Katja Heinisch

Katja Heinisch serves as Head of the Research Group "Econometric Tools for Macroeconomic Forecasting and Simulation" at the Halle Institute for Economic Research (IWH) since January 2013, and has been a member of the Department of Macroeconomics since September 2009. Her work focuses on developing advanced econometric methodologies for economic forecasting with practical applications for policymakers.

Dr. Heinisch earned her diploma from Chemnitz University of Technology and University of Strasbourg, followed by a PhD from Osnabrück University. Her international research experience includes significant positions at the European Central Bank (ECB) and the International Monetary Fund (IMF), which have shaped her expertise in macroeconomic analysis across different institutional contexts.

Her research program centers on international macroeconomics, applied time series econometrics, short-term forecasting, and macroeconometric modeling. A distinctive feature of her work is the rigorous evaluation of forecast accuracy, with particular attention to how assumption errors affect prediction quality. She has developed expertise in advanced statistical techniques including partial linear instrumental variable models and double machine learning approaches to address methodological challenges in forecast evaluation.

Analysis of her recent publications reveals a consistent focus on improving forecasting techniques for the German economy and the European Union. Her work demonstrates sophisticated methodological approaches while maintaining strong policy relevance, particularly in evaluating EU Commission GDP forecasts and developing tools like the IWH forecasting dashboard. Her research on economic sentiment analysis has provided novel methods for disentangling private information from public knowledge in survey data, enhancing the utility of consumer surveys for economic forecasting.

• Developed advanced methods for forecast evaluation using machine learning techniques
• Created tools for real-time economic analysis and forecast comparison
• Contributed significantly to understanding the relationship between assumption errors and forecast accuracy
• Advanced methodologies for economic sentiment analysis in forecasting contexts

Dr. Heinisch's leadership of her research group at IWH positions her at the forefront of methodological innovation in economic forecasting, with her work bridging theoretical econometrics and practical policy applications.