Balancing Identities: How Economic Inequality and Class Affect Work-life Balance

Silvia Filippi , Caterina Suitner , Bruno Gabriel Salvador Casara , Davide Pirrone , Mara Yerkes
1 1 1 2 2

1
University of Padua

Utrecht University
2

Author note

This research was supported by the 2017 PRIN research grant awarded by the

Italian Ministry of Education to Anne Maass (2017924L2B). Correspondence concerning this

article should be addressed to Silvia Filippi, Department of Developmental

Psychology and Socialization, University of Padova, Via Venezia 8, 35131 Padova (PD), Italy.

Email: silvia.filippi.1@phd.unipd.it

Declarations of interest: The authors declare no conflict of interest or funding sources. Studies

were approved by institutional IRB board and all participants consented to study protocols and data

use online. The present manuscript follows ethical guidelines specified in the APA code of

conduct and follows authors’ national ethics guidelines.

Datafiles and materials associated with the manuscript will be posted openly online on OSF.
 Abstract

Work-Life Balance (WLB) is recognized as a fundamental part of people’s well-being and

prioritized in European policy making. Until recently, little attention was given to the role of

economic inequality in people's inferences of WLB. In Study 1, we experimentally tested and

confirmed a) the effect of economic inequality on WLB, and b) the role of status anxiety in

mediating this relationship. In Study 2, we provided a replication and advancement of Study 1 by

manipulating socioeconomic class in addition to economic inequality. Results showed that in the

inequality condition, people expected less WLB through a partial mediation of status anxiety and

competitiveness. We also found that class mattered, with economic inequality mainly affecting

participants in the low-class condition. In sum, economic inequality enhanced participants’

competitiveness and concern about their social status, which in turn affected WLB. This

demonstrates the need for policies promoting WLB in those countries characterized by high

inequality.

Keywords: work-life balance, economic inequality, socioeconomic class, status anxiety,

competitiveness

1
 Introduction

Economic inequality is increasing in most OECD (Organisation for Economic Co-operation

and Development) countries (Oxfam, 2019), with several negative consequences at the individual

and societal level (Wilkinson & Pickett, 2010). Economic inequality is related to several negative

societal outcomes, such as the incidence of homicides and violence (Elgar & Aitken, 2011), lower

solidarity among people (Paskov & Dewilde, 2012), and increased erosion of social cohesion

(Sandel, 2020). The latter negative outcome is specifically related to the perceived distinctions

between socioeconomic classes, which can be rapidly and easily determined by citizens since

ubiquitous cues provide clear signals in everyday life (Kraus et al., 2017). On the one hand, low

social mobility is particularly present in highly unequal societies (Wilkinson & Pickett, 2007). On

the other hand, low social mobility damages social cohesion and support. The outcomes of this

vicious circle are mutual distrust, increased unhappiness, and -particularly relevant for the present

work- competitiveness and anxiety related to one's socioeconomic status (Buttrick & Oishi, 2017;

Paskov et al., 2013; Sánchez-Rodríguez et al., 2019). As economic inequalities increase, so too does

status anxiety (Layte, 2012) because economic stratification is salient, prompting competitiveness

and anxiety about one's position in society (Sánchez-Rodríguez et al., 2019; Wilkinson & Pickett,

2010). Indeed, high status entails a range of benefits, such as economic rewards, privileged access

to scarce resources, respect, and recognition by others (Paskov et al., 2013). Moreover, the

motivation to enhance one’s social status represents one of the core human values (Schwartz, 1992),

and is considered a natural phenomenon among people (Marmot, 2004). Despite this, a growing

concern about one's position in society is not always linked to positive outcomes, as status anxiety

can lead to a number of health-related stressors and decreased social trust (Elgar & Aitken, 2011).

Concerns about achieving status can generally be unpleasant (De Botton, 2008; Delhey &

Dragolov, 2014; Wilkinson & Pickett, 2009) and are not believed to motivate action, but rather may

be cognitively taxing or distracting, which may interfere with work tasks and private life.

2
Specifically, Bowles and Park (2005) stated that status anxiety and competition within the

workplace influences individuals’ allocation of time between labour and leisure, often resulting in

longer working hours. In sum, the perception of economic inequality may have consequences in

how people balance work and private life, due to status anxiety and competitiveness.

Work-life balance (WLB), a fundamental component of people’s well-being (OECD, 2011),

is a long-debated topic in science and a new policy priority in the European Union (e.g., see

European Commission, 2019). WLB is defined as “the individual perception that work and non-

work activities are compatible and promote growth in accordance with an individual’s current life

priorities” (Kalliath & Brough, 2008, p. 326). Research in the field of psychology and the social

sciences shows that WLB can provide benefits to different areas of life. WLB has positive effects

on both work-related (e.g., job performance, productivity, career development), and non-work

related (e.g., life satisfaction, family performance) outcomes (Khan & Fazili, 2016; Konrad &

Yang, 2012; Pheng & Chua, 2019; Whiston & Cinamon, 2015). Conversely, difficulties in

combining paid work with other activities negatively impact health, and increase stress, anxiety, and

depression (Haar et al., 2014; Khan & Fazili, 2016).

Several factors at the individual, organizational, and country level shape people’s WLB. Yet

the relationships between economic inequality and work-life balance remain understudied.

Recently, Hook and Paek (2020) highlighted that earnings inequality can disrupt the positive effect

of national family policies on maternal employment. Moreover, Chatrakul and colleagues (2019)

show that varying access to resources affects individuals’ real freedom to achieve a satisfactory

WLB. Extending this reasoning, economically unequal contexts may decrease people's ability to

balance work and non-work activities, yet whether this is the case and what this looks like remains

unclear.

While direct evidence is absent, related research leads to contrasting expectations. On the

one hand, a line of studies shows that those who are at the top of the wealth hierarchy are more

tolerant of inequality than those at the bottom (Hadler, 2005) and they are more motivated to

3
maintain such conditions of inequality (Brown-Iannuzzi et al., 2015). In fact, high status people are

less likely to endorse concrete strategies to reduce inequality compared to lower status individuals

(Bratanova et al., 2016; Côté, et al., 2015; Dawtry, et al., 2015; Piff et al., 2010). However,

economic inequality may evoke anxiety and fear among upper class individuals because they may

face increased awareness about possible consequences of downward social mobility. This constant

threat may intensify competition, and individualism (Sánchez-Rodríguez et al., 2019). According to

a cross-country correlational study by McGinnity and Calvert (2009), socioeconomic status may

affect subjective work-life conflict, especially among higher professionals, who are expected to

work longer hours and have more personal responsibility than non-professional workers. A second

line of studies suggests, in contrast, that low class individuals may struggle in an unequal context,

since they are more likely to live in an ongoing situation of resource scarcity and relative

deprivation (Wilkinson & Pickett, 2007; Mishra et al., 2012). Since economic inequality and

poverty are intrinsically connected (Nolan & Ive, 2009), poor people may face difficulties in

balance working and private life, given their disadvantaged situation (Warren, 2005). Indeed, low

status groups are more likely to have low wages and thus need to work sufficient hours in order to

afford living costs, neglecting other parts of life. According to Johnson and Lipscomb (2006),

working class individuals also have less control over their working schedule. Moreover, while high-

earning professionals may have the opportunity to alleviate work-life conflict by paying for

childcare or domestic labour, low-earning workers (Scherer & Steibe, 2007) may not have the same

privilege. Similarly, the quality of time spent on non-work activities may also be negatively affected

by their socioeconomic status.

Altogether, the reviewed literature suggests a potential link between economic inequality

and WLB. However, the two contrasting lines of studies call for specific testing the role of

socioeconomic class as a potential moderator in the relation between inequality and WLB.

The present research

4
 Although the literature suggests a link between subjective economic inequality and WLB,

there is still a lack of direct empirical evidence for a causal relation. One of the goals of the present

work is to fill this gap, by testing this relationship. Moreover, we suggest that living in a context

perceived to be economically unequal poses different challenges and threats to people belonging to

different socioeconomic classes.

In Study 1, we aim to test whether experimentally manipulating perceived economic

inequality leads to higher status anxiety, which in turn may decrease people's inferences of WLB.

In addition, in a preregistered Study 2, we aim to conceptually replicate Study 1 and to further

experimentally test the effect of socioeconomic class on inferred WLB. Moreover, we aim to

explore how economic inequality and identification with different socioeconomic classes affect

inferences of WLB through two potential psychological mediators: status anxiety and

competitiveness.

Data files and materials associated with the manuscript are posted openly online on OSF

(link: https://osf.io/3a6w9/?view_only=eb5e75fb0cff4314b31574588aca7f9f).

Study 1

In this first experiment, we manipulated the perception of inequality using the Bimboola

paradigm (Sánchez‐Rodríguez et al., 2019; Sprong et al., 2019). Specifically, participants had to

imagine their life in a fictional scenario characterized by high (vs. low) economic inequality. We

predicted that participants would expect their life to be characterized by lower WLB (H1) and more

status anxiety (H2) when assigned to a high (vs. low) economically unequal society. Given past

evidence suggesting a strong link between economic inequality and status anxiety (Paskov et al.,

2013), we also predict that status anxiety mediates the effect of the experimental conditions on

expectations of WLB (H3).

Method

5
Participants

The sample consisted of 81 bachelor students and teaching assistants of a course of Work

and Organizational Psychology (87.7% female, 12.3% male, 0% non-binary) aged between 19 and

36 years old (M = 21.06, SD = 2.92). Participants were sent a link to the online platform Qualtrics

which hosted the survey. Most participants (87.7%) were students; 9.9% were students with

employment and employees, and 1.2% were self-employed. Participants' highest education was a

high school diploma (90.1%), Bachelor’s degree (3.7%), Master’s degree (3.7%) and PhD (2.5%).

The majority of participants self-identified as belonging to the middle class (42.0%), upper-middle

class (33.3%), lower-middle class (22.2%), and 2.5% to low class. Participants reported a mean

score of 3.41 (SD = 2.10) for their political orientation on a scale from 0 (extreme left-wing) to 10

(extreme right-wing).

Material and measures

Perceived economic inequality

After signing the informed consent, participants were presented with the experimental

manipulation. Using the experimental paradigm developed by Jetten and colleagues (2015), we

manipulated perceived economic inequality (high vs. low) between participants. Participants were

asked to imagine that they were going to start a new life in a fictitious society named Bimboola,

whose income distribution was varied in two conditions to which participants were randomly

assigned:

- in the high economic inequality condition, Bimboola was characterized by three income

groups, which differed greatly in the average annual income earned (3000 Bimboolean Dollars per

year for the lower class; 40,000 Bimboolean Dollars per year for the middle class; 77,000

Bimboolean Dollars per year for the upper class);

6
 - in the low inequality condition, the three income groups differed slightly in their annual

earnings (lower class= 30,000 Bimboolean Dollars per year; middle class = 40,000 Bimboolean

Dollars per year; upper class = 50,000 Bimboolean Dollars per year).

Following Jetten and colleagues (2015), all participants were assigned to the middle class.

To improve the procedure’s realism and make the manipulation more effective, after asking

participants to imagine starting a new life in Bimboola, we invited them to make essential choices

for their new life, such as buying a house, a means of transportation, and a possible holiday.

Participants saw facilities available for all 3 socioeconomic classes in Bimboola but could only

purchase those that their socioeconomic class could afford. Whereas houses, means of transport,

and holidays in the low inequality condition were similar between income groups, items for the

wealthiest in the high inequality condition were significantly more luxurious than those of the

middle-class group. This was particularly true compared to the lower class, who could only

purchase substandard houses and old bikes. The poorest in the high inequality conditions could also

not afford to go on any kind of holiday. The options for the middle class were identical between the

two conditions.

After completing this task, participants answered 4 manipulation-check questions on a 10-

point Likert scale (from 0 = Strongly disagree to 10 = Strongly agree) regarding the economic

standing of the group they were assigned to (“my group is poor” and “my group is rich” (r = -.70),

and income inequality in Bimboola (“Income differences between Bimboola’s citizens are low” and

“Income differences between Bimboola’s citizens are high”, r = -.95).

Work-life balance

Expected WLB (referring to a Bimboolean citizen) was assessed with 17 items of the Work/

Nonwork Interference and Enhancement Scale (Fisher & Bulger, 2009), translated to Italian by two

authors (α = .76). This scale offers a broad and inclusive overview of the concept of WLB that is

not confined to that of work-family balance and is therefore independent of marital and family life

7
status. The scale is divided into four sub-scales, assessing participants’ work

interference/enhancement with personal life (WIPL) (e.g., “He/she comes home from work too tired

to do things he/she would like to do”); personal life interference with work (PLIW) (e.g., “When he/

she is at work, he/she worries about things he/she needs to do outside work”); work enhancement

of personal life (WEPL) (e.g., “Because of his/her job, he/she is in a better mood at home”), and

personal life enhancement of work (PLEW) (e.g., “His/her personal life helps him/her to relax and

feel ready for the next day’s work”). Response options ranged on a 10-point scale from 0 = Strongly

disagree to 10 = Strongly agree. In order to analyse participants’ inferences of WLB, items from

the WIPL and PLIW sub-scales were reversed.

Status anxiety

To investigate expected status anxiety, we used an Italian adaptation of the scale used by

Dehley and colleagues (2017). Participants were asked to what extent they agreed or disagreed with

the following 2 statements on a 10-point scale (0 = Strongly disagree, 10 = Strongly agree),

thinking about a citizen in Bimboola: “Some people look down on him/her because of his/her job

situation or income”, and “He/she does not feel that the value of what he/she does is recognized by

others'' (α = .85).

Results

To test H1, we ran two independent samples t-test using the software JASP (JASP Team,

2020).

Results illustrate that participants in the low economic inequality (MWLB = 5.35; SDWLB = .91;

Manxiety = 4.70; SDanxiety= 1.80) condition showed higher levels of WLB (t = 4.701, p < 0.001, 95% CI

= .58; 1.44, d = 1.054) and lower status anxiety (t = -7 .536, p < 0.001, 95% CI = -3.41; -1.98 , d = -

1.69) compared to those in the high economic inequality condition (MWLB = 4.34, SDWLB = .99,

Manxiety = 7.40, SDanxiety = 1.43).

8
Mediation Analysis

To examine whether status anxiety mediated the relationship between EI and WLB, we used the

software JASP (JASP Team, 2020) with bootstrapping for 5,000 resamples and 95% confidence

intervals (Preacher & Hayes, 2008). As illustrated in Figure 1, a significant indirect effect of

inequality manipulation on WLB, b = -.59 (SE = .17), 95% CI = [-1.03, -.28], was fully mediated

b = -.35 (SE = .24), 95% CI = [-.82, .15] by status anxiety. Moreover, the effect of status anxiety on

WLB was -.46, 95% CI [-.71, -.21]. Thus, H2 and H3 were supported.

Figure 1: Mediation model representing the relationship between economic inequality and WLB

mediated by status anxiety. Standardized coefficients are presented. Solid arrows and asterisks

indicate significant paths. Asterisks indicate p < .05.

Discussion

Study 1 provides initial evidence about the role of economic inequality in shaping people’s

inferences of WLB. That is, participants randomly assigned to the high inequality condition tended

to envisage less WLB as citizens of that society. This result was mediated by the status anxiety

elicited by the unequal economic situation. While our data shed light on so far neglected predictors

of WLB, these results also raise some questions concerning the role of socioeconomic class. In fact,

economic inequality may threaten high- vs. low- status group members in different ways and

degrees. Indeed, McGinnity and Calvert (2009) highlighted that high-earning privileged

professionals may perceive enhanced work-life conflict due to longer working hours and higher

pressure. In contrast, Warren (2005) argued that economic precarity may have a negative impact on

9
working class individuals’ WLB. Moreover, different theoretical approaches point towards different

potential mediators of this relationship. First, according to the Social Identity Approach (Tajfel &

Turner, 1979), members of low-status groups struggle to achieve a positive image of themselves

and their group and may be particularly threatened by the status anxiety triggered by high

inequality. Whereas, high-status individuals already have a positive image of their group, possibly

making less relevant for them the effect of inequality on status anxiety. A second possible

mediator, namely competitiveness, is specifically sustained by two other theoretical frameworks,

namely Relative Deprivation (Walker & Smith, 2002) and the Realistic Conflict Theory (e.g., Esses

et al., 2005; Sherif, 1961). According to the Relative Deprivation account, people assigned to the

low and middle classes in the high inequality condition would perceive their in-group as deprived

compared to middle and high-status individuals respectively. Such relative deprivation may then

result in enhanced competitiveness (Halevy et al., 2010). According to Realistic Conflict Theory,

the concrete threat of poverty may highlight resources-related problems, especially for low class

individuals, with the final outcome of enhancing competition toward others. Economic inequality

may also have a negative impact on upper class individuals. This can occur as the perception of

competitiveness may be enhanced by polarized and therefore highly evident and salient class

differences and strong intergroup conflicts of an unequal condition. From this perspective, the

perception of belonging to the middle class may have features that can result in both status anxiety

and competitiveness. On one hand, people of the middle class may experience status anxiety for the

same reason as low-status group members, namely they feel the need to perceive themselves

favourably compared to the high-status outgroup. On the other hand, middle class individuals may

also be threatened by perceived competition, as they may lose their resources.

In order to expand our research and to test these relationships, Study 2 was designed to conceptually

replicate the results of Study 1, while also addressing new research questions related to the role of

socioeconomic class and perceived competitiveness.

Study 2

10
 Study 2 was designed to test the hypotheses of Study 1 in a confirmatory fashion. For this

reason, Study 2 was preregistered on the platform AsPredicted.com on 26 November 2020 (link:

https://aspredicted.org/blind.php?x=jp9uk9). Once again, we use the Bimboola paradigm (Jetten,

Mols & Postmes, 2015) to manipulate the perception of economic inequality. Moreover, we

randomly assigned a socioeconomic class (lower, middle, or upper) to each participant, in line with

literature that suggests class could be potentially relevant for people’s WLB (McGinnity & Calvert,

2009; Warren, 2005).

We preregistered 5 main hypotheses. As in Study 1, we predicted that participants assigned

to the high (vs. low) inequality condition perceive lower WLB (H1), and more status anxiety (H2).

Similarly, we predicted WLB to be negatively associated with status anxiety (H3). In addition, we

predicted that participants assigned to lower- and upper-class conditions perceive lower WLB (H4)

and higher status anxiety (H5), compared to participants assigned to the middle class. Furthermore,

we tested the mediating role of status anxiety and competitiveness on inferred WLB.

Method

Participants

Participants were collected using a snowball sampling procedure starting from the same

group of respondents of Study 1, which were asked not to complete the questionnaire themselves,

but rather to forward the Qualtrics link of the study to their acquaintances, which involved 541

respondents. The minimum sample size needed for our study was identified through data

simulation. We expected that our third hypothesis would require more participants than the other

hypotheses, in order to obtain a power of .80. In the previous study, we found a strong effect of the

condition on status anxiety levels (d = 1.7). However, due to important differences in study design,

namely the addition of a new manipulation, we ran an a-priori power analysis, with β = .80 and α

= .05, using the package paramtest (Hughes, 2017) simulating a multiple linear regression with two

main effects: inequality manipulation and socioeconomic class manipulation. We fixed the main

effect of the inequality manipulation at b1 = .5, the main effect of middle socioeconomic class
11
manipulation at b2 = -.3, and the main effect of low socioeconomic class manipulation at b3 = .3.

The results of a simulation with 5000 iterations showed that in order to achieve the desired power

for these effects, we needed n = 240, which was our sample size goal. Participants that failed the

manipulation check question in which we asked “Which income level were you assigned to?” were

excluded from the analyses. We also checked the completion time in order to exclude participants

that failed to complete the questionnaire within two hours. After data cleaning, we obtained a final

sample size of 338 (68,6% women; mean age = 31.8; SD = 14.2 age ranging from 18 to 79).

Concerning educational level, the majority of participants had a high school degree (49.4%); the

remainder had a Master’s degree (26.6%), Bachelor’s degree (15.1 %) and Master/PhD (5.6%). Just

a small part of our sample had a lower educational attainment, such as primary/middle school

diploma (3.3%). Our sample was slightly left-wing politically oriented: on a scale from

0=extremely left wing to 10=extremely right wing we obtained a mean of 4.8 (SD = 2.3). The

majority of our participants perceived themselves as belonging to the middle class (N = 187),

upper-middle class (N = 78) and lower-middle class (N = 67), with just a few identifying as lower

class (N = 5) and upper class (N = 1). As an objective measure of participants’ economic standing,

participants self-reported their annual net household income, measured through seven groups of

income from < 12,000 to > 60,000 Euros a year. Here, 23 people reported an annual income lower

than 12,000; 62 people from 12,000 to 20,000; 64 people from 20,000 to 30,000; 71 people from

30,000 to 40,000; 49 people from 40,000 to 50,000; 30 people from 50000 to 60000; 30 people

above 60,000.

Materials and procedure

The experiment was run online using the platform Qualtrics and the link was disseminated

with both an anonymous link and a QR code. After providing our participants with informed

consent, we manipulated perceived economic inequality (high vs. low) as in Study 1. We then

manipulated socioeconomic status, randomizing participants across 3 different groups: upper,

12
middle, and lower class. The experimental design was then a 2 (high economic inequality vs. low

economic inequality) x 3 (lower vs. middle vs. upper class) between participants. After completing

the task, participants answered some manipulation-check questions to test whether they understood

the condition to which they had been assigned. In order to enhance the self-identification with the

role being played, in contrast to Study 1 in which participants’ expectation about a general citizen

of Bimboola was assessed, in Study 2 they were asked to report their expectation as citizens of

Bimboola regarding 1. perceived status anxiety; 2. perceived competitiveness; 3. inferences of

WLB.

Status Anxiety

We used the same scale as in Study 1 (α = .70)

Competitiveness

We measured expected competitiveness, with a 5-item scale translated to Italian and adapted

from Murayama and Elliot (2012; e.g., “In Bimboola, it seems that people are competing with each

other”; “People seem to share the feeling that competing with each other is important”; α = .86).

Work-life balance

Expected WLB was determined using the scale by Fisher and Bulger (2009), as in the

previous study. In Study 1, many participants failed to complete the entire survey. To shorten the

questionnaire in an attempt to improve survey completion, we decided to reduce the WLB to 11 of

the 17 items, including only the subscales WIPL and PLIW (α = .90). These sub-scales were chosen

as they provided the most reliable measurement of perceived WLB in Study 1.

Finally, demographic data (such as gender, age, political affiliation, subjective

socioeconomic status and net income of the household) were collected.

For exploratory purposes, we also investigated other potential predictors of WLB.

Specifically, we tested the role of social support, and the need for achievement. However, analyses

concerning these variables are not reported in the present work, since they are part of a different line

of research.

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 Results

Effect of inequality and socioeconomic class on inferred WLB

To test hypotheses H1, H4 and H5, we ran an ANOVA in JASP (JASP Team, 2020)

including WLB as dependent variable and inequality and socioeconomic class as predictors.

As shown in Figure 2, WLB was affected both by inequality F (1, 332) = 20.581; p < .001, η2 = .05

and class, F(2, 332) =14.133; p < .001, η2 = .02. In line with H1, WLB was lower in the higher

inequality condition (M = 5.40; SD = 1.97) than in the lower (M = 6.35, SD = 1.68) inequality

condition (t = 4.54; d = .48; p < .001). H4 was partially supported as WLB was lower in the lower

class (M = 5.19, SD = 2.13) compared to the middle (M = 5.93, SD = 1.85), t = 3.46, d = .41, p

= .002, and the upper (M = 6.47, SD = 1.44) class, t = 5.25 , d = .70, p < .001. There were no

statistically significant differences on WLB scores between the middle and the upper class, t = 2.00,

d = .28, p = .11.

WLB was further characterized by the interaction between class and inequality, F (2, 332) =

6.812; p = 0.001, η2 = 04. Specifically, post-hoc tests with Tukey correction highlighted that

differences between inequality conditions were found for the middle (M high inequality = 5.51; SD high

inequality = 1.68; M low inequality = 6.52; SD low inequality = 1.93; t = 3.21; d = .57; p = .02) and the lower

classes (M high inequality = 4.37; SD high inequality = 2.12; M low inequality = 6.06; SD low inequality = 1.36; t = 4.94; d

= .86; p < .001), but not for the upper class (M high inequality = 6.52; SD high inequality = 1.58; M low inequality =

6.44; SD low inequality = 1.36; t = .24; d = .06; p = 1). Looking at the data from a different perspective,

we can also see that in the high inequality condition, participants assigned to the middle class

reported lower levels of inferred WLB compared to participants assigned to the upper class (t = -

3.00; d = -.62; p = .04), but higher levels compared to the poor class (t= 3.62; d = .61; p = .005). No

statistically significant differences between classes were found in the low inequality condition (all

ds < .25; all p > .05).

14
Figure 2. Effect of economic inequality and socioeconomic class conditions on inferred WLB.

Effect of inequality and socioeconomic class on perceived status anxiety

The same analytic strategy was used with status anxiety as a dependent variable. The results

showed that both economic inequality, F (1, 332) = 19.158; p < .001, η2 = .04, and class, F (2, 332)

= 34.506; p < .001, η2 = .16 significantly predicted status anxiety. In line with H2, status anxiety

was lower in the lower (M = 4.21, SD = 2.13) inequality condition compared to the higher (M =

5.34, SD = 2.61) inequality condition, t = 4.54, d = .48, p < .001. H5 was partially supported as

status anxiety was higher in the lower class (M = 6.16, SD = 2.49) than in the middle (M = 4.42, SD

= 2.06), t = 6.33, d = .80, p < .001, and in the upper (M = 3.84, SD = 2.23) class, t = 7.89, d = .99, p

< .001. There was no statistically significant difference on status anxiety scores between the middle

and the upper class, t = 1.88, d = .25, p = .15.

Moreover, a significant interaction between class and inequality, F (2,332) = 10.745; p

< .001, η2 = .05 also emerged. Differences between inequality conditions were found for the lower

class (t = 5.71; d = 1.09; p < .001), but not for the middle (t = 2.76; d = .53; p = .07), or the upper

classes (t = .85; d = .16; p = .96). However, no statistically significant differences between classes

were found in the low inequality condition (MLow = 4.94; SD = 1.84; MMiddle = 3.80; SD = 2.29;

15
MHigh = 3.98; SD = 2.11, all p > .05; all d < .55 see Figure 3). Furthermore, in the high inequality

condition, participants assigned to the middle class (M = 4.87; SD = 1.76) reported higher levels of

status anxiety compared to participants assigned to the upper class (M = 3.62; SD = 2.41; t = 3.02;

d = .62; p = .03), but lower levels of status anxiety compared to the poor class (M = 7.33; SD =

2.48; t = 6.38; d = -.64; p < .001). These findings suggested that the effect of economic inequality

on WLB and perceived status anxiety depends also on socioeconomic class, affecting mainly lower-

class individuals.

Figure 3. Effect of economic inequality and socioeconomic class conditions on perceived Status

Anxiety.

Effect of inequality and socioeconomic class on perceived competitiveness

Using the same analytic strategy, we tested the effect of experimental manipulations on

competitiveness. Economic inequality enhanced competitiveness (MHigh ineq = 6.14, SDHigh ineq = 1.82,

MLow ineq = 4.96, SDLow ineq = 2.28, d = .52; F (1, 330) = 25.130; p < .001, η2 = .07). However,

socioeconomic class, F (2, 330) = 0.350; p =.71, η2 = .002, and the interaction between economic

inequality and socioeconomic class, F (2,330) = 1.464; p = .23, η2 = .008, did not affect perceived

16
competitiveness.

scores.

Figure 4. Effect of economic inequality and socioeconomic class conditions on perceived

competitiveness.

Relationship between status anxiety and WLB

17
 A Pearson’s r correlation showed a negative association between perceived status anxiety

and inferred WLB (r = -.536; p = < .001), thus supporting H4.

Mediation analysis

We then examined whether status anxiety mediated the relationship between inequality and

WLB using the software JASP (JASP Team, 2020) with bootstrapping for 5,000 resamples and

95% confidence intervals (Preacher & Hayes, 2008). We found a significant indirect effect of

inequality manipulation via status anxiety on inferred WLB, b = -.23 (SE = .06), 95% CI = [-.37,

-.12]. The direct effect remained significant, b = .27 (SE = .09), 95% CI = [-.46, -.09] (see Fig. 4).

Figure 5. Mediation model examining indirect effects of economic inequality on WLB, through

status anxiety. Standardized coefficients are presented. Solid arrows and asterisks indicate

significant paths. Asterisks indicate p < .05.

We then decided to include perceived competitiveness in our mediation model (see Figure

6). Indeed, we ran a mediation analysis with the experimental condition (high vs. low inequality) as

predictor, perceived status anxiety and competitiveness as mediators, and inferred WLB as the

outcome. Again, we found two significant indirect effects of inequality manipulation on inferred

WLB via status anxiety, b = -.20 (SE = .05), 95% CI [-.31, -.11], and via competitiveness, b = -.11

(SE = .03), 95% CI [-.18, -.05]. The direct effect remained significant, b = -.20 (SE = .09), 95% CI

[-.41, -.03].

18
Figure 6. Mediation model examining indirect effects of economic inequality on WLB, through

status anxiety and competitiveness. Standardized coefficients are presented. Solid arrows and

asterisks indicate significant paths. Asterisks indicate p < .05.

Finally, we tested the role of status anxiety separately as a mediator for all socioeconomic

classes (see Figure 7). In this case, we did not take the role of perceived competitiveness into

account as we did not find an interaction effect between economic inequality and socioeconomic

class for this variable.

First, for participants assigned to the lower-class condition, we found a statistically

significant indirect effect of inequality manipulation via status anxiety on inferred WLB, b = -.58,

SE = .13, 95% CI [-.83, -.34]. The direct effect did not remain significant, b = -.22, SE = .17, 95%

CI [-.55, .12]. Moreover, the effect of status anxiety on WLB was b = -.60, 95% CI [-.74; -.47].

Second, for participants assigned to the middle class, we found a significant indirect effect

of the inequality manipulation via status anxiety on inferred WLB, b = -.20, SE = .09, 95% CI

[-.37, -.03]. The direct effect remained significant, b = -.35, SE = .17, 95% CI [-.68, -.02].

Moreover, the effect of status anxiety on WLB was b = -.38, 95% CI [-.55; -.21].

Third, for participants assigned to the upper class, the economic inequality condition did not have a

statistically significant effect on inferred WLB (b = .06, SE = .21, 95% CI [-.35, .46]. Moreover, the

effect of status anxiety on WLB was b = -.32, 95% CI [-.50; -.15].

19
Figure 7. Path models for the assigned socioeconomic classes. Standardized coefficients are

presented. Solid arrows and asterisks indicate significant paths. Asterisks indicate p < .05.

Discussion

As a replication and extension of Study 1, Study 2 produced important insights about the

role of both economic inequality and socioeconomic class on inferred WLB. First, the role of

economic inequality on inferred WLB was confirmed. Indeed, participants’ inferences of WLB

were lower in the high inequality condition. As an extension of Study 1, we also studied the role of

socioeconomic class on this relationship. Results showed that participants assigned to the lower-

class inferred greater imbalance between working and non-working activities when assigned to a

20
higher (vs. lower) unequal society. Consistent with Study 1, we found that status anxiety partially

explained the relationship between economic inequality and inferred WLB. Moreover,

competitiveness was a second key factor acting in the relationship linking economic inequality to

WLB.

Importantly, the interaction between economic inequality and socioeconomic class did not

affect perceived competitiveness scores, which provides important insights about the socio-

psychological processes at play. Indeed, perceived economic inequality enhanced the inference of

competitiveness for lower-, middle- and upper-class individuals, suggesting the perception of a

broader competitive climate in the high inequality condition (Sánchez‐Rodríguez et al., 2019).

However, this factor was not the key one in the relationship between the diverse effects of

inequality on the three socioeconomic groups.

General Discussion

Economic inequality represents a tenacious problem in contemporary society. Despite the

rich literature on the negative effects of economic inequality on well-being, to the best of our

knowledge, no previous research has investigated its effects on WLB. The results of our studies

suggest that economic inequality increases people's concerns about their place on the social ladder

and their competitiveness, both factors being associated with lower WLB. However, different

socioeconomic groups responded to inequality in different ways, providing evidence for specific

social processes triggered by inequality among people belonging to different economic standing.

Participants assigned to the lower and middle classes in the high inequality condition

perceived more status anxiety compared to their wealthier counterparts. Given their concerns,

people may try to achieve more prestigious positions by working longer hours and neglecting other

parts of life. Indeed, this interpretation is supported by previous literature (Bowles & Park, 2005)

and by the fact that status anxiety mediated the effect of the economic inequality manipulation.

These findings can be explained in light of the fact that members of the poorer class may face a

21
bigger threat when society is characterized by large wealth differences. Indeed, the pattern of results

is in line with Social Identity Theory (1979), according to which members of low-status groups feel

more status anxiety, as they struggle to reach a positive identity of themselves and their ingroup.

Focusing on the effects of inequality for the wealthiest, we saw that they were protected by

their social standing, as their work-life balance did not decline, even when assigned to a highly

unequal condition. Such protection was specifically explained by a social identity account, as the

group of participants assigned to the upper class (different from the low class) did not enhance the

status anxiety associated with their socioeconomic condition. Stated differently, the attribution of

competition was not moderated by socioeconomic class, as in all three classes, inequality increased

attribution of competitiveness. Potentially, the real threat of poverty, which was stronger in the

inequality condition, highlights resources-related problems (e.g., Esses et al., 2005; Sherif, 1961).

Notwithstanding, these results allow us to infer that the protection that comes from being wealthy is

not specifically related to the amount of wealth, but rather to the buffering effects of the perceived

social status associated with that particular class. In line with this interpretation, the economically

unequal condition was generally associated with high competitiveness across classes. Therefore,

even for upper class participants, an unequal society enhances the perception of a competition for

resources. Yet, being protected by their status, this did not lead to an erosion of WLB for wealthier

individuals facing the threat of inequality.

In sum, economic inequality had a negative impact on lower- and middle-class individuals

through status anxiety. Differently, perceived competitiveness appears to be a more general factor

influenced by the perception of a more unequal society for all the assigned socio-economic classes

(Sánchez‐Rodríguez et al., 2019).

Despite providing methodological control, the use of experimental conditions to portray

societal economic inequality may have yielded biased responses. In fact, it is difficult to empathize

with a situation that is not real, especially with regard to wealthier class groups (Study 2). It is

therefore possible that respondents gave their answers based on stereotypes and prejudices

22
regarding the socioeconomic class to which they were assigned to within the study. Indeed, future

studies may investigate the impact of economic inequality on WLB at the country or cultural level.

Consequently, the study requires cross-cultural validation, especially in countries with different

levels of economic inequality and perceived WLB. Further research should also explore the role of

some protective factors, such as individual characteristics, in shaping people’s WLB in unequal

contexts.

Conclusion

Our research shows that both economic inequality, socioeconomic class and their

interaction, have a negative impact on inferred WLB. Moreover, this effect is explained by

perceived competitiveness for all classes and status anxiety for the low and middle class. This

research provides useful insights about the role of structural factors such as economic inequality and

socioeconomic class on an important part of people’s wellbeing, namely the ability to balance the

private realm and work. Governments, associations, organizations and other stakeholders interested

in promoting people’s well-being may take advantage of this research in order to implement

specific policies, focused on the role of structural factors in shaping people’s WLB.

23
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