Contextual Income Inequalities und Life Satisfaction: Mechanisms and Moderators

• Applicant: Dr. Peter Valet
• Subject Area: Empirical Social Research
• Term: since 2023
• Project identifier: Deutsche Forschungsgemeinschaft (DFG) - Project number 533150713

In public and academic debates, many experts and scholars argue that the current level of earnings inequality is too high and that reducing earnings inequality would improve overall well-being. The numerous studies on the impact of earnings inequality on individual life satisfaction, however, reveal surprisingly inconsistent findings. Moreover, the theoretical foundation, the methodological approach, and the interpretation of obtained research results are often inconsistent as well. Most studies investigate aggregate earnings inequality cross-comparatively. What often remains unclear, though, is if people have any knowledge about the level on macro earnings inequality or what the mechanisms are that explain effects from the macro level to the micro level. Therefore, this project addresses two key shortcomings of current research to understand whether and how earnings inequality affects individual life satisfaction: (1) Drawing on sociological approaches to relational inequalities, this project challenges the common practice of looking at earnings inequality exclusively at the macro level. Apart from earnings inequality at the national level, people also experience inequalities within and across economic sectors, occupations, and workplaces. To analyze the effects of contextual inequalities, we need data on income inequalities for different contexts. This project uses different sources of registry data to generate representative measures of contextual earnings inequality and link them to data from existing social science surveys. The computation and dissemination of representative measures of contextual earnings inequality closes a crucial gap in the German data infrastructure. Thus, the project also provides an important basis for the analysis of numerous current research questions on earnings research beyond the scope of the project question. (2) This project is dedicated to the problem of causality with a focus on methods for the identification of causal effects. Following the approach of modern causal analysis, the goal of data analysis in this project is explicitly not to investigate all factors that influence life satisfaction. The goal is to identify particular (causal) effects as precisely as possible. For this, I use methods of modern causal analysis and adequate data analysis procedures. Crucial for this is a clear theoretical understanding of which variables we must control for to identify the causal effect and which variables we must absolutely not control for. After the identification of the causal effect, I test the theoretically assumed mechanisms explaining the effect and the assumed moderators generating effect heterogeneity.

• DFG Programme: Research Grants