No evidence that economic inequality moderates the effect of income on generosity

A landmark study published in PNAS (Côté S, House J, Willer R, 2015, 112:15838-15843, doi:10.1073/pnas.1511536112) showed that higher income individuals are less generous than poorer individuals only if they reside in a U.S. state with comparatively large economic inequality. This finding might serve to reconcile inconsistent findings on the effect of social class on generosity by highlighting the moderating role of economic inequality. On the basis of the importance of replicating a major finding before readily accepting it as evidence, we analyzed the effect of the interaction between income and inequality on generosity in three large representative data sets. We analyzed the donating behavior of 27,714 U.S. households (Study 1), the generosity of 1,334 German individuals in an economic game (Study 2), and volunteering to participate in charitable activities in 30,985 participants from 30 countries (Study 3). We found no evidence for the postulated moderation effect in any study. This result is especially remarkable because (a) our samples were very large, leading to high power to detect effects that exist, and (b) the cross-country analysis employed in Study 3 led to much greater variability in economic inequality. These findings indicate that the moderation effect might be rather specific and cannot be easily generalized. Consequently, economic inequality might not be a plausible explanation for the heterogeneous results on the effect of social class on prosociality

Item Sum Double-List Technique: An Enhanced Design for Asking Quantitative Sensitive Questions

Social desirability bias is a problem in surveys collecting data on sensitive or private topics (e.g. sexual practices, health, income, deviant behavior) as soon as the respondent’s true status differs from a social norm. If confronted with sensitive questions, respondents often engage in self-protective behavior, either by giving socially desirable answers or by refusing to answer at all. Such systematic misreporting or nonresponse leads to biased estimates and poor data quality. To improve the measurement of sensitive topics in population surveys, various indirect questioning techniques have been proposed in the literature. One example, for the measurement of quantitative sensitive characteristics, is the "item sum technique" (IST). In this study we propose an enhanced design for the IST: the "item sum double-list technique" (ISDLT). Compared to the original IST, the ISDLT estimator has a higher statistical efficiency given the same sample size. We first describe our enhanced design, derive prevalence and variance estimators, and show how data collected by the ISDLT can be analyzed. We then provide evidence on the empirical viability of the ISDLT based on a large-scale experimental online survey that asked respondents about their lifetime number of sexual partners and their pornography consumption

The positive effect of social class on everyday helping behavior in the American General Social Survey (Study 7).

<p>Panel A shows the mean scale value of the everyday helping scale per decile of objective social class. Panel B illustrates a LOESS curve (local least squares fitting) for the scale value of the everyday helping scale by standardized objective social class (<i>N</i> = 3,902). Panel C (<i>N</i> = 3,886 persons) shows the mean scale value of the everyday helping scale per category of subjective social class. Panel D illustrates the predicted scale values for the everyday helping scale determined via OLS regression. It distinguishes between a curve for subjective social class and a curve for objective social class.</p

A Large Scale Test of the Effect of Social Class on Prosocial Behavior

<div><p>Does being from a higher social class lead a person to engage in more or less prosocial behavior? Psychological research has recently provided support for a negative effect of social class on prosocial behavior. However, research outside the field of psychology has mainly found evidence for positive or u-shaped relations. In the present research, we therefore thoroughly examined the effect of social class on prosocial behavior. Moreover, we analyzed whether this effect was moderated by the kind of observed prosocial behavior, the observed country, and the measure of social class. Across eight studies with large and representative international samples, we predominantly found positive effects of social class on prosociality: Higher class individuals were more likely to make a charitable donation and contribute a higher percentage of their family income to charity (32,090 ≥ <i>N</i> ≥ 3,957; Studies 1–3), were more likely to volunteer (37,136 ≥<i>N</i> ≥ 3,964; Studies 4–6), were more helpful (<i>N</i> = 3,902; Study 7), and were more trusting and trustworthy in an economic game when interacting with a stranger (<i>N</i> = 1,421; Study 8) than lower social class individuals. Although the effects of social class varied somewhat across the kinds of prosocial behavior, countries, and measures of social class, under <i>no</i> condition did we find the negative effect that would have been expected on the basis of previous results reported in the psychological literature. Possible explanations for this divergence and implications are discussed.</p></div

The positive effect of social class on volunteering in the German SOEP (Study 4; based on N = 33,072 persons and 82,966 observations).

<p>Panel A shows the proportion of volunteers per decile of objective social class. Panel B uses local likelihood fitting (Locfit) to adjust a curve to the raw data and illustrates the probability of volunteering by objective social class. Panel C shows the predicted values for the probability of volunteering determined via logistic regression. Panels D–F illustrate the frequency of volunteering based on four categories (0 = never, 3 = every week). Panel D shows the mean frequency of volunteering per decile of objective social class. Panel E shows a LOESS curve for the frequency of volunteering by objective social class. Panel F illustrates the predicted values for the frequency of volunteering determined via multilevel ordinary regression.</p

The positive effect of social class on volunteering in charitable activities using the complete data of the ISSP (Study 6).

<p>Panel A shows the proportion of volunteers per decile of objective social class (x-axis caption under the axis) and per category of subjective social class (x-axis caption above the axis). Panel B uses local likelihood fitting (Locfit) to adjust a curve to the raw data and illustrates the probability of volunteering by social class. Panel C shows the predicted values for the probability of volunteering determined via multilevel logistic regression. Panels D–F illustrate the frequency of volunteering using four categories (0 = no; 3 = yes, 6 or more times). Panel D shows the frequency of volunteering per decile of objective social class and per category of subjective social class. Panel E shows LOESS curves for the frequency of volunteering by social class. Panel F shows the predicted values for the frequency of volunteering determined via multilevel ordinary regression. Panels B–C and E–F distinguish between a curve for objective social class (solid line; x-axis caption under the axis; <i>N</i> = 37,136) and a curve for subjective social class (dashed line; 1 = lower class, 6 = upper class; <i>N</i> = 32,257).</p

The positive effect of social class on the frequency of volunteering in the American General Social Survey (Study 5).

<p>Panels A–D illustrate the frequency of volunteering using six categories (0 = not at all in the past year, 5 = more than once a week). Panel A shows the frequency of volunteering per decile of objective social class. Panel B uses local least squares fitting (LOESS curve) to adjust a curve to the raw data and illustrates the frequency of volunteering by standardized objective social class (<i>N</i> = 3,983 persons). Panel C (<i>N</i> = 3,964 persons) shows the frequency of volunteering per category of subjective social class. Panel D illustrates the predicted values for the frequency of volunteering determined via OLS regression. It distinguishes between a curve for subjective social class and a curve for objective social class.</p

The positive effect of social class on the probability of donating in the American General Social Survey (Study 3).

<p>Panel A shows the proportion of donors per decile of objective social class. Panel B uses local likelihood fitting (Locfit) to adjust a curve to the raw data and illustrates the probability of donating by standardized objective social class (<i>N</i> = 3,975 persons). Panel C (<i>N</i> = 3,957 persons) shows the proportion of donors per category of subjective social class. Panel D illustrates the predicted values for the probability of donating determined via logistic regression. It distinguishes between a curve for subjective social class and a curve for objective social class.</p

The positive effect of social class on donation behavior in the American Consumer Expenditure Survey (Study 2).

<p>Panel A shows the proportion of donating households per decile of objective social class. Panel B (<i>N</i> = 32,090 households) uses local likelihood fitting (Locfit) to adjust a curve to the raw data and illustrates the probability of donating by objective social class. Panel C shows the predicted values for the probability of donating determined via logistic regression. Panel D illustrates the amounts of the donations relative to household income per decile of objective social class. Panel E shows LOESS curves for the relative amounts of the donations by objective social class. Panel F shows the predicted values for the relative amounts of donations determined via OLS regression. Panels D–F distinguish between a curve for donor households (<i>N</i> = 14,084 households) and a curve for all households (<i>N</i> = 32,090 households).</p

Effects of objective social class and subjective social class on volunteering in charitable activities separately for each country from the International Social Survey Program (ISSP; Study 6).

<p>The panels use local least squares fitting (LOESS; smoothing parameter = 1.0, polynomial = 1) to adjust a curve to the raw data and illustrate the frequency of volunteering (y-axis; four categories: 0 = no; 3 = yes, 6 or more times) by social class (x-axis). They distinguish between a curve for standardized objective social class (solid line; x-axis caption under the axis) and a curve for subjective social class (dashed line; x-axis caption above the axis; 1 = lower class, 6 = upper class). Sample sizes for each country are given in parentheses (<i>N</i>_{<i>objective social class</i>} / <i>N</i>_{<i>subjective social class</i>}).</p