A new dissertation on intergenerational mobility
On Wednesday December 4 Erling Risa will hold a trial lecture on a prescribed topic and defend his thesis for the PhD degree at NHH.
Prescribed topic for the trial lecture:
Machine learning: What it can and cannot do for economics
10:15 in Karl Borch Aud, NHH
Title of the thesis:
Essays on Intergenerational Mobility
The focus of this dissertation is intergenerational mobility or more concretely the extent to which socioeconomic status persists between generations. In this context, socioeconomic status might refer to several things, but earnings, education, and occupation are typical examples. While there are many reasons why intergenerational mobility is worth studying, perhaps the two most important ones are fairness concerns and efﬁciency. Erling Risa´s dissertation consists of three chapters:
1: Income and family background: Are we using the right models?
Social scientists have long been interested in the relationship between parental factors and later child income. Finding the best characterization of this relationship for the question at hand is however fraught with choices. In this paper Risa and co-author Jack Blundell use machine learning methods to assess the ‘completeness’ of one popular modelling approach. Here, completeness refers to how well the model summarizes the total predictive relationship between multiple parental factors and a single child outcome. Machine learning methods enable us to depart from functional form assumptions, allowing flexible interactions between a large set of possible parental factors.
2: Status Traps in Social Mobility and Human Capital Investment
Although intergenerational income mobility is high in Nordic countries, parental education still plays an important role in explaining educational attainment. Using machine learning techniques, Risa, Aline Bütikofer and Kjell G. Salvanes show that, in Norway, obtaining a college degree is not a continuous function of parental years of education and that there are discontinuities and interactions at different parental education levels. Parental earnings and the transmission of cognitive ability are not the only reasons for the status traps in education. Moreover, our findings suggest that parental education can compensate for lower cognitive ability, whereas paternal earnings cannot compensate for low parental education.
3: Intergenerational Mobility over time and Across Regions in Norway
In this paper Risa (and co-authors Pedro Carneiro, Sarah Cattan, Sonya Krutikova, and Kjell G. Salvanes) analyze intergenerational mobility in Norway for cohorts of children born from the mid 1950s until the mid 1980s. They are particularly interested in the role of human capital investments, the role of the labor market and returns to human capital and characteristics of the industrial structure and other labor market characteristics. Risa uses machine learning to identify regional differences and labor market differences.
12:15 in Karl Borch Aud, NHH
Members of the evaluation committee:
Professor Erik Ø. Sørensen (leader of the committee), Department of Economics and FAIR, NHH
Associate Professor Jan Stuhler, Universidad Carlos III de Madrid
Reader Jo Blanden, Economics Department at the University at Surrey
Professor Kjell Gunnar Salvanes (main supervisor), Department of Economics and FAIR, NHH
Professor Mikael Lindahl, University of Gothenburg