USA [28], zippy in India, and puériculture in France [29], all of which are related to the extended residence of adult children with their parents. This leads to the crowded nest/cluttered nest effect [30], and young adults themselves are provocatively referred to as “chicks” [31].

Young adults are generally described as incapable of living independently mainly for economic reasons. They see the option of living with a parent as general financial risk coverage [32]. These people procrastinate in leaving home because they know they are at a greater risk of poverty than those who choose to stay at home [20]. Parents’ income “caring” of the family home supports young adults' consumption, providing them with material comfort and financial support [33]. Parents circle their adult children like “helicopters” out of concern for their well-being [34,35]. Living with your parents is also an important employment risk insurance mechanism [36]. Therefore, it seems clear that the macroeconomic conditions, and in particular the nature of the labor market, will have a large share in shaping the national trends in leaving the family home [37]. Young adults with precarious employment are more likely to stay at their parents’ homes. Employment on atypical employment contracts, working in a lower position or part-time increases their tendency to stay at home [38]. Moreover, the crisis in the real estate market, and thus too high house prices, especially in countries with a large purchasing market but only a small rental market, make moving out of the house even more difficult for young people [39]. Housing independence is determined, inter alia, by the cost of renting a flat [40] or the purchase price of one’s own house [41], and the lack of own income or problems with permanent employment additionally delay the decision of young adults to leave their parents’ home or are the reason for their more frequent returns to their home nest [37,42,43]. A crowded family nest is not only the result of poor macroeconomic conditions. The impact on living with the parents of young adults is also determined by cultural differences, such as attitude to family relationships and youth freedom and independence, ideology and religion, the generosity of the welfare state, or education [44].

Leaving the family home has become an important subject of research and media debate. Many sociologists, psychologists, demographers, and economists are looking for an answer to the question of what determines the decisions of young adults to live with their parents? The current trends leave no doubt that young adults extend the period in which they stay at home, either depending on their parents or running a household with them [45]. The period of studies, as well as the period of looking for a job or the desire to stabilize in the workplace is referred to as the “postponement syndrome” [46,47].

The process of young adult Europeans leaving their family home and the changes in this process vary in intensity. Thus, a comparison of the course of this process between countries is particularly important for understanding the postponement of the decision to leave the family nest.

The aim of our study is to fill the gap in the research on the phenomenon of nesting, paying attention to the changes in the percentage of nesters over time, considering their gender, age, and the form of professional activity and employment status. In addition, the study is an original approach to measuring the phenomenon of nesting due to the use of linear ordering of countries and, both in static and dynamic terms and clustering, and thus the identification of potential factors influencing the change in time of the situation in countries in terms of the level of the studied phenomenon.

We propose a broad view of the phenomenon of nesting in European countries, considering the spatial and temporal assessment of this phenomenon. To this extent, research on the phenomenon of nesting has not been conducted so far. As it is known that the time and reasons for leaving the family home are largely determined by the economic situation of young people and their families [48], we organize countries in terms of the form of professional activity and the employment status of nesters.

The following research question was formulated in the article: is the high percentage of young adults living with their parents correlated with the low level of professional activity and employment status the national level?

For the purposes of this study, the following definition of young adults living with parents was adopted: Young adult living with parents—a person 25–34 years of age, living with their parents, without a spouse and not being the parent themselves. The population in question does not include divorced persons and widowers. By adopting such an age frame, the completion of the stage of education during studies was considered, which allows for taking up highly qualified work and the possibility of self-fulfillment. Moreover, the age range adopted in the analysis is determined by developmental psychologists as the period of early adulthood [26].

2. Literature Review

A person’s life unfolds in stages over the years and with emerging new goals, challenges, and responsibilities. One of these stages is independence from parents in favor of self-dependence and adulthood, leaving the family home, engaging in partnerships, or starting a family. The issue of keeping young adults in the family home, referred to as nesting, was noticed already in the 1980s by American researchers Jill Suitor and Karl Pillemer [49], while in Polish sociology the term “nesting” was first used by Szlendak, describing the situation of adult people who, for various reasons, do not want to leave the nest [50]. One of the first studies dealing with the problem of nesting was the book The Crowded Nest Syndrome: Surviving the Return of Adult Children by the American sociologist Kathleen Shaputis [51]. In this book, the author noted the existence of adult children 25–35 years of age with their parents in their family home and used the term “nesting”.

In recent years, many scientific studies have been published in which the problems of the phenomenon of nesting were discussed. Milan [52] dealt with the factors influencing the nesting phenomenon in Canada by people 20–29 years of age. The results are based on data from the 2011 National Household Survey (NHS) as well as data from previous censuses. The author indicates factors that may affect the way of life of young people, which include high cost of education, economic uncertainty, or difficulties in finding a suitable job, relationship breakdown or conflict, as well as decisiveness regarding their future. Worth and Tomaszczyk [53], in turn, conducted a study of the phenomenon of nesting in the Greater Toronto Area (GTA) in Ontario, focusing on generation Y (people born in the 1980s and 1990s). Among the reasons for staying at home, the representatives of this generation most often indicated economic reasons, including saving money, paying off debts and unemployment, but also cultural traditions and closeness with the family.

Adamopoulou and Kaya [54] analyzed the impact of peer behavior on the living conditions of young adults in the United States. They used a unique set of longitudinal data on a representative sample of adolescents in the United States observed up to adulthood, which includes details of demographic and other individual characteristics, family of origin, neighborhood working and housing conditions, and high school friends. The results showed a statistically significant influence of peers on the decision of young adults to leave the family home. This is an important factor even after considering the labor and housing market conditions and a comprehensive list of individual and family characteristics. Having friends who still lived with their parents increased the likelihood of living with their parents. It has also been shown that women adapt to social norms more than men. Peer pressure played a crucial role in non-white or Hispanic young adults.

De Marco and Berzin [55] addressed the problem of young adults leaving their family home in terms of family wealth, including poverty among American families. Using the National Survey of Families and Users, this study examined the age of leaving home, multiple home departures, and departure location. The following features were included in the study: demographic (race and educational attainment for parents and for child: age, gender, teen parenthood, and educational), family economic status (below the poverty line or above the poverty threshold based on family size, family public assistance use during childhood) and outcome variables: age of home leaving, cycling behavior, and exit destination. The study used linear and logistic regression. Results suggest that poor emerging adults experienced home leaving differently than the non-poor adults. Poor young adults were less likely to leave the home of origin, though if they left, they were more likely to leave at younger ages, based on family public assistance use. In her research on changes in the organization of life in the USA and other developed countries, Goldscheider [56] also dealt with the issue of leaving the family home. In the study the authors focus on the relationship between parenthood and leaving home in early adulthood. The data were from the linked Child–Mother and Young Adult samples of the NLSY79. The work presented three research hypotheses that relate to the moment of leaving the family home at the time of becoming a parent: Hypothesis 1: We expect that becoming a parent prior to leaving home will increase the likelihood of leaving the parental home, with or without a romantic partner. Hypothesis 2: We expect that becoming a parent before leaving home will increase the likelihood of leaving more for women than for men. Hypothesis 3: We expect that becoming a parent prior to leaving home will increase the likelihood of leaving less for younger parents than for older ones. Logistic regression was used to verify the hypotheses. All three hypotheses were positively verified.

The phenomenon of nesting also appears in Australian research. Cobb-Clark [37] presented a historical outline of the phenomenon referring to the research of Goldscheider, which already in the 1990s indicated the phenomenon of nesting of young people [57,58]. The author emphasizes that living together with parents is an important form of intergenerational support for young adults. It pays particular attention to how Australia’s income support, education and housing policies can influence these patterns.

Research on the phenomenon of nesting was also carried out in European countries. Cote and Bynnerr [59], examining the changes among nesters in the UK, emphasize that young adults delay leaving the family nest in the context of increasingly uncertain labor market and living conditions, rising housing costs, and the need to remain in the educational system for a longer period of time.

Berngruber [22] studied the problem of young people returning to their family home in Germany. The analysis is based on the survey AID: A, conducted by the German Youth Institute in 2009. Data from 4300 young adults, 18–32 years of age, who left the parental home at least once, were used. The results showed that, the more financially and socially independent a young person is, the less likely they are to return to the family of origin. To identify factors affecting the probability of returning to the family home, after leaving the house at least once, the author uses variables such as, e.g., age, age of leaving home for the first time, gender, birth region, ethnic origin, living area, achieved educational level, own income, relationship, separation of the parents, importance of mother and father. In the study, the author used a binary logistic regression model. The results showed that the more financially and socially independent a person is, the less likely they are to return to their family of origin.

Andersson [60] investigated whether leaving the family home was influenced by the parents’ individual social capital and economic capital. The article also examines how these resources are related to the type of housing acquired. The study used a Swedish two-wave panel study of young adults 19 to 22 years of age. The variables used in the study were gathered into the following groups: housing outcomes (three variables: living arrangements, way of accommodation, and housing tenure), social and economic capita (estimating the resources embedded in social connections and the parents’ summed disposable income averaged from 1990 to 2012) and other variables (immigration background, gender, the number of siblings and birth order of the respondent, living together with parents, the respondent’s earning potential, the main activity declared by the respondent, domicile and whether the respondents live in the same communes as one of the parents). Due to the variables, the author used various models, e.g., linear probability models (LPM) with robust standard errors or regression analysis. The results showed that individual social capital is positively related to potential nest abandonment, but parental income is not.

Tsekeris et al. [61] explored the problem of boomerang kids in modern Greece using a qualitative method with partially structured, in-depth interviews. They proved that growing problems with access to the labor market severely limit young people’s ability to fulfill meaningful socially sanctioned roles, e.g., parent, wife/husband, etc. Moreover, the economic crisis in Greece has led to a situation where young people lack adequate self-fulfillment. Most of them are now confronted with the threat of unemployment and poverty, as well as a lack of life goals. So young adults stay at their parents’ home, claiming they have more benefits by sharing parental resources.

The problem of “staying at home” of Italian bamboccioni was investigated by Menniti et al. [62]. To understand why young Italians do not leave home, a multidimensional approach was used in a study conducted by Institute for Population Research of the National Research Council (IRP-CNR). They indicated that the reasons for Italian young adults staying longer in their parents’ home were either structural (higher unemployment, more time spent on education and no available housing) or cultural in nature. They argued that the profile of the Italian adult is part of a “Mediterranean” typology quite different from northern Europe, which characterizes people who tend to: study longer, extend the time to find a stable job, live with their parents even after achieving economic stability, and enter a marriage very soon after leaving home. The reasons for young Italians staying in the nest include: an unfavorable housing market, inadequate policies for young people, relationships that are not yet “mature” enough for the couple to decide to live together, the desire to maintain the standard of living they enjoy in the parents’ home and the nature of the parent/child relationship.

Iacovou [48] focused on the role of income in making it easier for young adults to leave the family home. For her multidimensional analyses, she used data collected by the European Community Household Panel (ECHP). As the research results show, factors that delay leaving the family home in European countries are: the scarcity of inexpensive rented housing, lack of a well-functioning mortgage market, high youth unemployment, plus low in-work wages. Evidence suggests that the timing and reasons for leaving home are determined by the economic resources of the young people themselves and their families. This article focuses on the role that income plays in making it easier for young people to leave the family home and is examined together with whether the effect is different if the income accrues to the young people themselves or to their parents. Skew and Iacovou [63] investigated the complex relationships between parental income and young people’s income and the time they leave home with a transnational perspective.

The results of Newman [21] confirm in turn that cultural factors influence the boomerang phenomenon. In Sweden and Denmark, where the public safety net provides significant support to unemployed adult children, it is almost unheard of for a person over 18 to live with their parents. Alternatively, countries such as Italy and Spain provide almost no public support, forcing young adults to rely on their parents’ ‘private safety net’. Young adults in these countries often live together for long periods until they are married.

Mencarini et al. [64] focusing on intergenerational exchange in Italy and France, estimated the multidimensional Tobit model and confirmed the thesis that the family home is a kind of “golden cage” for young Italians (mainly men) who perform a small amount of daily work and benefit from the care and attention of their parents (mainly mothers), which supposedly makes their home life very comfortable. From this point of view, it may be perfectly rational for them to postpone their departure from the family nest. In France, on the other hand, parents are demanding more participation and providing less services to their adult children in the household chores, possibly making cohabitation less comfortable, thus reducing the incentive to stay in the nest.

Chiuri and Del Boca [65] conducted an empirical analysis and used the ECHP, a longitudinal survey coordinated and supported by Eurostat. The survey involves a representative sample of households and individuals interviewed over eight years (1994–2001) in each of the 15 European countries (EU-15). They used the logit model for the analysis. Based on the analysis of the decision to leave home by their daughters and sons in European countries, they prove the emergence of a common pattern: young women leave home earlier than men (by 2–3 years). Moreover, the departure of daughters and sons from home is related to individual characteristics, parental resources, family structure, and institutional aspects. For example, in countries such as Italy, Greece, Portugal, and Spain, parental income has the opposite effect on children’s behavior. Greater family resources are associated with higher rates of leaving home for daughters and a higher rate of remaining in parents' household for sons. In turn, the family structure seems to be more important for daughters due to the durability of traditional roles. Sons, on the other hand, are more indifferent than daughters to institutional factors such as the labor market and the mortgage market.

Szluz [66], on the basis of Eurostat data, indicate that in Poland the main problem of nesting is due to the housing deficit. Young people rationalize the need to leave the family home with the aforementioned lack of housing, money, savings, or the desire to find a partner. Very often, the decision to stay at home is made under the influence of the parents themselves. Similar conclusions were reached by Piszczatowska-Oleksiewicz [67], who investigated the problem of postponing the removal from the nest by conducting a survey on a sample of 1005 people over 24 in Poland in 2010, which proves that the main reason that young adults live with their parents under one the roof is the lack of a flat, comfort, lack of money, a sense of connection, emotional dependence, willingness to live together, good housing conditions in the family home, no other family, or no job. Young adults leave the nest mainly because they undertake education outside their place of residence, work in another place (also abroad), and cohabitation.

Although existing research has shed light on the phenomenon of nesting, additional research is needed in this area to fully understand the reasons why young adults stay at home in European countries, considering the differences in time and space. Previous studies have not covered such a broad view of the leaving home behavior of Europeans in the context of their professional activity and employment status. In this article, we aim to fill that gap.

3. Dynamic Characteristics of Young Adults Living with Their Parents

The study used data from the Statistical Office of the European Union-Eurostat [68]. The time period of the study covers the years 2011–2019, while the spatial scope relates to 28 European Union countries. The research also covers Croatia, which joined the European Union in 2013, and the United Kingdom, by 2018, which officially left the European Union at the end of January 2020.

In 2019, the percentage of nesters in European countries was 30.5% and, on average, since 2011, it has increased by 0.33 pp from year to year. In 2019, the percentage of men 25–34 years of age who lived with their parents among all men was 23.9% and the percentage among women accounted for 27.3% of all women.

Among women, a higher average growth rate of the nesting scale was also noticed (0.70%) compared with men (0.17%) in the years 2011–2019. Figure 1 presents the percentage of nesters in the EU countries by gender in the years 2011–2019.

Figure 2 shows the percentage of nesters in EU countries in 2011, 2015, and 2019.

The number of nesters among European countries is the lowest in the Scandinavian countries. In Denmark it was 4% and in Finland 5%. In the countries of western Europe (e.g., Germany, France, and Austria) the level of the studied phenomenon was slightly higher (14–19%). In the countries of central and eastern Europe (e.g., Poland, Slovakia, Romania, and Hungary), the nesting scale was at the level of 40–50%, and the highest number of nesters was recorded in the countries of southern Europe (e.g., Croatia, Greece, Italy, Malta, and Spain) and it was often above 50%. In 2019, young residents of Croatia (31.8 years), Italy (30.1 years) and Bulgaria (30 years) left the family nest the latest; and the earliest were residents of Sweden—as the only ones before the age of 20 (17.8 years); the next lowest were Luxembourg (20.1 years) and Finland (21.8 years).

In most countries, men lived longer with their parents compared with women. Only in Luxembourg, the age of females leaving the nest was slightly higher (20.3 years) compared with that of males (20.0 years). Young adult men who lived the longest with their parents came from countries such as: Croatia (up to 33.6 years), Bulgaria and Slovakia (up to 32.1 years) and Malta (up to 30.4 years). Moreover, in Romania, Spain and Greece, the age of males leaving the family nest exceeded 30 years. The earliest were men in Sweden, who left the family home at the age of 18. Moreover, in the Netherlands, Luxembourg, France, Estonia, Germany, and Denmark, the age of men leaving the family home did not exceed 25 years of age. The average age of men, in 2019, leaving the family home was 27.1 years of age, and in the case of women—25.2 years of age. The fastest were the inhabitants of Sweden who left the family home at the age of 17.6 years. Moreover, relatively quickly, at just over 20 years of age, women from Finland (21.0 years of age), Luxembourg (20.3 years of age), and Denmark (20.8 years of age) left their family home. Women lived in the family home for the longest time in Croatia (29.9 years of age), Slovakia (29.6 years of age), Malta (29.1 years of age), Spain (28.7 years of age), and Greece (27.7 years of age).

Considering the spatial differentiation of European countries in terms of the scale of nesting and the age of leaving the family home, as well as the geographical location, the further assessed phenomenon was carried out in four groups of countries. This division was used in previous research by Iacovou [48], who distinguished the following groups of countries (Figure 3):

GroupI: North/Western: UK, France, Germany, Austria, Belgium, the Netherlands, Luxembourg, and Ireland;

Group II: Nordic: Sweden, Finland, Denmark, and Norway;

Group III: Eastern: Estonia, Latvia, Lithuania, Poland, Czechia, Slovakia, Slovenia, Hungary, Romania, and Bulgaria;

Group IV: Southern: Greece, Italy, Spain, Portugal, Cyprus, Malta, and Croatia.

The following part of the work presents a dynamic analysis in the years 2011–2019 relating to young adults 25–34 years of age living with their parents.

In the group of countries defined as north/western, a decrease in the percentage of nesters was observed in three countries: France, Austria, and Luxembourg. The largest decrease in the percentage of nesters was recorded in Austria (from 23.6% in 2011 to 19.3% in 2019). In France and Luxembourg, the decline was modest, amounting to less than 1 pp from year to year. In the five other countries belonging to the north/western group of countries, in the period 2011–2019 there was an average annual increase in the nesting scale, the largest in Belgium—3.8 pp, and the smallest in the Netherlands—0.6 pp.

In all the countries making up the Nordic group, the lowest level of nesting was observed in comparison with the other groups of countries (from 2.3% in Denmark in 2011 to 6.7% in Norway in 2016). However, from year to year in each of the Nordic countries there was an average annual increase in the scale of the studied phenomenon. The highest average increases were recorded in Denmark (7.2 pp) and Norway (6.1 pp). In Sweden and Finland, the level of nesting in the years 2011–2019 slightly increased. In Finland it was 2.0 pp, and in Sweden it was around 5.6%.

In the fourth group of countries, covering the south of Europe (southern), the nesting scale was at the highest level, e.g., in Greece it increased from 50.7% in 2011 to 57.8% in 2019. The lowest level of the studied phenomenon in the analyzed group was recorded in Cyprus (from 29.7% to 37.6%). The percentage of nesters in this group increased year by year in most countries (Greece, Italy, Spain, and Cyprus) or remained at a high level (Portugal and Malta). The highest average increase in the percentage of nesters was recorded in Spain and Cyprus in the period 2011–2019 (3.0 pp). Only in Malta there was a noticeable slight average decrease in the percentage of nesters—by 0.8 pp.

Among the most common reasons for young adults living with their parents, the economic situation is indicated, which is reflected in professional activity and employment status. This activity includes employed persons working full-time, employed persons working part-time, unemployed persons, students, employees with a permanent job, employees with a temporary job and other persons outside the labor force.

The percentage of employed persons working full-time in most of the surveyed countries exceeded 50%. In the north/western group of countries, the highest percentage of employed persons working full-time was recorded in Austria, UK, and Luxembourg. The lowest percentage of employed persons working full-time was in the Netherlands and France. Only two countries saw an increase in the percentage of employed persons working full-time from year to year. These were Ireland (by 5.8 pp) and Germany (by 2.4 pp). In Luxembourg, there was a decrease in the percentage of employed persons working full-time, on average, year by year by 4.1 pp (from 71.5% in 2011 to 52.2% in 2019). In other countries, the average decrease in the percentage of employed persons working full-time was in Belgium (0.8 pp) and the Netherlands (2.6 pp).

In the Scandinavian countries, the lowest percentage of employed persons working full-time was observed in Sweden and Finland. In each of the analyzed years, it was slightly below 45% and remained almost unchanged.

In the countries of southern Europe, there is a varied percentage of employed persons working full-time, from about 43.0% in Italy to about 82.0% in Malta. Only in one country there was a slight decrease in the percentage of employed persons working full-time from year to year. This was the case in Italy, where in 2011 there were 49.2% of employed persons working full-time, and in 2019 this percentage was 47.0%.

Quite a high percentage of employed persons working full-time in the analyzed period was recorded in all countries of the eastern group. The lowest was in Estonia in 2015 (57.8%) and the highest—in Slovakia in 2017 (81.6%).

Nesters in the distinguished groups of countries varied in terms of the percentage of employed persons working part-time. The highest percentage was recorded in two groups of countries: north/western and Nordic.

In the Nordic group, the percentage of employed persons working part-time was lower compared with the countries of the north/western group and ranged from 1.4% to 7.3% in Denmark and from 6.5% to 13.0% in Sweden.

Groups of southern and eastern countries are characterized by a relatively lower percentage of employed persons working part-time among nesters. Only in Spain and Italy was it observed to be around 10%. In the remaining countries of both groups, the percentage of employed persons working part-time oscillates around a few percent.

Due to the professional activity, in addition to employed persons, working full-time and employed persons, working part-time, and unemployed persons were also considered. The distinguished groups of countries show spatial differentiation in terms of the percentage of unemployed persons among nesters. Considering all European countries, the highest percentage of unemployed persons was recorded in Greece (from 29.5% in 2019 to 43.7% in 2013), and the lowest in Malta (6.2% in 2011 and 2.2% in 2019). In the north/western group, very large differences in the percentage of unemployed persons in individual countries were observed. It is lowest in Germany and highest in Ireland and France. The countries included in the Nordic group are characterized by a relatively high percentage of unemployed persons. The lowest was recorded in Denmark (from 3.7% in 2011 to 12.1% in 2019). The highest average annual increase in this percentage was observed, by 16.0 pp. On the other hand, Norway is characterized by the largest decrease in the proportion of unemployed persons, from 14.4% to 7.9% (by 7.2 pp). The percentage of unemployed persons in Sweden and Finland is at a similar level between 11.0% and 25.0%.

In the group of southern countries, it was observed that all countries, including Malta, are characterized by a high percentage of unemployed persons among nesters. The level of this phenomenon in these countries has not changed significantly. The percentage of unemployed persons is very high in Greece (43.7% in 2013 or 29.5% in 2019), and a slightly lower level is maintained in Spain (19.5–32.3%).

In each of the countries from the eastern group, there was a decrease in the percentage of unemployed persons, which was 3.0 pp in Bulgaria and 10.9 pp for Hungary in the period 2011–2019.

A varied percentage of people studying among the nesters was recorded in individual countries. In Germany there was the highest percentage of nesters that were students. In 2011, the percentage of studying nesters was almost 30.0%, and then it decreased from year to year, on average by 3.8 pp, to the level of 21.8%. The countries of the north/western group are characterized by a very varied percentage of students among the nesters. The lowest percentage related to the UK (1.0–4.5%) and the highest—to Luxembourg (9.7–27.3%). Moreover, in Luxembourg, the percentage of students increased by an average of 13.8 pp from year to year. On the other hand, Germany, Austria, and Ireland saw a decline in the percentage of studying nesters. The largest decline was in Ireland—12.7 pp on average. In each of the four Scandinavian countries, the percentage of students among the nesters ranged from a few to slightly above 20.0%. It was the lowest in Finland, from 7.6% to 17.4%, and the highest in Sweden (from 16.4% to 23.7%). In Sweden and Norway, a decrease in the percentage of students was recorded in the period 2011–2019, by 3.7% and 4.0%, respectively.

Southern European countries were also strongly diversified in terms of the percentage of students. A high percentage of them was found in Italy (around 18.0%) and Spain (around 11.0%), and lower in Cyprus (around 9.0%), Portugal (around 8.0%), and Greece (around 6% 5%). A decrease in the proportion of students was recorded in Greece, Cyprus, and Portugal. In the eastern countries, the percentage of students was low compared with other countries. Only in Slovenia were values above 10.0%. In the remaining countries, the percentage of students among nesters was below 10.0%. It was the lowest in Poland—approx. 3.0%, and the highest—in Hungary and Czechia—approx. 8.0%. Estonia, Latvia, Lithuania, Hungary, and Bulgaria showed an increase in the proportion of students, and a decrease in Czechia, Slovakia, Slovenia, and Romania. In Poland the number of nesting students had an almost constant level.

The nesting analysis in terms of employment included two groups, such as: employees with a permanent job and employees with a temporary job. The percentage of employees with a permanent job ranged from 32.0% in 2016 in Spain to almost 100.0% in Latvia. In the distinguished groups, countries are characterized by quite strong differentiation in terms of the percentage of employees with a permanent job. In the north/western group, the percentage of employees with a permanent job was stable in all countries. In the UK, nesters had the highest percentage of employees with a permanent job, in each of the surveyed years this percentage was over 90.0%. In Ireland, Austria, and Luxembourg, a high percentage of employees with a permanent job was noted—over 80.0%. In other countries, the examined percentage was above 60.0%. In the countries of the Nordic group, in each of the surveyed years, it was observed that over 50.0% of nesters are employees with a permanent job. Norway had the highest percentage, from 67.4% in 2013 to 90.5% in 2016. In all countries of the southern group in 2011–2019 there was a decrease in the percentage of employees with a permanent job, ranging from 0.8 pp in Portugal to 3.1 pp in Italy. The examined percentage was quite high, from slightly more than 50.0% (Portugal) to about 90.0% (Malta). The exception is Spain, with the percentage of employees with a permanent job ranging from 32.0% to 46.3%. The countries of the eastern group are characterized by the percentage of employees with a permanent job in the analyzed period at an almost identical, high level. The lowest percentage was recorded in Poland, its value oscillated around 50.0%. In countries such as Estonia, Latvia, Lithuania, Romania, and Bulgaria, the percentage of employees with a permanent job was very high and amounted to over 90.0%. On the other hand, in Slovenia, Slovakia, and the Czechia, employees with a permanent job were above 60.0%. Other people who were employed worked temporarily (employees with a temporary job).

In each of the analyzed countries, the percentage of persons outside the labor force was observed, the amount ranging from 2.2% in Slovenia to 18.6% in Finland. In the countries of the north/western group, this percentage ranged from about 2.0% to 15.0% and increased year by year in most countries, with the exception of: France and Ireland. The largest increase compared with the percentage in 2011 was observed in Luxembourg, where in 2019 there was an over 100% increase in the percentage of persons outside the labor force. Among the countries of the Nordic group, the highest percentage of persons outside the labor force was recorded in Finland (18.6% in 2011 and 16.4% in 2019). In the remaining countries, the average percentage was slightly below 10.0%. In the countries of southern Europe, the lowest percentages of persons outside the labor force were observed. Only in Malta and Italy the percentage was slightly above 6.0%, on average. In other countries, it did not exceed 5.5%. In the countries of eastern group, the highest percentage of persons outside the labor force is characteristic of Estonia (14.1% in 2011 and 11.4% in 2019) and Romania (7.6% in 2011 and 17.2% in 2018), where the highest percentage increase was recorded year on year, amounting to 4.5 pp. Moreover, Poland has a high percentage of persons outside the labor force and shows a growing tendency (9.0% in 2011 and 11.8% in 2019). In the remaining countries of this group, the average percentage ranged from 2.2% (Slovenia) to 9.6% (Lithuania).

4. Methods

In the case of time series, the assessment of the size and change in the studied phenomenon can be carried out using the following approaches:

• By analyzing the data for each year separately, i.e., creating a synthetic variable based on information relating to each year separately and then making comparisons of the obtained results for each year. This approach is called by some authors static or quasi-dynamic [69,70] because the construction of a synthetic variable for a given year does not consider data from other years, i.e., a causal relationship with each other.
• Considering data for all years, i.e., creating a synthetic variable from information pertaining to different years. Thanks to this approach, it is possible to assess the size of changes in the level of development of facilities in the period under study.

In the static approach, after obtaining a linear ordering of objects in each of the studied years, comparisons of the results of the rankings can be made, but it is only an examination of the location of a given object within each ranking. On the basis of the obtained results, it is possible to assess the compliance of the position occupied by the tested objects in individual orderings. For this purpose, for example, the rank correlation coefficient τ-Kendall [71] was used.

In the case of the dynamic approach in the linear ordering of objects, e.g., the rate of changes in time of partial diagnostic variables was used, constructing a measure used to determine the total rate of changes in the development over time of the examined objects in relation to the reference object or using individual, relative values of the growth rate of diagnostic variables or values of absolute increments of diagnostic variables, it is possible to study the similarity of objects in time from the point of view of the structure of the growth rate of individual measures for individual diagnostic variables [72].

In this paper, the static and dynamic approach to the creation of a synthetic variable are proposed, which consists in treating the set of values of diagnostic variables from all analyzed years as one whole.

The creation of a synthetic variable was carried out according to the following stages:

• Selecting variables on the phenomenon.

This stage includes the selection of variables that must play an important role in the description of the studied phenomenon. Variables should also be available so that can obtain complete numerical information about each variable included in the study. The result of this stage is the observation matrix:

$$X=\left[x_{ijt}\right] \left(i=1, 2, \dots , m;j=1, 2, \dots , n;t=1, 2, \dots , T\right),$$

(1)

where: $x_{ijt}$—value of the j-th variable in i-th object in year t, m—number of objects, n—number of variables in T years.

The X observation matrix is the starting point for the construction of a synthetic variable in both the static and dynamic approach. It is important that the variables show the appropriate variability, that is, they effectively discriminate against the objects.

2.

Determining the direction of the preferences of variables in relation to the considered criterion and their normalization

Considering the obtained set of diagnostic variables, the direction of variable preferences should be determined, i.e., stimulants, destimulants, and nominants should be distinguished [73]. Stimulants are features of which higher values determine a better level of the phenomenon under consideration, lower values for the characteristics considered to be destimulants are desirable. On the other hand, nominants are features whose absolute values increasing to the nominal value and cause an increase in the relative values of the feature, a further increase in primary values is related to a decrease in the normalized values.

The next step in building a synthetic feature is the normalization of the features. It leads to the deprivation of the measurement results and the unification of the orders of magnitude of the features. In this work, the zero unitarization method was used, due to the fulfillment of all the requirements for standardization procedures, to which they belong [74,75]:

• Deprivation of titers (units) in which the diagnostic features are expressed.
• Reducing the order of magnitude of diagnostic variables to the state of comparability, which means equalizing the ranges of variability of features and, consequently, the possibility of adding them.
• Equality of the spread of the ranges of variability of the values of all standardized features (range constancy) and the equality of the lower and upper limits of their range of variability, in particular, it concerns the interval [0; 1].
• The possibility of normalizing diagnostic features with positive, negative, or only negative values.
• The possibility of standardizing features taking the value of zero.
• Non-negative value of standard features.
• Existence of simple formulas—within a given normalization procedure—unifying the nature of the variables.

In the static terms (S), the following formulas were used to normalize the variables:

• For stimulants:

$$z_{ijt}^S=\frac{x_{ijt}-\underset{i}{\min }{x}_{ijt}}{R_{jt}},$$

(2)

• For destimulants:

  $$z_{ijt}^S=\frac{\underset{i}{\max }{x}_{ijt}-x_{ijt}}{R_{jt}},$$

  (3)

  where: $R_{jt}=\underset{i}{\max }{x}_{ijt}-\underset{i}{\min }{x}_{ijt}\left(j=1,2,\dots ,n;t=1,2,\dots ,T\right)$.

In the dynamic approach (D) of the structure of a synthetic variable, the normalization of variables is carried out according to the following transformations [70]:

• For stimulants:

$$z_{ijt}^D=\frac{x_{ijt}-{\mathrm{MIN}}_j}{R_j},$$

(4)

• For destimulants:

  $$z_{ijt}^D=\frac{{\mathrm{MAX}}_j-x_{ijt}}{R_j},$$

  (5)

  where:$R_j={\mathrm{MAX}}_j-{\mathrm{MIN}}_j$,

${\mathrm{MIN}}_j=\underset{t=1,2, \dots T}{\min }\left({\mathrm{MIN}}_{jt}\right), {\mathrm{MIN}}_{jt}=\underset{i=1,2, \dots , m}{\min }{x}_{ijt},$${\mathrm{MAX}}_j=\underset{t=1,2,\dots , m}{\max }\left({\mathrm{MAX}}_{jt}\right),{\mathrm{MAX}}_{jt}=\underset{t=1,2, \dots , T}{\max }{x}_{ijt}\left(j=1, 2, \dots ,n, t=1, 2, \dots , T\right)$.

3.

Determination of the value of a synthetic variable using the selected method of aggregation of variables and linear ordering of objects.

In static terms, the synthetic variable is determined according to the formula:

$$W_{it}^S={\displaystyle \sum }_{j=1}^n{z}_{ijt}^S \left(i=1,2, \dots , m;t=1,2, \dots , T\right),$$

(6)

In dynamic terms:

$$W_{it}^D={\displaystyle \sum }_{j=1}^n{z}_{ijt}^D \left(i=1,2, \dots , m;t=1,2, \dots , T\right)$$

(7)

On the basis of the values$W_{it}^S$ and $W_{it}^D$, a linear ordering of objects is prepared and then the indicators of the level of development are determined [70]:

$$P_{it}^S=\frac{W_{it}^S}{n},$$

(8)

$$P_{it}^D=\frac{W_{it}^D}{n},$$

(9)

For static and dynamic approach, respectively.

The pointers $P_{it}^S$ and $P_{it}^{D }$assume values in the range $\left[0;1\right]$. The higher the value of the indicators, the higher the level of development of the facility. The $P_{it}^S$ makes it possible to compare objects in terms of the level of the studied phenomenon in each year separately, but it does not allow for the assessment of the size and directions of changes occurring in the objects in a given period, while the comparison of the value of the $P_{it}^D$ indicator for the same object, e.g., in 2 years $t_1$ and $t_2$ enables the assessment of the direction and magnitude of changes for a specific object in the time from $t_1$ and $t_2$ [70]. The difference $S_{i{t}_1{t}_2}^D$ between $P_{it}^D$ in 2 years means the amount of changes that occurred in the object i.

The values of the synthetic variable can be used to distinguish typological groups of objects. After ordering the value of an aggregate feature, four typological classes of countries are determined on the basis of the arithmetic mean and the standard deviation calculated from its values. Division into four classes covering objects for which the synthetic feature takes values from the following ranges:

• Group I: $W_{it}\ge {\overline{W}}_t+s_{W_t}$;
• Group II: ${\overline{W}}_t\le W_{it}<{\overline{W}}_t+s_{W_t}$;
• Group III: ${\overline{W}}_t-s_{W_t}\le W_{it}<{\overline{W}}_t$;
• Group IV: $W_{it}<{\overline{W}}_t-s_{W_t}$.

where ${\overline{W}}_t—$arithmetic mean, $s_{W_t}$—standard deviation from the value of the synthetic feature.

The first class is characterized by the highest level of the studied phenomenon, while the last one—the lowest.

Friedman repeated measures analysis of variance by ranks and Dunn's post hoc test as well as Kendall’s Coefficient of Concordance were used to assess the concordance of orders for related variables [71,76].

The method of linear arrangement of objects in static and dynamic terms was used in the assessment of the professional activity and employment status of nesters 25–34 years of age in 28 European Union countries because, as research indicates, the main factor influencing the decision to leave the family nest is the economic aspect relating to both the situation of the young person and the family. Three years were selected for the study from the period 2011–2019: 2011, 2015, and 2018. The moments selected for the analysis referred to the beginning, the end and one of the middle moments of the analyzed period. Information on the professional activity and employment status of nesters 25–34 years of age comes from the Eurostat database. The presented methods were used to answer the research question: is the high percentage of young adults living with their parents correlated with the low level of professional activity and employment status the national level?

5. Results

To achieve the purpose of the study and to answer the research question the following set of diagnostic features was adopted:

• Employed persons working full-time (X₁);
• Employed persons working part-time (X₂);
• Unemployed persons (X₃);
• Students (X₄);
• Employees with a permanent job (X₅);
• Employees with a temporary job (X₆);
• Other persons outside the labor force (X₇).

Expressed as a percentage of the number of nesters,

Table 1. Descriptive statistics of the professional activity and employment status of nesters 25–34 years of age in European countries in 2011, 2015, and 2018.

Year	Variables
	X1	X2	X3	X4	X5	X6	X7
Mean
2011	61.39	5.76	15.74	9.89	75.43	24.57	7.18
2015	58.67	7.08	16.65	10.03	72.39	27.61	7.58
2018	63.32	7.89	11.83	9.33	72.99	26.83	7.62
Median
2011	62.80	5.60	15.20	9.40	78.95	21.05	7.20
2015	59.65	7.70	14.45	10.05	73.70	26.30	8.75
2018	64.70	7.30	11.50	7.80	73.90	26.10	5.90
Max
2011	81.8	19.8	32.5	29.6	95.3	53.7	18.6
2015	82.50	17.30	40.30	23.70	99.40	65.80	13.70
2018	84.10	26.50	31.00	24.90	99.80	64.80	17.20
Min
2011	41.70	1.00	3.70	2.40	46.30	4.70	2.40
2015	37.70	1.40	4.60	1.80	34.20	0.60	1.70
2018	42.00	1.40	0.60	2.60	35.20	0.20	2.20
Standard deviation
2011	10.38	4.01	7.14	6.25	13.66	13.66	3.54
2015	12.39	4.12	8.50	5.91	17.86	17.86	3.42
2018	11.27	5.27	6.85	5.83	17.25	17.18	3.79
Skewness
2011	−0.30	1.54	0.38	1.40	−0.24	0.24	1.36
2015	−0.08	0.40	0.78	0.51	−0.24	0.24	−0.07
2018	−0.18	1.48	0.89	1.02	−0.23	0.26	0.73
Variation coefficient
2011	16.90	69.68	45.37	63.20	18.11	55.61	49.32
2015	21.11	58.29	51.03	58.89	24.67	64.67	45.16
2018	17.80	66.80	57.93	62.51	23.63	64.05	49.74

presents the basic characteristics of diagnostic variables.

All variables in each analyzed year are characterized by a strong or very strong variability, from 16.90% for the variable X₁ in 2011 to 66.80% for the variable X₂ in 2018. The distributions of two variables: X₁ and X₅ are characterized by negative asymmetry with a rather weak strength in each year. The left-hand direction of the asymmetry of the distributions means that countries where the percentage of employed persons working full-time and the percentage of employees with a temporary job is higher than the average prevail. Such countries include, for example, Malta, Czechia, and Slovakia. The distributions of the remaining variables are characterized by moderate to strong right-hand asymmetry. The strongest right-hand asymmetry shows the distribution of the variables X₂ and X₄. The highest average percentage of employed persons working full-time was observed in 2018. The nesters are characterized by a similar percentage of students, amounting to approximately 10.00% in each of the surveyed years. The percentage of employees with a permanent job and employees with a temporary job was at a similar level in the analyzed years.

Considering the nature of the variables, it was concluded that the variables X₁, X₂, and X₄—X₆ are stimulants while the variables X₃ and X₇ are destimulants.

In the next step, measures of country development were calculated in static terms (

Table 2. Values of synthetic measures in static terms and rank of European countries according to level of professional activity and employment status of nesters 25–34 years of age in 2011, 2015, and 2018.

Countries	Rank of Countries	${\mathit{P}}_{\mathit{i}\mathit{t}}^{\mathit{S}}$	Rank of Countries	${\mathit{P}}_{\mathit{i}\mathit{t}}^{\mathit{S}}$	Rank of Countries	${\mathit{P}}_{\mathit{i}\mathit{t}}^{\mathit{S}}$
	2011		2015		2018
UK	8	0.514	9	0.505	17	0.456
France	18	0.441	21	0.457	27	0.397
Germany	1	0.626	2	0.613	5	0.554
Austria	2	0.623	3	0.589	3	0.558
Belgium	10	0.513	24	0.431	15	0.471
The Netherlands	3	0.618	18	0.474	1	0.655
Luxembourg	4	0.574	1	0.655	2	0.585
Ireland	25	0.366	23	0.436	11	0.484
Sweden	16	0.469	4	0.530	18	0.456
Finland	29	0.276	29	0.349	29	0.344
Denmark	14	0.486	6	0.516	26	0.405
Norway	11	0.509	8	0.508	9	0.506
Greece	26	0.359	28	0.362	28	0.358
Italy	15	0.479	20	0.467	21	0.438
Spain	23	0.416	16	0.476	20	0.438
Portugal	12	0.500	19	0.468	12	0.483
Cyprus	5	0.562	12	0.500	14	0.476
Malta	6	0.545	7	0.511	7	0.542
Estonia	27	0.359	17	0.476	22	0.435
Latvia	28	0.351	22	0.438	24	0.417
Lithuania	24	0.374	26	0.390	19	0.454
Czechia	13	0.500	13	0.500	10	0.505
Hungary	21	0.433	14	0.495	4	0.554
Poland	19	0.439	25	0.426	25	0.409
Slovakia	17	0.461	11	0.502	8	0.518
Slovenia	9	0.514	10	0.503	6	0.545
Romania	7	0.531	5	0.522	23	0.427
Bulgaria	20	0.438	27	0.371	16	0.462
Croatia	22	0.417	15	0.480	13	0.476

).

The Friedman repeated measures analysis of variance by ranks (ANOVA of Friedman) test [76] was used to assess the relationships between the values of the measure for individual countries in a linear ordering. The obtained results ${\chi }^2=0.991$ and $p=0.609$prove that there were no significant differences between the values of the measure for individual countries in the rankings in the 3 analyzed years. The conformity of the position occupied by the EU countries in individual orderings was also assessed with the use of the τ-Kendall rank correlation coefficient (

Table 3. Values of the τ-Kendall rank correlation coefficients according ordering in static terms of European countries in the years 2011, 2015, and 2018.

Year	2011	2015	2018
2011	1.000	0.542	0.453
2015	0.542	1.000	0.399
2018	0.453	0.399	1.000

).

The positions of individual countries in the analyzed years are strongly and significantly interrelated $(p<0.05$).

In 2011, Germany was in the first position, which in the subsequent analyzed years was ranked lower: in 2015—the second position; and in 2018—the fifth position. The decline in the percentage of employees with a permanent job in 2018 compared with 2011 by 35.48 pp contributed to the weakening of Germany’s position, and an increase in the percentage of other persons outside the labor force (by 67.39 pp). An interesting situation occurred in the case of positions in individual rankings occupied by the Netherlands. In 2011, this country was on the third position, while in the next audited year, the Netherlands fell to the 18th place and after 3 consecutive years, in 2018, it took the first position. The differences in the occupied positions result from a large increase in 2015 in the percentage of such variables as: unemployed persons and other persons outside the labor force, by 68.13 pp respectively and 165.31 pp. In 2018, a large drop in the percentage of these variables was observed, compared with 2015 (in both cases by 70.00 pp). Finland was last in the ranking in each of the analyzed years. This situation was related mainly to the high percentage of unemployed persons (25.4% in 2015 and 17.40% in 2018) and other persons outside the labor force among nesters (e.g., 18.60% in 2011). Moreover, the variable employed persons working full-time in each examined year had a value much lower than the average value for all the researched countries. In the case of Finland, the percentage of employed persons working full-time was 44.6%. 44.3%, and 49.5%, while the average for the 28 EU countries was around 60.00%. A significant decrease in the value was also observed in the percentage of employees with a permanent job from 81.20% in 2011 to 57.90% in 2018.

As shown in Table 2, Austria, Luxembourg, Malta, and Slovenia occupied stable high positions in the rankings. On the other hand, countries such as: Latvia, Spain, Poland, or France occupied low positions in the rankings. In some countries, there was an improvement in the position in 2018, e.g., in Ireland, Lithuania, Bulgaria, Hungary, and Slovakia; however, many countries saw a deterioration in their position, such as Romania, Cyprus, Denmark, and France.

In the next step of the study, synthetic variables were determined in dynamic terms (

Table 4. Values of synthetic measures in dynamic terms and rank of European countries according to level of professional activity and employment status of nesters 25–34 years of age in 2011, 2015, and 2018.

Countries	Rank of Countries	${\mathit{P}}_{\mathit{i}\mathit{t}}^{\mathit{D}}$	Rank of Countries	${\mathit{P}}_{\mathit{i}\mathit{t}}^{\mathit{D}}$	Rank of Countries	${\mathit{P}}_{\mathit{i}\mathit{t}}^{\mathit{D}}$	Change
	2011		2015		2018
UK	9	0.522	9	0.520	13	0.517	↓
France	21	0.492	21	0.490	24	0.493	↓
Germany	3	0.536	4	0.530	9	0.531	↓
Austria	1	0.546	2	0.536	5	0.534	↓
Belgium	11	0.516	19	0.492	11	0.521	—
The Netherlands	5	0.532	20	0.491	1	0.548	↑
Luxembourg	4	0.534	1	0.543	7	0.533	↓
Ireland	27	0.465	25	0.479	19	0.512	↑
Sweden	20	0.497	16	0.496	22	0.499	↓
Finland	29	0.455	27	0.464	27	0.480	↑
Denmark	8	0.523	18	0.493	23	0.498	↓
Norway	14	0.512	12	0.505	12	0.521	↑
Greece	28	0.465	28	0.446	28	0.470	—
Italy	18	0.500	24	0.480	26	0.487	↓
Spain	23	0.484	26	0.473	25	0.493	↓
Portugal	12	0.516	17	0.496	16	0.515	↓
Cyprus	7	0.526	22	0.486	18	0.514	↓
Malta	2	0.536	3	0.536	2	0.546	—
Estonia	25	0.482	10	0.514	17	0.515	↑
Latvia	26	0.475	11	0.507	20	0.510	↑
Lithuania	24	0.484	14	0.500	14	0.516	↑
Czechia	10	0.521	8	0.520	6	0.533	↑
Hungary	19	0.499	7	0.521	3	0.540	↑
Poland	16	0.503	13	0.502	21	0.509	↓
Slovakia	15	0.510	6	0.523	4	0.536	↑
Slovenia	13	0.516	15	0.498	8	0.531	↑
Romania	6	0.528	5	0.527	10	0.521	↓
Bulgaria	17	0.502	23	0.485	15	0.516	↑
Croatia	22	0.490	29	0.286	29	0.285	↓

).

The Friedman repeated measures analysis of variance by ranks test was used to assess the relationship between the values of the measure for individual countries in a linear dynamic ordering. The obtained results ${\chi }^2=15.252$and$p=0.00049$ prove the occurrence of significant differences between the values of the measure in the rankings in the 3 analyzed years. To assess which rankings differ in the values of the measure, Dunn’s post hoc test was used, and it was obtained that significant differences exist between the values of the measure in 2015 and 2018 ($z=3.87354;p=0.00032$).

The values of the τ-Kendall rank correlation coefficients (

Table 5. Values of the τ-Kendall rank correlation coefficients according ordering in dynamic terms of European countries in the years 2011, 2015, and 2018.

Year	2011	2015	2018
2011	1.000	0.433	0.488
2015	0.433	1.000	0.601
2018	0.88	0.601	1.000

) prove a strong significant correlation between the positions of the countries.

In 2018, the Netherlands was in first position, and Croatia was in the last position in ranking of countries in dynamic terms. The Netherlands owes its first position to, among others, a low percentage of unemployed and a high percentage of employees with permanent employment of young adults living with their parents.

Croatia came last in the country ranking due to the high percentage of unemployed young adults living with their parents and the low percentage of part-time workers.

Differences can be noticed between the rankings in static and dynamic terms, as evidenced by the results of the ANOVA Fridman’s test ${\chi }^2=30.459$and $p=0.000012$. Significant differences were observed between the values of the following measures: in 2011 in static and dynamic terms ($z=2.948; p=0.048)$ and in 2018 in static and dynamic terms ($z=3.755;p=0.003)$. The dynamic indicator of the level of development enables, in addition to arranging, the analysis of the dynamics of the examined complex phenomenon, allowing for the assessment of the direction and size of changes. For this purpose, indicators of the development level $S_{i{t}_1{t}_2}^D$ were calculated (

Table 6. Development level indicators of European countries in terms of level of professional activity and employment status of nesters 25–34 years of age in 2015 and 2018.

Countries	${\mathit{S}}_{\mathit{i}.2011; 2015}^{\mathit{D}}$	${\mathit{S}}_{\mathit{i}.2015;2018}^{\mathit{D}}$	${\mathit{S}}_{\mathit{i}.2011;2018}^{\mathit{D}}$
UK	−0.003	−0.003	−0.005
France	−0.002	0.003	0.001
Germany	−0.006	0.001	−0.005
Austria	−0.010	−0.001	−0.012
Belgium	−0.025	0.029	0.004
The Netherlands	−0.041	0.057	0.016
Luxembourg	0.009	−0.009	−0.001
Ireland	0.013	0.034	0.047
Sweden	−0.001	0.003	0.002
Finland	0.009	0.016	0.025
Denmark	−0.029	0.005	−0.024
Norway	−0.007	0.015	0.008
Greece	−0.020	0.025	0.005
Italy	−0.020	0.007	−0.013
Spain	−0.011	0.019	0.008
Portugal	−0.020	0.019	−0.002
Cyprus	−0.040	0.028	−0.012
Malta	−0.001	0.010	0.009
Estonia	0.032	0.001	0.033
Latvia	0.032	0.004	0.035
Lithuania	0.016	0.017	0.032
Czechia	−0.001	0.013	0.012
Hungary	0.022	0.019	0.041
Poland	−0.001	0.007	0.006
Slovakia	0.013	0.013	0.026
Slovenia	−0.018	0.033	0.015
Romania	−0.002	−0.006	−0.008
Bulgaria	−0.018	0.032	0.014
Croatia	−0.204	−0.001	−0.205

).

On the basis of the value of the dynamic indicator of the level of development, it is possible to identify objects in which the situation in terms of the adopted set of features changed to a worse or more favorable situation in the analyzed period. Negative values of $S_{i{t}_1{t}_2}^D$ indicate a deterioration of the situation in the country in terms of the level of professional activity and employment status of young adults living with their parents, while positive values indicate a more favorable situation. The situation of EU countries in terms of the professional activity and employment status of nesters in 2018 was subjected to a detailed assessment compared with 2011. In 10 countries (UK, Germany, Austria, Luxembourg, Denmark, Italy, Portugal, Cyprus, Romania, and Croatia) a decline in the value of the dynamic index was observed level of development. Five countries (UK, Germany, Austria, Luxembourg, and Croatia) are in the north/western group; three countries (Italy, Portugal, and Cyprus) are from the southern group; and one from the Nordic group—Denmark; and one from the eastern group—Romania. The largest decrease in the value of the dynamic indicator of the level of development was observed in Croatia, Denmark, Italy, and Austria. The decrease in the value of the index in 2018 indicates a lower level of professional activity and employment status of nesters 25–34 years of age compared with the level of 2011.

The remaining 19 countries saw an increase in the dynamic indicator of the level of development, the highest in Ireland, Hungary, and Slovakia.

In several countries (Ireland, Finland, Estonia, Latvia, Lithuania, Hungary, and Slovakia) a steady increase in the value of the dynamic indicator of the level of development was recorded. Among these countries, the majority (5) are countries in the eastern group. The increase in the value of the development index in these countries indicates an improvement in the level of professional activity employment status of nesters 25–34 years of age.

Four countries (UK, Austria, Romania, and Croatia) recorded a steady decline in the value of the dynamic indicator of the level of development.

In 2018, the largest range of values for the dynamic indicator of the level of development was recorded, amounting to 0.263. In 2011 and 2015, the range was 0.091 and 0.257, respectively. Increasing the range of the development measure means increasing disparities in the professional activity and employment status of nesters and widening the disparities between countries.

A linear order of countries by professional activity and employment status of nesters for 2019 was also performed. The UK was not included in the study due to this country’s withdrawal from the EU. Luxembourg was ranked first; Germany was second, and the Netherlands third. The last three places in the ranking were: Finland (28), Greece (27), and Lithuania (26).

Table 7. Values of the synthetic measure and the rank of European countries according to the level of professional activity and employment status of nesters 25–34 years of age in 2019.

i	Country	Symbol of Country	Values of Synthetic Measures	Rank of Coutries	Group
1	France	FR	0.425	23	III
2	Germany	DE	0.587	2	I
3	Austria	AT	0.532	6	II
4	Belgium	BE	0.427	22	III
5	The Netherlands	NL	0.566	3	I
6	Luxembourg	LU	0.594	1	I
7	Ireland	IE	0.447	20	III
8	Sweden	SE	0.428	21	III
9	Finland	FI	0.251	28	IV
10	Denmark	DK	0.419	24	III
11	Norway	NO	0.488	11	II
12	Greece	EL	0.348	27	IV
13	Italy	IT	0.478	14	II
14	Spain	ES	0.457	16	III
15	Portugal	PT	0.498	8	II
16	Cyprus	CY	0.478	13	II
17	Malta	MT	0.534	5	II
18	Estonia	EE	0.455	19	III
19	Latvia	LV	0.456	18	III
20	Lithuania	LT	0.406	26	III
21	Czechia	CZ	0.488	10	II
22	Hungary	HU	0.530	7	II
23	Poland	PL	0.414	25	III
24	Slovakia	SK	0.491	9	II
25	Slovenia	SI	0.558	4	I
26	Romania	RO	0.485	12	II
27	Bulgaria	BG	0.457	17	III
28	Croatia	HR	0.472	15	II
	Min		0.251
	Max		0.594
	Range		0.343
	Average		0.470
	Standard deviation		0.072
	Coefficient of variation (%)		15.26
	Average + Standard deviation		0.542
	Average-Standard deviation		0.399

shows the values of the synthetic measure, country positions (Figure 4) and the group to which the country belongs in terms of professional activity and employment status. The groups were distinguished on the basis of the mean value and standard deviation of the measure.

Four countries were included in the first group with the highest level of activity and employment status of young adults living with parents, including three from the north/western group: Luxembourg, Germany, and the Netherlands, and one country from the eastern group—Slovenia. The second high-level group includes eleven countries, including four from the southern group: Malta, Portugal, Cyprus, and Italy; five countries belonging to the eastern group: Hungary, Slovakia, Czechia, Romania, and Croatia; and one each from the north/western—Austria; and from Nordic—Norway. The third cluster also includes eleven moderate-level countries, including five from the eastern group: Bulgaria, Latvia, Estonia, Poland, and Lithuania; three from north/western: Ireland, Belgium, and France; two countries from the Nordic: Sweden and Denmark; and Spain from the southern class. The fourth group with the lowest level includes only two countries: Greece (southern) and Finland (Nordic). The spatial differentiation of countries in terms of activity and employment of nesters in 2019 is shown in Figure 5.

The following research question was formulated in the article: is the high percentage of young adults living with their parents correlated with the low level of professional activity and employment status the national level? In order to answer the question, the values of the synthetic variable and the percentage of nesters in individual countries were analyzed. Based on the research, it can be concluded that in many countries, a high percentage of young adults living with their parents 25–34 years of age is correlated with their low level of professional activity and employment status. This is the case, for example, in Croatia, Bulgaria, Greece, Spain, or Italy. However, it should be noted that in some countries, such as Germany, Austria, Luxembourg, or the Netherlands, there was a low percentage of nesters and a high level of their professional activity.

6. Discussion and Conclusions

A generation of young Europeans today is faced with a fragmented and uncertain reality far worse than the reality experienced by their parents [77]. Many Europeans persistently believe that the economic situation is not good and that it will not improve in the near future. Moreover, many see a slight improvement in their own well-being in relation to the past and looking to the future [78]. It is not conducive for young adult children to leave the family home or it causes them to return to the family nest like boomerangs. The nesting phenomenon in European countries has been gaining momentum recently. The information is not good as it indicates that young Europeans are postponing the transition to adulthood. The role of the labor market in shaping individual welfare and economic performance is key to understanding these trends. The unemployed, or people from outside the workforce, do not want or cannot become independent because they cannot afford it, while the employed, who, although approaching the age of 30, have acquired an education and are often successful and financially independent, still live with their parents in order to increase one’s own quality of life. However, work does not always allow young adults to become independent. Low earnings—a well-known problem in Europe, or working conditions do not allow one to take out a loan for a flat and become independent [49]; especially when these people have limited access to the labor market. They are only offered employment in the service sector called McJob, which is a low wage, contract, or part-time job [79]. Young people’s job and income insecurity not only hampers access to credit and housing independence and inhibits long-term obligations such as family formation but can also lead to subjective uncertainty [80]. This phenomenon may be explained by the fact that the life plans and aspirations of nesters focus mainly on the broadly understood stabilization, which should be understood through the prism of financial and family security, thus revealing the reluctance to change (taking risks) and loneliness (being alone). Thus, the fulfillment of this basic need (financial and family stability) is guaranteed by the family system in which they function here and now [49].

Our research sheds new light on the problem of nesting in European countries and their spatial diversity in terms of the form of activity and employment status of young adults. In many works [48,52,55,56,59,67], the authors used data obtained in surveys reflecting the subjective feelings of the respondents. Our work used objective data from the Eurostat database and supplements research on the phenomenon of nesting.

The novelty of the research consists in identifying groups of countries taking into account the criterion of activity and employment status of nesters 25–34 years of age, not only in a static but also in a dynamic way, enabling the preparation of a ranking of countries and the assessment of the direction and size of changes in the level of activity and employment status in the analyzed period.

It is worth emphasizing that in the study, apart from assessing the changes in time of variables relating to the phenomenon of nesting, a dynamic approach was also used on the basis of the methods of linear ordering of multi-feature objects, which allows for the identification of potential factors of changes in the time of the studied phenomenon. The use of linear ordering methods and the classification of EU countries made it possible to identify groups of countries characterized by a similar level of activity and employment status of nesters 25–34 years of age.

According to the data published by Eurostat, in 2019 the percentage of nesters 25–34 years of age in the surveyed countries was 30.5% and, on average, from 2011 onwards, it was increasing year by year. The percentage of female nesters was lower than the percentage of nesters among males. Young adult males very often emphasize the non-economic benefit as the reason for nesting, including the domestic value of living in a house, especially services provided by their mothers, such as cooking, cleaning, and washing [81].

The number of nesters in EU countries was the lowest in the Scandinavian countries, a higher level of the studied phenomenon was observed in the countries of western and southern Europe. This is the result of the emergence of different family ties in these countries, different public policies, and social welfare systems, as well as diversified infrastructure (e.g., labor and housing market, as well as educational opportunities) [82]. In Scandinavian society, autonomy is of great value and public support systems facilitate independence for young generations of the family [83]. In the Scandinavian model of social welfare, there are better conditions for young adults than in other European countries, making it easier for them to live independently [84]. These countries also show weaker family ties compared with other groups of European countries [85]. South European societies are characterized by strong family ties, hence young adults much more often postpone moving out of their family home [86]. They leave their parents late, marry late, and have children late (or at least later than in other European countries) [87]. In southern European countries, the family is the main source of support as social benefits are not significant [88]. When southern Europeans complete their educational career, they very frequently experience a period of instability, with several temporary contracts. Moreover, youth unemployment is currently highest in southern Europe [89].

The average age of young people leaving the parental household differs in the countries surveyed. In 2019, after the age of 30, young people from southern Europe left their nest, and those from northern Europe at the earliest, even before the age of 20. In the countries of Northern Europe there is a very generous social welfare system, young adults from these countries leave their family home earlier and start work relatively earlier [90]. In these countries, young adults are considered to be independent and responsible entities [91]. Hence, not only because of generous welfare transfers, but also because of the cultural perception of young adults as active and autonomous members of the society, youths enter the labor market and separate from the family of origin very early [90].

The research indicates that EU countries are strongly diversified in terms of the size of the nesting phenomenon and the age at which young adults leave their home. The research shows that the main factor influencing the decision to leave the family nest is the economic aspect relating both to the situation of the young person and the family [58]. The highest level in 2019 was recorded in three countries: Germany, the Netherlands and Slovenia, and the lowest—in Greece and Finland. A positive phenomenon is the taking up of professional activity by nesters. The percentage of working full-time nesters was similar in selected groups of countries, the highest in the group of eastern countries (60–77%), the lowest—in the Nordic group (42–56%). On the other hand, the highest percentage of unemployed persons was recorded in the southern group (19–37%). The exception is Malta with a very low percentage of unemployed persons. Moreover, all countries had a high percentage of employees with a permanent job (50–96%). The exception is Spain, where a lower percentage of employees with a permanent job was recorded. In Spain, temporary contracts are in most cases forced and less often end with a permanent job, which causes a feeling of greater uncertainty about the future financial situation and influences the decision to leave the family nest [92].

As our research proves, a high percentage of nesters are people with permanent employment. The highest percentage of employed nesters was recorded in four countries, including three from the north/western group: Luxembourg, Germany, and the Netherlands, and one country from the eastern group—Slovenia. At the same time, in these countries the percentage of unemployed nesters was at the lowest level in recent years. The results also indicate that in the case of two countries, i.e., the Netherlands and Slovenia, the situation of nesters on the labor market improved in the analyzed years. In these countries, the percentage of unemployed nesters has decreased, while the percentage of young adults having a job has increased. This was directly related to the improved economic situation in these countries, which was manifested by a decrease in the unemployment rate or an increase in the minimum wage. The highest proportions of unemployed nesters and a small proportion of nesters having employment were recorded in Greece (southern) and Finland (Nordic). This situation has been present in these countries for a long time and is related to the deteriorating economic situation in these countries in recent years.

Our study provides evidence that countries included in the geographically separated groups (Figure 3) are characterized by a different level in terms of the professional activity and employment status of young adults living with their parents. This means that it is not the geographical location, but social (family ties), institutional (state care), or economic conditions (the labor market and its conditions) that largely influence the decisions of young adult children to leave the family nest. The division of countries proposed by us may turn out to be very useful, in particular in studies taking into account the situation of young adults on the labor market during the COVID- 19 pandemic, and may constitute the basis for similar studies in the future.

Overall, our research has shown that in recent decades, young people in many countries have shown a tendency to stay at their parents’ home for longer periods of their lives. It is difficult to predict in which direction this social phenomenon will develop, considering the difficult situation of young people related to the COVID-19 pandemic and the deteriorating situation on the labor market. Therefore, further research on trends is needed, including comparative analyzes in the international context in the field of nesting, as there is still a lack of research relating to this very important social phenomenon.

Our research contributes to the existing literature by showing that the conditions in the labor market that are created for young adults can be a significant impulse to leave the family nest. They are also the basis for drawing conclusions that an appropriate labor market policy aimed at young adults is necessary to facilitate them leaving their family homes. Without effective measures to improve working conditions and pay, the independence of young European adults may be difficult in the near future.