Chairs of Statistics and Econometrics

Shu Wang

Research Interests

    I completed my dissertation in May 2023, focusing on modern methods for causal identification and statistical inference in structural vector autoregressions. Since June 2023, I have been a Postdoctoral Associate at the Chair of Econometrics. My study centers on the identification of structural dynamic simultaneous equations models, with a particular emphasis on developing econometric methods to investigate the transmission mechanisms of structural shocks in multivariate dynamic systems, as well as exploring the complex causal relationships among the observed variables within these systems. My broader research interests include various aspects of time series analysis, such as time-varying volatilities, time-varying parameters, and the study of integration and cointegration processes.

Working Papers

  • Markov-switching multivariate GARCH model with copula-distributed innovations (with M. Fülle, H. Herwartz) Link
  • Identification of independent shocks under (co-)heteroskedasticity (with H. Herwartz) Link
  • Transmission of shocks in a unified monetary and financial framework: Homogeneity, asymmetry and structural change in the Euro area (with H. Herwartz)

Publications

  • Hafner, C., Herwartz, H. and S. Wang (2024): Statistical identification of independent shocks with kernel-based maximum likelihood estimation and an application to the global crude oil market, Journal of Business & Economic Statistics, forthcoming. Link
  • Herwartz, H. and S. Wang (2024): Statistical identification in panel structural vector autoregressive models based on independence criteria, Journal of Applied Econometrics, 39(4), 620–639. Link
  • Herwartz, H., Theilen, B. and S. Wang (2024): Unraveling the structural sources of oil production and their impact on CO2 emissions, Energy Economics, 132, 107488. Link
  • Herwartz, H. and S. Wang (2023): Point estimation in sign-restricted SVARs based on independence criteria with an application to rational bubbles, Journal of Economic Dynamics and Control, 151, 104630. Link
  • Herwartz, H., H. Rohloff, and S. Wang (2022): Proxy SVAR identification of monetary policy shocks - Monte Carlo evidence and insights for the US, Journal of Economic Dynamics and Control, 139, 104457. Link

Work in Progress

  • Transmission of uncertainty
  • Identification of independent shocks with unstable volatility
  • Robust methods for blind source separation
  • Monetary policy transmission in economies with heterogeneous households
  • Time-varying Taylor rule

Teaching

  • Spring/Fall 2024 : Introduction to Statistical Methods in Economic Sciences (Graduate, Lecture) Lecture Notes
  • Fall 2023/2024: Multivariate Time Series Analysis (Graduate, Lecture)
  • Spring 2021/2022/2023: Introduction to Time Series Analysis (Graduate, Exercise)
  • Fall 2020: Applied Econometrics (Graduate, Exercise)