Prof. Dr. Christian Conrad Econometrics

Research at the Chair of Econometrics focuses on developing econometric methods for applications in macroeconomics and finance.

Specifically, the research focuses on measuring, modeling, and forecasting financial market risks, the interaction between macroeconomic developments and financial markets, and the expectation formation of professional forecasters and households. We offer introductory courses on econometrics and data science and advanced courses in macroeconometrics and financial econometrics.

News

July 2025

  • New publication: Conrad, C., Z. Enders, and G. Müller (2025). “Inflation forecast targeting revisited.” CEPR Discussion Paper No. 20467. 

    Link

June 2025

  • Christian Conrad presented the paper “The Perils of Inflation Forecast Targeting” (co-authored with Zeno Enders and Gernot Müller) at the Annual Conference of the International Association for Applied Econometrics, University of Torino, June 25-27, 2025.
  • The Chair of Econometrics is seeking to fill a Postdoc position starting in October 2025.

    Job advertisement

  • Julius Schoelkopf presented the paper "Beyond the Numbers. Professional Forecasters’ Narratives about Inflation and Stock Market Performance” (joint work with Christian Conrad, Michael Weber, and Frank Brückbauer) at the 8th Workshop on Subjective Expectations, hosted by Nova School of Business and Economics (Nova SBE), June 10, 2025.
  • The 12th HKMetrics workshop took place at the University of Mannheim on June 6, 2025.

    Program

April 2025

  • Christian Conrad presented the paper “The Perils of Inflation Forecast Targeting” (co-authored with Zeno Enders and Gernot Müller) at the Workshop on Machine Learning Economic Forecasting and Nowcasting, Copenhagen Business School, April 25, 2025.
  • Christian Conrad organized a “Macro and Financial Econometrics” workshop at the International Academic Forum Heidelberg on April 23. Eric Ghysels, University of North Carolina at Chapel Hill, delivered a keynote lecture on “Quantum and Quantum-Inspired Maximum Likelihood Estimation and Filtering of Stochastic Volatility Models.”

 

 

 

 

HKMetrics

HKMetrics ist eine gemeinsame Initiative von Prof. Dr. Christian Conrad (Universität Heidelberg), Prof Dr. Melanie Schienle (KIT) und Prof. Dr. Carsten Trenkler (Universität Mannheim) und besteht aus einem gemeinsamen Forschungsseminar in Ökonometrie und einem Doktoranden-Workshop, der einmal im Semester stattfindet. Weitere Informationen finden Sie auf der HKMetrics Website.