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Key research themes
1. How does relative income and social comparison influence individual well-being?
This research area investigates the impact of individuals' income relative to their reference or comparison groups on subjective well-being, happiness, and life satisfaction. It addresses the inconsistency in findings regarding whether income increases enhance well-being and explores the role of relative income, social comparisons, and reference groups in shaping individual utility beyond absolute income levels. Understanding these mechanisms is crucial because it informs theories of consumer behavior, happiness economics, and social welfare policies. Methodologically, this theme encompasses econometric regression analyses using panel data, consideration of reference group definitions, and testing multiple model specifications to discern the effect of comparison income on well-being.
Key finding: Using large German panel data (GSOEP), the study finds that individual subjective well-being (SWB) is influenced not only by absolute income but also by the average income of reference groups, demonstrating a significant... Read more
Key finding: Exploiting UK longitudinal data, this study reveals that the estimated effect of relative income on individual utility is sensitive both to the definition of the reference group (e.g., age/education/gender vs. geographic... Read more
Key finding: Analyzing a nationally representative Dutch sample, the study identifies that perceived income inadequacy is present across all absolute income levels and independently predicts worse health outcomes (chronic disease,... Read more
2. What are the dynamics and determinants of gender wage gaps and occupational segregation across income distributions and countries?
This theme synthesizes research exploring the gender pay gap and occupational gender segregation, emphasizing distributional heterogeneity, selection bias, education, and cross-national differences. The investigation addresses how wage disparities evolve across the wage distribution, the influence of family and children on pay differences, and how occupational segregation perpetuates wage gaps. It combines advanced econometric methods including quantile approaches, generalized entropy measures, and decomposition techniques, as well as cross-country comparative micro-data analyses to unravel the structural causes behind persistent gender inequality in income.
Key finding: Employing a novel quantile-Copula approach to jointly model wages and labor force participation, this work robustly challenges conventional understandings of the gender wage gap in the US. It demonstrates that selection... Read more
Key finding: Using microdata spanning seven industrialized countries, the paper identifies substantial cross-national variation in the wage penalties faced by women with children, attributing larger family pay gaps to higher part-time... Read more
Key finding: Analyzing US occupational data over several decades, this research documents that occupational gender segregation declined notably in the 1970s and 1980s but plateaued thereafter. It establishes a robust inverse relationship... Read more
3. How can income inequality and segregation be accurately measured and decomposed using advanced data sources and statistical methods?
This research cluster focuses on methodological innovations in income inequality and segregation measurement, including the use of administrative vs. survey data, income segregation indices accounting for cardinal income properties, decomposable inequality metrics based on information theory, and multilevel statistical modeling applied to regional and household income distributions. The goal is to improve data accuracy, interpretability, and policy relevance by better capturing heterogeneity within and between groups, structural income distribution characteristics, and the spatial dimension of inequality.
Key finding: Comparing Spanish administrative tax data with survey data reveals substantial discrepancies particularly at distributional tails, with administrative data capturing higher top incomes and survey data better recording low... Read more
Key finding: The paper axiomatizes two income segregation measures that treat income as a cardinal variable and satisfy decomposability into between- and within-region segregation components. One measure is based on variance and another... Read more
Key finding: Using the Mean Logarithmic Deviation (MLD) index, the study decomposes total income inequality in Poland by education and age groups, finding that differences between educational groups contribute significantly to overall... Read more
Key finding: Employing multilevel modeling techniques on Russian regional and municipal income data, the paper demonstrates that both inter-regional and intra-regional factors critically influence income inequality variations. Results... Read more