Analysing Inequalities in Germany

A Structured Additive Distributional Regression Approach
1. Auflage 2017
ISBN: 978-3-319-65330-3
Verlag: Springer

Buch, Englisch, 98 Seiten, Format (B × H): 155 mm x 235 mm, Gewicht: 1766 g

Reihe: SpringerBriefs in Statistics

This book seeks new perspectives on the growing inequalities that our societies face, putting forward Structured Additive Distributional Regression as a means of statistical analysis that circumvents the common problem of analytical reduction to simple point estimators. This new approach allows the observed discrepancy between the individuals’ realities and the abstract representation of those realities to be explicitly taken into consideration using the arithmetic mean alone. In turn, the method is applied to the question of economic inequality in Germany.

Zielgruppe

Research

Autoren/Hrsg.

Silbersdorff, Alexander

Fachgebiete

• Wirtschaftswissenschaften Volkswirtschaftslehre Volkswirtschaftslehre Allgemein Arbeitsmarkt
• Wirtschaftswissenschaften Volkswirtschaftslehre Volkswirtschaftslehre Allgemein Wirtschaftstheorie, Wirtschaftsphilosophie
• Sozialwissenschaften Soziologie | Soziale Arbeit Spezielle Soziologie Soziale Ungleichheit, Armut, Rassismus
• Wirtschaftswissenschaften Betriebswirtschaft Wirtschaftsmathematik und -statistik
• Wirtschaftswissenschaften Volkswirtschaftslehre Wohlfahrtsökonomie

Inhaltsverzeichnis

Preface.- Introduction.- Inequality and Earnings Distributions.- Estimating and Assessing Distributional Regression.- The Distributional Perspective and Labour Markets.- Applications of SADR in Economics.- Conclusion.- Index.

Über Autor(innen)

Alexander Silbersdorff is a research associate at the Department of Statistics, University of Göttingen, Germany, where he predominantly works on the development and application of regression techniques to economic contexts. Previously, he served at the Department of Economic History at the University of Bielefeld, Germany, where he investigated the development of historical income structures.