Intergenerational Upward and Downward Social Mobility: The Role of Intelligence,Effortful Control,Assertiveness,and Peer Competence in Early Adolescence

Abstract

Relatively little is known about which competencies adolescents need to experience intergenerational social mobility. We investigated if intelligence, effortful control, assertiveness, and peer competence at age 11 was associated with upward or downward mobility at age 26, utilizing data from the TRAILS study (N = 2229; age_T1 = 11.1 (SD = 0.55); 50.8% girls). Results from our multinomial logistic regressions indicate that intelligence and effortful control, but not social competencies, are associated with upward mobility. Only intelligence was associated with downward mobility. Having dissimilar levels of competence than peers with the same parental SES was more important for social mobility than having similar competencies as peers with the same young adulthood SES. Social mobility thus happens primarily based on competence. However, given the importance of genetic predispositions and socioeconomic environment for intelligence and effortful control, and the limited appreciation of alternative competencies, social mobility remains to some extent unmeritocratic.

Keywords

social mobility socioeconomic status adolescence intelligence effortful control assertiveness peer competence

Introduction

The literature suggests that early measures of intelligence are a primary predictor for upward or downward mobility (Chetty et al., 2011; Forrest et al., 2011), but also that a considerable portion of mobility remains unexplained (Acciari et al., 2019). In recent years, non-cognitive, psychosocial competencies have gained increased attention as potential relevant factors for social mobility (J. J. Heckman & Mosso, 2014; OECD, 2015). Some researchers even claim that such psychosocial competencies may be of greater relevance for social mobility than cognitive capabilities (Bowles & Gintis, 2002; Farkas, 2003), though this claim lacks extensive empirical testing. Testing a combination of competencies will help us better understand if social mobility happens based on meritocratic principles or is hindered by glass floor/glass ceiling effects (Breen & Goldthorpe, 1999; Saunders, 2002).

According to the meritocracy hypothesis (e.g., Young, 2011), adolescents end up in a socioeconomic position as adults based on their competencies, regardless of their socioeconomic background when growing up. Adolescents from a lower socioeconomic background can experience upward mobility if they display similar levels of competence as adolescents from a higher socioeconomic background, and adolescents from a higher socioeconomic background experience downward mobility if their competencies resemble those of adolescents from a lower socioeconomic background.

However, according to the glass ceiling hypothesis, some adolescents with a lower parental SES experience difficulties moving into a higher educational level (upward social mobility) despite displaying similar levels of competence as adolescents with a higher parental SES (e.g., Reeves & Howard, 2013). Similarly, some adolescents with a high parental SES are prevented from moving into a lower educational level (downward social mobility) even if their competencies resemble those of adolescents with a lower parental SES (glass floor hypothesis; Bourne et al., 2018). Under the glass ceiling/glass floor hypotheses, social mobility only occurs if adolescents display more extreme competencies than their peers (e.g., adolescents from a low socioeconomic background would only make it into university if they are more intelligent than adolescents from a high socioeconomic background).

Early adolescence is an important developmental period with regard to social mobility, in which (Dutch) adolescents first get selected into an educational track, strive to become more independent and autonomous from their parents and closer with peers, and experience drastic changes in their capacity to display behavioral and social competencies (Blum et al., 2014; Erola et al., 2016). Biologically, early adolescence starts after the onset of puberty, which is around the age of 9 for girls and slightly later for boys (Blum et al., 2014; Lee et al., 2001). Socially, early adolescence can be considered to start after completing primary school and transitioning to secondary school (Eccles et al., 1997), which in the Netherlands is around the age of 11–12. However, the exact age range of (early) adolescence is under constant debate, and will in part remain determined by culture and context (Sawyer et al., 2018). Collecting longitudinal data from early adolescence to young adulthood tends to be challenging for researchers due to its high costs and difficulties in participant tracking. As a result, research linking early adolescent characteristics to social mobility outcomes in young adulthood has been relatively scarce.

In this study, we will utilize TRAILS data to specifically investigate intelligence, effortful control, assertiveness, and peer competence as potential early adolescent competencies underlying social mobility in young adulthood. While separate studies underline the potential of such competencies (e.g., Esping-Andersen & Cimentada, 2018; Senia et al., 2016), a comprehensive framework that disentangles the specific effects of intelligence, effortful control, assertiveness, and peer competence on both upward and downward mobility has been lacking to date.

Parental SES and Educational Attainment in Young Adulthood

Approximately half of Dutch adolescents attain a different (mostly higher) educational level than their parents, in line with global averages (OECD, 2018; Weinberg et al., 2019). These relatively high social mobility rates are argued to be primarily the result of structural factors, such as funding for public education and social welfare policies, which removed or reduced some of the obstacles for social mobility as experienced by previous generations. As a result, the educational attainment of adolescents is increasingly predicted by individual competencies instead of socioeconomic background (OECD, 2015).

Educational attainment in young adulthood is considered to be a key indicator of SES in later adulthood (Erola et al., 2016). The type of educational attainment largely determines young adults’ occupation upon entering the labor market (Blau & Duncan, 1967). Young adults with a practical vocational education rarely end up in a specialized office job, and young adults with a university degree rarely end up in a labor-intensive occupation such as nurse or sales assistant. Hence, educational attainment is associated with both career opportunities and career boundaries (Hurley-Hanson et al., 2005). Furthermore, educational attainment is also among the strongest predictors of adulthood income (Bjarnason, 2000). In line with international trends, Dutch individuals with a higher level of education have considerably more income than those with a lower level of education – though differences may exist across occupations (Autor, 2014; OECD, 2023). In young adulthood, however, these educational differences in income are small to none (or even negative) as vocational educated students tend to have an earlier labor market entry than university students. Though educational attainment in young adulthood may be a simplified measure of SES, it tends to be a good predictor for later adulthood SES differences.

As such, attaining a different educational level than expected based on parental socioeconomic background is an important pathway for experiencing social mobility. However, which specific individual-level competencies are associated with this conceptualization of social mobility remains somewhat unclear to date.

Intelligence, Effortful Control and Social Competence as Facilitators of Social Mobility

Adolescents with a low SES need an eclectic combination of related but distinct competencies to effectively navigate challenges to social mobility at home (e.g., lack of quietness, lack of study materials) and at school (less help available, lower expectations) (Esping-Andersen & Cimentada, 2018; Ng-Knight & Schoon, 2017). Previous studies indicate that intelligence, effortful control, and social competence in adolescence have the potential to serve as protective factors against socioeconomic disadvantages (Breen & Goldthorpe, 2001; McGue et al., 2020). Previous studies also indicate how these same competencies can be positively linked to academic success (e.g., Blair & Razza, 2007). Hence, intelligence, effortful control, and social competence may facilitate social mobility, though comprehensive research that disentangles the independent effects of multiple psychosocial competencies on both upward and downward mobility is scarce (Deary et al., 2005; Senia et al., 2016).

Intelligence – often measured as IQ – reflects one’s cognitive abilities that facilitate learning and grasping abstract concepts (e.g., Hassler & Mora, 2000). Such cognitive abilities help adolescents perform well in an academic or school setting, and are also useful assets in a later occupational setting (Jencks et al., 1983). Across societies, intelligence is firmly established as a driving factor behind both upward and downward social mobility (Anni & Mõttus, 2019; Deary et al., 2005; Forrest et al., 2011). Nonetheless, even after controlling for measures of intelligence, a considerable portion of social mobility remains unexplained (Fergusson et al., 2008; Weinberg et al., 2019).

Besides intelligence, effortful control – or an individual’s ability to remain focused on a particular task without getting distracted (Eisenberg et al., 2005) – is important for adolescents to experience success in academic endeavors (Stadler et al., 2016). Effortful control reflects an adolescent’s capacity for prolonged attention (i.e., attentional control) as well as the ability to express a conscious thought or behavior over an impulsive one (i.e., inhibitory control) (Muris & Ollendick, 2005). Such competencies help adolescents prioritize (or balance) long-term goals, such as pending school assignments, over short-term leisure activities such as staying out late with friends (Andersson & Bergman, 2011). Effortful control has both theoretically (Saunders, 1997; Young, 1958) and empirically (Véronneau et al., 2014) been associated with social mobility. However, the unique effects of intelligence and effortful control on social mobility have so far been somewhat understudied. As a result, it remains elusive if intelligence and effortful control have a similar effect on social mobility or if either one has a more predominant effect.

Similarly, adolescents with higher levels of social competence may be better equipped to overcome obstacles to social mobility than those with lower levels of social competence (Bukodi et al., 2019). Assertiveness and peer competence in particular have been considered helpful assets that can potentially promote upward mobility or prevent downward mobility. Assertive adolescents – who pro-actively communicate their needs, wants, and opinions (Arrindell & Vanderende, 1985) – tend to ask for support or additional challenges related to school assignments, while also being able to effectively communicate disagreement about school rules, grading, or expectations (Elliott & Gresham, 2013). For example, assertive adolescents may tackle bureaucratic challenges or regulate their own learning and mobility structure in concordance with schools and teachers. As such, assertive adolescents increase their own efficacy, which facilitates academic performance (González Fragoso et al., 2018), and also extends into occupational success (Woods & Sofat, 2013).

Peer competence may be another aspect of social competence that promotes social mobility (Senia et al., 2016). Peer competence refers to the capacity to act in an effective and appropriate manner with peers, given the social context (Fabes et al., 2006; Rose-Krasnor, 1997). A high level of peer competence in early adolescence may indicate that one has sufficient social support as well as the skills to navigate social situations with people from various socioeconomic backgrounds, which is inherent to social mobility (Friedman, 2014).

Furthermore, the development of social competence and effortful control – though distinct constructs – have been argued to go hand in hand. For example, the need for social connection and awareness of social norms helps adolescents display better control, and adolescents who display better control tend to have more satisfying social relationships (Farley & Kim-Spoon, 2014; McKown et al., 2009). Similarly, verbal intelligence was found to be among the most prominent aspects of intelligence in facilitating social mobility (Anni & Mõttus, 2019), suggesting that an understanding of how to navigate complex social situations is an important prerequisite for experiencing social mobility. Some researchers even argue that psychosocial competencies such as effortful control and social competence outweigh intelligence in predicting adulthood socioeconomic status (Bowles & Gintis, 2002; J. J. Heckman & Kautz, 2012).

Given the importance of these competencies for educational and occupational success, adolescents with similar levels of intelligence, effortful control, and social competence in early adolescence would be expected to attain a similar young adulthood SES – even if their parental SES may differ. Instead of such a meritocratic stratification, adolescents’ parental SES may limit social mobility, urging adolescents to have more extraordinary levels of competence in order to experience social mobility (Breen & Goldthorpe, 1999). For example, adolescents with a lower parental SES may experience structural barriers (‘glass ceiling’), such as lack of resources, tensions at home, poorer quality education, and possible teacher prejudice, that require much higher levels of intelligence, effortful control, and assertiveness than that of adolescents with a higher parental SES to end up in the same young adulthood SES (Conger & Donnellan, 2007). Similarly, adolescents with a higher parental SES may experience structural benefits (‘glass floor’), such as plenty of resources, a stable and comfortable home situation with supportive, assertive parents, higher quality education including private tutoring, and positive teacher expectations, which may all help prevent downward mobility even if competencies are relatively low (Scherger & Savage, 2010).

If effortful control and social competence in early adolescence predict social mobility beyond intelligence then schools could consider incorporating a broader appreciation of competencies when evaluating the educational potential of students (Kautz, 2014; OECD, 2015). Currently in the Netherlands, the first educational stratification happens at the relatively young age of 11–12 at the end of primary school, based on a national exam and teacher evaluation. Utilizing assessments or even stimulating the development of psychosocial competence as part of the curriculum may help stratify adolescents more in line with their educational potential, thus boosting opportunities for social mobility.

While higher levels of social mobility are not a goal in and of itself, identifying individual factors underlying social mobility can provide opportunities to either reduce social inequalities (e.g., through training programs) or foster acceptance of (increasing) social inequalities (Jencks & Tach, 2005; Vrooman et al., 2023). It will also further our understanding of who experiences social mobility within a given educational system, even if the social mobility rates are not affected by psychosocial competencies (Savage & Egerton, 1997). Hence, this study aimed to contribute to the existing literature by investigating if early adolescent intelligence, effortful control, and social competence predict social mobility in young adulthood, in line with meritocratic principles or glass ceiling/glass floor principles (Breen & Goldthorpe, 2001; Saunders, 2002; Young, 2011).

To date, it remains elusive how important intelligence, effortful control, and social competence are for social mobility relative to each other. Potentially, intelligence may become less relevant for social mobility among adolescents with strong effortful control, or effortful control may become less relevant for social mobility among adolescents with strong social competencies. Furthermore, this combination of adolescent characteristics may differently impact processes of upward social mobility compared to downward social mobility. In this study, we aim to further specify the extent to which intelligence, effortful control, and social competence uniquely contribute to adolescents’ opportunities for social mobility.

Present Study

The aim of this study was to investigate if intelligence, effortful control, and social competence in early adolescence are associated with upward mobility and with downward mobility in young adulthood, and how much of these competencies adolescents need relative to peers in order to experience social mobility. For both upward mobility and downward mobility, we will contrast two competing hypotheses: the meritocracy hypothesis versus the glass ceiling/glass floor hypothesis.

Both the meritocracy hypothesis and the glass ceiling hypothesis are based on the presumption that adolescent competencies can compensate socioeconomic differences in educational attainment. However, the hypotheses crucially differ in their proposition of how much competencies relative to peers are required to experience social mobility. According to the meritocracy hypothesis (Blau & Duncan, 1967; Saunders, 1997), we would expect to find that adolescents with a lower parental SES experience upward mobility if they have similar intelligence, effortful control, and social competence as peers with a higher parental SES. Likewise, adolescents with a higher parental SES are expected to experience downward mobility if they have similar intelligence, effortful control, and social competence as peers with a lower parental SES. Initial socioeconomic differences in educational attainment could then ultimately be entirely explained in terms of competencies.

According to the glass ceiling hypothesis (e.g., Gugushvili et al., 2017), we would expect to find that adolescents with a lower parental SES only experience upward mobility if their intelligence, effortful control, and social competence is higher than that of peers with a higher parental SES. Similarly, according to the glass floor hypothesis, we expect to find that adolescents with a higher parental SES only experience downward mobility if they have lower intelligence, effortful control, and social competence than peers with a lower parental SES. The key to distinguishing between the meritocracy hypothesis and the glass ceiling/floor hypothesis lies therefore in how much competence is required for adolescents from different parental SES backgrounds to have similar odds for attaining particular educational levels. Alternatively, we may find that intelligence, effortful control, or social competence are mostly unrelated to upward or downward mobility – neither supporting the meritocracy hypothesis or the glass ceiling/glass floor hypothesis.

Method

Participants and Procedure

Data from two waves (T1 and T6) of the TRacking Adolescents’ Individual Lives Survey (TRAILS) were used. TRAILS is a population-based prospective cohort study that follows the development of adolescents (and their families) in Groningen, the northern region of the Netherlands (Oldehinkel et al., 2015). A total of 3134 eligible adolescents were identified after combining municipality registers and school registers (i.e., 90.3% of all eligible adolescents in the selected municipalities). Adolescents and their families were first informed about (the purpose of) the TRAILS study through school visits and brochures, after which telephone calls were made to inquire about participation and answer any remaining questions. This recruitment approach resulted in the inclusion of 2229 adolescents and their families (71.1% of eligible adolescents). Written informed consent was obtained from both adolescents and their parents prior to inclusion in the study. Ethical approval for TRAILS was obtained from the Dutch national ethics committee Central Committee on Research Involving Human Subjects (#NL38237.042.11).

Adolescents in the baseline sample (N = 2229; M_age = 11.1, SD = 0.55; 50.8% girls) were followed between 2000 and 2017 with assessments roughly every 3 years, from age 11 (T1) to age 26 (T6). The majority of participants identified as having a Dutch ethnicity (89.4%) and the sample has a higher socioeconomic status than the Dutch average (Fakkel et al., 2020).

All measures of early adolescent competence were obtained at T1. Out of N = 2229 participants at T1, 43 participants did not provide information on parental SES (1.9%), 712 on educational level (at T6) (31.9%), 9 on IQ (0.4%), 178 on effortful control (8.0%), 34 on social competence (1.5%), and 302 on assertiveness (13.5%). Assertiveness scores were obtained through teacher reports, which explains the relatively high number of missing values. Compared to participants that were retained from T1 to T6, participants who dropped out (n = 712; 31.9%) were more likely to be boys (χ² (1) = 54.09, p < .001), older (t (2226) = 2.24, p = .03), from a lower SES background (t (2184) = −14.49, p < .001), with a lower IQ (t (2218) = −13.28, p < .001), lower effortful control (t (2049) = −3.31, p < .001), and lower assertiveness (t (1925) = −8.41, p < .001).

Measures

Social Mobility

Participants were categorized in 1 of 9 groups, depending on their parental SES at age 11 and their educational attainment at age 26. Parental SES was assessed at T1 using five indicators: family income, mother’s and father’s educational attainment, and mother’s and father’s occupational level (based on the ISCO-88). Previous use of this SES variable explained 61.2% of the variance in the five indicators with good internal consistency, α = 0.84 (Amone-P’Olak et al., 2009; Vollebergh et al., 2005). The factor score of parental SES was split into three ordinal categories of equal size, i.e., low, middle, and high parental SES.

The lower parental SES group consists mostly of families with relatively lower educated parents and a lower family income. The middle parental SES group contains mostly intermediate combinations (e.g., middle educated parents with a middle income) as well as the most mixed combinations (e.g., lower educated father and higher educated mother or lower educated parents with a higher family income). The higher parental SES group contains mostly families with higher educated parents and higher family incomes. Parental SES group membership therefore reflects ordinal differences in developmental and educational opportunities – and thus opportunities for social mobility.

Educational attainment was self-reported by adolescents at age 26 (T6). Educational level was measured using a single item, and (ordinally) categorized as lower (practical vocational education), middle (theoretical vocational education), and higher (college/university), representing adolescents’ social destination group in young adulthood. If educational level was missing at T6, data on educational level from T5 (age 22) was used.

Combining the 3 categories of parental SES and 3 categories of educational attainment yielded 9 categories of social mobility: low/middle, low/high, middle/high, high/middle, high/low, and middle/low; and low/low, middle/middle, high/high (the latter three groups technically representing social reproduction and not mobility). For adolescents experiencing social mobility (e.g., low/middle), we refer to their social origin group as the stable adolescents with a similar parental SES (i.e., low/low) and the social destination group as the stable adolescents with a similar educational attainment (i.e., middle/middle).

Intelligence

Intelligence was measured using two subtests from the Wechsler Intelligence Scale for Children (WISC-R; Silverstein, 1973), i.e., the subtests on verbal intelligence and spatial intelligence. Scores were combined into an intelligence quotient (IQ), to approximate adolescent intelligence.

Effortful Control

The primary parent reported on their adolescent’s effortful control by filling out the effortful control-subscale of the Early Adolescent Temperament Questionnaire, at both T1 and T3 (EATQ-R; Hartman, 2000). This subscale consists of 11 items (e.g., “If my child has to do a difficult task, he/she starts immediately”), and can be answered from 1 (‘Almost never true’) to 5 (‘Almost always true’). The items have good internal consistency (α = 0.86). A standardized sum score was calculated, with a higher score indicating better effortful control.

Assertiveness

Assertiveness was measured by using teacher report on the assertiveness subscale of the Social Skills Rating System (SSRS; Gresham & Elliot, 1990) questionnaire. The assertiveness subscale consists of 10 items (e.g., “This student tells you in an appropriate manner if he/she feels to have been treated unfairly”) that are answered on a scale from 1 (‘Never’) to 3 (‘Very often’). Items are combined into an average score, with a higher score indicating more assertiveness. The internal consistency of the subscale can be considered as good, α = 0.88.

Peer Competence

Peer competence was measured by adolescents’ self-report on the Social Problems subscale of the Youth Self-Report (YSR; Achenbach & Rescorla, 2001) questionnaire. This subscale consists of 11 items (e.g., “Can’t get along with other boys/girls”) that are rated on an answer scale from zero (‘Not at all’) to 2 (‘Clearly or Often’). After recoding all items, an average score of social competence was obtained, with a higher score indicating more peer competence. Internal consistency of the items is regarded as good, α = 0.71.

Strategy of Analysis

A multiple imputation procedure was performed to minimize biases resulting from attrition and missing data. Variables included in the multiple imputation procedure were parental SES, age, assertiveness, effortful control, social competence, and IQ at T1, and educational level at T6 (i.e., 7 variables). A large number of high scores resulted in a left-skewed distribution for social competence, which was resolved (before multiple imputation) by applying a square root transformation (Mangiafico, 2016). Predictive mean matching was the preferred imputation method of choice in order to minimize bias and yield small confidence intervals (CI) while still maintaining power (Peeters et al., 2015; Van Buuren, 2018). A total of 5 imputed datasets was obtained and split for separate analyses, after which the results were pooled (Buuren & Groothuis-Oudshoorn, 2011).

We performed two multinomial logistic regressions (i.e., for upward mobility and for downward mobility), each consisting of a model selection procedure and a model testing procedure (i.e., post-hoc group comparisons). In the model selection procedure data of all participants were used whereas in the model testing procedure we contrasted participants from the social mobility groups under investigation.

For model selection, we tested separately for upward mobility and for downward mobility if each predictor contributed to the odds of being in one of six social mobility groups (i.e., explains unique variance in social mobility). For upward mobility, we assessed if intelligence, effortful control, assertiveness, and peer competence at age 11 predicted being in the Low-Low, Mid-Mid, High-High, Low-Mid, Low-High, or Mid-High group (N = 1860). Similarly for downward mobility, we assessed if intelligence, effortful control, assertiveness, and peer competence at age 11 predicted being in the Low-Low, Mid-Mid, High-High, High-Mid, High-Low, or Mid-Low group (N = 1425). A full model with all four predictors was sequentially tested against a nested, more parsimonious model excluding one of the predictors (i.e., backwards elimination method; see Table 3). If the likelihood ratio test indicated that the model fit of the full model was significantly better than the model fit of the nested model, then the predictor was retained in the final model. In these two model selection procedures, we assessed the contribution of individual predictors for understanding group membership, but we did not yet contrast different groups on these predictors. Following these two model selection procedures, we found that IQ, effortful control, and assertiveness explained unique variance in both upward and downward social mobility, but social competence did not. Hence, IQ, effortful control, and assertiveness were selected into the final upward mobility and downward mobility models.

For model testing, we performed a total of six post-hoc comparisons (3 for the upward mobility model and 3 for the downward mobility model), only utilizing data of participants in the specific social mobility, social origin, and social destination groups of interest per post-hoc comparison. For each upward mobility group (i.e., Low-Mid; Low-High; Mid-High), we contrasted levels of intelligence, effortful control, assertiveness, and peer competence at age 11 to its respective social origin group (i.e., Low-Low; Low-Low; Mid-Mid, respectively) and social destination group (i.e., Mid-Mid; High-High; High-High, respectively). Table 4 describes the results of these three separate post-hoc comparisons for upward mobility.

Similarly, we performed three post-hoc comparisons for each downward mobility group (i.e., High-Mid; High-Low; Mid-Low), in which we contrasted levels of intelligence, effortful control, assertiveness, and peer competence at age 11 to the respective social origin group (i.e., High-High; High-High; Mid-Mid, respectively) and social destination group (i.e., Mid-Mid; Low-Low; Low-Low, respectively). Table 5 describes the results of these three separate post-hoc comparisons for downward mobility.

Results

Descriptive statistics (Table 1) and Pearson’s correlations (Table 2) of standardized variables were obtained from the pooled imputed datasets. Approximately 47.5% of participants experienced social reproduction (i.e., educational attainment in line with parental SES), 36% experienced upward mobility (i.e., higher educational attainment in young adulthood than expected based on parental SES), and 16.5% experienced downward mobility (i.e., lower educational attainment in young adulthood compared to parental SES). At baseline, parental SES appeared to be positively associated with intelligence, effortful control, assertiveness, and educational attainment, but not with peer competence – mostly in line with earlier findings from social reproduction research (Heckman et al., 2013; Mangiavacchi & Piccoli, 2024). These positive associations are to an important extent driven by a select number of highly competent adolescents most of whom are from families with a high SES, and adolescents with the lowest levels of competence most of whom are from families with a low parental SES (Table 1). For most adolescents in our sample, the association between parental SES and competencies is more nuanced with more variability. During model selection, peer competence did not explain variation in social mobility, and was thus excluded from the final models and post-hoc comparisons of upward mobility and downward mobility (see Table 3).

Table 1.

Descriptive Statistics of Variables of Interest after Multiple Imputation.

Social Mobility	N	Parental SES	Intelligence	Effortful Control	Assertiveness	Peer Competence
Total	2229	1.89 (0.80)	97.2 (15.0)	3.58 (0.54)	2.23 (0.43)	1.08 (0.14)
Stable	1056	2.08 (0.83)	97.6 (15.9)	3.60 (0.54)	2.25 (0.44)	1.08 (0.14)
High/High	478	2.84 (0.33)	106.5 (13.0)	3.72 (0.52)	2.40 (0.40)	1.09 (0.14)
Middle/Middle	345	1.89 (0.22)	95.7 (12.5)	3.54 (0.51)	2.23 (0.41)	1.08 (0.13)
Low/Low	239	0.89 (0.36)	83.0 (13.3)	3.40 (0.52)	2.00 (0.42)	1.06 (0.15)
Upward	804	1.36 (0.53)	97.1 (13.7)	3.62 (0.55)	2.22 (0.43)	1.08 (0.14)
Low/Middle	329	1.00 (0.35)	92.3 (12.6)	3.54 (0.56)	2.11 (0.41)	1.07 (0.15)
Low/High	173	1.05 (0.32)	97.7 (14.4)	3.67 (0.57)	2.23 (0.42)	1.07 (0.14)
Middle/High	293	1.93 (0.22)	101.7 (12.9)	3.65 (0.51)	2.34 (0.42)	1.08 (0.12)
Downward	369	2.47 (0.47)	96.0 (14.9)	3.48 (0.53)	2.20 (0.43)	1.08 (0.13)
High/Low	39	2.65 (0.29)	92.5 (14.4)	3.40 (0.50)	2.03 (0.39)	1.07 (0.13)
High/Middle	228	2.70 (0.31)	99.4 (14.3)	3.53 (0.55)	2.30 (0.40)	1.07 (0.14)
Middle/Low	105	1.86 (0.21)	89.9 (14.2)	3.43 (0.49)	2.03 (0.44)	1.09 (0.12)

Table 2.

Correlation Matrix.

	Age	Parental SES	Intelligence	Effortful Control	Assertiveness	Peer Competence
Age
Parental SES	−0.03
Intelligence	−0.08***	0.39***
Effortful control	−0.04	0.08***	−0.06*
Assertiveness	−0.02	0.26***	−0.25***	0.10***
Peer competence	−0.02	0.03	−0.05	0.34***	0.11***
Educational attainment	−0.02	0.39***	−0.41***	0.19***	0.26***	0.05

*p < .05; **p < .01; ***p < .001.

N.B. p-values have been corrected for multiple testing using the Holm-Bonferroni method.

Table 3.

Testing Intelligence, Effortful Control, Assertiveness, and Peer Competence in the Model Selection Process before Model Testing.

	df	Δχ²	p-value
Upward mobility	20
Model without intelligence	15	415.63	<0.001
Model without effortful control	15	42.94	<0.001
Model without assertiveness	15	69.42	<0.001
Model without peer competence	15	5.21	0.412
Downward mobility	16
Model without intelligence	12	357.47	<0.001
Model without effortful control	12	42.79	<0.001
Model without assertiveness	12	60.68	<0.001
Model without peer competence	12	6.41	0.323

N.B. p-values have been corrected for multiple testing using the Holm-Bonferroni method. Age and gender were included as covariates.

Post-hoc Group Comparisons

After model selection, final models were tested using post-hoc group comparisons to identify specific associations of intelligence, effortful control and assertiveness with upward mobility (Table 4) and downward mobility (Table 5). Based on the likelihood ratio test (χ² (15) = 504.87, p < .001), the upward mobility model (Table 3) had a good fit to the data, and explained a considerable part of the variation in upward mobility at age 26 (Cox-Snell R² = 0.24; Nagelkerke R² = 0.24; McFadden R² = 0.08). The downward mobility model also had a good fit to the data (LR: χ² (15) = 111.06, p < .001), but explained less of the variation in downward mobility at age 26 (Cox-Snell R² = 0.08; Nagelkerke R² = 0.08; McFadden R² = 0.02).

Table 4.

Multinomial Logistic Regression for Upward Mobility. Reference Group is Compared to Both Origin Group and Destination Group.

Upward Mobility	Estimate	SE	Wald z-value	df	OR
Reference group: Low/High
Low/Low
Intercept	−2.80	3.01	−0.93	17	0.06
Intelligence	−1.25***	0.15	−8.61	108	0.29
Effortful control	−0.50**	0.15	−3.33	18	0.61
Assertiveness	−0.43	0.19	−2.22	9	0.65
High/High
Intercept	−1.77	2.13	−0.83	69	0.17
Intelligence	0.72***	0.11	6.39	370	2.06
Effortful control	0.10	0.10	1.04	276	1.11
Assertiveness	0.28	0.13	2.13	18	1.33
Reference group: Low/Middle
Low/Low
Intercept	−1.25	3.01	−0.42	9	0.29
Intelligence	−0.79***	0.14	−5.69	26	0.45
Effortful control	−0.28	0.15	−1.83	10	0.76
Assertiveness	−0.19	0.12	−1.59	29	0.83
Middle/Middle
Intercept	4.45*	2.12	2.09	22	85.28
Intelligence	0.25	0.11	2.30	45	1.29
Effortful control	−0.02	0.10	−0.16	31	0.98
Assertiveness	0.24**	0.09	2.62	135	1.27
Reference group: Middle/High
Middle/Middle
Intercept	3.58*	1.81	1.98	152	36.05
Intelligence	−0.54***	0.10	−5.31	299	0.58
Effortful control	−0.25**	0.09	−2.81	123	0.78
Assertiveness	−0.21	0.11	−1.88	28	0.81
High/High
Intercept	−1.09	1.55	−0.70	707	0.34
Intelligence	0.40***	0.09	4.34	358	1.48
Effortful control	0.08	0.08	1.05	1538	1.08
Assertiveness	0.08	0.10	0.84	50	1.08

*p < .05; **p < .01; ***p < .001.

N.B. p-values have been corrected for multiple testing using the Holm-Bonferroni method. Age and gender were included as covariates.

Table 5.

Multinomial Logistic Regression for Downward Mobility. Reference Group is Compared to Both Social Destination Group and Social Origin Group.

Downward Mobility	Estimate	SE	Wald z-value	df	OR
Reference group: High/Low
High/High
Intercept	−0.57	3.93	−0.15	82	0.56
Intelligence	1.15***	0.21	5.51	766	3.17
Effortful control	0.64^†	0.22	2.96	52	1.90
Assertiveness	0.67**	0.20	3.34	169	1.95
Low/Low
Intercept	−0.87	4.19	−0.21	50	0.42
Intelligence	−0.77***	0.21	−3.64	1070	0.46
Effortful control	0.03	0.24	0.11	26	1.03
Assertiveness	−0.02	0.21	−0.11	82	0.98
Reference group: High/Middle
High/High
Intercept	−1.60	1.69	−0.95	341	0.20
Intelligence	0.58***	0.10	5.79	886	1.78
Effortful control	0.36***	0.09	3.87	149	1.44
Assertiveness	0.13	0.13	1.04	16	1.14
Middle/Middle
Intercept	3.25	1.79	1.81	381	25.69
Intelligence	−0.36***	0.10	−3.41	525	0.70
Effortful control	0.01	0.10	0.11	132	1.01
Assertiveness	−0.15	0.10	−1.47	97	0.86
Reference group: Middle/Low
Middle/Middle
Intercept	3.40	2.46	1.38	382	30.08
Intelligence	0.43**	0.16	2.73	57	1.54
Effortful control	0.21	0.12	1.70	1127	1.24
Assertiveness	0.37	0.17	2.12	16	1.45
Low/Low
Intercept	−1.73	2.87	−0.60	51	0.18
Intelligence	−0.55**	0.17	−3.34	56	0.58
Effortful control	−0.05	0.15	−0.33	61	0.95
Assertiveness	−0.04	0.16	−0.24	33	0.96

*p < .05; **p < .01; ***p < .001; ^†p = .05.

N.B. p-values have been corrected for multiple testing using the Holm-Bonferroni method. Age and gender were included as covariates.

Intelligence was consistently associated with both upward mobility and downward mobility. Adolescents who experienced upward mobility by age 26 (e.g., Low/High) had higher intelligence at age 11 than peers in their origin group (Low/Low), but lower intelligence than peers in their destination group (High/High) in 5 out of 6 comparisons. Similarly, adolescents who experienced downward mobility (e.g., High/Low) had lower intelligence at age 11 than peers from their origin group (High/High), but higher intelligence than peers in their destination group (Low/Low) in 6 out of 6 comparisons. Thus, intelligence facilitates social mobility regardless of socioeconomic background, in line with the meritocracy hypothesis and contradicting the glass ceiling/glass floor hypothesis.

Effortful control was more often associated with upward mobility than with downward mobility. Adolescents who experienced upward mobility by age 26 (e.g., Middle/High) had more effortful control at age 11 than peers in their origin group, and similar effortful control as peers in their destination group (High/High) in 5 out of 6 comparisons. These findings are in line with the meritocracy hypothesis, and not in line with the glass ceiling/glass floor hypotheses. In contrast, adolescents who experienced downward mobility by age 26 (e.g., Middle/Low) mostly had a similar level of effortful control as peers in both their origin group (Middle/Middle) and their destination group (Low/Low) in 5 out of 6 comparisons. These findings support neither the meritocracy hypothesis nor the glass ceiling/glass floor hypothesis.

Just like peer competence, assertiveness was mostly not associated with upward or downward mobility. Adolescents who experienced upward mobility by age 26 (e.g., Low/High) had a similar level of assertiveness as peers in their origin group (Low/Low) and peers in their destination group (High/High) in 5 out of 6 comparisons. Adolescents who experienced downward mobility (e.g., High/Low) also had similar assertiveness at age 11 as peers in their origin group (High/High) and peers in their destination group (Low/Low) in 5 out of 6 comparisons. Hence, assertiveness – like peer competence – does not offer support for the meritocracy or the glass ceiling/floor hypothesis.

Discussion

Our findings support the meritocracy hypothesis over the glass floor/glass ceiling hypothesis indicating that adolescent competencies are more important than socioeconomic background for attaining an educational level. Adolescents with higher levels of intelligence and effortful control than peers with a similar parental SES (i.e., origin group) were more likely to experience upward social mobility, despite lower levels of intelligence and effortful control than peers with a similar young adulthood SES (i.e., destination group). Social competence – in terms of peer competence and assertiveness – was mostly not related to upward mobility. Adolescents with lower levels of intelligence than peers from their origin group were more likely to experience downward mobility, despite higher levels of intelligence than peers from their destination group. Effortful control and social competence were mostly not related to downward mobility.

Theoretical Implications

Our findings imply that adolescents with high levels of intelligence and effortful control are more likely to succeed in higher education, also when they grew up in families with a lower SES. Adolescents with a lower parental SES who display a similar level of intelligence and effortful control as adolescents with a higher parental SES end up in a similar young adulthood SES. This suggests that our educational system is sufficiently meritocratic to identify and stratify adolescents from different socioeconomic backgrounds into appropriate levels that match their competencies. It also suggests that risk factors associated with a lower parental SES, such as limited resources, tensions at home, and poorer educational quality or expectations, have a limited or negligible impact on adolescents’ opportunities to attain a higher young adulthood SES.

However, our findings that assertiveness and peer competence at age 11 are unrelated to social mobility in young adulthood contradict previous research that underlines the importance of adolescent social competence for educational and occupational success (González Fragoso et al., 2018; Woods & Sofat, 2013). Potentially, social competence may promote upward mobility after young adulthood. For example, more assertive adults may be able to negotiate a higher salary and adults who maintain professional relationships with colleagues may be more likely to obtain a management position. As such, we encourage future research to investigate the role of social competence in other developmental contexts or age cohorts relevant for social mobility.

While these findings mostly support the meritocracy hypothesis over the glass ceiling/glass floor hypothesis, social mobility in our sample did not progress entirely in line with the meritocracy hypothesis. According to meritocratic principles, adolescents with the same competencies (e.g., level of intelligence and effortful control) end up in the same educational level. On the one hand, our findings support such a scenario: for example, adolescents with a low SES but a higher level of intelligence than their peers with a low SES are more likely to attain a higher educational level. On the other hand, however, our findings seem somewhat unmeritocratic: for example, adolescents with a low SES who attain university education had a lower level of intelligence than peers from their destination group (i.e., adolescents with a high parental SES who attained university). Similarly, adolescents with a high SES who attained practical vocational education had a higher level of intelligence than peer from their destination group (i.e., adolescents with a middle parental SES who attained practical vocational education). It thus seems that despite differences in intelligence, some adolescents with a low SES and some adolescents with a high SES end up in the same educational level. This finding contradicts previous research which suggests that adolescents with a lower parental SES are less likely to be enrolled in (pre-) university than adolescents with a higher parental SES, despite similar competence levels (Zumbuehl et al., 2022). Potentially, some teachers may interpret adolescents’ level of competence in the context of their socioeconomic background (Auwarter & Aruguete, 2008).

Three observations may explain why these findings could still indicate a meritocracy. First, deviating levels of competence relative to peers in the destination group do not indicate underqualification or overqualification for an educational level. For example, adolescents with a low SES and a lower level of intelligence than peers in university nonetheless meet all official requirements for entry into higher education, and as our data shows, to successfully complete this education. Second, the average intelligence among adolescents with a high SES who attain university education (i.e., High/High) may be inflated by a number of extreme outliers from a few intellectually gifted adolescents. The same argument applies to the average intelligence among adolescents with a low SES who attain practical vocational education. As such, intelligence levels of adolescents who experienced social mobility may be similar to the modal or median intelligence level of peers in their destination group. And third, intelligence (at age 11) and educational attainment (at age 26) were measured 15 years apart. The initial gap in intelligence between socially mobile and socially stable adolescents could have easily been closed in the meantime, for example through peer and teacher association, or higher educational expectations and academic self-confidence (Mortimer et al., 2017). We therefore conclude that our findings are more likely to support the meritocracy hypothesis than the glass ceiling/glass floor hypothesis.

Practical Implications

The Dutch educational system is characterized by relatively early educational stratification around the age of 11–12 (compared to the international average age of 14 or even 16 in Scandinavian countries; OECD, 2016). A potential advantage of early stratification is that it creates more homogenous groups of students early on which can increase teaching efficacy (Hanushek & Woßmann, 2006). However, early stratification also comes with the risk of underestimating the educational potential of underprivileged adolescents who have not fully blossomed yet as a result of having received limited investments throughout childhood (Van de Werfhorst & Mijs, 2010). Rearranging the educational system to reduce educational inequalities is a complex, resource consuming procedure. Our study suggests that simpler alternatives such as integrating a psychological assessment of effortful control (but not social competence) can be more feasible for improving the accuracy of educational advice and reducing bias.

Schools and teachers could in fact even consider stimulating the development of effortful control to boost educational performances and upward mobility (Pandey et al., 2018). While improvements in effortful control may be limited (for example by genetic predispositions; Krapohl et al., 2014), previous interventions have yielded modest but robust improvements that spill over into real-life (Allom et al., 2016; Boendermaker et al., 2017).

Strengths and Limitations

Our study is characterized by a number of strengths and limitations. Strengths include the large sample size, simultaneous testing of multiple early adolescent characteristics, and extensive analyses and robustness checks (all pre-registered). However, a number of limitations must be taken into account when interpreting our findings.

First, growing up in low SES circumstances may result in test scores that underestimate adolescents’ potential. For example, adolescents from a low SES background are more likely to have received lower quality education and training, less tutoring, or even miss out on breakfast before school (Conger & Donnellan, 2007; Zumbuehl et al., 2022). If under such circumstances, adolescents from a low SES background obtain average scores on standardized tests, this may be indicative of ‘untapped educational potential’ – in contrast to average scores of adolescents from a high SES background. Furthermore, in circumstances characterized by scarcity and unpredictability, displaying more impulsiveness instead of more effortful control may be more adaptive (Ellis et al., 2017) – and thus indicate more competence in a specific low SES context. Future studies may opt to broaden their measure of effortful control by taking into account different (socioeconomic) circumstances that may require different expressions of behavioural control.

Second, our tertile split categorization of parental SES may deviate from the SES ratio in the population. Due to difficulties to include and retain participants from the lower socioeconomic strata (Fakkel et al., 2020), the lower SES group may represent a relatively higher subgroup of the low stratum. However, considering that (1) we used 5 indicators to estimate parental SES, and that these 5 indicators tend to be positively correlated in the population; (2) our percentages of social reproduction and social mobility are in line with previous studies (e.g., OECD, 2018); and (3) alternative measures of parental SES, such as highest educated parent, may have similar shortcomings, we believe that our overall findings are likely to reflect the situation in the population.

Furthermore, differences between parental SES groups are relative and not absolute. As a result, upward mobility out of the lower parental SES group and downward mobility out of the highest parental SES group may be most likely to occur among adolescents whose parental SES is already closest to the middle parental SES group, whereas social reproduction is generally most rigid in the lowest and highest socioeconomic strata (De Neubourg et al., 2018; Hertz, 2009). While this would potentially result in overestimated or skewed odds for experiencing social mobility, our current extensive group comparisons provide sufficiently nuanced findings. Future research can aim to further distinguish between socioeconomic groups.

Third, upward mobility was more common than downward mobility in our sample which is in line with previous research (e.g., OECD, 2018). This may, however, also in part be the result of incorporating educational attainment in young adulthood into our measure of social mobility. Though educational attainment in young adulthood is a strong stable indicator of later adulthood SES (Erola et al., 2016), there is an important limitation to this measure of social mobility. In most cases, higher education is available to all adolescents who meet the entry requirements (e.g., 45.0% of TRAILS participants attained higher education). On the labor market, however, high-status, high-paid jobs are limited, and many higher educated young adults may thus not end up in such jobs. Therefore, using educational attainment as measure of young adulthood SES may overestimate the rate of true social mobility in the population.

Conclusion

Our findings indicate that social mobility happens commonly, and is driven by competencies more than by socioeconomic background. However, the importance of intelligence and effortful control for social mobility may in itself be somewhat unmeritocratic in nature, because both are (1) genetically determined to a considerable extent (Willems et al., 2020); and (2) better developed under high SES circumstances than low SES circumstances (e.g, Jerrim & Vignoles, 2013). Furthermore, alternative competencies related to creativity, problem solving, or interpersonal service may be somewhat overlooked in our educational system – despite strong demand on the labor market (Suarta et al., 2017). As a result, adolescents with such alternative competencies may feel stigmatized or unworthy from a very young age onwards. Hence, while it could be argued that our current educational system is as meritocratic as it intends to be, we also argue for a broader appreciation of competencies which would better reflect the sociocultural diversity among adolescents as well as the diversity in employer demands (Sandel, 2021).

Supplemental Material

Supplemental Material - Intergenerational Upward and Downward Social Mobility: The Role of Intelligence, Effortful Control, Assertiveness, and Peer Competence in Early Adolescence

Supplemental Material for Intergenerational Upward and Downward Social Mobility: The Role of Intelligence, Effortful Control, Assertiveness, and Peer Competence in Early Adolescence by Matthijs Fakkel, Susan Branje, Wilma A. M. Vollebergh, Gonneke W. J. M. Stevens, and Margot Peeters in Emerging Adulthood

Footnotes

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This work was supported by the Nederlandse Organisatie voor Wetenschappelijk Onderzoek (024.001.003).

Transparency and Openness Statement

The raw data, pre-registration, analysis syntax, and codebook/variable overview are all publicly available through the project created at the Open Science Framework (OSF; []). Any specific questions related to the materials are best directly addressed to the researcher(s).

ORCID iD

Matthijs Fakkel

Supplemental Material

Supplemental material for this article is available online.

Author Biographies

Matthijs (Ties) Fakkel is a postdoctoral researcher at the SYNC Lab (Erasmus University Rotterdam) after recently obtaining his Ph.D. at the department of Interdisciplinary Social Science, Utrecht University (NL). His research interests focus on the role of adolescent psychosocial competencies in the intergenerational transmission of socioeconomic status. As first author, Fakkel has been central to the investigation, conceptualization, methodology, formal analysis, writing, and visualization of this research paper.

Prof. Dr. Susan Branje is head of the department of Youth and Family at the Faculty of Social and Behavioral Sciences, Utrecht University. She is also Professor of Development and Socialization in Adolescence. Her expertise is in young people’s relationships with parents, siblings, friends and intimate partners in relation to their psychosocial adjustment. Branje has provided extensive input concerning the investigation, conceptualization, methodology, and writing of this research paper.

Prof. Dr. Wilma A. M. Vollebergh is an emeritus Professor of Youth Studies at the department of Interdisciplinary Social Science, Utrecht University. Her research expertise varies from cross-cultural education to socioeconomic inequalities in adolescent health and development. Vollebergh has been most helpful with the conceptualization, methodology, and writing of this research paper.

Prof. Dr. Gonneke W.J.M. Stevens is Professor of Adolescent Health & Wellbeing at the Department of Interdisciplinary Social Science, Utrecht University. She is an expert in multiple fields or research, including migration and diversity, social inequality, risk behavior, and trust, and most prominently, the (mental) health and well-being of adolescents in a local, national, and international context. Stevens has elaborately contributed to the investigation, conceptualization, supervision, methodology, and writing of this research paper.

Dr. Margot Peeters is an Associate Professor and program coordinator of Youth Studies at the department of Interdisciplinary Social Science, Utrecht University. In her research, she explores the development of youth culture focusing on subjects such as risk behavior and (substance) addiction, (problematic) gaming, truancy and externalizing behavior. Peeters has provided an invaluable contribution to the conceptualization, methodology, and writing of this research paper, as well as overall project administration.

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