December 11-12, 2026: T H E Workshop 2026 at the University of Hohenheim.
Inheritances and the Structure of the Wealth Distribution in Germany.
Jan Simon Wiemann [IAW]
Understanding the Formation of Social Policy Preferences: Evidence from a Factorial Survey on Pension and Unemployment Reforms.
Dr. Natalie Herdegen [IAW]
Representing Employment Histories.
Dr. Philipp Kugler [IAW]
Complementarities Between Import and Export Activities: Firm-Level Evidence for Goods and Services.
Matthias Fauth [IAW]
October 7, 2026: Lecture at the “Denkraum” of the Federal Ministry of Housing, Urban Development, and Construction (BMWSB) - online.
Is Large-Scale Labor Mobility a Challenge for Civil Protection? (in German)
Dr. Andreas Koch [IAW]
September 25, 2026: Statistics Conference of the German Federal Pension Insurance Fund, Erkner.
Predicting employment trajectories and retirement dates using machine learning – initial findings and applications (in German).
Dr. Martin Kroczek [IAW]
September 20, 2026: Deißlingen Community Trade Show (Rottweil District).
Succession Planning. Current Situation and Local Stories (in German).
Marcel Reiner [IAW]
September 14, 2026: German Center for Aging Research (DZA) in Berlin.
Modeling Employment Histories Using Machine Learning Methods (in German).
Dr. Natalie Herdegen [IAW]
July 15, 2026: 20th SGB II Forum – “Networking. Making an Impact. Thinking Ahead,” conference of the job centers in Baden-Württemberg, Eislingen.
Facilitator of the workshop ‘Binding, measurable and effective: embedding equality in the SGB II target-based management system’ (in German).
Andrea Kirchmann and Christin Schafstädt [IAW]
Juli 3rd, 2026: “Fridays at 10:30” series by the Federal Institute for Occupational Safety and Health (BAuA).
What Do We Know About the Costs and Benefits of Prevention in Occupational Safety and Health? An International Literature Review of the Evidence (in German).
Dr. Andreas Koch [IAW]
June 18, 2026: Annual conference of the Pension Insurance Research Data Centre in Berlin.
Predicting employment trajectories and retirement dates using machine learning (in German).
Dr Natalie Herdegen [IAW]
