Asymmetric tail risk contagion across China’s automotive industrial chain: a study based on input–output network

Abstract

The input-output network of an industrial chain provides a channel for risk transmission. Using Smooth-Transition Vector Autoregression model (STVAR) and Diebold-Yilmaz directional connectedness measures, we explore tail risk (extreme risk) contagion across China’s automotive industrial chain. We find significant spillover effects that are asymmetric in different phases of China’s business cycle, monetary cycle, and policy uncertainty. When China’s economy is in a recession, under a monetary expansion, or at a high level of policy uncertainty, the total risk spillover across the chain is higher. We also find apparent risk spillover from the financial services industries to the automotive industrial chain as China’s economy is in a recession or a monetary expansion period. Still, a reverse spillover is found as policy uncertainty is at a high level. Meanwhile, the direction of risk propagation across the automotive industrial chain may change with the transition in the economic state or policy uncertainty state.