2021/01/01 by Nathan Deutscher, Bhashkar Mazumder · 1 voice
Social Sciences · Decision Sciences · #Intergenerational and Educational Inequality Studies #demographic modeling and climate adaptation #Education Systems and Policy
paper · doi:10.21033/wp-2021-09
openalex publication_date 2021/01/01 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/31
The literature on intergenerational income mobility uses a diverse set of measures and there is limited knowledge about whether these measures provide similar information and yield similar conclusions. We provide a framework to highlight the key concepts and properties of the different estimators. We then show how these measures relate to one another empirically. Our main analysis uses income tax data from Australia to produce a comprehensive set of empirical estimates for each of 19 different mobility measures at both the national and regional level. We supplement this analysis with other data that uses either within or between country variation in mobility measures. A key finding is that there is a clear distinction between relative and absolute measures both conceptually and empirically. A region may be high with respect to absolute mobility but could be low with respect to relative mobility. However, within broad categories, the different mobility measures tend to be highly correlated. For rank-based estimators, we highlight the importance of how the choice of the distribution used for calculating ranks can play a critical role in determining its properties as well as affect empirical findings. These patterns of results are important for policy makers whose local economy might fare well according to some mobility indicators but not others.