5180 Sustainable Economics and Business II: Inequality, Well-Being, and Sustainability
Assist.Prof. Mag. Simon Sturn, Ph.D.
Contact details
Weekly hours
Language of instruction
02/09/23 to 02/14/23
Registration via LPIS
Notes to the course
Subject(s) Bachelor Programs
Day Date Time Room
Wednesday 03/01/23 10:00 AM - 01:30 PM TC.3.11
Wednesday 03/15/23 10:00 AM - 01:30 PM TC.5.15
Wednesday 03/22/23 10:00 AM - 01:30 PM TC.2.01
Wednesday 03/29/23 10:00 AM - 01:30 PM Online-Einheit
Wednesday 04/12/23 10:00 AM - 01:30 PM Online-Einheit
Wednesday 04/19/23 10:00 AM - 01:30 PM Online-Einheit
Wednesday 04/26/23 10:00 AM - 01:30 PM TC.3.21

In this course we investigate effects of socio-economic inequality on well-being and sustainability. A thriving literature analyses the development of income inequality over time, its determinants, and its consequences. The aim of this course is to read several significant contributions to these fields, and discuss their implications. Specifically, the first part of the course focuses on recent trends in income inequality. We also briefly discuss inequality by gender and race. The second and largest part looks at the effects of inequality on various outcomes, like crime, consumerism, household indebtedness, and the environment. The third part investigates determinants of income inequality, and options of policy makers to address high inequality.

Learning outcomes

Upon successful completion of the course students will know:

  • About recent trends in income inequality in and between countries, and understand the core-differences between various measures of inequality.
  • How inequality affects our society, economy, and environment.
  • Key determinants of income inequality, and how policy makers can tackle inequality without causing significant unintended side effects.
  • Basics about causality and credible identification strategies.
  • How to (critically) read academic articles.
Attendance requirements

Examination-immanent courses (PI) have compulsory attendance. A minimum attendance of 80% is required. In case of absence, please inform the lecturer in advance. Especially the first three sections provide crucial inputs and attendance is important.

Teaching/learning method(s)

  • Lectures
  • Student group presentations
  • Discussions
  • Videos
  • Note: Students are required to read, present, and discuss academic articles.
  • Presentation (40%)
  • Prepared comment on other group's presentation (10%)
  • Discussion questions on readings (15%)
  • Short quizzes on previous topics (15%) 
  • Participation (20%)
Prerequisites for participation and waiting lists

Course enrollment is on the basis of "first-come, first-served” principle. If you have registered but cannot participate in the course, please de-register via LPIS during the registration period so that your course is available to students on the waiting list. If there is a waiting list for enrollment in the course, students at the waiting list will be notified after the end of the enrollment period, and will be allocated to available places. Students will be ranked by their study progress not by their rank on the waiting list. This procedure, however, is not to be understood as a place guarantee.


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Recommended previous knowledge and skills

Students are required to read, present, and discuss academic articles and papers on covered topics. Many of these papers apply advanced regression analysis. Students are not required to know these methods to accomplish this course, since the focus lies on intuition and big picture of these papers. It helps, however, if they are interested in learning how to interpret empirical findings.

Availability of lecturer(s)
Last edited: 2023-02-15