Advertisement

Journal of Youth and Adolescence

, Volume 47, Issue 8, pp 1580–1594 | Cite as

Parental Support and Youth Occupational Attainment: Help or Hindrance?

  • Anna Manzoni
Empirical Research

Abstract

Although several concerns surround the transition to adulthood and youth increasingly rely on parental support, our knowledge about the implications of parental support for youth development and transition to adulthood is limited. This study fills this gap by conceptualizing development within a life course perspective that links social inequality and early life course transitions. It draws on a subsample of youth observed between age 18 and 28 from the Transition to Adulthood supplement of the Panel Study of Income Dynamics 2005–2015 (N = 7,542; 53% female, 51.3% white). Mixed-effects models reveal that the more direct financial transfers youth receive, the higher their occupational status. Yet, indirect financial support parents offer through co-residence shows the opposite pattern. Among youth receiving monetary transfers, college graduates have particularly high occupational status; however, among youth living with their parents, college graduates have the lowest occupational status. Although different types of parental support may equally act as safety nets, their divergent implications for youths’ occupational attainment raise concerns about the reproduction and possible intensification of inequality during this developmental stage.

Keywords

Parental support Youth development Occupational attainment Transition to adulthood Social inequality 

Introduction

Over the last few decades, concerns about the timing and patterns of youths’ transition to adulthood, particularly as it relates to economic independence and stability, have become widespread. The transition to adulthood represents a critical developmental stage, when previous socialization combines with current experiences to shape the future. During this stage the world of work offers unique experiences (Arnett 2004; Hamilton and Hamilton 2006), offering youth a main avenue to develop toward autonomy from their parents. However, the labor market has changed in ways that make acquiring consistent and well-paid employment challenging. Large-scale structural changes beginning in the 1970s have led to a shift toward a service economy and to job polarization (Kalleberg 2011). With more inconsistent and unstable employment relationships, older people are delaying retirement, contributing to younger people’s challenges in the job market (Kalleberg 2011). The Millennial generation—that is, those coming of age in the 2000s—face a uniquely problematic situation as the Great Recession of the late 2000s keenly affected them, as they graduated from high school and college into high unemployment rates (Edwards and Hertel-Fernandez 2010; Harrington et al. 2015). In addition, the rising importance of a college degree, which now yields unprecedented returns, and the consequent prolongation of education—with its costs and inequality among degree holders—translate into a new landscape for youth transitioning to adulthood (Roksa and Levey 2010).

While youth during this stage are more independent than children and adolescents, their parents still actively influence their career opportunities (Arnett 2004; Whiston and Keller 2004). For recent cohorts, the educational context and a dismal labor market situation have jointly contributed to protracting dependence on the family of origin (Buchmann and Solga 2016), and made support from parents increasingly necessary as young adults attempt to find their footing. This draws attention to the role of parental support to young-adult children as they transition to adulthood.

Parental support is subjected to high expectations (Goldscheider et al. 2001). Parents are regarded as having continued obligations toward their children, and young adults are now receiving substantial material assistance from their parents (Schoeni et al. 2005; Wightman et al. 2013). However, the debate about the implications of parental support during the transition to adulthood remains open. On the one hand, parental resources could foster successful youth development. Parental support may provide young adults with more concrete goals and better psychological well-being (Fingerman et al. 2012), possibly due to the security 'intense support' provides as young adults attempt to complete education or find stable, well-paying employment. In line with this perspective, help from parents may facilitate getting better jobs. On the other hand, parental assistance may further extend youths’ dependence on their parents and delay economic self-sufficiency; accordingly, it may disincentivize youth from holding demanding high-status jobs.

Yet, to date, attention to intergenerational support in the context of the transition to adulthood has been scarce. A rigorous and comprehensive examination of the interplay between parental support and young adults’ successful transition into the labor market is important as the United States recovers from the recession, the labor market becomes increasingly polarized into good and bad jobs, and economic inequality rises. Inequality in the capacities and resources of American parents (Lareau 2011; Schoeni et al. 2005) may mean that youth from different backgrounds receive different support while coping with institutionalized transitions, differ in their agentic capacities, and may be differently protected from unfavorable cumulative disadvantage (Bernardi 2014), transforming unequal childhoods into unequal adulthoods.

This study uses longitudinal data on a sample of Millennials drawn from the Panel Study of Income Dynamics (PSID, [dataset] 2017) to address the question of whether parental support hinders or facilitates youths’ transition to adulthood. Specifically, it examines the association between material support parents offer through monetary transfers and co-residence on the one hand and, on the other hand, young adults’ occupational status, a good indicator of their economic standing as they transition into adulthood (Torche 2015). Drawing on recent literature conceptualizing adolescent development within a life course framework that links the perspectives on social inequality and early life course transitions (Buchmann and Steinhoff 2017), this study offers several contributions to the literature on youth development and the transition to adulthood, as well as on social inequality. First, it is unprecedented in specifically assessing the effect of different types of parental material support on young adults’ occupational status. Second, it extends previous research that focused on the short-term effect of parental support on adolescents’ activities to investigate youths’ early occupational outcomes. As early occupational trajectories are critical to future development (Messersmith et al. 2008), this is particularly relevant. Third, as college education is a key means to occupational mobility, as well as a major reason for parental financial support, it explores differences across youth with different levels of education. Finally, it pays specific attention to family characteristics and models such effects in detail; this is particularly important as family financial, social, and cultural capital significantly explain parental assistance and the intergenerational transmission of occupational status.

Young Adults in the Current Labor Market

Success in work has been shown to be particularly crucial for youth well-being (Schulenberg et al. 2004) and marks important transitions in youth development (Luyckx et al. 2008). However, economic changes since the 1970s changed the occupational structure and work characteristics in the United States, leading to employment that is 'uncertain, unpredictable, and risky [for] the worker' (Kalleberg 2009: 2; Kalleberg 2011). Precarious work has been increasing for several decades, but the Millennial generation, who entered the labor market in the course of the Great Recession and the still-rebounding economy, is at particular risk (Harrington et al. 2015). Unemployment in the Great Recession was greatest for the age group 16–24, with historically high rates, over 18% (Bell and Blanchflower 2011; Bureau of Labor Statistics 2009). The overall economic shifts and the Great Recession have made it increasingly difficult to find stability in the labor market, especially for younger workers who became 'last hired [and] first fired' (Danziger and Ratner 2010). Consequently, young workers are now more likely to be in a job below their skill level, with little financial security. Lower level occupations may contribute to the loss of human capital, which may jeopardize returns to higher education and translate into permanent negative effects (Edwards and Hertel-Fernandez 2010). Many young adults also experience job churning or floundering, moving among a series of dead-end jobs or experiencing bouts of unemployment. Although some scholars argue that early job churning and floundering can lead to upward job mobility (e.g., Neumark 2002), or have no effect on late labor market experiences (e.g., Gardecki and Neumark 1998), others have found that it creates a scarring effect (Arulampalam et al. 2001; Krahn et al. 2015). At the same time, the increased costs of education, a particular burden to individuals from lower socio-economic backgrounds, further complicates young adults’ finances (Houle 2014).

Parental Support of Young Adults

Developmental psychologists often perceive the transition to adulthood as development toward independence as opposed to the tendency to rely on others, on parents in particular (Fousiani et al. 2014). However, as the path to adulthood grows longer, young people increasingly rely on their parents for support (Swartz et al. 2011; Waters et al. 2011), requiring their families to play a larger role in their transition to adulthood (Settersten and Ray 2010). Parental support is important for youths’ development and well-being (Levitt et al. 2007) and has been linked to positive mental health, social competence, self-esteem, academic achievement, and healthy peer relationships (McNeely and Barber 2010).

Recent literature has demonstrated that, particularly for college youth, occupational success largely depends on access to parental resources (Armstrong and Hamilton 2013). Parents who provide their children with intense attention and support in childhood continue to do so into adulthood (Fingerman et al. 2012). Such support may include monetary transfers (Wightman et al. 2012), co-residence (Mykyta 2012), social or cultural capital (Kim and Schneider 2005; Lareau 2011), as well as emotional support or advice.

As youth increasingly depend on their parents for support during their transition into adulthood and parents are more and more involved in their children’s transition to adulthood (Johnson and Benson 2012), socio-economic background and family context play an ever-greater role during this developmental stage. Depending on the resources they have available and are willing to transfer, families can vary substantially in the level and type of support they provide to young adults and the circumstances in which they provide it. Several factors affect parental support of their children. Recent research has shown that family socio-economic status and youth college attendance are the biggest predictors of parental assistance (Wightman et al. 2012). Higher status families are more likely to support their young-adult children (Cobb-Clark and Gørgens 2014), and parents provide significant help to their children pursuing higher education (Schoeni et al. 2005). Haider and McGarry (2012) have shown that parents determine cash transfers to their children based on children’s resources, providing more funds to children who earn less, rather than seeking to offset unequal contributions to siblings’ schooling with cash transfers. Parents may provide material support not only as direct cash transfers, but also indirectly by allowing young adults to live in their childhood homes for little or no rent. Looking at youths’ developmental pathway toward an adult status, Kins and Beyers (2010) highlighted how delayed home leaving can be an unfavorable living situation for youth transitioning to adulthood. Previous literature looking at co-residence and SES reported mixed results, with some researchers finding no differences by family SES (Garasky et al. 2001) and others showing different patterns in parental home leaving across SES, with inconsistencies in the direction of the relationship (De Marco and Berzin 2008; Tang 1997).

Research looking at the effects of parental support for young adults has mostly focused on human capital investments (e.g., Kalenkoski 2008; Kalenkoski and Pabilonia 2010; Keane and Wolpin 2001), showing that parental support is linked to college attendance (Charles et al. 2007), to successful transitions to higher education (Kim and Schneider 2005), as well as to postsecondary achievement (Hamilton 2013). Parents also act to compensate for the weakened association between parental origin and child’s educational and occupational outcomes (Ballarino and Bernardi 2016; Pöyliö et al. 2017). Occupational status is a good indicator of youths’ economic standing (Torche 2015). Earnings differences capture inequality effectively at the most disaggregate individual level; however, they are susceptible to fluctuations. Occupational status is less volatile and a good proxy for long-term economic well-being. This study contributes to our understanding of how individuals attain their occupational status by investigating the role of parental material support. Specifically, it looks at whether parents provide support to their children, the extent of that support, and differentiates between monetary transfers and co-residence. Furthermore, it pays attention to the role of education and thoroughly investigates family effects.

The Present Study

The central research question pertains to whether parental assistance fosters occupational attainment ('positive investment' hypothesis) or instead discourages and depresses it ('negative investment' hypothesis). The 'positive investment' perspective suggests that parental support may provide young adults a launching pad to develop a successful career. According to status attainment and human capital theories, parents use their resources to help their children, and parental support provides youth with distinct advantage (Osgood et al. 2005; Settersten and Ray 2010). Social resources—such as wealth, status, power, social ties—have been shown to have an important effect on occupational achievement (Lin et al. 1981) and recent literature has demonstrated that 'parental bridging' provides children of affluent parents with additional resources (Witteveen and Attewell 2017), which may facilitate accessing higher status jobs. Qualitative studies have also shown that parents use their means and networks to ensure their children take a successful career path (Armstrong and Hamilton 2013) and the resources available to youth may facilitate the transition from school to the labor market (Rivera 2015). Particularly for college youth, occupational success largely depends on access to parental financial, cultural, and social resources (Armstrong and Hamilton 2013; Hamilton 2016). Youth are increasingly dependent on involved parents to navigate college (Hamilton 2016) and intense parenting often leads to a better sense of goals and more satisfaction for adult children, especially if the support meets their needs (Fingerman et al. 2012). Access to parental resources may also allow children not to settle for low-paying jobs (Settersten and Ray 2010). Accordingly, we may expect that parental material support will be positively associated with youths’ occupational attainment (Hypothesis 1a). Such association may occur through multiple mechanisms. It may be simply due to investing, and material support could indicate general investment. Supportive parenting may also contribute directly to youth development by acting as a launching pad and allowing specific activities that facilitate occupational attainment. For example, support may allow youth to further develop their résumés with extracurricular activities and internships, wait for better jobs, or relocate where good jobs are. It may allow them to accept temporarily unpaid jobs leading to future opportunities, or may protect them from harmful effects of unemployment (Sirniö et al. 2016). Supportive behaviors may also exert a positive influence by buffering individuals from the negative consequences of stressful life events (McNeely and Barber 2010). Furthermore, a positive association may be due to mediating factors; specifically, education may play a major role in explaining a positive association, as elaborated below.

The 'negative investment' perspective suggests the possibility that parental support may be ineffective or even problematic. As parents have been increasingly expected to support their children further into the life course (Acocella 2008), concern about parental investment has grown together with the possibility that parental support may create an environment that does not motivate, encourage, facilitate, or require young adults to find good jobs. Parental support may alter financial responsibility, allowing youth to postpone adult statuses, like full-time employment, with unintended effects on their independence and their sense of entitlement (Danziger and Rouse 2007; Lareau 2011; Newman and Aptekar 2007). Perspectives stemming from rational choice theory suggest that parental support may create moral hazard by offsetting costs associated with low occupational performance. Parental help may also have unique characteristics distinguishing it from most other forms of assistance. It is often non-merit-based and may not be upheld to strict performance standards; consequently, it may not incentivize youth to get better jobs. Youth receiving support may underperform at work as they are less motivated due to anticipated economic security through parental support. Youth may instead direct more effort to work when they personally feel the economic costs of poor performance. In this context, youth receiving material support from their parents would behave differently compared to youth not receiving support, as they are differently exposed to the consequences of their behavior. Specifically, moral hazard theory would suggest that parental support provides a disincentive for youth to become self-sufficient, consequently extending youths’ dependence on their parents. Grown children may also feel less competent than those who are not supported (Smith and Goodnow 1999), and may be discouraged from gaining self-sufficiency. This view reflects popular concerns over increasing expectations of parental support, the resulting burden for parents, and the unintended consequences for their children. A competing hypothesis derived from this view is that parental material support will be negatively associated with youths’ occupational attainment (Hypothesis 1b).

Parents may provide material support in various forms and amounts. This study focuses on two major forms of material support: direct cash transfers and support provided through shared living arrangements. These two types of material support may be associated with youths’ occupational attainment by way of different mechanisms and may have different effects on youths’ occupational outcomes. For example, residential support may limit individuals to opportunities where parents reside, whereas direct monetary transfers may open further opportunities by allowing personal investments and residential mobility. Consequently, the positive and negative investment hypotheses may differently apply to each type of support.

It is also likely that parents’ resources affect youths’ occupational status through educational attainment. As the expansion of education and its increasing returns have been paralleled by skyrocketing costs, societal expectations and the structure of college financial aid presume that parents help their children to pay for their education, and education-related expenses are indeed a significant area of parental support (Wightman et al. 2012). At the same time, parental support may affect educational outcomes: it increases the likelihood of graduating from college, but can lower grades in college, as students tend to satisfice (Hamilton 2013). In turn, youth with a college degree enjoy much higher returns in the labor market compared to their high-school-educated counterparts (Autor et al. 2008). Furthermore, youth with and without college degree may differently benefit from parental support in terms of their occupational status as they may take advantage of the additional resources differently; those who get a degree use parental resources to build their human capital, which has specific benefits in terms of occupational attainment. In terms of residential support, parental resources may not be similarly employed and their provision may hinder further opportunity. Accordingly, the second research question pertains to the role of education in mediating or moderating the effect of parental support on occupational outcomes. This study will investigate whether parental support has a direct effect on occupational attainment, net of education, and whether the effect of parental support on occupational attainment holds equally for youth regardless of college attainment.

It is also possible that the association between material support and occupational attainment is not due to support per se, but is instead linked to other characteristics that parents giving support have. For example, parents of lower socio-economic status may choose co-residence over cash transfers, as residence sharing is cheaper than providing comparable support living apart. Parents’ resources also determine the advantages they offer, such as social capital and networks that may improve employment chances (Erikson and Jonsson 1998). Employers may also prefer social skills and personal characteristics useful in the workplace, and youth in advantaged households may acquire these more easily (Jackson 2007). Advantaged parents may also be able to help their children navigate career and employment processes, besides shaping their career aspirations. However, heterogeneity exists in the provision of aid for youth from similar backgrounds. Parents with limited resources may find strategies to provide more than expected, whereas parents who could afford to support their children may opt not to do so (Hamilton 2013). As the U.S. is characterized by a relatively underdeveloped welfare system, differences in access to parental resources and in their impact on youths’ success may reproduce and even amplify social inequality. Accordingly, the third research question refers to the role of family characteristics in explaining the relationship between parental support and youths’ occupational attainment.

Method

Data

This study draws on data from the PSID, collected by the University of Michigan. Starting in 2005, the Transition to Adulthood (TA) supplement of the PSID has been interviewing biennially a subset of young adults in families that had been followed since 1968. The TA draws on the Child Development Supplement (CDS) sample, which is a nationally representative sample of young adults who were between 0 and 12 years old in 1997. When youth in the CDS sample turned 18, they became eligible for the TA study if their family was still involved with the collection of the main PSID data, and remained eligible until they turned 28. Data collected between 2005 and 2015 are currently available and included in this study. The TA covers a broad array of issues that are important to the transition to adulthood, encompassing traditional markers of adulthood—education, employment, parental co-residence, marriage, and parenthood. In addition, information is collected about social relationships, time use, self-evaluations of responsibility, and aspirations for education and work, as well as detailed information on the receipt and value of financial assistance from parents. (McGonagle et al. 2012). Additionally, the timing of the TA data collection provides an important opportunity to explore the situation of the Millennial generation around the Great Recession. This study follows an initial sample of 2710 respondents over 10 years of data collection, for a total of 7542 observations at the times respondents were employed.

Measures

Occupational Attainment

The Nam-Powers-Boyd Occupational Status Scale (Nam and Boyd 2004) approximates the relative status of each job and social class position based on occupation. This scale builds on analysis of occupational status in the U.S. censuses and scores reflect the average education and income of incumbents of each detailed occupation, making it a valid indicator of socio-economic status and of the level of living. Values range from 1 to 100, with higher scores indicating higher occupational status.

Monetary Support

The TA questionnaire asks respondents whether they received help with a variety of costs, including rent, purchasing housing, car payments, tuition, miscellaneous bills or expenses, as well as personal loans, gifts and inheritances obtained in the past year, and the amount of each. Based on such questions, a categorical variable distinguishes between less than $5,000, between $5,001 and $14,999, and $15,000 or more, with no monetary support as reference category.

Residential Support

Based on respondents’ reports about their living situations, a dichotomous variable captures whether or not they spent most of a year living with their parents.

Control Variables

Age is captured by a continuous variable measured in years, gender by a dummy for female, and race by a dummy for non-white.1 A categorical variable defines level of education distinguishing between respondents with a college degree, those attending college, and those with no college experience. A time-varying variable controls for the number of siblings. As various aspects of the parents’ background matter (Johnson and Hitlin 2017), multiple variables account for family socio-economic background. A time-varying categorical variable denotes parental education, which has been shown to capture most of family variation in siblings’ occupation (Erola et al., 2016), distinguishing between whether neither parent had any college experience, at least one of the respondent’s parents had some college experience (but no degree), or at least one parent held a college degree. Parental occupation, measured at each time point with the Nam-Powers-Boyd Occupational Status Scale, accounts for the fact that occupations of parents and children are correlated. As parents’ occupational status is correlated with the extent of their financial transfers, controlling for it protects against omitted variable bias. A time-varying dummy indicates whether parents experienced unemployment in the previous year. As parents’ characteristics may matter in ways not fully channeled through contemporary factors (Johnson and Hitlin 2017), additional family controls comprise a time-constant dummy for whether or not respondents grew up with two married parents and a control for family income the year before respondents’ first interview.

Analytic Strategy

While the major interest is in occupational attainment, parental support is also likely to affect whether youth work in the first place, raising issues of social selection. If parental support is positively associated with the probability of employment, not accounting for selection would underestimate its positive effect on attainment. This could be the case if parents who provide more support have social networks that help their children to find a (good) job. However, if parental support is negatively related to the probability of employment, for example because it increases reservation wages, results may overestimate its positive association with attainment. To account for selection into employment, the following panel regression analyses rely on a two-step approach focusing on the role of parental support for getting a job in a first step, and for occupational attainment in a second step, with respondents’ marital and parental status, their parents’ expectations about their education, and calendar year as instruments. Missing data are treated using multiple imputation (by chained equation).2

To account for non-independent observations due to individuals being repeatedly measured, linear mixed models are used, which, through random effects, can handle the heterogeneity in model parameters across subjects, if it is due to stochastic sources (Baltagi 2013; Hsiao 2014; Wooldridge 2010). To start, a baseline model (Model 1) predicts occupational status for individual i at time t (OSti) based on parental support, separating between monetary support (MS) and residential support (RS), measured at t−1 (lagged paths). Next, additional predictors are added to account for individual and family related factors (Model 2a, 3a, and 3b). Such linear mixed models are estimated using maximum-likelihood (Allison 2009) and can be written as:
$$OS_{ti} = {\mathrm{\beta }}_0 + {\mathbf{\beta }}_j\,{\mathrm{MS}}_{\left( {t - 1} \right)i} + {\mathrm{\delta RS}}_{\left( {t - 1} \right)i} + {\mathrm{\lambda }}_jX_{ti} + {\mathrm{\mu }}_i + \varepsilon _{ti}$$
where OSti is the attainment of respondent i at time t, β0 is the overall mean across respondents, µi is the effect of individual i on attainment and εti is a time-varying error term. The person-specific (time-invariant) unobserved factor μ (random effect) is assumed to follow a normal distribution.

βj is the vector of coefficients of monetary support (one for each amount category), δ is the coefficient of residential support. λj is a vector of coefficients associated with the additional independent and control variables, not included in Model 1.

To establish a temporal order potentially along a causal effect of parental support on youths’ occupational attainment, parental support is measured at t−1. However, following Allison (2015), no lagged dependent variable is introduced as predictor. In many situations what happened at t−1 is one of the best predictors of what happens at t, including a lagged dependent variable in a mixed model usually leads to severe bias due to the violation of the assumption that the random intercept which represents the combined effect on y of all unobserved variables that do not change over time is independent of the other variables on the right-hand side (Allison 2015).

To test the specific role of education in explaining the effect of parental support on occupational status, Model 2b includes an interaction between each form of parental support and youths’ education. This allows the possibility that the effect of parental support on occupational status differs across youth with different education.

In estimating the effect of parental material support on youths’ occupational attainment, a major empirical challenge is to distinguish the role of support from the effect of other characteristics of the parents. As parents’ assistance depends on their own financial, social, and cultural capital (Schoeni et al. 2005; Wightman et al. 2012), the models outlined above attempted to isolate the role of parental support by accounting for all the other relevant, observed parental characteristics. However, this may not be enough to capture family effects. A major threat to estimating the effect of parental support is that parents influence their children’s achievement in several other ways, which may not be measured in a given data set. An alternative strategy is to estimate sibling effects models. Linear mixed models methods can easily be extended from two-level models to models with more levels with nested random effects, in which the random effects shared within lower level subgroups are unique to the upper-level groups. Individuals, who are observed repeatedly over time, are also nested within families. Mixed effect models allow to analyze the effect of unobserved family characteristics, minimizing the possibility that estimated differences between individuals result from a prior sorting process or from unobserved sibling-invariant parental characteristics. Such models hold sibling-invariant unobserved family characteristics constant, providing a control for those factors that are permanent features of families or that are present in the family for each of the children being examined but are not explicitly examined in the statistical model. Such uncontrolled factors in the models may include family values or aspirations for the children, parental skills not captured by educational variables included in the models, or the emotional well-being of the parents.

Three-level models (Model 5 and 6) are estimated on the subsample of siblings and can be written as:
$$OS_{tik} = {\mathrm{\beta }}_0 + {\mathbf{\beta }}_{\mathrm{j}}\,{\mathrm{MS}}_{\left( {t - 1} \right)ik}{\mathrm{ + \delta }}\,{\mathrm{RS}}_{\left( {t - 1} \right)ik}{\mathrm{ + \lambda }}_jX_{tik}{\mathrm{ + }}\upsilon _{\mathrm{k}}{\mathrm{ + \mu }}_{{\mathrm{0}}ik}{\mathrm{ + }}\varepsilon _{tik}$$
OStik is the observed attainment at time t for respondent i in family k, β0 is the mean score across all families, ʋk is the effect of family k, µik is the effect of individual i, and εtik is the time-varying residual error term. The family, individual effects and the time level residual errors are assumed independent and normally distributed with zero means and constant variances. Such models decompose the total variance in occupational attainment into separate family, individual, and observation variance components. As above, βj is the vector of coefficients of monetary support, δ is the coefficient of residential support and, for models including extra predictors, λj is a vector of coefficients associated with the additional independent and control variables.

Throughout the text, estimates are not interpreted as causal effects, which would require relying on strong and untestable assumptions. Instead, the focus is on describing how parental support in the form of co-residence and monetary transfers is associated with young people’s occupational status.

Results

Descriptive Results

Descriptive results in Table 1 show that in over half of the observed years respondents receive monetary support from their parents, and even more receive support through co-residence. Significant differences emerge in youths’ occupational status depending on the level and type of support they receive: those getting high monetary transfers (over $15,000/year) have an occupational status over 5 points higher than those receiving no or little (below $5,000/year) monetary support. Conversely, the occupational status of youth receiving residential support is about 10 points lower than that of youth living independently.
Table 1

Descriptive results. Sample distribution and youth occupational status

 

%

Mean [SD]

Range

(Average) Occupational status

Parents/ Family context characteristics

Parents education

No college

44.8

  

32.2

College experience

45.0

  

39.1

College degree

10.0

  

46.1

Parents occupational status

 

49.7 [29]

0–99

 

Family income ($)

 

80,314 [99,000]

0–2,133,500

 

Parents unemployed in past year

No

90.0

  

37.3

Yes

10.0

  

31.4

Two parents household

No

47.0

  

33.0

Yes

53.0

  

39.9

Number of siblings

 

0.65 [0.9]

0–7

 

Youth characteristics

Education

No college

37.9

  

29.8

In College

43.0

  

34.8

College Degree

19.1

  

54.7

Age

 

22.1 [2.6]

18–28

 

Gender

Men

47.0

  

35.9

Women

53.0

  

37.4

Race

Whites

51.3

  

40.2

Non Whites

48.7

  

33.1

 

%

Variance within/between

(Average) occupational status

Parental Support

Monetary transfers

 

0.65/0.38

 

No transfers (0)

45.1

 

35.9

Up to $5,000 (1)

31.0

 

35.1

$5,000–15,000 (2)

12.3

 

39.5

Over $15,000 (3)

11.6

 

41.4

Residential support

 

0.16/0.08

 

No (0)

41.0

 

42.3

Yes (1)

59.0

 

32.9

N-individuals

2,710

  

N-observations

7,542

  

Such findings dovetail with previous literature suggesting that residential support may inadvertently have the effect of limiting geographic mobility and access to thriving labor markets. Residential support may reflect parental inability to provide the type of cash transfers that would allow geographic mobility, and college-educated youth, in particular, need to get to where (good) jobs are in order to obtain suitable returns to their human capital (Hamilton 2013; Settersten and Ray 2010).

Models Results

To account for possibly spurious effects, Table 2 shows the results from panel regression analysis.3 Findings support the hypothesis that more is more in terms of the relation between parents’ monetary support and youths’ future occupational status: receiving cash transfers is associated with higher occupational status, and the higher the transfers, the higher youths’ later occupational status.
Table 2

Estimates from mixed-effects models predicting occupational status

 

Model 1

Model 2a

Model 2b

Model 3a

Model 3b

Parental Support

Amount monetary transfers (t−1):

     

No transfers (ref cat)

     

Up to $5000

0.393

−0.086

−0.241

0.974

0.502

$5,000–15,000

1.974*

0.716

1.437

1.955*

0.825

Over $15,000

5.962**

3.580***

−0.026

4.887**

3.233**

Up to $5000* In College

  

−1.489

  

Up to $5000* College degree

  

2.921

  

$5,000–15,000* In College

  

−1.219

  

$5,000–15,000* College degree

  

0.013

  

Over $15,000* In College

  

1.358

  

Over $15,000* College degree

  

7.509**

  

Co-residence (t−1)

−6.511**

−3.857***

−3.517**

−1.639**

−1.818**

Co-residence (t−1)* In College

  

1.811

  

Co-residence (t−1)* College degree

  

−3.032*

  

Education: No College (ref cat)

In College

 

3.672***

3.258*

4.972**

3.228**

College Degree

 

18.570***

18.122**

16.223**

12.543**

Age

   

1.613**

1.667**

Race (White: ref cat)

   

−3.225**

0.136

Gender (Male: ref cat)

   

−0.181

0.433

Parents education: No college (ref cat)

College experience

    

2.154**

College degree

    

4.312**

Parents occupational status

    

0.021

Family income (in 1000$)

    

0.015**

Parents unemployed in past year

    

−2.287*

Two parents household

    

1.588*

Number of siblings

    

−1.309**

Inverse mills ratios

−54.481**

−21.803**

−20.614**

−21.624**

−35.588**

Intercept

52.275**

39.39***

39.270**

1.348

−0.920

Log-Likelihood

−21245.35

−21015.92

−21003.06

−20943.67

−20890.36

variance between individuals in families

36.47

34.96

34.59

35.91

35.10

variance between observations

63.53

65.04

65.41

64.09

64.90

N

4832

4832

4832

4832

4832

The number of observations is reduced to 4832 as no lagged values are observed at t1

ref cat Reference category

* p < 0.05; ** p < 0.01; *** p < 0.001

Table 3

Estimates from mixed-effects models predicting occupational status for siblings

 

Model 4

Model 5

Model 6

Parental Support

Amount monetary transfers (t−1):

No transfers (ref cat)

   

Up to $5000

1.518

1.273

1.543

$5,000–15,000

4.180**

3.873**

3.191**

over $15,000

6.380**

5.734**

3.745**

Co-residence (t−1)

−6.797**

−6.806**

−1.875*

Education: No College (ref cat)

In College

  

3.501**

College Degree

  

11.269**

Age

  

1.933**

Race (White: ref cat)

  

1.004

Gender (Male: ref cat)

  

−0.655

Parents education: No college (ref cat)

College experience

  

1.881

College degree

  

4.854**

Parents occupational status

  

0.025

Family income (in 1000$)

  

0.018**

Parents unemployed in past year

  

−2.914*

Two parents household

  

1.781

Number of siblings

  

−1.298**

Inverse mills ratios

−54.910**

−52.430**

−38.316**

Intercept

51.728**

51.489**

−7.660

Log-Likelihood

−12893.21

−12881.85

−12654.30

variance between families

 

13.23

7.59

variance between individuals in families

33.09

20.25

25.59

variance between observations

66.91

66.52

66.82

N

2932

2932

2932

Note: ref cat = Reference category. The sample size is reduced to 2932 as only cases in which at least two children in a family are included.

* p < 0.05; ** p < 0.01

Results from the baseline model reveal that those receiving $15,000 or more display an occupational status almost 6 points higher than those not receiving any direct financial support. Such advantage decreases just slightly (to about 5 points) and remains statistically significant when controlling for a series of individual socio-demographic characteristics (Model 3a). Even when controlling for socio-economic and other family observed variables (Model 3b), the effect remains strong and statistically significant. Residential support, by contrast, is associated with lower occupational status than living independently. The baseline model reveals that those who live with their parents report on average an occupational status 6.5 points lower than those who do not; when adding controls, such disadvantage decreases to less than 2 points but remains significant.

To address the second research question about the role of education, two steps are taken. First, Model 2a isolates the effect of education from other factors, by adding education to the baseline. A likelihood ratio test confirms a significant model improvement. Controlling for education, occupational status remains positively associated with monetary transfers and negatively associated with co-residence, although effects are smaller in size, indicating that education partly mediates the association between parental support and occupational status. Second, Model 2b tests whether education moderates the association between parental support and occupational status. Results show that the association between parental support and occupational status is significantly stronger for college graduates. While college for graduates higher monetary transfers are associated with higher occupational status, no such evidence emerges for youth with no college. However, residential support operates differently. Specifically, residential support is significantly more strongly negatively associated with occupational attainment for college graduates than for non-college graduates.

To account for the effect of parental influence not captured by the observed variables, additional models focus on siblings and control for the effect of unobserved family characteristics. Controlling for sibling-invariant unobserved constant family characteristics provides a measure of the variance at the family level. The sample size is reduced to 2932 as only cases where at least two children in a family were included. Model 4 reproduces Model 1 on the selected subsample of siblings, confirming that occupational status is positively associated with parents’ monetary transfers and negatively associated with co-residence. Model 5 introduces a family effect in the model. The likelihood ratio test statistic gives evidence of family effect and confirms that youth from the same family are significantly more alike than youth from different families. Furthermore, Model 5 reveals that about 13% of the variance in occupational attainment can be attributed to differences between families, while about 20% can be attributed to variance between individuals within families. The remaining variation (66.5%) in occupational attainment lies between observations. Model 6 adds all the individual and family level observed characteristics. Results confirm the positive relation between occupational attainment and monetary support and the negative relation between occupational attainment and co-residence (Table 3).

Additional Analyses

Several steps were taken to ensure findings were robust. Overall, the robustness of the findings to the sensitivity checks and analyses replications determined confidence in answering the research questions above. First, the sensitivity of the findings to several measurement decisions was examined, focusing on different operationalizations of support. Initially, a dichotomous measure of monetary support was used; however, this appeared to be an oversimplification as more detailed differentiation of the amount of support revealed it is not simply receiving any financial support which matters; instead, higher amount of support in particular are strongly and significantly associated with occupational attainment. The choice of categories for the amount of monetary support was the result of several steps checking for different operationalizations, including power polynomials, logarithmic transformation and higher number of subcategories. Further distinction below $15,000 added no explanatory power.

While the models above account for the possibility that individuals receive both types of support, additional analyses were performed to investigate the possibility that the effect of one type of support differs depending on the effect of the other type. Models (results available upon request) including multiplicative effects between monetary support and co-residence suggested that the negative effect of residential support on occupational attainment may be particularly strong when co-residence is combined with monetary transfers; however, the positive effect of direct financial support seemed to be reduced when youth lived with their parents.

Sensitivity analyses also explored multiple strategies for capturing family background, including adding each indicator separately. All the alternatives for capturing family background showed similar effects, for all the indicators, suggesting their independent and non-spurious effects. Alternative specifications of youth education were examined, including distinguishing respondents without any college experience from those with some college but no degree; results confirmed that the findings about the effect of a college degree were robust to such alternatives

In addition, in order to further investigate the effect of parental support net of education, a model was estimated looking at the relationship between parental support and occupational status specifically for youth currently not involved in higher education, while controlling for their achieved level of education. Results from this model are shown in Table 4 (Model 7), and confirm a strong and significant effect of high amounts of parental monetary support and a strong negative effect of co-residence on occupational status.
Table 4

Estimates from mixed-effects models predicting occupational status for youth not in education (Model 7) and youth continuously employed (Model 8)

 

Model 7:

Not in education

Model 8:

Continuously employed

Parental Support

Amount monetary transfers (t−1):

  

No transfers (ref cat)

  

Up to $5,000

1.281

0.458

$5,000–15,000

0.466

1.104

Over $15,000

3.935**

2.799*

Co-residence (t−1)

−2.133**

−2.343**

Education: No College (ref cat)

In College

 

3.155**

College Degree

16.458**

13.405**

Age

1.350**

1.388**

Race (White: ref cat)

−0.594

0.223

Gender (Male: ref cat)

2.082*

−0.028

Parents education: No college (ref cat)

College experience

2.762**

2.202*

College degree

4.662*

4.220**

>Parents occupational status

0.013

0.017

Family income (in 1000$)

0.011*

0.013*

Parents unemployed in past year

−2.827*

−1.923

Two parents household

1.656

1.894

Number of siblings

−1.697**

−1.377**

Inverse mills ratios

−22.278**

−35.440**

Intercept

3.688

6.343

N

2434

3414

N is reduced to 2434 in model 7 since only respondents in education are included and to 3414 in model 8 since only respondents continuously employed in the past 2 years are include

ref cat reference category

* p < 0.05; ** p < 0.01

As high variation may exist in the quality and quantity of youths’ employment, supplemental analyses were performed to isolate more stable and permanent employment by focusing on the subsample of youth who were continuously employed in the previous two years.4 Results in Table 4 (Model 8) confirm a strong and significant effect of high amounts of parental monetary support and a strong negative effect of co-residence on occupational status for this subsample.

Discussion

In the face of difficult economic times, changes in the occupational structure, and overall worsening employment prospects, concerns about the occupational attainment of the millennial generation have been rising. At the same time, norms regarding parental support to their young-adult children have shifted. Parents are often expected to support their children indefinitely and young adults often receive substantial material support from their parents. This study filled a gap in our knowledge about the consequences of parental material support by investigating its implications for their children’s occupational success.

The study’s findings suggest that intergenerational support is related to the youths' occupational success. The more monetary transfers youth receive during their transition to adulthood, the higher their subsequent occupational status. Financial support seems particularly advantageous for youth who pursue a college education. For youth without college experience, effects are not significant, which may reflect the circumstances and reasons triggering support for this group. Co-residence with parents, instead, is associated with lower occupational attainment. In light of recent research suggesting that residential segregation could limit labor market opportunities (Gregg et al. 2017), one potential explanation for the different implications of residential support compared to direct monetary transfers is that the former constrains individuals to opportunities where parents reside. Direct monetary transfers, instead, support other types of activity, such as personal investments and residential mobility. Unfortunately, the data do not allow to test those potential explanations, but this could be an interesting avenue for future research.

The study’s results also reveal differences across youth with different involvement in higher education, shedding light on the role of education in explaining the effect of intergenerational support on occupational attainment; in this way, this study contributes to our understanding of how inequality is reproduced more broadly. This is particularly interesting as recent literature has questioned widespread ideas of the United States as a country where the role of ascription is limited and meritocratic stratification prevails (Gregg et al. 2017), showing that intergenerational income association is not primarily channeled via education. Furthermore, youths’ education, besides triggering parental support, partly shapes youths’ occupational attainment. College partly mediates the effect of parental monetary assistance; however, the effect of parental monetary support remains even controlling for its role in children’s college enrollment and attainment. One explanation may be that monetary transfers partly capture the effect of social networks. Alternatively, they may support other investments that lead to better jobs.

By analyzing status passages in the institutional life course, this study also emphasizes the significance of social inequality in the analyses of youth transition to adulthood, raising concerns on several fronts. The fact that young adults’ occupational success is associated with parental material support suggests that the differential ability of parents to support their adult children will reproduce inequality into the next generation. Parents may have different constraints, which affect both the ways and the extent to which they may support their children. Although any form of support may act as a safety net, these results raise concerns about how the forms and extent of parental support may perpetrate or exacerbate old inequalities or even produce new ones. Considering the crucial developmental changes occurring during the transition to adulthood, such findings highlight the importance of intergenerational processes facilitating (or hindering) youth development and contribute to better understand them.

Some limitations should be acknowledged. First, despite all precautions, the threat of reverse causation remains and the results presented here cannot be interpreted as causal evidence of an effect of parental support on youths’ occupational status. The use of lagged-variables allows us to account for temporal order in the relationship between parental financial support and young adults’ occupational status. However, a causal test would need to address endogeneity concerns due their simultaneity (i.e., reverse causality). In fact, while the hypotheses above refer to different ways in which support may affect attainment, the reverse may also occur, and youths’ status may prompt parental response. Parents may use their resources to compensate their children’s negative prospects when context or personal characteristics may compromise the desired occupational outcome (Pöyliö et al. 2017). According to Cox’s (1990) liquidity constraint argument, transfers are made in response to short-term income fluctuations (McGarry 2000). Furthermore, young-adult children facing particularly challenging situations may elicit greater support. For example, the onset of children’s ill health increases the amount they receive (Hurd et al. 2011), and events such as marriage, buying a house, or becoming a parent trigger parental transfers (Leopold and Schneider 2011). Accordingly, youth in suboptimal occupational conditions may prompt their parents to help them. Conversely, parents may give support to reward young adults’ achievements.

Second, limitations remain in the account of family effects. Sibling models allow to control for permanent family components. However, they do not allow to account for unobserved varying family variables. If parents treat children differently for unobserved reasons, results may be biased. Furthermore, the threat of unobserved sibling heterogeneity, due for example to individual ability and ambition, remains. Notwithstanding their advantages, such models may also produce another type of selection bias, as they require analyzing families with more than one child. This may sort families by cultural and class backgrounds.

Third, differences may exist based on the characteristics of youths’ employment. For example, some youth may be marginally employed, whereas others may be in stable, full-time, and permanent employment. Data constraints prevented the possibility to control for such differences. However, isolating youth with more stable and permanent employment by looking at those who were continuously employed during the previous two years confirmed the results for the whole sample, suggesting that findings are not specific to youth in particular employment situation.

Lastly, Although this study focused on the effect of receiving support, its form and amount, support may affect youth during their transition to adulthood not only through its presence or amount, but also through its persistence. While this goes beyond the scope of this study, this represents an interesting avenue for future research.

Conclusion

This study contributes to knowledge about intergenerational processes related to youth development by investigating the relation between parental transmission of resources and youths’ attainment. In line with life-course perspectives conceptualizing human development as the dynamic interaction between a changing individual and a changing context (Conger and Donnellan 2007; Elder and Shanahan 2006; Sameroff and Mackenzie 2003), it sheds light on how parents can contribute to youth development as well as how inequality may be transmitted. Higher interdependence of recent generations of families compared to previous ones translates into higher importance of parental influences in developing well-being among their children (Bengston et al. 2002), making the study of a recent cohort of youth a particularly relevant contribution. Aligning with previous research suggesting to incorporate parental provision of money and things in parenting frameworks to strengthen our understanding of youth development (McNeely and Barber 2010), this study pays attention to the association of different types of parental material support with youths’ occupational status. By capitalizing on longitudinal data, it extends previous research looking at the short-term effect of parental support on adolescents’ activities to investigate youths’ early occupational outcomes, which is critical to the transition to adulthood (Messersmith et al. 2008). In this way, it further contributes to our understanding of youth development, by framing it in a life course perspective, recognizing its connection to individual circumstances providing resources, as well as its embeddedness in the social structural and institutional context. The findings show that the more monetary support youth receive during their transition to adulthood, the higher their subsequent occupational status. Residential support reveals a very different picture: earlier co-residence is associated with lower occupational status later. This dovetails with previous research showing that the developmental process of transitioning to adulthood is connected to the living arrangements; independent living is associated with an accelerated attainment of certain criteria for adulthood, whereas continued co-residence with parents seems to stunt this process (Kins and Beyers 2010). Accordingly, supporting children by providing a shared residence may be detrimental to their occupational attainment. Success in work represents a major criteria for adulthood, and is positively related to young adults’ well-being (Schulenberg et al. 2004; Luyckx et al. 2008); developmental scholars are therefore encouraged to pay attention to the potentially harmful implications prolonged co-residence may have during this stage of life, as well as to inequality possibly deriving from intergenerational financial support.

Footnotes

  1. 1.

    Due to the very limited number of non-white non-black cases, a more detailed categorization is not feasible.

  2. 2.

    The 'mi impute chained' command in Stata 14 (StataCorp 2015) was used to impute missing values due to item non-response for occupational status, residential support, number of siblings, job expectations, parental unemployment, parental occupation, family income, race, and parental education. Missingness due to a lack of t-1 values at t1 did not involve imputation; instead, those missing cases were listwise deleted. Independent variables taken into account for generating imputed data include gender, age, race, education, marital and childbearing status, and financial support.

  3. 3.

    The number of observations is reduced to 4832 as no lagged values are observed at t1.

  4. 4.

    The information about continuous employment was derived by transforming the biyearly data into a person-month format, accounting for employment status in each month and calculating the proportion of time each respondent was employed between interview waves.

Notes

Acknowledgements

The author thanks participants to the Center for Social Inequality Studies Brownbag series at the University of Trento, as well as Sergi Vidal and Toby Parcel for comments on earlier drafts of this paper.

Funding

The collection of data used in this study was partly supported by the National Institutes of Health under grant number R01 HD069609 and the National Science Foundation under award number 1157698. No support for this specific research was received by the author.

Data Sharing Declaration

The datasets generated and/or analyzed during the current study are available in the Open ICPSR repository, https://www.openicpsr.org/openicpsr/project/101421/version/V2/view

Compliance with ethical standards

Conflict of interest

The author declare that she has no conflict of interest.

Ethical Approval

The author certifies compliance with the Committee on Publications Ethics listed on the Journal of Youth and Adolescence website. This manuscript has not been published and is not under consideration with any other publication.

References

  1. Acocella, J. (2008). The child trap: The rise of over-parenting. The New Yorker: Books, November 17. www.newyorker.com/arts/critics/books/2008/11/17/081117crbo_books_acocella New York: Google Scholar.
  2. Allison, P. D. (2009). Fixed effects regression models (Vol. p160). Thousand Oaks, CA: SAGE publications.Google Scholar
  3. Allison, P. D. (2015). Don’t put lagged dependent variables in mixed models. Statistical Horizon Blog, June 2, 2015: https://statisticalhorizons.com/lagged-dependent-variables.
  4. Armstrong, E. A., & Hamilton, L. T. (2013). Paying for the Party. Cambridge, MA: Harvard University Press.Google Scholar
  5. Arnett, J. J (2004). Emerging adulthood: The winding road from the late teens through the twenties. New York, NY: Oxford University Press.Google Scholar
  6. Arulampalam, W., Gregg, P., & Gregory, M. (2001). Unemployment scarring. The Economic Journal, 111(475), 577–584.CrossRefGoogle Scholar
  7. Autor, D. H., Katz, L. F., & Kearney, M. S. (2008). Trends in US wage inequality: revising the revisionists. The Review of Economics and Statistics, 90(2), 300–323.CrossRefGoogle Scholar
  8. Ballarino, G. & Bernardi, F. (2016). The intergenerational transmission of inequality and education in fourteen countries: a comparison. In F. Bernardi & G. Ballarino (Eds.), Education, occupation and social origin: Acomparative analysis of the transmission (pp. 255–282). Cheltenham, UK: Edward Elgar Publishing.Google Scholar
  9. Baltagi, B. H. (2013). Econometric Analysis of Panel Data (5th ed.). New York, NY: John Wiley & Sons.Google Scholar
  10. Bell, D., & Blanchflower, D. G. (2011). Young people and the Great Recession. Oxford Review of Economic Policy, 27(2), 241–267.CrossRefGoogle Scholar
  11. Bengston, V. L., Biblarz, T. J., & Roberts, R. E. L. (2002). How families still matter: A longitudinal study of youth in two generations. New York, NY: Cambridge University Press.Google Scholar
  12. Bernardi, F. (2014). Compensatory advantage as a mechanism of educational inequality: A regression discontinuity based on month of birth. Sociology of Education, 87(2), 74–88.CrossRefGoogle Scholar
  13. Buchmann, M., & Solga, H. (2016). School-to-work transitions across time and place—Introduction and summary. Research in Social Stratification and Mobility, 46, 1–2.CrossRefGoogle Scholar
  14. Buchmann, M., & Steinhoff, A. (2017). Social inequality, life course transitions, and adolescent development: Introduction to the special issue. Journal of Youth and Adolescence, 46(10), 2083–2090.CrossRefPubMedGoogle Scholar
  15. Bureau of Labor Statistics (2009). U.S. Department of Labor. Employment and unemployment among youth—summer 2009. News. https://www.bls.gov/news.release/archives/youth_08272009.pdf.
  16. Charles, C., Roscigno, V. J., & Torres, K. C. (2007). Racial inequality and college attendance: The mediating role of parental investments. Social Science Research, 36(1), 329–352.CrossRefGoogle Scholar
  17. Cobb-Clark, D. A., & Gørgens, T. (2014). Parents’ economic support of young-adult children: Do socio-economic circumstances matter? Journal of Population Economics, 27(2), 447–471.CrossRefGoogle Scholar
  18. Conger, R. D., & Donnellan, M. B. (2007). An interactionist perspective on the socioeconomic context of human development. Annual Review of Psychology, 58, 175–199.CrossRefPubMedGoogle Scholar
  19. Cox, D. (1990). Intergenerational transfers and liquidity constraints. The Quarterly Journal of Economics, 105(1), 187–217.CrossRefGoogle Scholar
  20. Danziger, S., & Ratner, D. (2010). Labor market outcomes and the transition to adulthood. The Future of Children, 20(1), 133–158.CrossRefPubMedGoogle Scholar
  21. Danziger, S., & Rouse, C. E., (2007). The Price of Independence: The Economics of the Transition to Adulthood. New York: Russell Sage Foundation.Google Scholar
  22. De Marco, A., & Berzin, S. C. (2008). The influence of family economic status on home-leaving patterns during emerging adulthood. Families in Society: The Journal of Contemporary Social Services, 89(2), 208–218.CrossRefGoogle Scholar
  23. Edwards, K. A., & Hertel-Fernandez, A. (2010). The kids aren't alright: A labor market analysis of young workers. Washington, DC: Economic Policy Institute.Google Scholar
  24. Elder, G. & Shanahan, M. (2006). The life course and human development. In: In W. Damon, R. M. Lerner(eds.) The handbook of child psychology. (vol. 1. 665–715). New York, NY: Wiley.Google Scholar
  25. Erikson, R., & Jonsson, J. O. (1998). Social origin as an interest-bearing asset: Family background and labour-market rewards among employees in Sweden. Acta Sociologica, 41(1), 19–36.CrossRefGoogle Scholar
  26. Fingerman, K. L., Cheng, Y., Wesselman, E. D., Zarit, S., Furstenberg, F., & Birditt, K. S. (2012). Helicopter parents and landing pad kids: Intense parental support of grown children. Journal of Marriage and Family, 74(4), 880–896.CrossRefPubMedGoogle Scholar
  27. Fousiani, K., Van Petegem, S., Soenens, B., Vansteenkiste, M., & Chen, B. (2014). Does parental autonomy support relate to adolescent autonomy? An in-depth examination of a seemingly simple question. Journal of Adolescent Research, 29(3), 299–330.CrossRefGoogle Scholar
  28. Garasky, S., Haurin, R. J., & Haurin, D. R. (2001). Group living decisions as youths transition to adulthood. Journal of Population Economics, 14(2), 329–349.CrossRefGoogle Scholar
  29. Gardecki, R., & Neumark, D. (1998). Order from chaos? The effects of early labor market experience on adult labor market outcomes. Industrial and Labor Relations Review, 51(2), 299–322.CrossRefGoogle Scholar
  30. Gregg, P., Jonsson, J. O., Macmillan, L., & Mood, C. (2017). The role of education for intergenerational income mobility: A comparison of the United States, Great Britain, and Sweden. Social Forces, 96(1), 121–152.CrossRefGoogle Scholar
  31. Goldscheider, F. K., Thornton, A., & Yang, L. (2001). Helping out the kids: Expectations about parental support in young adulthood. Journal of Marriage and Family, 63(3), 727–740.CrossRefGoogle Scholar
  32. Haider, S. J. & McGarry, K. (2012). Parental investments in college and later cash transfers. Cambridge, MA: The National Bureau of Economic Research. https://msu.edu/~haider/Research/WP-transfers.pdf.
  33. Hamilton, L. T. (2013). More is more or more is less? Parental financial investments during college. American Sociological Review, 78(1), 70–95.CrossRefGoogle Scholar
  34. Hamilton, L. T. (2016). Parenting to a Degree: How Family Matters for College Women's Success. Chicago, IL: University of Chicago PressGoogle Scholar
  35. Hamilton, S. F., & Hamilton, M. A. (2006). School, work, and emerging adulthood. In J. J. Arnett & J. L. Tanner (Eds.), Emerging adults in America: Coming of age in the 21st century (pp. 257–277). Washington, DC: American Psychological Association.CrossRefGoogle Scholar
  36. Harrington, B. Van Deusen, F., Sabatini Fraone, J., & Morelock, J. (2015). How millennials navigate their careers: Young adult views on work, life and success. https://www.bc.edu/content/dam/files/centers/cwf/research/publications/researchreports/How%20Millennials%20Navigate%20their%20Careers.
  37. Hsiao, C. (2014). Analysis of Panel Data. 3rd Edition London: Cambridge, UK: Cambridge University Press.CrossRefGoogle Scholar
  38. Houle, J. N. (2014). A generation indebted: Young adult debt across three cohorts. Social Problems, 61(3), 448–465.CrossRefGoogle Scholar
  39. Hurd, M., Smith, J. P., & Zissimopoulos, J. (2011). Intervivos giving over the lifecycle. RAND Working Paper Series No. WR-524-1. https://ssrn.com/abstract=1022215.
  40. Jackson, M. (2007). How far merit selection? Social stratification and the labour market. The British Journal of Sociology, 58(3), 367–390.CrossRefPubMedGoogle Scholar
  41. Johnson, M. K., & Benson, J. (2012). The implications of family context for the transition to adulthood. In A. Booth, S. L. Brown, N. S. Landale, W. D. Manning & S. M. McHale (Eds.), Early adulthood in a family context (pp. 87–103). New York, NY: Springer.CrossRefGoogle Scholar
  42. Johnson, M. K., & Hitlin, S. (2017). Adolescent agentic orientations: contemporaneous family influence, parental biography and intergenerational development. Journal of Youth and Adolescence, 46(10), 2215–2229.CrossRefPubMedGoogle Scholar
  43. Kalenkoski, C. (2008). Parent–child bargaining, parental transfers, and the post-secondary education decision. Applied Economics, 40(4), 413–436.CrossRefGoogle Scholar
  44. Kalenkoski, C. M., & Pabilonia, S. W. (2010). Parental transfers, student achievement, and the labor supply of college students. Journal of Population Economics, 23(2), 469–496.CrossRefGoogle Scholar
  45. Kalleberg, A. L. (2009). Precarious work, insecure workers: Employment relations in transition. American Sociological Review, 74(1), 1–22.CrossRefGoogle Scholar
  46. Kalleberg, A. L. (2011). Good jobs, bad jobs: The rise of polarized and precarious employment systems in the United States, 2000. New York, NY: Russell Sage Foundation.Google Scholar
  47. Keane, M. P., & Wolpin, K. I. (2001). The effect of parental transfers and borrowing constraints on educational attainment. International Economic Review, 42(4), 1051–1103.CrossRefGoogle Scholar
  48. Kim, D. H., & Schneider, B. (2005). Social capital in action: Alignment of parental support in adolescents’ transition to postsecondary education. Social Forces, 84(2), 1181–1206.CrossRefGoogle Scholar
  49. Kins, E., & Beyers, W. (2010). Failure to launch, failure to achieve criteria for adulthood? Journal of Adolescent Research, 25(5), 743–777.CrossRefGoogle Scholar
  50. Krahn, H. J., Howard, A. L., & Galambos, N. L. (2015). Exploring or floundering? The meaning of employment and educational fluctuations in emerging adulthood. Youth & Society, 47(2), 245–266.CrossRefGoogle Scholar
  51. Lareau, A. (2011). Unequal childhoods: Class, race, and family life. Berkeley, CA: University of California Press.Google Scholar
  52. Leopold, T., & Schneider, T. (2011). Family events and the timing of intergenerational transfers. Social Forces, 90(2), 595–616.CrossRefGoogle Scholar
  53. Levitt, M. J., Silver, M. E., & Santos, J. D. (2007). Adolescents in transition to adulthood: Parental support, relationship satisfaction, and post-transition adjustment. Journal of Adult Development, 14, 53–63.CrossRefGoogle Scholar
  54. Lin, N., Vaughn, J. C., & Ensel, W. M. (1981). Social resources and occupational status attainment. Social Forces, 59(4), 1163–1181.CrossRefGoogle Scholar
  55. Luyckx, K., Schwartz, S. J., Goossens, L., & Pollock, S. (2008). Employment, sense of coherence, and identity formation. Contextual and psychological processes on the pathway to sense of adulthood. Journal of Adolescent Research, 23, 566–591.CrossRefGoogle Scholar
  56. McGarry, K. (2000). Testing parental altruism: Implications of a dynamic model. (NBER Working Paper No. 7593). National Bureau of Economic Research. http://www.nber.org/papers/w7593.
  57. McGonagle, K. A., Schoeni, R. F., Sastry, N., & Freedman, V. A. (2012). The panel study of income dynamics: Overview, recent innovations, and potential for life course research. Longitudinal and Life Course Studies, 3(2), 268–284.Google Scholar
  58. McNeely, C. A., & Barber, B. K. (2010). How do parents make adolescents feel loved? Perspectives on supportive parenting from adolescents in 12 cultures. Journal of Adolescent Research, 25(4), 601–631.CrossRefGoogle Scholar
  59. Messersmith, E. E., Garrett, J. L., Davis-Kean, P. E., Malanchuk, O., & Eccles, J. S. (2008). Career development from adolescence through emerging adulthood: Insights from information technology occupations. Journal of Adolescent Research, 23(2), 206–227.CrossRefPubMedPubMedCentralGoogle Scholar
  60. Mykyta, L. (2012). Economic downturns and the failure to launch: The living arrangements of young adults in the U.S. 1995–2011. (SEHSD Working Paper No. 2012-24). U.S. Census Bureau. https://www.census.gov/content/dam/Census/library/working-papers/2012/demo/SEHSD-WP2012-24.pdf.
  61. Nam, C. B., & Boyd, M. (2004). Occupational status in 2000: Over a century of Census-based measurement. Population Research and Policy Review, 23(4), 327–358.CrossRefGoogle Scholar
  62. Newman, K., & Aptekar, S. (2007). Sticking around: Delayed departure from the parental nest in Western Europe. The price of independence: The economics of early adulthood, 207–230.Google Scholar
  63. Neumark, D. (2002). Youth labor markets in the United States: Shopping around vs. staying put. Review of Economics and Statistics, 84(3), 462–482.CrossRefGoogle Scholar
  64. Osgood, W., Ruth, G., Eccles, J., Jacobs, J., & and Barber, B., (2005). Six paths to adulthood: Fast starters, parents without careers, educated partners, educated singles, working singles, and slow starters. In R. A. Settersten, F. F. Furstenberg, & R. G. Rumbaut (Eds.), On the frontier of adulthood: Theory, research, and public policy (pp. 320–355). Chicago, IL: University of Chicago Press.Google Scholar
  65. PSID, [dataset] Panel Study of Income Dynamics, public use dataset. (2017). Produced and distributed by the Survey Research Center. Ann Arbor, MI: Institute for Social Research, University of Michigan. .Google Scholar
  66. Pöyliö, H., Erola, J., & Kilpi-Jakonen, E. (2017). Institutional Change and Parental Compensation in Intergenerational Attainment. The British Journal of Sociology. https://doi.org/10.1111/1468-4446.12298
  67. Rivera, L. A. (2015). Pedigree: How Elite Students Get Elite Jobs. Princeton, NJ: Princeton University Press.CrossRefGoogle Scholar
  68. Roksa, J., & Levey, T. (2010). What can you do with that degree? College major and occupational status of college graduates over time. Social Forces, 89(2), 389–415.CrossRefGoogle Scholar
  69. Sameroff, A. J., & Mackenzie, M. J. (2003). Research strategies for capturing transactional models of development: The limits of the possible. Development and psychopathology, 15(3), 613–640.CrossRefPubMedGoogle Scholar
  70. Schoeni, R. F., & Ross, K. E. (2005). Material assistance from families during the transition to adulthood. In R. A. Settersten, Jr., F. F. Furstenberg & R. G. Rumbaut (Eds.), On the frontier of adulthood (pp. 396–417). Chicago, IL: University of Chicago Press.CrossRefGoogle Scholar
  71. Schulenberg, J. E., Bryant, A. L., & O'Malley, P. M. (2004). Taking hold of some kind of life: How developmental tasks relate to trajectories of well-being during the transition to adulthood. Development and psychopathology, 16(4), 1119–1140.PubMedGoogle Scholar
  72. Settersten, R., & Ray, B. E. (2010). Not quite adults: Why 20-somethings are choosing a slower path to adulthood, and why it’s good for everyone. New York, NY: Bantam.Google Scholar
  73. Sirniö, O., Martikainen, P., & Kauppinen, T. M. (2016). Entering the highest and the lowest incomes: Intergenerational determinants and early-adulthood transitions. Research in Social Stratification and Mobility, 44, 77–90.CrossRefGoogle Scholar
  74. Smith, J., & Goodnow, J. J. (1999). Unasked-for support and unsolicited advice: Age and the quality of social experience. Psychology and Aging, 14(1), 108.CrossRefPubMedGoogle Scholar
  75. StataCorp (2015). Stata 14 base reference manual. College Station, TX: Stata Press.Google Scholar
  76. Swartz, T. T., Kim, M., Uno, M., Mortimer, J., & O’Brien, K. B. (2011). Safety nets and scaffolds: Parental support in the transition to adulthood. Journal of Marriage and Family, 73(2), 414–429.  https://doi.org/10.1111/j.1741-3737.2010.00815.x.CrossRefPubMedGoogle Scholar
  77. Tang, S. (1997). The timing of home leaving: A comparison of early, on-time, and late home leavers. Journal of Youth and Adolescence, 26(1), 13–23.CrossRefGoogle Scholar
  78. Torche, F. (2015). Analyses of intergenerational mobility: An interdisciplinary review. The Annals of the American Academy of Political and Social Science, 657(1), 37–62.CrossRefGoogle Scholar
  79. Waters, M. C., Carr, P. J., Kefalas, M. J. & Holdaway, J. (Eds.) (2011). Coming of age in America: The transition to adulthood in the twenty-first century.. Berkeley, CA: University of California Press.Google Scholar
  80. Whiston, S. C., & Keller, B. K. (2004). The influences of the family of origin on career development: A review and analysis. The Counseling Psychologist, 32, 493–568.CrossRefGoogle Scholar
  81. Wightman, P., Schoeni, R., & Schulenberg, J. (2013). Historical trends in parental financial support of young adults. (PSC Research Report No. 13-801.) Retrieved from Population Studies Center website: http://www.psc.isr.umich.edu/pubs/pdf/rr13-801.pdf.
  82. Wightman, P., Schoeni, R., & Robinson, K. (2012). Familial financial assistance to young adults. (National Poverty Center Working Paper Series No. 12-10). Retrieved from National Poverty Center website: http://npc.umich.edu/publications/u/2012-10%20NPC%20Working%20Paper.pdf.
  83. Witteveen, D., & Attewell, P. (2017). Family Background and Earnings Inequality among College Graduates. Social Forces, 95(4), 1539–1576.CrossRefGoogle Scholar
  84. Wooldridge, J. M. (2010). Econometric Analysis of Cross Section and Panel Data. Cambridge, MA: MIT Press.Google Scholar

Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2018

Authors and Affiliations

  1. 1.North Carolina State UniversityRaleighUSA

Personalised recommendations