Year: 2020
Type: dissertation
Abstract: In this thesis I investigate the inequality in opportunity for income in Norway. In contrast to studies utilizing Roemer's (1993) identifying monotonicity assumption, I propose a direct measure of effort that does not depend on type, and develop a novel framework for incorporating these various measures of effort. I also develop a decomposition of the generalized entropy index with $\\alpha = 0$, that is helpful for presenting my results. Moreover, I utilize a simple machine-learning algorithm to partition the observations into different types. This is particularly useful when circumstance-variables are continuous, and, as far as I know, novel in this context. I find circumstances to account for about 40 percent of the total inequality in expected income, conditional on effort. This is about 15 percentage-points higher than what I find in the same data, using Roemerian effort. Furthermore, I find gender and parental socioeconomic status to be the main determinant of opportunities.
Author: Håvarstein, Morten
Language: English
Subfield: Sociology and Political Science
Field: Social Sciences
Domain: Social Sciences
Open Access status: green
Funder: Universitetet i Oslo
OpenAlex ID: W7057892213