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INCOME, INEQUALITY, AND PROSOCIALITY 1

Higher Income Individuals Feel More Entitled and Report Giving

Proportionally Less to Charity Where Economic Inequality is High

Authors: Stéphane Côté1*, Robb Willer2, Julian House1, Chloe Kovacheff1

Affiliations:

1 Joseph L. Rotman School of Management, University of Toronto, Toronto, Ontario, M5S 3E6, Canada.

2 Department of Sociology, Stanford University, Stanford, CA 94305, USA.

*Corresponding author: [email protected] (S.C.)

Manuscript in preparation


ABSTRACT

Studies disagree on how income relates to prosociality, variously finding that higher

income individuals are more prosocial, equally prosocial, or less prosocial than lower

income individuals. Recent research suggests that economic inequality may explain these

disparate results, with higher income individuals being less prosocial where inequality is

high. However, it is not yet known why inequality would condition the relationship in

this way. We examine whether inequality leads higher income individuals to a) feel

uniquely entitled to resources, or b) endorse economic meritocracy. Results of a survey

(n=978) show that higher income residents of relatively unequal areas reported donating

proportionally less of their income to charity than their lower income counterparts. This

relationship was mediated by entitlement, but not meritocratic beliefs. Inequality did not

predict raffle ticket donations to a pre-specified charity. These results suggest that higher

income residents of unequal areas may be less prosocial because they feel entitled.

Keywords: Economic Inequality, Income, Prosociality, Entitlement


Higher Income Individuals Feel More Entitled and Report Giving

Proportionally Less to Charity Where Economic Inequality is High

In recent years the relationship between income and prosociality has received

considerable attention from researchers. While a growing body of work finds that higher

income individuals donate less resources to others (cf. Chen, Zhu, & Chen, 2013; Miller,

Kahle, & Hastings, 2015; Piff, Kraus, Côté, Cheng, & Keltner, 2010), other studies show

no association or even a positive link between income and prosociality (cf. Korndörfer,

Egloff, & Schmukle, 2015; Yamagishi, Li, Takagishi, Matsumoto, & Kiyonari, 2014).

One promising route to reconcile these mixed findings involves considering features of

the macrosocial structure. In particular, research in both field and laboratory contexts

finds that higher income individuals are less prosocial than lower income individuals

under unequal economic conditions, but equally or more prosocial where inequality is

lower (Côté, House, & Willer, 2015; Hargreaves Heap, Ramalingam, & Stoddard, 2016;

Nishi, Shirado, Rand, & Christakis, 2015).

While this past research suggests an overarching framework for understanding

when and where a negative relationship between income and prosociality will obtain, it is

not yet clear why economic inequality—the extent to which income is concentrated in the

hands of a small proportion of the population (Wilkinson & Pickett, 2009)—conditions

the relationship in this way. Here, we examine two candidate explanations—one based on

feelings of psychological entitlement, the other based on beliefs that society is

meritocratic—for why higher income individuals might be less prosocial under unequal

economic conditions. In doing so, we test the possibility that income relates to important


beliefs about the self and the society, and further whether these beliefs vary depending on

levels of inequality.

Income, Inequality, and Psychological Entitlement

Psychological entitlement is the belief that one is more important and deserving of

resources and privileges than others (Campbell, Bonacci, Shelton, Exline, & Bushman,

2004). High levels of inequality might increase feelings of entitlement among individuals

at the top of the economic distribution because it facilitates favorable downward social

comparisons among these individuals. In settings with greater inequality, distinctions

between different economic positions are sharp (Stiglitz, 2012; Wilkinson & Pickett,

2009), and these distinctions might serve as a salient basis of self-perception. For

instance, higher income residents of highly unequal areas are more likely to self-identify

as a “have” or as “upper class” than higher income residents of less unequal areas

(Andersen & Curtis, 2012; Newman, Johnston, & Lown, 2015). Thus, inequality might

lead higher income individuals to find that they compare particularly favorably to others

because it highlights their superior economic standing. Further, when inequality is high,

economic positions are separated by a greater absolute distance, and higher income

individuals’ economic advantage over others is especially pronounced. Where the gap

between their economic standing and that of most others is especially large, inequality

might lead higher income individuals to make particularly favorable downward social

comparisons.

In turn, downward social comparisons may increase feelings of entitlement

among higher income residents of highly unequal areas. When successful individuals

explain their social standing, they often prioritize self-serving explanations that


emphasize unique personal characteristics (Major, 1994). By emphasizing unique

characteristics that they possess and others do not, successful individuals engage in

favorable downward social comparisons that may lead to feelings of entitlement

(Campbell et al., 2004). We therefore predicted a positive relationship between income

and entitlement that is especially pronounced where inequality is relatively high and

attenuated where inequality is relatively low (Hypothesis 1).

Moreover, entitlement facilitates self-serving behaviors. People with a high sense

of entitlement believe that resources rightfully belong to them, and these beliefs lead

them to share fewer resources with others. Past research finds that more entitled

individuals make more selfish, competitive, and greedy decisions, are less

accommodating, empathic, and respectful in romantic relationships, and respond more

aggressively to negative feedback (Campbell et al., 2004; Zitek, Jordan, Monin, & Leach,

2010). Thus, we proposed that high feelings of entitlement among higher income

residents of highly unequal economic areas would lead them to exhibit lower levels of

prosociality (Hypothesis 2).

Income, Inequality, and Meritocratic Beliefs

Meritocratic beliefs refer to views that resources within a social system are

distributed appropriately based on worth (Pratto, Sidanius, Stallworth, & Malle, 1994).

High levels of inequality could increase meritocratic beliefs among individuals at the top

of the economic distribution, because higher income individuals are motivated to justify

their privileged position in a society where resources are unevenly distributed. Higher

income residents of unequal areas might feel insecurities that their resources are not truly

deserved, and also they may fear that those at the bottom of the economic distribution


will challenge the concentration of resources at the top of the distribution (Newman et al.,

2015; Zimmerman & Reyna, 2013). To address these concerns, higher income

individuals may adopt meritocratic beliefs as a means for justifying their privileged

position within the existing distribution of resources. An important aspect of meritocratic

beliefs is the notion that success is the outcome of hard work (rather than luck or

privilege), a sentiment that supports the fairness of the current distribution of resources.

As such, meritocratic beliefs might equip higher income individuals against concerns

about the legitimacy of their privileged social standing. We thus hypothesized a positive

relationship between income and meritocratic beliefs that is especially pronounced where

inequality is high and attenuated where inequality is low (Hypothesis 3).

Meritocratic beliefs may, in turn, reduce the prosociality of higher income

residents of unequal areas. Central to meritocratic beliefs is the notion that people have

the resources that they deserve: those at the top of the economic hierarchy deserve a

disproportionate share of resources, while those at the bottom deserve less (Pratto et al.,

1994). Thus, meritocratic beliefs might reduce prosociality, because people who hold

these beliefs think they deserve the resources they possess (Wakslak, Jost, Tyler, & Chen,

2007). Where strongly held, these beliefs may also reduce the motivation to rectify

disparities by implying that others already possess the resources that they have earned.

Therefore, we expected that meritocratic beliefs endorsed by higher income individuals

where inequality is high would explain their lower levels of prosociality under these

conditions (Hypothesis 4).

Method

Participants and Procedure


One thousand and three United States residents were recruited from a panel

maintained by Clearvoice, a research and marketing firm that holds a large database of

potential participants. This sample size provided over .95 power to detect a small effect

for the increase in variance explained by the interaction (Cohen, 1988; Hunsley & Meyer,

2003). To obtain a representative sample with respect to income—the focal individual-

level predictor—we set quotas for 15 income categories (separately for men and women)

using data from the Current Population Survey (U.S. Census Bureau, 2015b). Of the

1,003 individuals recruited to the study, 24 (or 2%) could not be included in the analyses

because they did not give responses to one or more questions used in analysis. One other

participant could not be included because this participant resided in a territory (the U.S.

Virgin Islands) for which no inequality estimate was available. The sample used for

analysis included 978 respondents (492 women and 486 men) between the ages of 17 and

89 (M = 50, SD = 15). Of these, 805 participants (82%) were European-American, 86

(9%) were African-American, 57 (6%) were Hispanic, 28 (3%) were Asian-American,

and 39 (4%) selected another category (some participants selected more than one

category). Residents of 47 of 50 U.S. states plus the District of Columbia (DC)

responded.

The survey included measures of state of residence, income, prosociality,

characteristics used as controls in the analyses (described below), and other constructs

that we did not analyze in this study. The survey, data, and R code to conduct the

analyses can be accessed at

https://www.dropbox.com/sh/qvgao7qunnh0qkp/AADSyBKDRkWfPMJH4Idf-

Ghsa?dl=0


Measures

Economic inequality. We gathered Gini coefficients for each state (plus DC)

from the American Community Survey, a yearly representative survey of U.S. citizens

(U.S. Census Bureau, 2015a). The Gini is a widely used measure of inequality that

theoretically ranges from 0, indicating that all have the exact same income, to 1,

indicating that a single person holds all of the income (Wilkinson & Pickett, 2009). Ginis

ranged from .427 (Wyoming) to .522 (District of Columbia; M = .466, SD = .020).

Income. Participants reported their yearly income by choosing one category

ranging from 1 (0-$9,999) to 15 ($250,000 or more). We assigned midpoint income

amounts corresponding to the chosen category (Hout, 2004). We assigned $250,000 (the

lower bound) to participants who chose the highest category. The results were the same

when we adopted a strategy often used in sociology research using frequencies for the

second-highest and highest brackets to assign a value (in this sample, $560,742) for the

highest category (Hout, 2004; Parker & Fenwick, 1983). Mean income was $36,521 (SD

= $41,337). To aid interpretation of the results, we divided income values by 10,000.

Psychological entitlement. We administered the 9-item Psychological

Entitlement Scale (Campbell et al., 2004). Respondents indicated their agreement with

items including “I honestly feel I’m just more deserving than others” and “I do not

necessarily deserve special treatment” (reverse-scored) on a 1 (strongly disagree) to 7

(strongly agree) scale (M = 3.46, SD = 1.26; α = .90; 1 unreported).

Meritocratic beliefs. We administered an 8-item measure previously used by

Major, Kaiser, O’Brien, and McCoy (2007). Respondents indicated how much they

agreed with items such as “If people work hard they almost always get what they want”


and “Advancement in American society is possible for all individuals” using a 1 (strongly

disagree) to 7 (strongly agree) scale (M = 3.84, SD = 1.12; α = .84).

Prosociality. We administered two measures of prosociality. The first measure is

the self-reported proportion of annual income donated to charity. Participants reported

whether they donated any money to a charitable organization in the year prior to the

survey (2014). Those who donated indicated how much. To facilitate accurate recall, we

listed some common types of charity (e.g., charity for animals, the environment, health,

or specific religions) and participants indicated how much they donated to each type. We

divided reported donation totals by income, and then multiplied these values by 100.

Reported charitable donation values were positively skewed, and thus, we logged these

values (Tabachnick & Fidell, 2007). The results were virtually the same when we

repeated the analyses with values that were not log-transformed. Reported charitable

donations data often include outliers that unduly influence results (Pedhazur &

Schmelkin, 1991). Therefore, following procedures described by Tabachnick and Fidell

(2007), we removed from the analyses participants with values for the reported

proportion of income donated to charity more than 3.29 standard deviations higher than

the mean (in this sample, participants who donated 26.3% or more of their annual

income). This procedure was conservative, affecting only 14 observations, or 1% of the

sample. On average, participants donated 1.12% of their income (SD = 2.92; range = 0 to

24.70). The mean logged value was .41 (SD = .65).

Second, we administered a modified “dictator game” (Bekkers, 2007) in which

participants decided how many of a set number of raffle tickets they wished to either

keep or donate to a well-known charitable organization. Respondents were offered a


chance to win a raffle for $100, over and above their regular payment for completing the

study. Participants were told they had been assigned the role of “sender,” and that a

charitable organization, the United Way, would be in the role of the “receiver.” The

United Way was presented as one of the largest charitable organizations aimed at

reducing poverty. As “senders,” participants allocated 10 raffle tickets, each offering an

equal chance to win the cash prize, between themselves and the United Way. Participants

were told that, if the United Way won the raffle, the organization would receive the

winnings as an anonymous donation (a participant actually won the raffle). To increase

the believability of the raffle, we provided an email address to ask questions about the

raffle. On average, participants donated 4.14 tickets (SD = 3.44).

Controls (state level). We controlled for state characteristics that might correlate

with inequality and, thus, potentially confound analysis of the effects of inequality: mean

household income, population, proportion of the population living in urbanized areas and

urban clusters, and diversity in age, ethnicity, and gender. We retrieved state mean

household incomes (M = $73,129, SD = $12,415) and populations (M = 6.59 million, SD

= 7.21 million) in year 2014 from the American Community Survey (U.S. Census

Bureau, 2015a). To aid interpretation, we divided income values by 10,000 and

population values by 1,000,000. We obtained values for the proportion of the population

living in urbanized areas and urban clusters from the 2010 Decennial Census (U.S.

Census Bureau, 2015c; M = 75.3, SD = 14.23). We calculated diversity in age, ethnicity,

and gender using Blau’s index (Harrison & Klein, 2007). The formula for Blau’s index is

1 − Σpk2, where k denotes the category and p denotes the proportion of individuals in the

kth category. To calculate these indices, we obtained values for age (tracked in 18


categories), ethnicity (tracked in 7 categories), and gender in each state from the

American Community Survey (U.S. Census Bureau, 2015a). We applied the formula for

Blau’s index to these values to obtain diversity scores for age, ethnicity, and gender. For

ease of interpretation, we then multiplied the values by 100 (age: M = 93.85, SD = .19;

ethnicity: M = 36.91, SD = 14.09; gender: M = 49.98, SD = .02).

Controls (individual level). We controlled for individual characteristics that

might correlate with income and, thus, potentially confound analysis of the effects of

income: age, gender (coded 1 = female or 0 = male), ethnicity (coded 1 = Caucasian or 0

= non-Caucasian), education, employment status, marital status, subjective social class,

religiosity, and political ideology. Education was coded 1 = less than high school, 2 =

high school diploma or GED, 3 = Associate or vocational degree, 4 = Bachelor's degree,

5 = Master's degree, or 6 = PhD or Professional degree (M = 3.18, SD =1.16; 1

unreported). Employment status was coded 1 = working as a paid employee or self-

employed (N = 479) or 0 = unemployed (n = 499). Marital status was coded 1 = married

(N = 477) or 0 = not married (N = 499; 2 unreported). Subjective social class was coded 1

= lower class, 2 = lower middle class, 3 = middle class, 4 = upper middle class, or 5 =

upper class (M = 2.5, SD = .87). Religiosity was rated on a scale of 1 (not at all religious)

to 7 (very religious; M = 3.98, SD = 2.09). Political ideology was rated on a scale of 1

(very liberal) to 7 (very conservative; M = 4.16, SD = 1.69).

Analysis

We ran hierarchical linear models (using the nlme package for R; Pinheiro, Bates,

DebRoy, Sarkar, & R Core Team, 2016) because respondents were nested within states,

and observations were thus non-independent (Aguinis, Gottfredson, & Culpepper, 2013;


Preacher, Curran, & Bauer, 2006). We first conducted analyses without controls, and then

verified that any results were not spurious by repeating all analyses with controls. Income

was centered at its group mean (i.e., within states) and inequality was centered at its

grand mean (i.e., across states) to appropriately test cross-level interactions (Enders &

Tofighi, 2007; Hofmann & Gavin, 1998). We probed interactions by examining regions

of significance, which reveal the levels of inequality at which income was significantly

related to prosociality (Preacher et al., 2006). To generate regions of significance, we

used the web utility developed by Preacher, Curran, and Bauer (2006). Further, we

conducted mediated moderation analyses as outlined by Muller, Judd, and Yzerbyt

(2005), and supplemented these analyses with a bootstrap test (MacKinnon, 2008).

Results

Income, Inequality, and Psychological Entitlement

There was a significant interaction between income and inequality predicting

entitlement (Table 1, Model 1) that resisted individual- and state-level controls (Table 1,

Model 2). The interaction is displayed in Figure 1. Supporting Hypothesis 1, in the most

unequal states, having a higher income was associated with feeling more entitled.

According to the analysis of regions of significance, this relationship was positive in

areas with Ginis exceeding .470, a set that included 18 states plus DC in 2014. By

contrast, in the least unequal states (with Ginis lower than .470), there was no

relationship between income and entitlement. According to the analysis of regions of

significance, this relationship became significantly negative at Ginis lower than .163. No

state or country features such a low level of inequality (e.g., Sweden’s Gini is 27.3;

“GINI index (World Bank estimate),” 2016), suggesting that there is no realistic level of


inequality where having a higher income is associated with feeling less entitled. Thus,

inequality moderated the relationship between income and entitlement in a way that could

explain why higher income individuals are less generous under unequal economic

conditions.


Table 1 Hierarchical Linear Model Results Predicting Entitlement Model 1 Model 2 ⎯⎯⎯⎯⎯⎯ ⎯⎯⎯⎯⎯⎯ Variable γ SE t γ SE t ⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯ Intercept 3.41 .04 79.67*** 3.87 .12 32.37*** Income .02 .01 1.45 .02 .01 1.57 Inequality 6.16 2.18 2.82** 4.08 3.74 1.09 Income x Inequality 1.03 .48 2.14* .99 .47 2.12* Age -.01 .00 -2.24* Gender .11 .08 1.34 Subjective social class .05 .05 .91 Ethnicity -.59 .11 -5.48*** Education -.03 .04 -.84 Employment status .17 .09 1.97* Marital status -.22 .08 -2.64** Religiosity .02 .02 .77 Conservative ideology -.03 .03 -1.25 State mean income .00 .05 .03 State population .00 .01 .57 State urban population .00 .01 .55 State gender diversity -3.13 3.73 -.84 State ethnic diversity -.00 .01 -.85 State age diversity -.05 .34 -.15 ⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯ Note. For Model 1, n = 977. For Model 2, n = 974. Gender was coded 1 = female or 0 = male. Ethnicity was coded 1 = Caucasian or 0 = other. Employment status was coded 1 = working as a paid employee or self-employed or 0 = unemployed. Marital status was coded 1 = married or 0 = not married. *p < .05. ** p < .01. *** p < .001.


Entitlement

Figure 1. Entitlement as a function of income (±1 SD) and inequality in respondents’ home states. Lines are projections based on regression estimate from the regression model. The solid line depicts the projected association between income and entitlement in the area with the lowest level of inequality (the state of Wyoming). The dotted line depicts this projected association in an area with an average level of inequality. The dashed line depicts this projected association in the area with the highest level of inequality (the District of Columbia).

1

2

3

4

5

Lowerincomeindividuals Higherincomeindividuals

Highestinequality

Averageinequality

Lowestinequality


Income, Inequality, and Meritocratic Beliefs

There was a significant interaction between income and inequality predicting

meritocratic beliefs (Table 2, Model 1), which became marginally significant with

controls (Table 2, Model 2). The interaction, displayed in Figure 2, shows that having a

higher income was consistently associated with endorsing meritocratic beliefs more

strongly. Further, this positive association was more pronounced when inequality was

lower, not higher. The analysis of regions of significance revealed that income was

significantly positively associated with meritocratic beliefs in the majority of states (i.e.,

states with Ginis below .492, a set that included 48 states). By contrast, there was no

relationship between income and meritocratic in the most unequal states (i.e., states with

Ginis above .492, a set that included 2 states plus DC), because under such highly

unequal conditions, both higher and lower income residents endorsed meritocracy. These

findings suggest that meritocratic beliefs do not explain why higher income individuals

are less prosocial when inequality is especially high. Hypothesis 3 was not supported.

Further, Hypothesis 4 that meritocratic beliefs would explain how inequality combines

with income to predict prosociality was also not supported.


Table 2 Hierarchical Linear Model Results Predicting Meritocratic Beliefs Model 1 Model 2 ⎯⎯⎯⎯⎯⎯ ⎯⎯⎯⎯⎯⎯ Variable γ SE t γ SE t ⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯ Intercept 3.83 .04 100.96*** 3.80 .10 38.74*** Income .05 .01 5.13*** .03 .01 2.62** Inequality 2.48 1.93 1.28 5.88 3.08 1.91 Income x Inequality -1.05 .42 -2.48* -.70 .38 -1.81 Age .01 .00 2.74** Gender .02 .07 .33 Subjective social class .25 .04 5.68*** Ethnicity -.06 .09 -.62 Education -.12 .03 -3.92*** Employment status .07 .07 .96 Marital status .12 .07 1.77 Religiosity .02 .02 1.13 Conservative ideology .21 .02 9.71*** State mean income -.06 .04 -1.45 State population -.01 .01 -1.64 State urban population -.01 .00 -1.31 State gender diversity 3.82 3.07 1.24 State ethnic diversity .01 .00 2.29* State age diversity -.33 .28 -1.19 ⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯ Note. For Model 1, n = 978. For Model 2, n = 975. Gender was coded 1 = female or 0 = male. Ethnicity was coded 1 = Caucasian or 0 = other. Employment status was coded 1 = working as a paid employee or self-employed or 0 = unemployed. Marital status was coded 1 = married or 0 = not married. * p < .05. ** p < .01. *** p < .001.


Meritocratic Beliefs

Figure 2. Meritocratic beliefs as a function of income (±1 SD) and inequality in respondents’ home states. Lines are projections based on regression estimate from the regression model. The solid line depicts the projected association between income and meritocratic beliefs in the area with the lowest level of inequality (the state of Wyoming). The dotted line depicts this projected association in an area with an average level of inequality. The dashed line depicts this projected association in the area with the highest level of inequality (the District of Columbia).

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5


Highestinequality

Averageinequality

Lowestinequality


Income, Inequality, and Prosociality

Income, inequality, and the reported proportion of income donated to

charity. There was a significant interaction between income and inequality predicting the

reported proportion of income donated to charity (Table 3, Model 1), which resisted

controls (Table 3, Model 2). This interaction, shown in Figure 3, reveals that in areas

where inequality was high, having a higher income was associated with reporting

donating less, but in areas where inequality was low, having a higher income was

associated with reporting donating more. The analysis of regions of significance revealed

that income was significantly positively related to reported donations in states with Ginis

below .471, a set that included 33 states. By contrast, income was significantly negatively

related to reported donations where the Gini exceeded .502 (i.e., the state of New York

and DC). This pattern is consistent with past findings on the relationship between

inequality, hierarchical standing, and prosocial behavior (Côté et al., 2015; Hargreaves

Heap et al., 2016; Nishi et al., 2015).

Mediated moderation analysis of income, inequality, entitlement, and the

reported proportion of income donated to charity. We conducted a mediated moderation

analysis to test whether entitlement explained why having a higher income was

associated with reporting giving less where inequality was high. Meeting the first

condition for mediated moderation (Muller et al., 2005), in a previous analysis, there was

an interaction between inequality and income predicting reported donations, and the

pattern matched the prediction. Meeting the second condition, in another previous

analysis, there was an interaction between inequality and income predicting entitlement,

and the pattern also matched the prediction. Further, meeting the third criterion,


entitlement was negatively correlated with reported donations, r(961) = -.21, p < .001,

replicating past findings that individuals with high levels of entitlement are less prosocial

(Campbell et al., 2004). Further, the estimate for the interaction between inequality and

income predicting reported donations was reduced, though remained significant, γ = -.92,

SE = .27, t = -3.48, p < .001, when entitlement was added to the model.

We also tested mediated moderation by assessing the significance of the

conditional indirect effect using bootstrap confidence intervals (using 20,000 random

samples with replacement; MacKinnon, 2008). The 95% confidence ranged from -.22 to -

.01. Because the confidence interval excluded 0, mediated moderation was supported.

Thus, in highly unequal areas, higher income individuals reported giving a lower

proportion of their income to charity because they felt more entitled than lower income

individuals. These findings support Hypothesis 2.


Table 3 Hierarchical Linear Model Results Predicting the Reported Proportion of Income Donated to Charity (Logged) Model 1 Model 2 ⎯⎯⎯⎯⎯⎯ ⎯⎯⎯⎯⎯⎯ Variable γ SE t γ SE t ⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯ Intercept .43 .02 17.17*** .25 .06 3.99*** Income .02 .01 2.76** -.01 .01 -.80 Inequality -2.08 1.32 -1.57 -2.81 2.30 -1.22 Income x Inequality -1.04 .29 -3.62*** -.87 .31 -2.78** Age .00 .00 3.24** Gender .06 .04 1.45 Subjective social class .09 .03 3.55*** Ethnicity .10 .05 1.91 Education .07 .02 3.87*** Employment status -.06 .04 -1.41 Marital status .20 .04 4.63*** Religiosity .04 .01 4.06*** Conservative ideology .01 .01 1.01 State mean income -.05 .03 -1.62 State population -.00 .00 -.37 State urban population .01 .00 1.82 State gender diversity -1.90 2.24 -.85 State ethnic diversity .00 .00 .16 State age diversity -.46 .21 -2.22* ⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯ Note. For Model 1, n = 964. For Model 2, n = 961. Gender was coded 1 = female or 0 = male. Ethnicity was coded 1 = Caucasian or 0 = other. Employment status was coded 1 = working as a paid employee or self-employed or 0 = unemployed. Marital status was coded 1 = married or 0 = not married. * p < .05. ** p < .01. *** p < .001.


Reported Proportion of Income Donated to Charity (Logged)

Figure 3. Reported proportion of income donated to charity (logged) as a function of income (±1 SD) and inequality in respondents’ home states. Lines are projections based on regression estimate from the regression model. The solid line depicts the projected association between income and the reported proportion of income donated to charity in the area with the lowest level of inequality (the state of Wyoming). The dotted line depicts this projected association in an area with an average level of inequality. The dashed line depicts this projected association in the area with the highest level of inequality (the District of Columbia).

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Highestinequality

Averageinequality

Lowestinequality


Income, inequality, and raffle ticket donations to the United Way. There was

a positive association between income and raffle ticket donations to the United Way, but

this association did not vary as a function of inequality. Thus, there was no significant

interaction between income and inequality predicting raffle ticket donations (Table 4,

Models 1 and 2). This result is inconsistent with the previous analysis concerning

charitable donations and results reported in past research (Côté et al., 2015; Hargreaves

Heap et al., 2016; Nishi et al., 2015), suggesting that some prosocial behaviors might not

be reduced by inequality. In the discussion, we consider potential explanation of this

result. This finding does not support Hypothesis 2. Thus, Hypothesis 2 was partially

supported. The findings on reported donations to charity supported Hypothesis 2, but the

findings on raffle ticket donations to the United Way did not support it.


Table 4 Hierarchical Linear Model Results Predicting Raffle Ticket Donations to the United Way Model 1 Model 2 ⎯⎯⎯⎯⎯⎯ ⎯⎯⎯⎯⎯⎯ Variable γ SE t γ SE t ⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯ Intercept 4.10 .15 28.05*** 4.30 .35 12.28*** Income .09 .03 3.03** .08 .04 2.21* Inequality 6.36 7.90 .81 8.89 13.34 .67 Income x Inequality -1.76 1.30 -1.35 -1.79 1.31 -1.37 Age .00 .01 .17 Gender -.18 .23 -.77 Subjective social class .30 .15 2.01* Ethnicity -.09 .30 -.30 Education -.10 .11 -.92 Employment status -.12 .24 -.48 Marital status .01 .24 .05 Religiosity .10 .06 1.64 Conservative ideology -.24 .07 -3.21** State mean income -.05 .19 -.25 State population -.00 .03 -.17 State urban population .01 .02 .57 State gender diversity 3.03 12.98 .23 State ethnic diversity -.00 .02 -.10 State age diversity .21 1.20 .18 ⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯ Note. For Model 1, n = 978. For Model 2, n = 975. Gender was coded 1 = female or 0 = male. Ethnicity was coded 1 = Caucasian or 0 = other. Employment status was coded 1 = working as a paid employee or self-employed or 0 = unemployed. Marital status was coded 1 = married or 0 = not married. * p < .05. ** p < .01. *** p < .001.


Discussion

This study makes several contributions to our understanding of how income

relates to prosociality. First, our findings about the reported proportion of income donated

to charity was consistent with past findings that having a higher income is associated with

being less prosocial under unequal economic conditions, and more prosocial under more

equal conditions (Côté et al., 2015; Hargreaves Heap et al., 2016; Nishi et al. 2015).

Second, we found evidence for a mechanism that explains this pattern: psychological

entitlement. Where inequality was high, higher income individuals felt more entitled than

their lower income counterparts. Further, entitlement mediated the moderated association

between income, inequality and reported charitable donations, suggesting that higher

income individuals are particularly self-serving under conditions of pronounced

economic inequality because these conditions make them feel important and deserving.

By contrast, our analyses suggest that meritocratic beliefs do not explain this pattern.

Higher income individuals endorsed meritocratic beliefs where inequality was relatively

high and also where it was relatively low.

Researchers have linked high levels of economic inequality with a host of social

problems, including crime, obesity, teenage births, drug and alcohol abuse, gender

inequality, and reduced social cohesion (Hsieh & Pugh, 1993; Kawachi, Kennedy,

Lochner, & Prothrow-Smith, 1999; Wilkinson & Pickett, 2009). Our findings illuminate

micro processes that might explain these macro patterns, a possibility that should be

examined in future research. For instance, inequality might reduce social cohesion in part

by increasing entitlement among those at the top of the economic distribution.


Our findings extend past research by showing that inequality might reduce higher

income individuals’ donations of earned income, whereas past research had tested this

pattern with resources received unexpectedly from experimenters (Côté et al., 2015;

Hargreaves Heap et al., 2016; Nishi et al. 2015), a method that invites questions about

generalizability. In interpreting these findings, it is important to consider that self-reports

of charitable donations may be influenced by memory limitations and social desirability

response bias (Podsakoff & Organ, 1986), particularly because generous acts are among

the most socially desirable acts (Willer, 2009).

Our study also reveals boundary conditions for the pattern between income,

inequality, and prosociality found for reported donations to charity and in past research

(Côté et al., 2015; Hargreaves Heap et al., 2016; Nishi et al. 2015), as our analysis of

raffle ticket donations to the United Way did not yield this pattern. We conducted

exploratory analyses revealing that counter to past findings that entitlement is a robust

predictor of self-serving behavior (Campbell et al., 2004; Zitek et al., 2010), entitlement

did not correlate with raffle ticket donations, r(975) = -.03, p = .96. We also reviewed the

responses to an open-ended question asking for comments at the end of the survey. A few

participants reported having negative attitudes about the United Way because of prior

wrongdoing by executives, which sometimes led to prison sentences (Johnston, 2004;

Markon, 2004; Strom, 2006). Participants’ motivation to be prosocial toward the United

Way might thus depend in part on factors beyond the scope of our study—particularly

pre-existing, polarized attitudes towards this organization—and, as a result, less on other

predictors such as entitlement. As such, the findings suggest a boundary condition for the


relationship between income, inequality, and prosociality—the perceived legitimacy of

the target of prosociality—that could be explored in future research.

In sum, the findings illuminate why the relationship between income and

prosociality has been found to vary depending on levels of inequality. Under highly

unequal economic conditions—but not when income is more evenly distributed—higher

income individuals feel highly entitled, and because of this they report giving less of their

income to charity. As such, the findings identify a previously unexamined correlate of

high economic inequality: high entitlement among those who earn the most. One

mechanism for the perpetuation of inequality might involve moneyed elites who are

highly entitled and donate little—a pattern of beliefs and behaviors that contribute to

maintaining that advantage.


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