This course delves into a substantial body of empirical studies highlighting the detrimental impact of income inequality on social, economic, and environmental sustainability. We critically evaluate key contributions to this literature, commencing with a brief exploration of methodological challenges and fundamental principles of causal identification. We then analyze global trends in income inequality across countries, and also briefly discuss inequality by gender and ethnicity. The core segment of the course centers on detailed studies examining the consequences of escalating income inequality. These studies investigate its effects on diverse outcomes, including crime rates, household consumption and debt, innovation dynamics, and environmental conditions. In the final section, we assess the underlying factors driving income inequality and explore policy options available to policymakers aimed at mitigating high levels of inequality. Through rigorous analysis and critical evaluation, this course provides a comprehensive understanding of the complexities surrounding income inequality and its broad societal implications.

Upon completion of the course, students will:

• Deepen their understanding of trends in income inequality by analyzing global and national data and distinguishing between different metrics.
• Gain insight into socio-economic impacts by exploring how inequality affects society, the economy, and the environment.
• Learn key determinants and effective policy strategies to address inequality without unintended consequences.
• Acquire foundational knowledge of causality and credible research methods for investigating cause-and-effect relationships.
• Develop critical analysis skills for scholarly articles, enhancing the ability to contribute to discussions of complex economic challenges.
• Cultivate teamwork skills through student-led presentations and collaborative assignments that promote peer learning.

Examination-immanent courses (PI) are compulsory. A minimum attendance of 80% is required. In case of absence, please inform the lecturer in advance. No makeup assignments will be provided in case of missed assessments. The first three sections are particularly important and attendance is essential.

• Lectures
• Interactive discussions
• Group exercises
• Multimedia presentations (Videos)
• Student-led group presentations analyzing academic articles
• Short quizzes and discussion questions on assigned readings

• Student-led group presentation (40%)
• Prepared comment on student-led group presentation (10%)
• Discussion questions on assigned readings (10%)
• Short quizzes on previous topics (20%) 
• Participation in class (20%)

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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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.

simon.sturn@wu.ac.at