Shu Wang

Research Interests

    My research currently focuses on causal inference and identification in structural vector autoregressive (SVAR) models from both the frequentist and bayesian perspectives. I am also interested in other topics in time series analysis, such as integrations and co-integrations, stochastic volatilities et cetera.

Working Papers

  • Causal inference with (partially) independent shocks and structural signals on the global crude oil market (with C. Hafner and H. Herwartz) Link
  • Causality assessment in panel structural VAR models: A novel approach based on independence tests (with H. Herwartz)
  • Transmission of shocks in a unified monetary and financial framework: Homogeneity, asymmetry and structural change in the Euro area (with H. Herwartz)


  • 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, forthcoming. 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

  • 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


  • WiSe 2020/21: Applied Econometrics (Master)
  • SoSe 2021/2022: Introduction to Time Series Analysis (Master)