The Development of Materialism in Emerging Adulthood: Stability,Change,and Antecedents

Abstract

The present study investigated stability and change in materialism in emerging adulthood as well as the predictive roles of socioeconomic status (SES) and gender on the development of materialistic values. Indicator-specific latent state-trait growth models were applied to four-wave longitudinal data from a sample of 738 Chinese college students. The results showed that materialism was stable: 67% to 86% of the variance in the reliable interindividual differences in materialism was due to trait factors. In addition, materialism showed an increasing trajectory over the college years, and this developmental trend could not be attributed to measurement artifacts or confounding influences. Moreover, low family SES magnified the increase in materialism, whereas being female predicted lower initial levels of materialism. Collectively, these findings illustrate the nature and antecedents of the development of materialism in emerging adulthood.

Keywords

materialism emerging adulthood stability change longitudinal study

Introduction

Materialism, or “the importance ascribed to the ownership and acquisition of material goods in achieving major life goals or desired states” (Richins, 2004, p. 210), is negatively related to a wide array of important life outcomes, such as well-being (Dittmar et al., 2014; Kasser & Ryan, 1993; Richins & Dawson, 1992), social functioning (Dittmar, 2010; Kasser & Ryan, 1993), achievement-related outcomes (Ku et al., 2014), and proenvironmental attitudes and behaviors (Gu et al., 2018; Hurst et al., 2013).

Given the negative consequences of materialism, research has increasingly addressed the development of materialism across the life span and under varying circumstances (Jaspers & Pieters, 2016; Kasser et al., 2004; Martin et al., 2019; Richins, 2017). However, existing studies focus mainly on the period before adulthood (Chaplin & John, 2007; Richins, 2017) and examine environmental influences (e.g., family circumstances, parenting style, and exposure to advertisements; see Richins, 2017). These studies are more cross-sectional in nature and have less longitudinal evidence (Chaplin & John, 2007; Martin et al., 2019). In addition, few studies have examined the stability and change of materialism. In studies that have included this issue, these results are not the focal topics of the studies and are not thoroughly explored. The present longitudinal research aimed to fill the gap in the previous literature by investigating how materialism develops over time in emerging adulthood, a period from the late teens through the twenties (Arnett, 2000). Three important questions are addressed.

Research Question 1: To what extent does materialism demonstrate stability or malleability over time?

Research Question 2: Are there intraindividual changes in the endorsement of materialistic values in this period?

Research Question 3: What individual characteristics contribute to this developmental change?

The Importance of Materialism Stability

In discussing stability and changes in materialism, it is important to distinguish different types of stability. Rank-order stability refers to the extent to which the relative ranking of individuals on the importance they ascribe to materialistic values remains constant over time. A high level of rank-order stability indicates that those who demonstrate a high/low level of materialism relative to others at a given time are more likely to remain high/low in materialism than others at a later point. In contrast, low rank-order stability suggests a more likely shift in materialism ranking over time. Mean-level change refers to the average absolute change in the level of materialism for a group of people. An increase in the relative ranking of the individuals within a group does not necessarily result in a mean-level increase across individuals.

Understanding the stability of materialism is of great importance. Theoretically, it indicates whether materialism may become a strong indicator of individual characteristics (at specific life stages)—that is, whether materialism can be a reliable and valid predictor of materialism-related thoughts, feelings, and behaviors over time. Practically, research on the stability of materialism can lend support to future targeted interventions regarding when materialism is malleable and how difficult it is for change to occur (for similar descriptions of the importance of personality stability, see Wagner et al., 2019).

Unfortunately, there is little information about the stability of materialism. The broader literature on value and value change has provided some insights, suggesting that basic personal values endure over time and across situations (e.g., Rokeach, 1973). Nonetheless, people experience significant changes in value priorities throughout their life span (e.g., Bardi et al., 2009; Milfont et al., 2016), especially during adolescence and young adulthood (Bardi & Schwartz, 1996). The aims of these changes are at least partly to help people better negotiate and adapt to the changing environment, to master developmental priorities, and to meet growing demands from multiple emerging social roles (Gouveia et al., 2015).

The present study focused on emerging adulthood, a transitional life period when people leave their homes, encounter new circumstances (for many, campus life), and face new demands (e.g., being financially independent, preparing for prospective jobs, and seeking intimacy; Arnett, 2000). We expect that materialism, like other personal values, can be relatively stable and yet reveal mean-level changes in emerging adulthood.

Stability and Change of Materialism in Emerging Adulthood

Erikson’s theory of stage development (Erikson, 1950) identified eight psychosocial stages across the life span and people’s relevant goals and values in each life stage. Of focal concern is the central crisis in identity formation versus role confusion, which is predominant in adolescence and is difficult to resolve without further exploration in emerging adulthood (Arnett, 2000; Erikson, 1950). Entrance into emerging adulthood, which encompasses college life, enables people to engage in extended identity exploration in the relationship, work, and worldview domains (Arnett, 2000), and to have the freedom to choose their lifestyle, hobbies, habits, and goals in a context in which they embrace diverse cultures, beliefs, and values.

Materialistic values are usually involved and even reinforced in this process of establishing a clearer identity and roles in relation to others. For example, emerging adults use material goods as tools to clarify self-identity (Chang & Arkin, 2002) and to maintain closeness with others (Isaksen & Roper, 2012). Emerging adults also turn to material possessions to manage temporarily unpleasant psychological states arising from stressful life events (e.g., Jiang et al., 2015). This is partly due to their misperception that the acquisition of desirable products can dramatically transform the way they are viewed by others, their relationships with others, and the extent to which they experience happiness in life (Richins, 2011, 2017). Given individuals’ motivation to seek an adult identity, relatedness, and desirable life circumstances in emerging adulthood, it is reasonable to assume that materialism is susceptible to environmental influence at this life stage.

In addition, emerging adulthood is typically characterized by striving for self-oriented and resource-related goals, such as studying, working, and developing meaningful relationships. During this period, the development of materialism is encouraged because (a) self-interest is highly valued and (b) the underlying motivation for education and occupation at this stage is, at least to some extent, concerned with the possession of material resources and how to acquire them (Jaspers & Pieters, 2016). Consequently, emerging adults may increasingly prioritize materialistic concerns as a means of achieving important life goals.

Past Research on the Rank-Order Stability of Materialism in Emerging Adulthood

Empirically, longitudinal research reporting the rank-order stability of materialism in emerging adulthood is rare and has yielded mixed findings. Using retest correlations, some studies have suggested that materialism demonstrates low stability over a 4-year span (Sheldon, 2005), other studies have indicated that materialism is highly crystallized after a 1-year interval (Wang et al., 2017), and the remaining studies (e.g., Kasser et al., 2014) have found medium-to-high stability of materialism (.43–.80) over varying time frames (6 months to 12 years).

Notably, extant research suffers from one basic methodological limitation—the reliance on retest correlations to illustrate stability. Retest correlations confound two important sources of stability factors, that is, trait factors and occasion-specific factors. Although trait factors often refer to an invariant component of a variable in an individual across time (e.g., Kenny & Zautra, 1995; Usami et al., 2019; Wagner et al., 2019), the present study defines a trait factor as the consistent component of the reliable variance that could not be explained by short-term state variability (i.e., occasion-specific factors). Accordingly, trait factors include long-lasting trait and trait growth influences (Bishop et al., 2015; Gnambs & Buntins, 2017). With regard to materialism, trait factors, such as childhood experiences and family environment, shape an initial state of reliable interindividual differences in materialism, affect them enduringly, and foster long-term changes in materialistic values across time. New experiences and life events, however, serve as occasion-specific factors that lead to the temporary within-person fluctuation of materialistic values and alter one’s relative ranking within a group or population. Both factors contribute to the rank-order stability of materialism.

Latent state-trait (LST) theory (Steyer et al., 2015) and its extension (e.g., Bishop et al., 2015) provide a comprehensive framework that separates trait variance (i.e., trait and trait growth components of materialism) from occasion-specific variance (i.e., influences of situational factors or person–situation interactions) and random measurement error (see the next part for details). Previous studies have applied LST analyses to trait constructs such as life satisfaction (Eid & Diener, 2004), the Big Five personality traits (Wagner et al., 2019), and self-esteem (Donnellan et al., 2012), and have found that trait effects contribute to the majority of the variance in the respective measures. However, no existing research has used LST methodology to evaluate the longitudinal consistency of materialism in emerging adulthood.

The first goal of the present study was to examine the rank-order stability of materialism in emerging adulthood. We adopted the LST perspective and partitioned the relative influence of trait versus occasion-specific factors. If materialism mainly consists of trait (vs. occasion-specific) variance, materialism can be interpreted as a trait-like (vs. state-like) construct in emerging adulthood.

Past Research on the Mean-Level Change in Materialism in Emerging Adulthood

For mean-level changes, the results are also inconclusive. A few empirical works show that emerging adults move toward intrinsic and self-transcendence values over time (Dobewall et al., 2017; Hope et al., 2014; Sheldon, 2005) because of advanced social roles and organismic valuing processes (Hope et al., 2014; Rogers, 1964; Sheldon et al., 2010). Another study using a direct measure of materialism found no consistent changes in materialism across studies (Kasser et al., 2014). The limitation of previous research lies in the conventional measurement points, which preclude more robust estimates of long-term value (Willett, 1989). Thus, longitudinal evidence with multiple waves of measures is needed to solidify the within-individual changes in materialism over time.

To date, the most comprehensive study was conducted by Jaspers and Pieters (2016). In their study, longitudinal data from 4,297 Dutch individuals (16–90 years old) over eight waves spanning 9 years were used to examine age effects on materialism across the life span. The results indicated that materialism followed a U-shaped developmental trajectory across the life span. That is, materialism decreased from adolescence to middle adulthood but increased again in late adulthood. Moreover, this age effect held after controlling for cohort effects, period effects, and a series of sociodemographic characteristics, such as income or employment status.

Although Jaspers and Pieters (2016) found an overall curvilinear change in materialism across the life span, a closer look at their results suggests that materialism might actually increase in emerging adulthood for the following reasons: (a) meta-analyses of prior research (study 1b) indicated the prevalence of materialism in young adulthood, (b) the desire for money became increasingly dominant as people aged (study 2), and more importantly, (c) a transitory rise in materialism was observed specifically during the period from age 20 to 25 (see figure 1 in Jaspers & Pieters, 2016). This evidence jointly supports an increasing trajectory of materialism in emerging adulthood.

Figure 1.

Path diagram of the indicator-specific latent state-trait growth model for materialism.

The Role of Socioeconomic Status (SES) and Gender

If emerging adults indeed show an increase in materialism, what factors might contribute to between-person variability in the development of materialism? Given that emerging adults may turn to materialistic values in search of group acceptance and self-identity and that emerging adults may internalize the importance of possessing material goods because of repeated exposure to self-interest and extrinsic, materialistic concerns in this period, any factors that increase the salience of materialistic-related engagement would magnify the increase in materialism.

Previous studies have linked SES with the development of materialism in adolescence. Compared with teenagers from well-off backgrounds, those from economically deprived backgrounds are more likely to construe materialistic consumption as a way to fit in with others and to restore self-worth (Chaplin et al., 2014; Isaksen & Roper, 2008); they, therefore, may orient themselves toward materialistic values (Chaplin et al., 2014; Ku, 2015). However, it remains to be explored whether family SES persists to affect the long-term growth of materialism beyond adolescence. We propose that because emerging adults from low-SES families are more occupied with materialistic-related thinking, feelings, and behaviors in the pursuit of an independent and social self (to ensure acceptance, maintain self-esteem, and save and earn money to support their family), they would experience a steeper increase in materialism over the college years.

In addition to SES, gender may play a crucial role in the development of materialism. Compared with males, females are more vulnerable to compulsive buying (Dittmar, 2010). Females also perceive more emotional, psychological, and symbolic value from shopping compared with males (Dittmar & Drury, 2000), suggesting a more positive attitude toward materialistic consumption. In addition, females place more importance on appearance and image concerns in their values, self-view, and self-evaluation compared with males (Dittmar, 2008). It is possible that female (vs. male) emerging adults will be more inclined to turn to materialistic consumption and endorse such materialistic values over time.

The Present Study

The objective of the present study was to investigate the stability and changes in materialism as well as the factors that contribute to individual differences in the growth trajectory of materialism. In doing so, the present study applied the indicator-specific LST growth model (Bishop et al., 2015) to longitudinal data covering 738 Chinese college students over a period of 3 years (2011–2014) with four-wave measurements of materialism. The indicator-specific LST growth model allows examination of both questions related to consistency/occasion-specificity (short-term state variability) and long-term trait growth (Bishop et al., 2015). To address whether materialism is stable or malleable over time, we tested the degree to which reliable variances in materialism could be explained by trait- versus occasion-specific components.

Another advantage of the indicator-specific LST growth model involves the examination of indicator-specific trait growth. Given that materialism is multidimensional (i.e., possession-defined success, acquisition centrality, and acquisition as the pursuit of happiness; Richins & Dawson, 1992) and that the three themes of materialism have distinct developmental trajectories (Jaspers & Pieters, 2016), we created three parcels representing the three facets and explored the differential patterns of indicator-specific trait change. We focused on mean estimates of the linear growth (slope) factors of materialism to examine the developmental trajectory of materialism.

Finally, to explore the developmental origin of materialism, a conditional model that included SES and gender as covariates was established to predict the initial levels as well as the developmental changes in materialism in emerging adulthood.

Method

Participants and Procedure

The present study was part of a project that examined the long-term consequences of materialism among Chinese college students. Our previous works focused on the boundary conditions and mechanisms in the longitudinal associations of materialism on well-being (e.g., Wang et al., 2017), whereas the current study focuses on the development and antecedents of materialism. This study was conducted in accordance with the ethical principles published by the local research ethics committee. The participants were 738 Chinese college students (56.0% females) who provided data in at least one wave of our four-wave longitudinal study between 2011 and 2014. The students were approached annually over 4 years (T1–T4, from freshman to senior year) through their schools (T1: September 2011, n = 642, M _age = 18.99 years, SD = 0.91 years, 57.8% females; T2: October 2012, n = 529, M _age = 20.03 years, SD = 0.93 years, 61.4% females; T3: September 2013, n = 546, M _age = 21.00 years, SD = 0.95 years, 63.1% females; T4: November 2014, n = 396, M _age = 22.14 years, SD = 0.95 years, 58.3% females).

On average, participants completed 2.90 waves (72.50% participation rate), but only one third (33.60%) participated in all four waves. Given the relatively high attrition rates, we conducted a series of independent-sample t tests to investigate whether those who participated in all four time points (stayer, n = 248) differed from those who did not (nonstayer, n = 490) with respect to the main variables (including materialism, age, gender, and SES). The results showed that stayers were more likely to report lower levels of materialism, but they did not differ from nonstayers in terms of gender, age, and SES (see supplemental material Table S1). Therefore, a full information maximum likelihood (FIML) approach was employed to provide unbiased and more efficient parameter estimates (Enders & Bandalos, 2001).

Measures

Materialism

Materialism was assessed with the Chinese version of the nine-item Material Values Scale (MVS; Richins, 2004). To ensure that the original translations were accurate and easily understood, the MVS was first translated into Chinese and then pilot tested using the back-translation approach prior to data collection. The scale assessed the extent to which participants conceived of owning and acquiring material goods as the defining feature of success, the central goal of life, and the means to acquire happiness. Participants responded to all the items on a 5-point scale from 1 (“totally disagree”) to 5 (“totally agree”). An example item was “Some of the most important achievements in life include acquiring material possessions.” Higher scores indicated higher levels of materialism. The Cronbach’s alpha coefficients for the overall scale were .66, .71, .74, and .70 from T1 to T4, respectively. In the present study, confirmatory factor analysis showed that the three-factor model had good fit across measurement waves: χ²/df = 1.30 to 1.87, comparative fit index (CFI) = 0.950 to 0.988, root mean square error of approximation (RMSEA) = 0.024 to 0.047, standardized root mean square residual (SRMR) = 0.027 to 0.036 (see Table S1 in the supplemental material).

Covariates

To evaluate the extent to which the developmental trajectory of materialism is robust to potential confounds and to test the developmental origins of materialism in emerging adulthood, we included family SES and gender (see Jaspers & Pieters, 2016) as control variables (97 participants had missing data for SES or gender). SES (M = 3.67, SD = 0.97, range = 1–7) was assessed by averaging across household income and parental education levels.

Analytic Strategy

Figure 1 provides a general path diagram for the model tested. Latent growth modeling (LGM) was used to estimate the growth trajectory of materialism over time. The latent intercept factor $ξ_{{int}_{i}}$ and latent slope factor $ξ_{{lin}_{i}}$ were specified to reflect individual differences in materialism scores at the first measurement occasion and the linear change in materialism across measurement occasions, respectively. Because previous research indicates a linear change in materialism in emerging adulthood (Jaspers & Pieters, 2016), the loadings $λ_{t}$ on each latent slope factor were fixed to 0, 1, 2, and 3 ( $λ_{t}$ = t $-$ 1, see Figure 1), corresponding to linear growth over the four measurement occasions.

To separate true trait change processes from situational influences and random measurement error, we introduced an extension of LGM, indicator-specific LST growth models (Bishop et al., 2015), that specified different intercept and slope factors for each measured variable (in the present study, the three parcels of materialism). Accordingly, we included a latent state residual factor $ζ_{t}$ at each measurement occasion. The four state residual factors were not correlated to each other or to the latent growth factors. The indicator-specific trait factor approach takes method-specific effects into account by allowing indicator-specific trait/growth factors to be correlated. Thus, no correlated errors (or additional method factors) need to be specified, which avoids underestimation of the trait stability of scales/parcels and their reliabilities (Geiser & Lockhart, 2012). Formally, the indicator-specific LST growth model for the observed score $Y_{i t}$ of measure i at measurement occasion t is given as

Y_{i t} = τ_{i t} + ∊_{i t} = ξ_{{int}_{i}} + λ_{t} ξ_{1 {in}_{i}} + γ_{i} ζ_{t} + ∊_{i t}

Here, $τ_{i t}$ , which represents the true score for measure i at time t, is further decomposed into three components: The two latent growth factors $ξ_{{int}_{i}}$ and $ξ_{{lin}_{i}}$ reflect the trait and trait change components for measure i, whereas the state residual factor $ζ_{t}$ describes situation effects unique to a specific measurement occasion t. Random measurement error $∊_{i t}$ reflects unsystematic influences on each observed score. Notably, we assessed the measurement invariance of materialism by constraining the loadings $γ_{i}$ on the latent state residual factors $ζ_{t}$ to be equal across time.

The LST methodology allows the partition of the observed variance into several variance components. The reliability coefficient Rel ( $Y_{i t}$ ) is the proportion of the variance of an observed variable that is explained by systematic processes (i.e., trait and trait growth processes + state variability), the consistency coefficient Con ( $τ_{i t}$ ) indicates the proportion of the true score variance that is due to trait and trait growth components, and the occasion-specificity coefficient OSpec ( $τ_{i t}$ ) indicates the degree to which true score variance is due to occasion-specific fluctuation, Con ( $τ_{i t}$ ) + OSpec ( $τ_{i t}$ ) = 1. Following Bishop and colleagues (2015), the observed variance Var ( $Y_{i t}$ ) in an indicator-specific LST growth model is specified as

Var (Y_{i t}) = Var (τ_{i t}) + Var (∊_{i t}) = Var (ξ_{{int}_{i}}) + λ_{t}^{2} Var (ξ_{{lin}_{i}}) + 2 λ_{t} Cov (ξ_{{int}_{i}}, ξ_{{lin}_{i}}) + γ_{i}^{2} Var (ζ_{t}) + Var (∊_{i t}) .

Then, we calculated the reliability Rel ( $Y_{i t}$ ) of the observed scores² as

Rel (Y_{i t})= \frac{Var (τ_{i t})}{Var (Y_{i t})} = \frac{Var (ξ_{{int}_{i}}) + λ_{t}^{2} Var (ξ_{{lin}_{i}}) + 2 λ_{t} Cov (ξ_{{int}_{i}}, ξ_{{lin}_{i}}) + γ_{i}^{2} Var (ζ_{t})}{Var (ξ_{{int}_{i}}) + λ_{t}^{2} Var (ξ_{{lin}_{i}}) + 2 λ_{t} Cov (ξ_{{int}_{i}}, ξ_{{lin}_{i}}) + γ_{i}^{2} Var (ζ_{t}) + Var (∊_{i t})} .

More relevant to the present topic, consistency Con( $τ_{i t}$ ) and occasion-specificity OSpec( $τ_{i t}$ ) were calculated as

Con (τ_{i t}) = \frac{Var (ξ_{{int}_{i}}) + λ_{t}^{2} Var (ξ_{{lin}_{i}}) + 2 λ_{t} Cov (ξ_{{int}_{i}}, ξ_{{lin}_{i}})}{Var (τ_{i t})}

and

OSpec (τ_{i t}) = \frac{γ_{i}^{2} Var (ζ_{t})}{Var (τ_{i t})} .

Thus, to the extent that materialism is stable, the true score variance should mainly consist of trait and trait growth components (i.e., a high proportion of Con( $τ_{i t}$ $)$ ).Otherwise, the majority of the reliable variance in materialism should be attributed to state variability (i.e., a high proportion of OSpec( $τ_{i t}$ $)$ ), suggesting the malleability and fluctuation of materialism.

All analyses were performed using Mplus 7.4 (Muthén & Muthén, 1998-2012). Model fit was evaluated using the CFI, the RMSEA, and the SRMR. Values of the CFI ≥ 0.95, RMSEA ≤ 0.06, and SRMR ≤ 0.08 reflect good fit (Hu & Bentler, 1999). A ΔCFI of 0.01 and ΔRMSEA equal to or greater than 0.015 were used as criteria to judge significant model differences (Chen, 2007). In addition, we report the Bayesian information criterion (BIC; Schwarz, 1978) as a complement for model comparisons. Invariance was supported if the nested models with more equality constraints did not cross the indicated thresholds and showed a smaller BIC.

Results

Descriptive Statistics

The stability correlations across 1 year were medium in size for the composite materialism scores (r = .50–.63, ps < .001, see Table 1) as well as for the three parcels of materialism (r = .38–.56, ps < .001, see Table 2), suggesting that materialism was moderately stable across time. Moreover, materialism showed a mean-level increase across the four measurement occasions, but the three parcels of materialism differed in their initial levels and in the magnitude of long-term changes (see Figure 2).

Table 1.

Descriptive Statistics of the Variables.

Variable	1	2	3	4	5	6
1. T1 materialism	—
2. T2 materialism	.50***	—
3. T3 materialism	.45***	.63***	—
4. T4 materialism	.37***	.53***	.52***	—
5. Gender^a	−.12**	−.07	−.10**	−.05	—
6. SES	.10*	.06	−.05	−.01	.11**	—
α	.66	.71	.74	.70	—	—
M	2.69	2.87	2.90	2.93	0.56	3.67
SD	0.52	0.52	0.53	0.50	0.50	0.97

Note. N varies because of missing data (range N = 396–642). SES = socioeconomic status.

^a 0 = male, 1 = female.

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

Table 2.

The Means, Standard Deviations, Covariances, and Correlations for the Three Parcels of Materialism Across Time.

Indicator	MVS₁₁	MVS₂₁	MVS₃₁	MVS₁₂	MVS₂₂	MVS₃₂	MVS₁₃	MVS₂₃	MVS₃₃	MVS₁₄	MVS₂₄	MVS₃₄
MVS₁₁	—	.14	.19	.16	.09	.09	.14	.08	.08	.12	.07	.11
MVS₂₁	.35***	—	.16	.11	.17	.07	.10	.17	.06	.05	.09	.03
MVS₃₁	.37***	.33***	—	.14	.12	.22	.14	.10	.19	.10	.08	.17
MVS₁₂	.40***	.27***	.28***	—	.18	.21	.21	.14	.15	.21	.08	.13
MVS₂₂	.22***	.43***	.24***	.42***	—	.16	.13	.22	.11	.13	.13	.06
MVS₃₂	.20***	.16**	.42***	.45***	.36***	—	.19	.16	.28	.17	.11	.21
MVS₁₃	.31***	.22***	.27***	.45***	.30***	.40***	—	.18	.24	.22	.08	.12
MVS₂₃	.23***	.45***	.21***	.33***	.56***	.37***	.40***	—	.17	.12	.14	.10
MVS₃₃	.18***	.13**	.35***	.32***	.25***	.56***	.49***	.38***	—	.16	.09	.21
MVS₁₄	.27***	.11*	.20***	.47***	.31***	.38***	.45***	.28***	.33***	—	.15	.21
MVS₂₄	.17**	.24***	.17**	.20***	.35***	.27***	.20***	.38***	.21***	.37***	—	.13
MVS₃₄	.24	.08	.34***	.30***	.14*	.46***	.26***	.25***	.45***	.46***	.34***	—
M	2.90	2.24	2.94	3.02	2.41	3.17	3.04	2.50	3.16	3.03	2.55	3.20
SD	0.65	0.65	0.77	0.67	0.62	0.69	0.71	0.62	0.71	0.68	0.60	0.66

Note. Correlations are shown below the diagonal, and covariances are shown above the diagonal. MVS = Material Values Scale.

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

Figure 2.

The observed mean scores including the standard errors for overall materialistic values and the three parcels of materialism measures.

Disentangling the Stability of Materialism

We disentangled the stability of materialism with indicator-specific LST growth models. The parameters corresponding to the linear LST growth model are given in Tables 3, 4, and 5. Fit indices illustrated that the indicator-specific LST growth models provided a good fit to the data (χ²(39, N = 738) = 88.323, p < .001, CFI = 0.972, RMSEA = 0.041, RMSEA 90% confidence interval [CI] = [0.030, 0.053], SRMR = 0.054, BIC = 11,402.913). Constraining the loadings on the latent state residual factors to equality did not worsen the model fit, χ² (45, N = 738) = 94.357, p < .001, CFI = 0.972, RMSEA = 0.039, RMSEA 90% CI = [0.028, 0.049], SRMR = 0.053, BIC = 11,369.323, ΔCFI = 0, ΔRMSEA = −0.002. Therefore, the measure of materialism functioned equivalently across time.

Table 3.

Parameter Estimates in the Linear ISGM.

Parameter label	Unconditional model		Conditional model
Parameter label	M/λ (SE)	Var (SE)	M/λ (SE)	Var/Res (SE)
Growth factor means and variances
ξ ${int}_{1}$	2.95*** (0.02)	0.18*** (0.03)	3.10*** (0.11)	0.16*** (0.03)
ξ ${int}_{2}$	2.29*** (0.02)	0.21*** (0.03)	1.92*** (0.12)	0.19*** (0.02)
ξ ${int}_{3}$	3.02*** (0.03)	0.23*** (0.03)	3.07*** (0.13)	0.21*** (0.03)
ξ ${lin}_{1}$	0.04*** (0.01)	0.02* (0.01)	0.13* (0.06)	0.01 (0.01)
ξ ${lin}_{2}$	0.10*** (0.01)	0.01 (0.01)	0.10* (0.05)	0.01 (0.01)
ξ ${lin}_{3}$	0.08*** (0.01)	0.00 (0.01)	0.17** (0.06)	0.00 (0.01)
State residual factor means and variances
ζ₁	0.00^a	0.09*** (0.02)	0.00^a	0.09*** (0.02)
ζ₂	0.00^a	0.06*** (0.02)	0.00^a	0.05*** (0.02)
ζ₃	0.00^a	0.08*** (0.02)	0.00^a	0.07*** (0.02)
ζ₄	0.00^a	0.07** (0.02)	0.00^a	0.06*** (0.02)
State residual factor loadings
γ₁	1.00^b		1.00^b
γ₂	0.70*** (0.11)		0.68*** (0.12)
γ₃	1.10*** (0.19)		1.18*** (0.24)
Error variances
ε₁₁	0.00^a	0.16*** (0.03)	0.00^a	0.17*** (0.03)
ε₂₁	0.00^a	0.20*** (0.02)	0.00^a	0.20*** (0.02)
ε₃₁	0.00^a	0.28*** (0.04)	0.00^a	0.27*** (0.04)
ε₁₂	0.00^a	0.18*** (0.02)	0.00^a	0.17*** (0.02)
ε₂₂	0.00^a	0.17*** (0.02)	0.00^a	0.17*** (0.02)
ε₃₂	0.00^a	0.17*** (0.02)	0.00^a	0.18*** (0.02)
ε₁₃	0.00^a	0.20*** (0.02)	0.00^a	0.20*** (0.02)
ε₂₃	0.00^a	0.14*** (0.01)	0.00^a	0.13*** (0.01)
ε₃₃	0.00^a	0.17*** (0.02)	0.00^a	0.16*** (0.03)
ε₁₄	0.00^a	0.14*** (0.03)	0.00^a	0.18*** (0.03)
ε₂₄	0.00^a	0.20*** (0.03)	0.00^a	0.22*** (0.03)
ε₃₄	0.00^a	0.16*** (0.03)	0.00^a	0.17*** (0.03)

Note. Unstandardized parameter estimates are presented. Gender (0 = male, 1 = female) and socioeconomic status (SES) were included as covariates in the conditional model. ISGM = indicator-specific growth model; λ = unstandardized factor loading (measurement invariance was established); Var = variance; Res = residual variance; LST = latent state-trait.

^a Fixed parameter based on LST theory. ^b Fixed for identification.

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

Table 4.

Coefficients Based on the Decomposition of the Variances of the Unconditional ISGM.

Parcel i	Time t	Rel( $Y_{i t}$ )	Con( $τ_{i t}$ )	OSpec( $τ_{i t}$ )
1	1	0.62	0.67	0.33
2	1	0.56	0.83	0.17
3	1	0.54	0.69	0.31
1	2	0.57	0.75	0.25
2	2	0.56	0.86	0.14
3	2	0.63	0.76	0.24
1	3	0.59	0.72	0.28
2	3	0.59	0.81	0.19
3	3	0.65	0.70	0.30
1	4	0.70	0.79	0.21
2	4	0.51	0.83	0.17
3	4	0.66	0.73	0.27

Note. Rel( $Y_{i t}$ ) = coefficient of reliability; Con( $τ_{i t}$ ) = coefficient of consistency; OSpec( $τ_{i t}$ ) = occasion-specificity coefficient. ISGM = indicator-specific growth model.

Table 5.

Trait Covariance and Correlation Estimates in the Unconditional ISGM.

Parameter	ξ ${int}_{1}$	ξ ${int}_{2}$	ξ ${int}_{3}$	ξ ${lin}_{1}$	ξ ${lin}_{2}$	ξ ${lin}_{3}$
ξ ${int}_{1}$	—	.10 (0.02)	.11 (0.02)	−.01 (0.01)	−.00 (0.01)	.00 (0.01)
ξ ${int}_{2}$	.54 (0.08)	—	.10 (0.02)	.00 (0.01)	−.02 (0.01)	−.02 (0.01)
ξ ${int}_{3}$	.52 (0.08)	.48 (0.08)	—	.02 (0.01)	.01 (0.01)	−.01 (0.01)
ξ ${lin}_{1}$	−.15 (0.18)	−.01 (0.15)	.35 (0.21)	—	.00 (0.00)	−.00 (0.01)
ξ ${lin}_{2}$	−.06 (0.22)	−.43 (0.14)	.18 (0.26)	.33 (0.36)	—	.01 (0.00)
ξ ${lin}_{3}$	−.02 (0.43)	−.83 (1.09)	−.26 (0.29)	−.28 (1.06)	1.17 (1.52)	—

Note. Correlations are shown below the diagonal, and covariances are shown above the diagonal. Standard errors are given in parentheses. ISGM = indicator-specific growth model.

The decomposition of the observed variance enables the examination of the stability versus the malleability of materialism in emerging adulthood. The proportions of reliability, consistency, and occasion-specificity are summarized in Table 4. The coefficients of reliability ranged from .51 to .70, suggesting that systematic influences (i.e., trait and trait growth processes and state variability) accounted for more than half of the observed variances in materialism. More important, the coefficients of consistency ranged from .67 to .86, indicating that the largest portions of reliable variances in materialism were attributed to trait and trait growth factors. However, occasion-specificity was not negligible because as much as one third (14%–33%) of reliable variance could be explained by within-person fluctuation of materialism. Taken together, the results indicate that materialism is relatively trait like in emerging adulthood, but the results leave room for materialism to illustrate malleability and state variability.

Developmental Trajectory of Materialism

To obtain a precise understanding of how materialism develops over time, we focused on the parameter estimates of the indicator-specific LST growth model (see Table 3).¹ The mean slopes for the three parcels of materialism were positive (M = 0.04–0.10, ps < .001), which suggested an increase in materialism over time. Constraining the means of the three slope factors to equal resulted in a reduction in model fit: ΔCFI = −0.009, ΔRMSEA = 0.005, BIC = 11,375.760 > 11,369.323. This indicates that the three parcels of materialism exhibited different change processes. Moreover, the variances for the latent intercept factors were significant (Var = .18–.23, ps < .001), suggesting that participants varied in their initial levels of materialism. For slope factors, however, the variances were nonsignificant (Var_{parcel 2} = .01, p = .24; Var_{parcel 3} = .00, p = .72) except for Parcel 1 (Var_{parcel 1} = .02, p = .023). Despite this, we proceeded to our final examination of factors that contributed to interindividual variability in the initial status as well as the developmental trajectory of materialism.

Developmental Origins

We estimated models that simultaneously included gender and SES as predictors of the intercept and slope factors of materialism. This conditional model served to test the robustness of the findings and to identify potential predictors of the growth trajectory of materialism. The model fit the data well: χ²(57, N = 641) = 100.881, p < .001, CFI = 0.973, RMSEA = 0.035, RMSEA 90% CI = [0.023, 0.046], SRMR = 0.053, BIC = 10,252.726.

Table 3 presents the parameter estimates of the conditional model. Again, we found significant linear slopes (M = 0.13–0.17, p = .004–.050). This finding indicated that, on average, participants showed an increase in materialism over the college years, and this effect held even after taking into account the role of demographic characteristics such as gender and SES.

A closer look at the predictive roles of demographic characteristics (see Table 6) suggested that SES positively predicted the intercept factors of materialism and negatively predicted the slope factors of materialism (Parcel 2 was an exception: B _lin = −0.01, SE = 0.01, p = .38). Compared with individuals from higher SES families, those from lower SES families reported a lower initial level of materialism but experienced a steeper increase in materialism over the college years. Contrary to our hypothesis, gender (0 = male, 1 = female) negatively predicted the intercept factors of materialism (Parcel 2 was an exception: B _int = 0.03, SE = 0.05, p = .58), indicating that females scored lower in materialism than males in their freshman year. Gender failed to predict the slope factors of materialism (B = 0.07–0.14, p = .35–.71). Together, the predictors in the model (i.e., SES and gender) accounted for 3.4% to 7.9% of the total variance in materialism intercepts and 3.1% to 38.6% of the variance in materialism slopes.

Table 6.

Regressions of Intercept and Slope Factors of Materialism on Gender and SES.

Predictors	Intercept factors			Slope factors
Predictors	Parcel 1	Parcel 2	Parcel 3	Parcel 1	Parcel 2	Parcel 3
Intercept	3.10*** (0.11)	1.92*** (0.12)	3.07*** (0.13)	0.13* (0.06)	0.10* (0.05)	0.17** (0.06)
Gender	−0.22*** (0.05)	0.03 (0.05)	−0.20*** (0.06)	0.02 (0.02)	0.02 (0.02)	0.01 (0.02)
SES	0.05 (0.02)	0.08** (0.03)	0.06* (0.03)	−0.03* (0.01)	−0.01 (0.01)	−0.03* (0.01)
Adjusted R ²	.08	.03	.05	.08	.03	.39

Note. The numbers in the table (except for R ²) represent regression coefficients (B). Standard errors are given in parenthesis. Gender: 0 = male, 1 = female. SES = socioeconomic status.

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

Discussion

Studies have long documented the negative consequences of materialism in various life domains. However, less attention has been paid to understanding the nature and antecedents of materialism over time. To address these issues, the present study examined the rank-order stability and developmental trajectory of materialism in emerging adulthood. In addition, individual characteristics such as SES and gender were used to predict the development of materialism over time. We found the following results: (a) Materialism was trait like, (b) materialism showed an increasing trend across the college years, and (c) low SES magnified the increase in materialism, although females reported lower initial levels of materialism.

The Stability of Materialism in Emerging Adulthood

Consistent with the finding that values are fairly enduring and stable across time (Rokeach, 1973), materialism displayed medium rank-order stability (in the sense of retest correlations) over the 1-year period. The decomposition of materialism variance using an indicator-specific LST growth model further showed that the majority (67%–86%) of reliable variance in materialism could be attributed to trait and trait growth processes. Therefore, materialism is characterized by a substantial amount of stability in emerging adulthood. Trait factors, such as childhood experience and family environment, contribute substantially to initial interindividual differences in materialism and maintain the relative ranking of materialism within a group over time. However, it should be noted that the proportions of state residual variances are not negligible even after a short time interval (i.e., 1 year). This suggests the existence of fluctuation or malleability of materialism that is due to new experiences, life events, and person–situation interactions. Given the instrumental role of materialism in the extended exploration of identity and social roles as well as in the escape from undesirable psychological states (Chang & Arkin, 2002; Chaplin & John, 2005; Isaksen & Roper, 2012; Richins, 2011, 2017; Sheldon & Kasser, 2008), it is not surprising that materialism is susceptible to environmental influence. Collectively, our results reveal that materialism has a stable kernel but is still responsive to situational influences.

The present study enriches the understanding of the stability of materialism. Due to the lack of a more precise differentiation of the source of variance in materialism, previous longitudinal studies have explored the stability of materialism but confounded its different sources (e.g., Kasser et al., 2014; Sheldon, 2005; Wang et al., 2017). The present study is the first to separate long-term consistency from temporary within-person fluctuation in the reliable individual differences of materialism. The finding that occasion-specific factors explained up to one third of the variance in materialism might provide an explanation for why experimental manipulation and the intervention of materialism targeting young people (e.g., Chaplin et al., 2019; Lambert et al., 2009; Sheldon & Kasser, 2008) has usually resulted in satisfactory results. However, laboratory and intervention studies typically focus on short-term effects, which might fall within state residual variance. Thus, a more valuable issue would be to examine whether and how intervention efforts foster long-lasting trait change in materialism in emerging adulthood.

Notably, the LST growth model is not the only method (and is not the necessarily popular approach) to analyze the current data. Other analytic approaches such as the trait–state–occasion model (TSO; Cole et al., 2005) and the trait–state–error model (TSE; also known as the STARTS model, see Kenny & Zautra, 1995) might serve as alternative models and complement information concerning the stability of materialism.² However, the LST growth model shows its unique strength, in that, it presents a single hybrid analysis on both the short-term state variability and long-lasting trait growth processes (Bishop et al., 2015). In other words, the LST growth model extends beyond the clear differentiation of stability components and simultaneously taps into the developmental trajectory of materialism.

Developmental Increase in Materialism

Our results showed a normative increase in materialism over time, implying that emerging adults ascribe more importance to materialistic values throughout the college years. This result is inconsistent with the hypothesis that materialism decreases with age due to the mastery of developmental priorities and cumulative maturation (Chaplin & John, 2007; Sheldon, 2005; Sheldon et al., 2010). In addition, this finding conflicts with empirical research showing that emerging adults orient away from extrinsic values toward intrinsic strivings over time (Dobewall et al., 2017; Hope et al., 2014; Sheldon, 2005).

However, the current findings are consistent with those of a recent study on the life span development of materialism. Whereas Jaspers and Pieters (2016) documented a fluctuating upswing in materialism and an ongoing increase in monetary desires in emerging adulthood (Jaspers & Pieters, 2016), we observed a linear rise (although the three parcels differed in growth patterns) in materialism, suggesting that materialism monotonically increases and reaches a maximum until the end of the college years. Expanding on previous findings, the present study taps into a distinct period (i.e., emerging adulthood) when materialistic values consolidate rather than weaken. Notably, the self-report measures of materialism functioned equivalently across the college years. This result, coupled with our examination of the robustness of the developmental trajectory, suggests that the overarching trend cannot be attributed to measurement artifacts or confounding effects but rather reflects actual developmental changes.

Several explanations can account for the findings. First, it may be that the primary focus on self- and resource-oriented tasks in this period prompts emerging adults to rely on tangible resources to achieve important life goals and to be more concerned with self-welfare and self-centered values, which might “crowd out” intrinsic aims in life (Frey & Oberholzer-Gee, 1997). Second, the mean-level increase may be a transitory state. Therefore, previous research may have overlooked the mean-level increase when the interval was large enough to bypass the transitional period or when measurement occasions were too few to provide reliable estimates of longitudinal trait change (Willett, 1989). As people age and enter middle adulthood, they may be oriented toward other-centered values (e.g., the welfare of families, communities, and societies), suggesting a concomitant decline in conflicting values such as materialism.

More broadly, we speculate that cultural differences may explain, at least in part, why we observed an increasing trajectory of materialism that contradicts the findings of previous studies (which have been conducted exclusively in Western countries). The emphasis on academic excellence leaves little time for Chinese students to manage money matters or obtain a taste of financial independence before adulthood. Consequently, Chinese students place less focal attention on materialism-related concerns. However, entrance into college life enables students to obtain full spending power and consumption freedom for the first time, to choose what they spend and how much they consume and to begin to think about being financially independent. Accordingly, the explosion of life themes regarding materialistic concerns makes materialistic-oriented thinking and behaviors highly available and accessible, which may direct Chinese college students toward extrinsic strivings over time.

Notably, we do not expect that the normative increase in materialism in emerging adulthood is an exception that is specific to Chinese culture as recent longitudinal evidence has documented an upswing in materialism in this period among Western populations (Jaspers & Pieters, 2016). Instead, we suggest that because materialism and conspicuous consumption are increasingly prevalent in China (Podoshen et al., 2011), the developmental increase is “amplified” in the context of modern Chinese culture. Despite our reasoning, future research is needed to directly test whether cultural differences serve as a predictor of differential patterns of developmental changes in materialism.

Influence of SES and Gender

One final issue that should be highlighted is the examination of the influence of SES and gender on the initial levels and the development of materialism. Overall, the results showed that low levels of SES predicted smaller intercepts of materialism and predicted larger slopes of materialism, suggesting that compared with higher SES counterparts, emerging adults from lower SES families started out with lower levels of materialism but experienced more rapid growth in materialism over the college years. This finding dovetails with the notion that young people growing up in economically disadvantaged circumstances count on materialism as a compensation strategy for security and self-certainty (Ku, 2015). However, lower SES emerging adults were no more materialistic than higher SES counterparts when they had just entered college life; indeed, they scored lower in initial materialism.

A possible explanation is that an affluent childhood environment may make people likely to rely on tangible resources for the mastery of developmental priorities (Richins, 2017). Consequently, materialistic concerns become more salient for emerging adults from high-SES families. Going through the college years, however, would make such developmental patterns different. Whereas higher SES emerging adults learn how to cope with daily events in a less materialistic way (due to more mature practice), lower SES individuals may still be “occupied” with the explosion of materialistic themes arising from new events, experiences, and demands. Over time, low-SES adults end up with a steeper increase in materialism.

Unlike SES, gender did not predict the trajectory of materialism. Instead, gender predicted the intercept factors of materialism. We found that compared with males, females tended to report lower levels of materialism in the freshman year. This finding is contrary to the prediction that females may be (more) predisposed to materialistic values because they attach more emotional and identity-related value to shopping and consumption (Dittmar, 2010). Regardless, the gender difference is modest at the first measurement occasion (d = 0.05–0.30), and this gender gap persists without narrowing or widening during emerging adulthood. This finding is in line with the gender similarity hypothesis (Hyde, 2005), and indicates that entering into emerging adulthood poses challenges and opportunities to males and females equally with regard to the relative importance they place on owning possessions and material goods.

Limitations and Future Directions

Some limitations of the present study should be noted. First, all data were self-reported with explicit measures. Considering that peer reports provide additional information about personality traits over and above self-report data (Connelly & Ones, 2010) and that implicit measures of materialism (e.g., Muniz-Velazquez et al., 2017) have several advantages beyond explicit assessment, multimethod designs would help to solidify the findings about the development of materialism while ruling out confounding influences, such as self-perception bias and social desirability bias.

Second, the variables in the current study (SES and gender) explained only small portions of the variance in initial levels and slopes of materialism. In addition, these predictors are trait factors. It may be important to explore other possible predictors of the trajectory of materialism after taking into account the roles of occasion-specific factors. For example, daily stressful events are associated with maladaptive personality change (Ong et al., 2019). It is possible that emerging adults who are frequently exposed to such events would turn to materialism as an escape and thus experience more rapid growth in materialism.

Another limitation of this study is the fact that the participants were exclusively college students. Future longitudinal studies are needed to establish the generalizability of the findings not only to other emerging adults who do not receive higher education but also to emerging adults in other nations that share similar cultural contexts with China. In addition, we focused solely on longitudinal relations during the college years. It remains to be explored whether there are ongoing developmental changes in materialism beyond the college years. For example, recent evidence suggests that the choice of an academic versus a vocational pathway matters for long-term personality change (Golle et al., 2019). Future research can test whether and how different career pathways are associated with a differential pattern of materialism development and its downstream effect over time.

Finally, the nine-item version of the MVS precluded a more fine-grained analysis of indicator-specific trait change. Future research that captures a broader spectrum of materialistic values (e.g., the full MVS) is needed to better illustrate the differential patterns of changes for the three themes of materialism.

Conclusion

To date, this is the first study to systematically investigate the stability and change of materialism in emerging adulthood among non-Western samples. The findings showed that materialism displayed a stable pattern over time as most variances in reliable interindividual differences in materialism fell into trait and trait growth components. We also found a normative increase in materialism over the college years. Moreover, low SES accelerated the increase in materialism. In conclusion, the present study advances our understanding of the developmental change in materialism and sheds light on the nature of and change in materialism in emerging adulthood.

Supplemental Material

Supplemental Material, Jiang_Online_Appendix - The Development of Materialism in Emerging Adulthood: Stability, Change, and Antecedents

Supplemental Material, Jiang_Online_Appendix for The Development of Materialism in Emerging Adulthood: Stability, Change, and Antecedents by Wen Jiang, Hongyun Liu and Jiang Jiang in Personality and Social Psychology Bulletin

Supplemental Material

R2.Supplementary_Material - The Development of Materialism in Emerging Adulthood: Stability, Change, and Antecedents

R2.Supplementary_Material for The Development of Materialism in Emerging Adulthood: Stability, Change, and Antecedents by Wen Jiang, Hongyun Liu and Jiang Jiang in Personality and Social Psychology Bulletin

Footnotes

Authors’ Note

This study, which was based on data collected from 2011 to 2014, was not preregistered. Participants did not consent to individual-level data being shared with the public. All output files, including measurement invariance and (unconditional and conditional) indicator-specific latent state-trait growth models, are available at: .

Author Contributions

W.J. was involved in the study design and article writing, and was responsible for data processing and data analysis. H.L. was involved in data processing and data analysis. J.J. was involved in the study design, data collection, and article writing.

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 study was supported by Chinese National Funding of Social Sciences (Number 13BSH055).

ORCID iD

Jiang Jiang

Supplemental Material

Supplemental material is available online with this article.

Notes

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