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Prosociality predicts labor market success around the world

Business

Prosociality predicts labor market success around the world

F. Kosse and M. M. Tincani

Discover groundbreaking insights into how prosocial behavior influences labor market success across the globe, based on a massive study of 80,000 individuals conducted by Fabian Kosse and Michela M. Tincani. This research challenges prior assumptions and highlights the universal benefits of being kind and helpful in your career.

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Playback language: English
Introduction
Prosocial behaviors, encompassing reciprocity, altruism, and trust, significantly impact human interactions and economic decisions. Extensive research highlights their importance for societal and market functioning. Trust facilitates economic exchange, while reciprocity acts as a contract enforcement mechanism, leading to more efficient market outcomes. Recent evidence also links prosociality and social skills to improved individual life outcomes, aligning with the broader literature on the returns to non-cognitive or socio-emotional skills. Deming's model suggests social skills decrease coordination costs, enabling worker specialization and collaboration. However, most of this evidence comes from WEIRD (Western, Educated, Industrialized, Rich, and Democratic) societies, raising concerns about generalizability. This study addresses this limitation by examining the correlation between prosociality and labor market success across a diverse range of countries, aiming to provide a broader understanding of this relationship.
Literature Review
Existing literature extensively documents the positive effects of prosociality on societal well-being and individual success, particularly within WEIRD societies. Studies show that trust drives economic exchange, reciprocity strengthens contract enforcement, and prosociality generally improves life outcomes. This research builds on the work emphasizing the importance of non-cognitive skills, particularly social skills. However, the limited geographical scope of these studies raises questions about their generalizability to non-WEIRD contexts, given potential societal variations stemming from factors like market integration, community size, and religious institutions.
Methodology
This study utilizes data from the Global Preference Survey (GPS), which includes experimentally validated measures of prosociality and encompasses approximately 80,000 individuals across 76 representative country samples, covering about 90% of the world's population. The analyses use household income (log-transformed), underemployment (binary indicator), and unemployment (binary indicator) as measures of labor market success. Prosociality is measured using a composite score derived from standardized measures of altruism, positive reciprocity, and trust, obtained through hypothetical choice experiments and survey items. Regressions include subnational region fixed effects, and standard errors are clustered at the country level. Observations are weighted using sampling weights to ensure representativeness. All analyses were performed using Stata 14.2. To explore potential non-linear relationships, analyses were conducted using prosociality quartiles. Heterogeneity across countries was investigated by examining country-specific estimates of the income premium of prosociality, comparing these estimates across continents and WEIRD/non-WEIRD countries, and assessing their relationship with average prosociality levels and GDP per capita. The study also analyzed the predictive power of individual facets of prosociality (altruism, positive reciprocity, and trust).
Key Findings
The study reveals a sizable and robust positive relationship between prosociality and labor market success across all countries. A one-standard-deviation increase in prosociality is associated with an 8% higher household income (before controlling for cognitive ability). Controlling for cognitive ability, gender, age and other factors does not substantially alter this relationship. Prosociality is also negatively associated with underemployment and unemployment. Individuals with higher prosociality scores are significantly less likely to be underemployed or unemployed. Analysis of the individual components of prosociality shows that altruism, positive reciprocity, and trust each independently predict labor market success, with positive reciprocity having the strongest effect. Between-country analysis reveals no significant differences in income premia of prosociality across continents or between WEIRD and non-WEIRD countries. Furthermore, no significant relationship was found between income premia and average national prosociality levels or GDP per capita. While the effects are generally positive across the prosociality distribution, there's some suggestion of diminishing returns at the highest levels.
Discussion
The findings strongly support the generalizability of the positive relationship between prosociality and labor market success beyond WEIRD societies. The consistent positive correlation across diverse countries and contexts suggests that models incorporating prosociality and social skills likely have broad applicability. The lack of significant differences across continents and economic development levels reinforces this conclusion. While the study demonstrates a correlation, not causation, the robustness of the findings across various measures of labor market success enhances their credibility. The findings highlight the potential for policies targeting prosociality development to improve labor market outcomes.
Conclusion
This research demonstrates a robust and generalizable positive association between prosociality and labor market success across a globally representative sample. The consistency of the findings across diverse contexts underscores the importance of prosociality in various labor markets. Future research should focus on understanding the mechanisms driving this relationship and investigating the potential for interventions to cultivate prosociality, particularly in contexts where it may be less prevalent.
Limitations
The cross-sectional nature of the data limits causal inference. Reverse causality or omitted variables could potentially confound the observed relationship. The reliance on self-reported measures for some variables introduces potential measurement error. Additionally, the study does not explore the potential moderating roles of specific cultural or institutional contexts.
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