Dynamics of Global Supply chain Pressure Index in Responding to Information Shocks

Global supply chains exhibit dynamic responses to economic stimuli, including information shocks. This thesis investigates the impact of information shocks on the Global Supply Chain Pressure Index (GSCPI) using a Vector Autoregression (VAR) model. By leveraging Miranda Agrippino's instrumental variable time series, the study explores how information shocks influence the GSCPI, with a particular focus on demand-side dynamics. The research contributes to a deeper understanding of information shock transmission within global supply chains by elucidating the mechanisms through which they affect pressure on the GSCPI. Empirical findings are expected to reveal a significant positive relationship between information shocks and the GSCPI. Additionally, the thesis draws on relevant economic literature to examine the theoretical underpinnings supporting the link between information flows and supply chain pressures. Overall, this research offers valuable insights for policymakers and practitioners seeking to enhance supply chain resilience and responsiveness in a globally interconnected environment.