Rising income inequalities are widely debated in public and academic discourse. In this paper, we contribute to this debate by proposing a new family of measures of unfair inequality. To do so, we acknowledge that inequality is not bad per se, but that its underlying sources need to be taken...

Are the United States still a land of opportunity? We provide new insights on this question by invoking a novel measurement approach that allows us to target the joint distribution of income and wealth. We show that inequality of opportunity has increased by 77% over the time period 1983-2016....

In this paper we propose the use of machine learning methods to estimate inequality of opportunity. We illustrate how our proposed methods—conditional inference regression trees and forests—represent a substantial improvement over existing estimation approaches. First, they reduce the risk...

Equality of opportunity is an important normative ideal of distributive justice. In spite of its wide acceptance and economic relevance, standard estimation approaches suffer from data limitations that can lead to both downward and upward biased estimates of inequality of opportunity. These...

Rising income inequalities are widely debated in public and academic discourse. In this paper, we contribute to this debate by proposing a new family of measures of unfair inequality. To do so, we acknowledge that inequality is not bad per se, but that its underlying sources need to be taken...

Are the United States still a land of opportunity? We provide new insights on this question by invoking a novel measurement approach that allows us to target the joint distribution of income and wealth. We show that inequality of opportunity has increased by 77% over the time period 1983-2016....

Are the United States still a land of opportunity? We provide new insights on this question by invoking a novel measurement approach that allows us to target the joint distribution of income and wealth. We show that inequality of opportunity has increased by 77% over the time period 1983-2016....

We measure the distributional impact of the COVID-19 pandemic using newly released population register data in Sweden. Monthly earnings inequality increased during the pandemic, and the key driver is income losses among low-paid individuals while middle- and high-income earners were almost...

This report analyses the economic consequences of the coronavirus pandemic and support policies using underutilized data sources from the Swedish Tax Agency's tax register, which provides real-time information on firm sales and employees' wage income. Firms' sales, particularly in areas heavily...

We measure the distributional impact of the COVID-19 pandemic using newly released population register data in Sweden. Monthly earnings inequality increased during the pandemic, and the key driver is income losses among low-paid individuals while middle- and high-income earners were almost...