Time-varying effects of policy uncertainty on supply chain market connectivity in Chinese photovoltaic industry

Abstract

The transition to renewable energy is essential to address global environmental challenges. Central to this shift, the photovoltaic (PV) industry is vital for achieving low-carbon goals. Supported by government policies, China’s PV sector has led the world in newly installed capacity for a decade. However, the impact of policy uncertainty on the interconnected dynamics of the PV supply chain remains underexplored. This study uses a Time-Varying Parameter Vector Autoregression (TVP-VAR) model and Granger causality tests to analyze dynamic price dependencies within the Chinese PV supply chain. The results reveal midstream markets as net shock receivers, while upstream markets act as primary transmitters. Economic and trade policy uncertainties significantly and asymmetrically influence market connectivity, with economic policy uncertainty having a stronger impact. These findings highlight the critical role of policy frameworks in shaping supply chain dynamics and resilience. By offering a nuanced understanding of price interdependencies and temporal variations in spillovers, this research provides actionable insights for policymakers and stakeholders. It supports strategic decision-making to promote sustainable development and investment in China’s PV sector while addressing the challenges posed by policy-induced risks.