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RESEARCH REPORT

The Rich Get Richer and the Poor Get Poorer: Country- and State-Level Income Inequality Moderates the Job Insecurity-Burnout Relationship

Lixin Jiang University of Wisconsin Oshkosh

Tahira M. Probst Washington State University Vancouver

Despite the prevalence of income inequality in today’s society, research on the implications of income inequality for organizational research is scant. This study takes the first step to explore the contextual role of national- and state- level income inequality as a moderator in the relationship between individual-level job insecurity (JI) and burnout. Drawing from conservation of resource (COR) theory, we argue that income inequality at the country-level and state-level threatens one’s obtainment of object (i.e., material coping) and condition (i.e., nonmaterial coping) resources, thus serving as an environmental stressor exacerbating one’s burnout reactions to JI. The predicted cross-level interaction effect of income inequality was tested in 2 studies. Study 1 consisting of 23,778 individuals nested in 30 countries explored the moderating effect of country-level income inequality on the relationship between individual JI and exhaustion. Study 2 collected data from 402 employees residing in 48 states in the United States, and tested the moderating effect of state-level income inequality on the relationship between JI and burnout (i.e., emotional exhaustion and cynicism). Results of both studies converge to support the exacerbating role of higher-level income inequality on the JI -burnout relationship. Our findings contribute to the literature on psychological health disparities by exploring the contextual role of income inequality as a predictor of differential reactions to JI.

Keywords: job insecurity, burnout, income inequality

“Inequality, rather than want, is the cause of trouble.” —Confucius

Statistics indicate that the catchphrase “the rich get richer and the poor get poorer” is an unfortunately accurate depiction of today’s economy. Since 2009, the number of the world’s billion- aires, who jointly account for $6.4 trillion in wealth, has doubled (Brown, 2014). Among Organisation for Economic Co-operation and Development (OECD) countries, the average income of the richest 10% of the population is about nine times that of the poorest 10%, up from seven times 25 years ago (OECD, 2015). The United States is no exception. In the United States, income inequality, assessed by every major statistical measure, has been growing significantly for over the last 40 years (Hacker & Pierson, 2010). Indeed, the top 1% households accounted for 9% of all pretax income in 1976, whereas those households accounted for 22% in 2012. Between 1979 and 2012, the top 5% of families had a 75% increase in income, while the lowest income earners had a

12% decrease. Given this, the slogan “we are the 99%” referring to the wealth inequality in the United States where a concentration of wealth lies among the top earning 1% has been widely cited since the Occupy Wall Street protests in 2011 (Krugman, 2011). Re- cently, Bernie Sanders in his 2016 presidential campaign often asserted, “Now is the time to create a government which represents all Americans and not just the 1%.”

Although researchers within the fields of economics (Piketty & Saez, 2003), political science (Bartels, 2009), sociology (Blau & Blau, 1982), and social epidemiology (Kawachi, Kennedy, Loch- ner, & Prothrow-Stith, 1997) have investigated social conse- quences of this growing inequality, there has been relatively little empirical work on the contextual effects of income inequality within the domain of organizational psychology (see Muckenhu- ber, Burkert, Gro�schädl, & Freidl, 2014 for the sole exception). However, Bapuji (2015) argues that such research is pertinent for at least three reasons: (a) as the economic engines of society, organizations create and distribute wealth and, therefore, are at the core of economic inequality; (b) societal assumptions about the acceptability of inequality affect organizational strategic and man- agement decisions; and (c) given that organizations are embedded within societies, they (and their employees) can be positively or negatively affected by the inequality present in the society.

Researchers from a variety of disciplines have found negative impacts of income inequality. In summarizing previously published evidence, Wilkinson and Pickett (2007; Wilkinson & Pickett, 2009) highlighted the damaging effects of income inequality on societies,

This article was published Online First November 28, 2016. Lixin Jiang, Department of Psychology, University of Wisconsin Osh-

kosh; Tahira M. Probst, Department of Psychology, Washington State University Vancouver.

Correspondence concerning this article should be addressed to Lixin Jiang, Department of Psychology, University of Wisconsin Oshkosh, 800 Algoma Boulevard, Oshkosh, WI 54901-8670. E-mail: [email protected]

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Journal of Applied Psychology © 2016 American Psychological Association 2017, Vol. 102, No. 4, 672– 681 0021-9010/17/$12.00 http://dx.doi.org/10.1037/apl0000179

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including physical and mental health, drug abuse, education, impris- onment, obesity, social mobility, trust and community life, violence, teenage pregnancies, and child well-being. Using General Social Survey data from 1972 and 2008, Oishi, Kesebir, and Diener (2011) found that Americans were happier in years with less national income inequality than in years with greater inequality.

We argue that income inequality may serve as a contextual stressor (Wilkinson & Pickett, 2008) that can exacerbate the rela- tion between job insecurity (JI) and burnout. Because contextual stressors can operate at multiple levels (e.g., organizations, states, countries), we test our proposition by examining the predictive power of country-level and state-level income inequality in the JI-burnout relation in two heterogeneous samples across the globe (Study 1) and across the United States (Study 2). Specifically, Study 1 relied on data from 23,778 individuals nested in 30 countries to explore the cross-level interaction effect of country- level income inequality on the JI-burnout (i.e., exhaustion) rela- tionship. In an attempt to constructively replicate (Schmidt, 2009) the results from Study 1, Study 2 collected data from 402 employ- ees residing in 48 states in the United States, which provided converging evidence of the exacerbating effect of income inequal- ity operating at the state level on the JI-burnout (i.e., emotional exhaustion and cynicism) relationship.

Together, we make the following contributions to the literature. First, by explicitly conceptualizing income inequality at both the country and state levels, our study represents one of the first system- atic investigations into the potential cross-level impact of income inequality on the JI-burnout relation. We were only able to identify one study (Muntaner, Li, Ng, Benach, & Chung, 2011) examining the impact of contextual economic inequality on individual-level relation- ships between emotional strain and health outcomes. Thus, despite the well-documented negative, main effects of income inequality on wellbeing (e.g., Wilkinson & Pickett, 2007), the potential moderating role of income inequality has been largely overlooked. Using Con- servation of Resources (COR; Hobfoll, 1989) as a theoretical foun- dation, this study tests the exacerbating effect of higher-level income inequality on the individual-level JI-burnout relation.

Second, JI, a threat to the desired continuity of one’s job (Ashford, Lee, & Bobko, 1989), has been related to a host of negative outcomes (e.g., burnout; Dekker & Schaufeli, 1995). Most research exploring moderators that impact employee reactions to JI has focused on variables operating at the individual- or organizational-levels, which is insufficient because contextual factors can operate at other levels (Jiang, Probst, & Sinclair, 2013). Indeed, Gelfand, Erez, and Aycan (2007) encourage organizational researchers to examine contextual factors (e.g., economic factors), in addition to cultural characteristics (e.g., Debus, Probst, König, & Kleinmann, 2012). This study adds to that nascent literature by exploring the exacerbating effect of higher- level income inequality on employee burnout reactions to JI, thus contributing to the growing body of findings on the impact of societal contexts on individual reactions to JI.

Third, although COR theory has been widely applied in the stress and burnout literature, one of its less-studied tenets is the proposal that environmental factors, in conjunction with individual processes, in- fluence individual stress experiences (Hobfoll, 2001). Shared contex- tual circumstances, within which individual are nested, often make individuals who lack resources more vulnerable to resource loss (Hobfoll, 2001). Therefore, when examining individual outcomes, social contexts provide explanatory power above and beyond

individual-level variables. Given that individuals are nested in groups, organizations, states, and countries, the applications of COR theory are promising. Nevertheless, few studies have empirically examined the utility of COR theory at the individual level while simultaneously incorporating aspects of social contexts. This study, therefore, ex- pands the application of COR theory by empirically examining whether and how higher-level income inequality impacts employee reactions to JI. More importantly, because of the inherently nested structure proposed by COR theory, we utilized two multilevel data sets where individuals were nested in their country or state and multilevel modeling to achieve the congruence among the level of theory, the level of measurement, and the level of statistical analysis (Klein, Dansereau, & Hall, 1994).

Fourth, given the recent criticism of psychological research for a lack of reproducibility tests (Open Science Collaboration, 2015), two studies were conducted to provide a convergence of evidence. Our two studies build on each other in a number of important ways enabling us to achieve constructive replication by using different methodologies to test the underlying conceptual model (Lykken, 1968). Income inequality as a higher-level variable was operation- alized at the country level in Study 1 and at the state level in Study 2. JI was measured with a single item in Study 1 and with a well-validated scale in Study 2. Burnout was operationalized as exhaustion in Study 1 and emotional exhaustion and cynicism in Study 2. A heterogeneous sample with employees from various occupations across the globe was used in Study 1 and a heteroge- neous sample of employees across the U. S. was used in Study 2. Thus, the strength of our conclusions may be bolstered to the extent that there are consistent findings across the two studies. Moreover, the results of Study 1 can be freely replicated, since they are based upon publicly available data.

The Positive Relationship Between JI and Burnout

The basic tenant of COR theory is that people are driven to maintain, foster, and protect resources (i.e., objects, conditions, personal characteristics, energies). Psychological stress occurs when: (a) individuals are threatened with resource loss, (b) indi- viduals actually lose resources, or (c) individuals fail to gain resources after investing resources. Resources are valued and sought after by individuals in their own right, and serve as a means to obtaining other valued resources. Stable employment is valued in its own right (Warr, 1987) and is considered an instrument to gain other valued resources (e.g., incomes, housing, food, social status). JI, accompanied by the potential loss of manifest and latent benefits (Jahoda, 1981; Selenko & Batinic, 2013), has been shown to result in negative employee outcomes (Cheng & Chan, 2008; Sverke, Hellgren, & Naswall, 2002 for meta-analyses), including burnout, or emotional exhaustion and a callous or uncaring atti- tudes toward one’s job (Maslach, 1982). As such, we predicted that:

Hypothesis 1 (replication): JI is positively related to burnout (i.e., exhaustion in Study 1 and emotional exhaustion and cynicism in Study 2).

Income Inequality: A Contextual Stressor

Income inequality is the extent to which income is distributed unevenly among members of a group (most commonly conceptu-

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673JOB INSECURITY AND INCOME INEQUALITY

alized at the country or state level). In contexts of high income inequality, individuals perceive themselves to be deprived of de- sirable resources in relation to their counterparts in the wider society (Wilkinson & Pickett, 2008). Income inequality has been conceptualized as a contextual stressor (Wilkinson, 1999; Wilkin- son & Pickett, 2009) that promotes social and environmental degeneration harmful to health (Daly, Duncan, Kaplan, & Lynch, 1998). Zafirovski (2005) argues that high income inequality is a societal indicator of distributive injustice, a variable that has been proposed to exacerbate the relationship between JI and its various outcomes (Piccoli, De Witte, & Pasini, 2011).

In addition to supporting a positive relation between JI and burnout at the individual level, COR theory also predicts the influence of environmental factors (such as high income in- equality) on individual stress experiences (Hobfoll, 2001). As an extension of Hobfoll’s work, ten Brummelhuis and Bakker (2012) explicitly identify social equality as an example of macrolevel contextual resources (i.e., variables in the larger economic, social, and cultural system in which a person is nested) determining “the extent to which individuals need to call upon resources that are more directly in their reach and the extent to which other resources can be used effectively” (p. 548). Particularly, COR theory proposes that: individuals are embedded within their social contexts, these contexts can threaten people’s resources, and those who lack resources are more vulnerable to resource loss. We argue that income in- equality can threaten both object and condition resources (ten Brummelhuis & Bakker, 2012), which might serve as two explanatory mechanisms underlying the hypothesized exacer- bating effect of income disparity on the JI-burnout relation.

First, higher income inequality with greater disparity between the “haves” and the “have nots” within society is indicative of societal distributive injustice (Zafirovski, 2005). Societies with high income disparity tend to have fewer employment protections, an absence of labor standards, shorter duration of unemployment benefits, lower union density, and coverage (Zafirovski, 2005). As such, greater income inequality may inhibit the obtainment of object (i.e., material coping) resources for those who are faced with the possibility of job loss. Thus, within the context of high income inequality, individuals who perceive a high likelihood of job loss not only contend with the threat of losing the valuable latent and manifest benefits of employ- ment, but also may not expect to have equal opportunities to regain adequate employment and sustain themselves during any unexpected periods of unemployment.

Second, income inequality may divide community members (Putnam, 2000) and make people trust others less (Ichida et al., 2009). Under high income disparity, individuals are more inter- ested in “keeping up with the Joneses” at the expense of trust and social cohesion (Wilkinson & Pickett, 2009). Indeed, Oishi et al. (2011) found that the perceptions that other people were less fair and trustworthy explain the negative relationship between income disparity and happiness. Not surprisingly, having access to a supportive system has been found to buffer the negative impact of JI on life satisfaction (Lim, 1996). Thus, because income inequal- ity impedes the obtainment of condition (i.e., nonmaterial coping) resources (e.g., supportive relationships), it may aggravate the positive relationship between JI and burnout.

According to COR theory, broader social trends serving as a sociocultural backdrop can interact with variables on more meso-

and microsocial levels to pose a threat to or cause a depletion of individual resources. Because greater income inequality may ham- per the obtainment of object (i.e., material coping) and condition (i.e., nonmaterial coping) resources (ten Brummelhuis & Bakker, 2012), those who are highly uncertain about the future of one’s job may experience higher burnout. On the contrary, due to the avail- able object and condition resources in the context of low income inequality (ten Brummelhuis & Bakker, 2012), individuals who perceive the possibility of job loss may experience relatively low burnout. Thus, individuals exposed to the environmental stressor of greater income inequality posing a threat to one’s object and condition resources may be more susceptible to other threats of resource loss (e.g., JI). This would suggest that the experience of JI might be compounded when it occurs in a context of greater income inequality. Therefore, we expected to find a cross-level exacerbating effect of higher-level income inequality on the rela- tionship between individual-level JI and burnout. Specifically, we predicted that:

Hypothesis 2: Income inequality at the country level (Study 1) and at the state level (Study 2) moderates the positive relation between job insecurity and burnout such that this relationship is stronger within the context of greater income inequality.

Study 1: The Moderating Role of Country-Level Income Inequality

Method

Sample. Individual-level JI and burnout (i.e., exhaustion) came from the International Social Survey Program (ISSP), a continuing, annual of program of cross-national collaboration (43 nations) on surveys covering important social science topics. This study used the 2005 module on work orientations completed by 32 countries (ISSP Research Group, 2016). Country-level data on income inequality was based on the Gini index derived from the Standardized World Income Inequality Database (Solt, 2009). Combining these two data sets led to 23,778 individuals nested in 30 countries.1 A total of 52% of participants were male, and the majority of participants (61%) were married. The mean age was 41.24 (SD � 12.23) and the mean years of education was 15.41 (SD � 15.12).

Measures. Individual-level JI was assessed with a single item “My job is secure” on a 5-point Likert scale ranging from 1

1 These countries were Australia, Belgium, Bulgaria, Canada, Cy- prus, Czech Republic, Denmark, Dominican Republic, Finland, France, Germany, Hungary, Ireland, Israel, Latvia, Mexico, Netherlands, New Zealand, Norway, Portugal, Russia, Slovenia, South Africa, South Korea, Spain, Sweden, Switzerland, Taiwan, United Kingdom, and the United States. Due to missing data on the Gini index for Japan and Philippines, these two countries were excluded from analyses.

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674 JIANG AND PROBST

(strongly agree) to 5 (strongly disagree), which was previously examined and validated by Debus et al. (2012).2

Individual-level exhaustion was measured with an item “How often do you come home from work exhausted” on a 5-point Likert scale from 1 (always) to 5 (never).3

Country-level income inequality was measured by the Gini coefficient provided by the Standardized World Income Inequality Database (Solt, 2009). Based on the net income available for consumption, Gini coefficients, used in most cross-national studies of societal income inequality (Oishi et al., 2011), range from 0 (representing perfect equality) to 100 (representing perfect in- equality). In our study, country-level income inequality ranged from 22.80 to 71.36.

Results

Table 1 provides descriptive statistics and zero-order correla- tions at both individual and country levels. At the individual level, JI was positively related to exhaustion.

We tested our hypotheses using hierarchical linear modeling (HLM 6.0; Raudenbush & Bryk, 2002). Because we compared nested models, parameters were estimated using full maximum- likelihood estimation (Raudenbush & Bryk, 2002). The individual level predictor was group-mean centered and the country level predictor was grand-mean centered (Enders & Tofighi, 2007). Before proceeding with multilevel analyses, we examine whether there was a significant amount of variance in the outcome across countries (i.e., ICC1; Bliese, 2000). Between-country differences accounted for 2.95% of the total variance in exhaustion. Although the amount of between-country variance is not large, it is possible to find interactive effects even in the apparent absence of substan- tial between-groups variance (Snijders & Bosker, 1999).

Three nested models were compared to test hypotheses (Table 2). Model 1, where individual-level JI was entered as the predictor, found that JI was positively related to exhaustion, t � 6.16, p � .001, supporting H1. Model 2, where country-level income in- equality was entered as the predictor, revealed that country-level income inequality was also significantly related to exhaustion, t � 2.87, p � .01. Model 3, where the Individual-Level JI � Country- Level Income Inequality was entered as the cross-level interaction term, discovered a marginally significant cross-level interaction effect, t � 1.90, p � .068, explaining a 20% variance in the JI-exhaustion slope across countries. We plotted the relationship at �1 SD of income inequality (Figure 1) indicating that high

country-level income inequality marginally exacerbated the posi- tive relationship between JI and exhaustion whereby a steeper slope was observed under higher levels of country-level income inequality. The region of significance analysis (Preacher, Curran, & Bauer, 2006) revealed that the relationship between JI and exhaustion was significant in the full range of country-level in- come inequality. Thus, H2 was partially supported.

4

Study 2: The Moderating Role of State-Level Income Inequality

To constructively replicate the findings of Study 1, we made several changes in Study 2. First, whereas the operational defini- tion of burnout in Study 1 was limited to exhaustion due to ISSP dataset constraints, Study 2 included both emotional exhaustion and cynicism as indicators of burnout to be more consistent with the burnout literature. Second, JI and exhaustion were each mea- sured by a single item in Study 1. Thus, measurement error is expected to be far from trivial. Although previous research (e.g., Debus et al., 2012) using the ISSP dataset has relied on the same

2 Debus et al. (2012) also derived their individual-level data on JI, job satisfaction, and affective commitment from the International Social Sur- vey Program: Work Orientation module (2005). However, they used JI data from 15,200 individuals nested in 24 countries, whereas ours was from 23,778 individuals nested in 30 countries. Moreover, they examined the relationships of JI with job satisfaction and affective commitment, whereas we explored the relationship between JI and exhaustion. Finally, they explored the moderating roles of enacted uncertainty avoidance and the social safety net in the relationships of JI with job satisfaction and affective commitment, whereas we examined the moderating role of income inequal- ity in the relationship between JI and exhaustion. Given that both studies used the same dataset, we ran correlation analyses using the overlapping sample (N � 16,834 individuals nested in 22 countries; note: our sample is slightly higher, likely due to different treatment of missing data and inclusion of control variables). We found that the correlation between job satisfaction and exhaustion was �.18 while the correlation between affec- tive commitment and exhaustion was �.06. According to Cohen’s (1988) rule of thumb, these correlation coefficients represent a small strength of association.

3 In order to validate the use of the single item, we conducted a validation study among 332 employees recruited from MTurk in which we concurrently administered the original ISSP exhaustion item along with the previously validated emotional exhaustion subscale by Schaufeli, Salanova, González-Romá, and Bakker’s (2002) MBI-General Survey. The correlation between the two exhaustion measures was .77. Thus, it appears that the single item measure of exhaustion is an acceptable indicator of emotional exhaustion as conceptualized in the burnout literature.

4 Supplementary analyses: we conducted preliminary examinations of whether perceived object and condition resources might mediate the exac- erbating effect of country-level income inequality on the job insecurity- exhaustion relationship using the available ISSP data. As an example of perceived object resources, we used one item “How difficult or easy do you think it would be for you to find a job at least as good as your current one (1 � very easy; 5 � very difficult)” from the ISSP. As examples of perceived condition resources, we used two items “in general, how would you describe relations at your workplace between management and em- ployees (1 � very good; 5 � very bad)” and “in general, how would you describe relations at your workplace between workmates/colleagues (1 � very good; 5 � very bad)” from the ISSP. We conducted a series of two-level Type II mediated moderation structural equation modeling (Liu, Zhang, & Wang, 2012) where the perceived object and condition resources served as proxies for the country-level income inequality in altering the job insecurity-exhaustion relationship. However, our multilevel mediated mod- eration SEM revealed that none of these items were significant mediators when they were analyzed at the individual or country level.

Table 1 Means, Standard Deviations, and Zero-Order Correlations of Study 1

Variable Mean SD 1 2 3

1. Job insecurity 2.40 1.13 �.14 .05 2. Exhaustion 3.32 .96 .07��� .21 3. Country-level income inequality 32.69 9.51 �.01† .07���

Note. Correlations above the diagonal are at the country level (N � 30), whereas those below the diagonal are at the individual level (N � 23,778). Mean and SDs of job insecurity and exhaustion are reported at the indi- vidual level, whereas mean and SD of country-level income inequality are reported at the country level. † p � .10. ��� p � .001.

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675JOB INSECURITY AND INCOME INEQUALITY

single-item measure, it is important to replicate those findings with better-validated multi-item scales. Third, rather than using country-level income inequality, we conceptualized income in- equality at the state level in Study 2. Because country-level income inequality is more distal than state-level inequality, we expected that the magnitude of the cross-level interaction effect would be greater within the context of state-level inequality (Study 2) than the context of country-level inequality (Study 1).

Method

Sample and procedure. We collected individual-level JI and burnout data from employees in the United States using Mechan- ical Turk. Ten individuals who failed quality control attention checks were removed from subsequent analyses (Oppenheimer, Meyvis, & Davidenko, 2009). State-level data of income inequal-

ity came from the County Health Rankings and Roadmaps pro- gram (CHR). Combining these two data sets resulted in 402 individuals from 48 states. A total of 57% of participants were female. The mean age was 34.37 (SD � 10.14) and the mean organizational tenure was 5.51 years (SD � 5.10). The majority of participants (81%) were Anglo/White, worked full-time (91%), and held a permanent position (93%).

Measures. Individual-level JI was assessed by the nine-item Job Security Index (Probst, 2003). Participants responded to the prompt of “My future employment is . . .” using a series of adjectives or short phrases (e.g., “insecure”) on a 3-point response format (yes/no).

Individual-level burnout was measured by the 10-item Exhaus- tion (e.g., “I feel emotionally drained from my work”) and Cyni- cism (e.g., “I have become more cynical about whether my work contributes anything”) subscales of the Maslach Burnout Inventory (MBI)-General Survey (Schaufeli et al., 2002) using a response scale from 0 (never) to 6 (daily).

State-level income inequality was derived from the 2015 CHR dataset (County Health Rankings & Roadmaps, 2015). Income inequality is operationalized as the ratio of household income at the 80th percentile to that at the 20th percentile. A higher inequal- ity ratio indicates greater disparity between the top and bottom ends of the income spectrum. In our study, state-level income inequality ranged from 3.90 to 6.90.

Results

Table 3 provides descriptive statistics and zero-order correla- tions at both individual and country levels. At the individual level, JI was positively related to burnout.

The same analytic process as in Study 1 was used. Between- state differences accounted for 1.96% of the total variance in exhaustion. Three nested models were examined to test our hy- potheses (Table 4). Model 1, where individual-level JI was entered as the predictor, showed that JI was positively related to burnout, t � 5.94, p � .001, supporting H1. Model 2, where state-level income inequality was entered as the predictor, revealed that

Table 2 Multilevel Estimates for Models Predicting Exhaustion in Study 1

Predictors

Exhaustion

Model 1 Model 2 Model 3

B SE t B SE t B SE t

Intercept 3.32��� .03 108.33 3.32��� .03 115.73 3.32��� .03 115.75 Level 1

Job insecurity .05��� .01 6.16 .05��� .02 6.18 .05��� .01 6.54 Level 2

Country-level income inequality (II) .06�� .02 2.87 .06��� .01 2.71 Job Insecurity � Country-Level II .01† .01 1.90 �within

2 .88339 .88339 .88341 �u0

2 .02702 .02351 .02350 �u1

2 .00114 .00113 .00090 �2�log(lh) 64,649.99 64,646.29 64,643.42 Diff-2�log 3.71† 2.86†

df 6 7 8

Note. B � unstandardized coefficients; SE � standard error of parameter estimate. Diff-2�log of Model 2 refers to the comparisons with Model 1; Diff-2�log of Model 3 refers to the comparisons with Model 2. † p � .10. �� p � .01. ��� p � .001.

1

2

3

4

5

Low Job Insecurity High Job Insecurity

E xh au st io n

Low Country-level Income Inequality High Country-level Income Inequality

Figure 1. The moderating effect of country-level income inequality on the job insecurity-exhaustion relationship in Study 1. Simple slope analyses revealed that job insecurity was related to exhaustion under both high and low income inequality. However, the relationship between job insecurity and exhaustion was stronger under high income inequality (simple slope � .06, p � .001) compared with low income inequality (simple slope � .04, p � .001).

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state-level income inequality itself was not related to burnout. Model 3, where the Individual-Level JI � State-Level Income Inequality was entered, found a significant cross-level interaction effect, t � 2.62, p � .05, explaining 44% of variance in the JI-burnout slope across states. Figure 2 illustrates the form of the interaction by plotting the relationship at �1 SD of income in- equality and reveals that high state-level income inequality exac- erbated the positive relationship between JI and burnout where a steeper slope was observed under high state-level income inequal- ity. The region of significance analysis (Preacher et al., 2006) revealed that the relationship between JI and burnout was not significant when the observed value of state-level income inequal- ity was relatively low (i.e., below 4.14; Utah, Alaska, and Idaho). Thus, H2 was supported.

5

Discussion

Researchers (e.g., Sinclair, Sears, Probst, & Zajack, 2010) have repeatedly called for a better understanding of socioeconomic variables that may impact employee responses to economic stres- sors. Two studies conceptualizing income inequality at the country and state level provided converging evidence that the relationship between JI and burnout is intensified within the context of greater income inequality. Thus, while previous research has demon- strated that JI is related to greater burnout, these are the first studies to indicate that the strength of this relationship is, in part, due to societal differences in income inequality.

The threat of losing one’s job is one of the most significant organizational stressors experienced by employees (Ironson, 1992). Indeed, it is the chronic uncertain nature of the duration of the stressor that is argued to partially account for its effect on employee burnout (Westman & Etzion, 1995). Income inequality is an indicator of societal distributive injustice (Zafirovski, 2005). Those living in a context of greater income inequality may per- ceive that they have access to fewer object and condition resources (ten Brummelhuis & Bakker, 2012) in order to cope with that chronic stressor. COR theory posits that those facing greater stres- sors and with access to fewer resources will exhibit more mal- adaptive coping. Thus, faced with JI, those within high income inequality contexts not only contend with the threat of losing valuable latent and manifest benefits of employment, but also contend with fears of how they will sustain themselves during any unexpected periods of unemployment in the context of greater disparity between the haves and the have nots in society.

Theoretical and Empirical Contributions

This study contributes to our understanding of the nomological network of variables associated with JI. As early as Greenhalgh and Rosenblatt’s (1984) seminal article, researchers predicted that contextual variables such as economic insecurity might moderate employee reactions to JI. Despite this recognition, the vast major- ity of 30 years of subsequent research on the JI process has focused on individual-level variables. Building upon the nascent body of research investigating relevant contextual variables (e.g., Debus et al., 2012), our set of studies provides yet another piece of evidence that macroeconomic variables can shape individual re- sponses to workplace stressors. In finding that income inequality at the country and state level exacerbates burnout reactions to JI, this suggests that the experience of JI may be even more adverse when it occurs in the context of greater disparity between the rich and the poor.

These results also have implications for organizations, as Bapuji (2015) argues that economic inequality can directly and indirectly affect organizational performance via its impact on individuals, their interactions with each other, and the environment in which organizations are embedded. As initial empirical evidence of this, Desai, Brief, and George (2009) found that higher pay dispersion within an organization was related to increased aggression by managers. A more recent study (Desai, 2015) found greater pay disparity was predictive of more organizational policies that were detrimental to employees (e.g., maximizing production over safe- ty; use of layoffs to maintain financial performance). Finally, in a study of 1,400 firms, Wang, Zhao, and Thornhill (2015) found that greater pay dispersion predicted voluntary turnover, which, in turn, reduced organizational innovation. Notably, this effect was even stronger if the extent of pay dispersion within the organiza- tion was higher than its industrial average, suggesting that this broader context matters. Because these studies examined inequal- ity within the organizational and industry contexts, rather than broader societal-level inequality, our research further contributes to this literature by examining how the state- and country-level inequality context can also influence individual processes within organizations.

Our findings also have implications for the income inequality literature. Much of the extant research on outcomes of income inequality can be found in the economic and social epidemiology literatures; however, that research has overwhelmingly focused on the main effects of income inequality, largely ignoring potential interactions between income inequality and other well-being pre- dictors. Thus, this study contributes to the income inequality

5 Supplementary analyses: with limited available data, we preliminarily examined whether object resources might mediate the moderating effect of state-level income inequality in the job insecurity and burnout relationship. We used the ratio of state-level unemployment benefits and gross state product as an example of object resources. We conducted a two-level Type II mediated moderation structural equation modeling (SEM; Liu et al., 2012) where the object resource (i.e., the ratio of unemployment benefits and gross state product) served as a proxy for the state-level income inequality in altering the job insecurity-burnout relationship. Although the ratio was negatively related to income inequality, r � �.31, p � .025, the multilevel mediated moderation SEM revealed that the mediation role of the proposed object resource was not significant.

Table 3 Means, Standard Deviations, and Zero-Order Correlations of Study 2

Variable Mean SD 1 2 3

1. Job insecurity .71 .98 (.94) .60�� .15 2. Burnout 3.23 1.48 .36�� (.94) �.06 3. State-level income inequality 4.70 .51 .08 .01

Note. Correlations above the diagonal are at the state level (N � 48), whereas those below the diagonal are at the individual level (N � 402). Mean and SDs of job insecurity and burnout are reported at the individual level, whereas mean and SD of income inequality are reported at the state level. Cronbach’s alpha is reported along the diagonal. �� p � .01.

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literature by revealing the moderating effect of income inequality above and beyond its main effect.

Practical Implications, Limitations, and Future Directions

JI is an increasingly prevalent stressor within today’s workplace as 49% of United States respondents reported worrying about the future stability of their job (American Psychological Association, 2010); moreover, its effects are broad-ranging and overwhelm- ingly adverse. Unfortunately, income inequality may exacerbate the negative impact of JI on burnout. Thus, it adds another reason

for policymakers to address the growing phenomenon of income inequality.

Within the current study, the regions of significance analyses indicate that, from a practical perspective, the relation between JI and exhaustion was significant across all levels of the observed range of country-level inequality. This indicates that country-level policy initiatives aimed at reducing income inequality will not completely attenuate the negative relationship between JI and exhaustion. Thus, company-level initiatives (e.g., participatory decision making, Probst, 2005; organizational communication, Jiang & Probst, 2014) should still be viewed as vital complemen- tary efforts to reduce the impact of this prevalent stressor. Inter- estingly, the regions of significance analysis conducted at the state level indicated that the effect of JI on burnout was not significant for relatively low observed values of state-level income inequality. This suggests that more proximal-level (i.e., state level) policy initiatives to reduce income inequality may be more successful at reducing the adverse effect of JI on employee burnout.

Despite the converging evidence from two independent studies using multiple data sources, there are several limitations to the current studies. First, the cross-sectional design of both studies did not allow us to draw causal conclusions. Although past research has demonstrated that JI has a causal impact on burnout (Dekker & Schaufeli, 1995), it would be beneficial to utilize a multiwave survey design to investigate the longitudinal impact of JI, as well as the impact of changes in income inequality over time.

Although we detected a marginally significant effect of country- level income inequality explaining 20% of variance in the JI- exhaustion slope in Study 1 and a statistically significant effect of state-level income inequality explaining 44% of variance in the JI-burnout slope in Study 2, which are considered moderate effect sizes in the social sciences (Ferguson, 2009), these findings may have limited practical implications because of small between- groups variance in the outcome variable in both studies. Given this, future research may be focused on outcomes with relatively larger between-groups variance to detect cross-level interaction

Table 4 Multilevel Estimates for Models Predicting Burnout in Study 2

Burnout

Predictors

Model 1 Model 2 Model 3

B SE t B SE t B SE t

Intercept 3.23��� .07 45.57 3.23��� .08 40.19 3.23��� .08 40.30 Level 1

Job insecurity .50��� .08 5.94 .50��� .08 5.92 .44��� .08 5.28 Level 2

State-level income inequality (II) �.04 .22 �.16 �.00 .22 �.01 Job Insecurity � State-Level II .35� .13 2.62 �within

2 1.90875 1.90658 1.90621 �u0

2 .01592 .01839 .01299 �u1

2 .03392 .03403 .01909 �2�log(lh) 1,408.63 1,408.59 1,405.69 Diff-2�log .04 2.90†

df 6 7 8

Note. B � unstandardized coefficients; SE � standard error of parameter estimate. Diff-2�log of Model 2 refers to the comparisons with Model 1; Diff-2�log of Model 3 refers to the comparisons with Model 2. † p � .10. � p � .05. ��� p � .001.

1

2

3

4

5

6

7

Low Job Insecurity High Job Insecurity

B ur no ut

Low State-level Income Inequality High State-level Income Inequality

Figure 2. The moderating effect of state-level income inequality on the job insecurity-burnout relationship in Study 2. Simple slope analyses revealed that job insecurity was related to burnout under both high and low income inequal- ity. However, the relationship between job insecurity and burnout was stronger under high income inequality (simple slope � .62, p � .001) compared to low income inequality (simple slope � .27, p � .03).

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effects of income inequality that are of both statistical and practical significance.

It is also important from a practical and theoretical perspective to explore the mediating explanatory mechanisms for the observed relation, as this might inform potential interventions. As noted earlier, as an indicator of societal distributive injustice (Zafirovski, 2005), higher income inequality may threaten one’s object and condition resources (Hobfoll, 2001; ten Brummelhuis, & Bakker, 2012). Although our exploratory examinations of the mediation roles of potential proxy object and condition resources failed to reach significance in both studies, it may be premature to rule these mechanisms out. It would be beneficial to reexamine the cross- level mediated moderation model, whereby threatened object and condition resources mediate the moderating effect of higher-level income inequality on the relationship between JI and burnout, using more valid operationalizations of object and condition re- sources.

On the contrary, although we argue that the underlying psy- chological process of why individuals respond negatively to the potential resource loss implied by JI is the same in the country- and state-level income inequality contexts, state and country contexts may differentially constrain individuals’ options for “resource replacement” (Hobfoll, 2001), that is, gaining reem- ployment. According to COR theory, after actual resource loss (e.g., job loss), individuals invest available resources through the optimization strategy (Baltes, 1997) and position oneself through selection (Baltes, 1997) in circumstances that place one and one’s family at an advantage (Hobfoll, 2001) in an attempt to gain resources (e.g., reemployment). Because of the optimi- zation strategy, the vast majority of the unemployed choose to seek local reemployment. For those who choose to relocate in an attempt to gain reemployment, country and state contexts may constrain the available options they may have. For exam- ple, although it might be easier to relocate to a different state than to a different country, the societal circumstances may be more advantageous in another country than another state. How- ever, the question of how individuals develop strategies to determine the payoff they will receive for resource investment is beyond the scope of this paper. Nevertheless, future research may take a more nuanced approach to examining the resource replacement process after actual job loss.

Although we examined country- and state-level income inequal- ity, it would also be interesting to test whether our findings generalize to income inequality within an organization. Indeed, the average American CEO earns approximately 300 times as much as the lowest-paid employees (Gray, 2015). Given the limited resources within an organization and the importance of supportive relationships in the organizational setting, employees who perceive a larger pay inequality between the CEO and themselves may be more likely to experience negative consequences of JI. Our current results suggest that an exacerbating effect might be present and that it might be even stronger than our current results, given the more proximal nature of that context. As such, achieving greater pay equality within organizations, states, and/or countries may be more than an endeavor of social justice; it might also reap concrete organizational benefits in terms of increased employee health and well-being, particularly in times of JI.

Conclusion

Our research focused on the role of country- and state-level income inequality as an exacerbating factor in the JI-burnout relation. Our findings suggest that psychological demands placed on employees as a result of JI are compounded when they occur in a context of economic inequality. By taking a multilevel perspec- tive on the experience of JI as an economic stressor, we provide a more comprehensive picture of the complex interplay between socioeconomic and psychosocial variables in employee reactions to this ubiquitous stressor.

References

American Psychological Association. (2010). Stress in America findings. Washington, DC: Author.

Ashford, S. J., Lee, C., & Bobko, P. (1989). Content, cause, and conse- quences of job insecurity: A theory-based measure and substantive test. Academy of Management Journal, 32, 803– 829. http://dx.doi.org/10 .2307/256569

Baltes, P. B. (1997). On the incomplete architecture of human ontogeny: Selection, optimization, and compensation as foundation of develop- mental theory. American Psychologist, 52, 366 –380. http://dx.doi.org/ 10.1037/0003-066x.52.4.366

Bapuji, H. (2015). Individuals, interactions and institutions: How economic inequality affects organizations. Human Relations, 68, 1059 –1083. http://dx.doi.org/10.1177/0018726715584804

Bartels, L. M. (2009). Unequal democracy: The political economy of the new gilded age. Princeton, NJ: Princeton University Press.

Blau, J. R., & Blau, P. M. (1982). The cost of inequality: Metropolitan structure and violent crime. American Sociological Review, 47, 114 – 129. http://dx.doi.org/10.2307/2095046

Bliese, P. D. (2000). Within-group agreement, non-independence, and reliability: Implications for data aggregation and analysis. In K. Klein & S. W. J. Kozlowski (Eds.), Multilevel theory, research methods in organizations: Foundations, extensions, and new directions (pp. 349 – 381). San Francisco, CA: Jossey-Bass.

Brown, A. (2014, March 3). Forbes billionaires: Full list of the world’s 500 richest people. Forbes. Retrieved from http://www.forbes.com/sites/ abrambrown/2014/03/03/forbes-billionaires-full-list-of-the-worlds-500- richest-people/

Cheng, G. H. L., & Chan, D. K. S. (2008). Who suffers more from job insecurity? A meta-analytic review. Applied Psychology: An Interna- tional Review, 57, 272–303. http://dx.doi.org/10.1111/j.1464-0597.2007 .00312.x

Cohen, J. (1988). Statistical power analysis for the behavioral sciences (2nd ed.). Hillsdale, NJ: Erlbaum.

County Health Rankings and Roadmaps. (2015). 2015 County Health Rankings National Data. Retrieved from http://www.countyhealth rankings.org/rankings/data

Daly, M. C., Duncan, G. J., Kaplan, G. A., & Lynch, J. W. (1998). Macro-to-micro links in the relation between income inequality and mortality. The Milbank Quarterly, 76, 315–339, 303–304. http://dx.doi .org/10.1111/1468-0009.00094

Debus, M. E., Probst, T. M., König, C. J., & Kleinmann, M. (2012). Catch me if I fall! Enacted uncertainty avoidance and the social safety net as country-level moderators in the job insecurity-job attitudes link. Journal of Applied Psychology, 97, 690 – 698. http://dx.doi.org/10.1037/ a0027832

Dekker, S. W. A., & Schaufeli, W. B. (1995). The effects of job insecurity on psychological health and withdrawal: A longitudinal study. Austra- lian Psychologist, 30, 57– 63. http://dx.doi.org/10.1080/00050069 508259607

T hi

s do

cu m

en t

is co

py ri

gh te

d by

th e

A m

er ic

an P

sy ch

ol og

ic al

A ss

oc ia

ti on

or on

e of

it s

al li

ed pu

bl is

he rs

. T

hi s

ar ti

cl e

is in

te nd

ed so

le ly

fo r

th e

pe rs

on al

us e

of th

e in

di vi

du al

us er

an d

is no

t to

be di

ss em

in at

ed br

oa dl

y.

679JOB INSECURITY AND INCOME INEQUALITY

Desai, S. D. (2015). Organizational income inequality and precarious employee relations: The role of social distance. Paper presented at the Inequality, Trust and Ethics Conference, London, UK. Retrieved from the Social Science Research Network website: http://ssrn.com/ abstract�2607641

Desai, S. D., Brief, A. P., & George, J. (2009). Meaner managers: A consequence of income inequality. In: R. M. Kramer, A. E. Tenbrunsel and M. X. Bazerman (Eds), Social decision making: Social dilemmas, social values, and ethical judgments (pp. 315–334). New York, NY: Psychology Press.

Enders, C. K., & Tofighi, D. (2007). Centering predictor variables in cross-sectional multilevel models: A new look at an old issue. Psycho- logical Methods, 12, 121–138. http://dx.doi.org/10.1037/1082-989X.12 .2.121

Ferguson, C. J. (2009). An effect size primer: A guide for clinicians and researchers. Professional Psychology: Research and Practice, 40, 532– 538. http://dx.doi.org/10.1037/a0015808

Gelfand, M. J., Erez, M., & Aycan, Z. (2007). Cross-cultural organizational behavior. Annual Review of Psychology, 58, 479 –514. http://dx.doi.org/ 10.1146/annurev.psych.58.110405.085559

Gray, E. (2015, November 12). How publishing salaries could close the wage gap. Time. Retrieved from http://time.com/4109842/how- publishing-salaries-could-close-the-wage-gap/

Greenhalgh, L., & Rosenblatt, Z. (1984). Job insecurity: Toward concep- tual clarity. The Academy of Management Review, 9, 438 – 448.

Hacker, J. S., & Pierson, P. (2010). Winner-take-all politics: How Wash- ington made the rich richer-and turned its back on the middle class. New York, NY: Simon & Schuster.

Hobfoll, S. E. (1989). Conservation of resources. A new attempt at con- ceptualizing stress. American Psychologist, 44, 513–524. http://dx.doi .org/10.1037/0003-066X.44.3.513

Hobfoll, S. E. (2001). The influence of culture, community, and the nested-self in the stress process: Advancing conservation of resources theory. Applied Psychology: An International Review, 50, 337– 421. http://dx.doi.org/10.1111/1464-0597.00062

Ichida, Y., Kondo, K., Hirai, H., Hanibuchi, T., Yoshikawa, G., & Murata, C. (2009). Social capital, income inequality and self-rated health in Chita peninsula, Japan: A multilevel analysis of older people in 25 commu- nities. Social Science & Medicine, 69, 489 – 499. http://dx.doi.org/10 .1016/j.socscimed.2009.05.006

Ironson, G. H. (1992). Job stress and health. In L. Goldberger & S. Breznitz (Eds.), Handbook of stress: Theoretical and clinical aspects (pp. 419 – 444). New York, NY: Free Press.

ISSP Research Group. (2016). International Social Survey Programme: Work Orientation III - ISSP 2005. GESIS Data Archive, Cologne ZA4350 [Data file Version 2.0.0].

Jahoda, M. (1981). Work, employment, and unemployment: Values, the- ories, and approaches in social research. American Psychologist, 36, 184 –191. http://dx.doi.org/10.1037/0003-066X.36.2.184

Jiang, L., & Probst, T. M. (2014). Organizational communication: A buffer in times of job insecurity. Economic and Industrial Democracy, 35, 557–579. http://dx.doi.org/10.1177/0143831X13489356

Jiang, L., Probst, T. M., & Sinclair, R. R. (2013). Perceiving and respond- ing to job insecurity: The importance of multilevel contexts. In A. Antoniou & C. Cooper (Eds.), The psychology of the recession on the workplace (pp. 176 –195). Cheltenham, UK: Edward Elgar. http://dx.doi .org/10.4337/9780857933843.00020

Kawachi, I., Kennedy, B. P., Lochner, K., & Prothrow-Stith, D. (1997). Social capital, income inequality, and mortality. American Journal of Public Health, 87, 1491–1498. http://dx.doi.org/10.2105/AJPH.87.9 .1491

Klein, K. J., Dansereau, F., & Hall, R. J. (1994). Levels issues in theory development, data collection, and analysis. Academy of Management Review, 19, 195–229.

Krugman, P. (2011, November 25). We are the 99.9%. The New York Times. Retrieved from http://www.nytimes.com/2011/11/25/opinion/ we-are-the-99-9.html?_r�0

Lim, V. K. (1996). Job insecurity and its outcomes: Moderating effects of work-based and nonwork-based social support. Human Relations, 49, 171–194. http://dx.doi.org/10.1177/001872679604900203

Liu, D., Zhang, Z., & Wang, M. (2012). Mono-level and multilevel medi- ated moderation and moderated mediation: Theorization and test. Paper presented at the Southern Management Association Conference, Fort Lauderdale, FL.

Lykken, D. T. (1968). Statistical significance in psychological research. Psychological Bulletin, 70, 151–159. http://dx.doi.org/10.1037/ h0026141

Maslach, C. (1982). Burnout: The cost of caring. Englewood Cliffs, NJ: Prentice Hall.

Muckenhuber, J., Burkert, N., Gro�schädl, F., & Freidl, W. (2014). Income inequality as a moderator of the relationship between psychological job demands and sickness absence, in particular in men: An international comparison of 23 countries. PLoS ONE, 9, e86845. http://dx.doi.org/10 .1371/journal.pone.0086845

Muntaner, C., Li, Y., Ng, E., Benach, J., & Chung, H. (2011). Work or place? Assessing the concurrent effects of workplace exploitation and area-of-residence economic inequality on individual health. Interna- tional Journal of Health Services, 41, 27–50. http://dx.doi.org/10.2190/ HS.41.1.c

Oishi, S., Kesebir, S., & Diener, E. (2011). Income inequality and happi- ness. Psychological Science, 22, 1095–1100. http://dx.doi.org/10.1177/ 0956797611417262

Open Science Collaboration. (2015). Estimating the reproducibility of psychological science. Science, 349, aac4716. http://dx.doi.org/10.1126/ science.aac4716

Oppenheimer, D. M., Meyvis, T., & Davidenko, N. (2009). Instructional manipulation checks: Detecting satisficing to increase statistical power. Journal of Experimental Social Psychology, 45, 867– 872. http://dx.doi .org/10.1016/j.jesp.2009.03.009

Organisation for Economic Co-operation and Development. (2015). In- equality and income. Retrieved from http://www.oecd.org/social/ inequality.htm

Piccoli, B., De Witte, H., & Pasini, M. (2011). Job insecurity and organi- zational consequences: How justice moderates this relationship. Roma- nian Journal of Applied Psychology, 13, 37– 49.

Piketty, T., & Saez, E. (2003). Income inequality in the United States, 1913–1998. The Quarterly Journal of Economics, 118, 1– 41. http://dx .doi.org/10.1162/00335530360535135

Preacher, K. J., Curran, P. J., & Bauer, D. J. (2006). Computational tools for probing interaction effects in multiple linear regression, multilevel modeling, and latent curve analysis. Journal of Educational and Behav- ioral Statistics, 31, 437– 448.

Probst, T. M. (2003). Development and validation of the job security index and the Job Security Satisfaction Scale: A classical test theory and IRT approach. Journal of Occupational and Organizational Psychology, 76, 451– 467. http://dx.doi.org/10.1348/096317903322591587

Probst, T. M. (2005). Countering the negative effects of job insecurity through participative decision making: Lessons from the demand-control model. Journal of Occupational Health Psychology, 10, 320 –329. http:// dx.doi.org/10.1037/1076-8998.10.4.320

Putnam, R. D. (2000). Bowling alone: The collapse and renewal of Amer- ican community. New York, N Y: Simon & Schuster. http://dx.doi.org/ 10.1145/358916.361990

Raudenbush, S. W., & Bryk, A. S. (2002). Hierarchical linear models (2nd ed.). Thousand Oaks, CA.

Schaufeli, W. B., Salanova, M., González-Romá, V., & Bakker, A. B. (2002). The measurement of engagement and burnout: A two sample

T hi

s do

cu m

en t

is co

py ri

gh te

d by

th e

A m

er ic

an P

sy ch

ol og

ic al

A ss

oc ia

ti on

or on

e of

it s

al li

ed pu

bl is

he rs

. T

hi s

ar ti

cl e

is in

te nd

ed so

le ly

fo r

th e

pe rs

on al

us e

of th

e in

di vi

du al

us er

an d

is no

t to

be di

ss em

in at

ed br

oa dl

y.

680 JIANG AND PROBST

confirmatory factor analytic approach. Journal of Happiness Studies, 3, 71–92. http://dx.doi.org/10.1023/A:1015630930326

Schmidt, S. (2009). Shall we really do it again? The powerful concept of replication is neglected in the social sciences. Review of General Psy- chology, 13, 90 –100. http://dx.doi.org/10.1037/a0015108

Selenko, E., & Batinic, B. (2013). Job insecurity and the benefits of work. European Journal of Work and Organizational Psychology, 22, 725– 736. http://dx.doi.org/10.1080/1359432X.2012.703376

Sinclair, R., Sears, L. E., Probst, T. M., & Zajack, M. (2010). A multilevel model of economic stress and employee well-being. In J. Houdmont & S. Leka (Eds.), Contemporary Occupational Health Psychology: Global Perspectives on Research and Practice (Vol. 1, pp. 1–20). Hoboken, NJ: Wiley-Blackwell. http://dx.doi.org/10.1002/9780470661550.ch1

Snijders, T. A., & Bosker, R. (Eds.). (1999). Multilevel analysis: An introduction to basic and advanced multilevel modeling. Thousand Oaks, CA: Sage.

Solt, F. (2009). Standardizing the world income inequality database. Social Science Quarterly, 90, 231–242. http://dx.doi.org/10.1111/j.1540-6237 .2009.00614.x

Sverke, M., Hellgren, J., & Näswall, K. (2002). No security: A meta- analysis and review of job insecurity and its consequences. Journal of Occupational Health Psychology, 7, 242–264. http://dx.doi.org/10.1037/ 1076-8998.7.3.242

ten Brummelhuis, L. L., & Bakker, A. B. (2012). A resource perspective on the work-home interface: The work-home resources model. American Psychologist, 67, 545–556. http://dx.doi.org/10.1037/a0027974

Wang, T., Zhao, B., & Thornhill, S. (2015). Pay dispersion and organiza- tional innovation: The mediation effects of employee participation and

voluntary turnover. Human Relations, 68, 1155–1181. http://dx.doi.org/ 10.1177/0018726715575359

Warr, P. (1987). Work, unemployment, and mental health. New York, NY: Oxford University Press.

Westman, M., & Etzion, D. (1995). Crossover of stress, strain and re- sources from one spouse to another. Journal of Organizational Behav- ior, 16, 169 –181. http://dx.doi.org/10.1002/job.4030160207

Wilkinson, R. G. (1999). Income inequality, social cohesion, and health: Clarifying the theory—A reply to Muntaner and Lynch. International Journal of Health Services, 29, 525–543. http://dx.doi.org/10.2190/ 3QXP-4N6T-N0QG-ECXP

Wilkinson, R. G., & Pickett, K. E. (2007). The problems of relative deprivation: Why some societies do better than others. Social Science & Medicine, 65, 1965–1978. http://dx.doi.org/10.1016/j.socscimed.2007 .05.041

Wilkinson, R. G., & Pickett, K. E. (2008). Income inequality and socio- economic gradients in mortality. American Journal of Public Health, 98, 699 –704. http://dx.doi.org/10.2105/AJPH.2007.109637

Wilkinson, R. G., & Pickett, K. E. (2009). The spirit level: Why more equal societies almost alwasy do better. London, UK: Allen Lane.

Zafirovski, M. (2005). Labor markets’ institutional properties and distrib- utive justice in modern society: A comparative empirical analysis. Social Indicators Research, 72, 51–97. http://dx.doi.org/10.1007/s11205-004- 1544-9

Received November 27, 2015 Revision received September 26, 2016

Accepted October 8, 2016 �

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