Dr. Anna Damm

Assistant Professor

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Biography

Anna Piil Damm is a research fellow at TrygFonden’s Centre for Child Research at Aarhus University and an external research fellow at CReAM, IZA, GLO, and the Rockwool Foundation Research Unit. Her research focuses on the role of social networks and local public resources in influencing individual outcomes for the integration of immigrants in the host country. Utilizing quasi-experimental methods, she aims to establish cause-and-effect relationships. Anna has published articles in top journals including the American Economic Review and Review of Economic Studies. In addition to her research, Anna teaches courses that provide students with a strong theoretical and empirical foundation in economic analysis, covering real estate markets and the public regulations that affect them. She is responsible for both a graduate course on Housing Economics Policy and an undergraduate course in Real Estate Economics. Furthermore, Anna actively supervises students at multiple levels, including PhD candidates, on topics related to Urban Economics, Migration, Education Economics, and Labour Economics.

Research Interests

Experience

Research Fellow

2015-09-01 — Present

Aarhus University • Aarhus, Denmark

Conducting research on social networks and immigrant integration, focusing on economic factors.

Lecturer

2010-09-01 — Present

Aarhus University • Aarhus, Denmark

Teaching courses in Housing Economics Policy and Real Estate Economics.

Requirements for Aarhus University

Master Program
Requirements
GPA Requirement
Required:3
IELTS
Overall
Required:6.5
TOEFL
Total
Required:83
Prerequisites
Bachelor's degree in a relevant field Specific credit requirements in programming, algorithms, and computer systems
Application Checklist
  • Official Bachelor's degree certificate
  • Official transcripts of records
  • Course descriptions
  • Curriculum Vitae (CV)
  • Documentation of English language proficiency
Specialization Notes

Department of Computer Science offers tracks in Software Efficiency, Cryptography, and Data Science.