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)

Publications

• 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

Teaching

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