Understanding Patterns and Trends in Income Mobility through Multiverse Analysis

Abstract

Rising inequalities in rich countries have led to concerns that the economic ladder is getting harder to climb. Yet, research on trends in intergenerational income mobility finds conflicting results. To better understand this variation, we adopt a multiverse approach that estimates trends over 82,944 different definitions of income mobility, varying how and for whom income is measured. Our analysis draws on comprehensive register data for Swedish cohorts born 1958 to 1977 and their parents. We find that income mobility has declined, but for reasons neglected by previous research: improved gender equality in the labor market raises intergenerational persistence in women’s earnings and the household incomes of both men and women. Dominant theories that focus on childhood investments have blinded researchers to this development. Methodologically, we show how multiverse analysis can be used with abduction—inference to the best explanation—to improve theory-building in social science.

Explaining Gender-Specific Trends in Income Mobility: The Role of Education

“…Recently, when studying intergenerational mobility, researchers often rank parents' and children's incomes within the child birth cohort. Compared with other mobility measures, rank-rank slope is less sensitive to measurement error, the treatment of zero income, life-cycle bias, and changes in income inequality between generations (Chetty et al 2014;Engzell and Mood 2023). It is hence more consistent with the traditional sociological approach to examining relative mobility (Erikson and Goldthorpe 1992).…”

“…6. Engzell and Mood (2023) show that even when using rank correlations, measuring child earnings at younger ages significantly underestimates both levels and trends.…”

“…Intriguingly, recent research using individual income or earnings data finds that trends in income mobility are not uniform across genders. The intergenerational rank association in income has remained relatively stable between family (or fathers) and sons but has increased significantly between family (or mothers) and daughters in the US, Scandinavia, and the Netherlands (Ahrsjö, Karadakic, and Rasmussen 2023;Branden, Nybom, and Vosters 2023;Colagrossi, Geraci, and Mazzarella 2023;Engzell and Mood 2023;Markussen and Røed 2020).…”

A dynamic functional connectivity toolbox for multiverse analysis

“…In addition to the standard application of multiverse analysis to assess the robustness of results across various analytical decisions through e.g. specification curve analysis (Simonsohn, Simmons, and Nelson, 2020), we also aim to explore new perspectives which understand multiverse analysis as an exploratory tool to identify key covariates that significantly impact study outcomes (Bowring, Nichols, and Maumet, 2022) and as a framework for abduction and inferential decisions (Engzell and Mood, 2023). This can help in excluding ineffective methods in new dataset analyses and provide insights into conditions for expected effects.…”

Which Economic Sectors Influence Average Household Income? A Spatial Econometric Study of Thailand’s 76 Provinces

“…Changes in household composition, such as marriage, childbirth, or divorce, significantly influence income, impacting resource division and dependent numbers (Burgess and Propper 1998). Age and gender also play pivotal roles, with female-headed households and younger workers experiencing distinct income mobility patterns (Aristei and Perugini 2015;Engzell and Mood 2023). Additionally, variables such as household size and presence of elderly members influence income growth (Devicienti et al 2014;Jin and Xie 2017).…”