Climate policy uncertainty and forest bioenergy demand: evidence from Chinese prefecture-level cities

Purpose The forest bioeconomy and the low-carbon energy transition are highly sensitive to climate policy environments. However, the effects of climate policy uncertainty (CPU) on energy systems, particularly those related to forest-based bioenergy, remain insufficiently explored. This study aims to examine how CPU influences energy consumption and to assess its implications for forest bioenergy demand within the context of China’s low-carbon transition. Design/methodology/approach This study uses panel data from 280 Chinese prefecture-level cities covering the period from 2008 to 2022. Econometric panel regression models are used to analyze the impact of CPU on both the scale and intensity of energy consumption. Mechanism analyses are conducted to examine the roles of industrial structural upgrading and technological innovation. In addition, the moderating effects of fiscal decentralization and the digital economy are empirically tested. Findings The results show that CPU significantly increases both total energy consumption and energy consumption intensity. Industrial structural upgrading induced by policy uncertainty leads to an energy rebound effect, thereby raising energy demand. In contrast, CPU also promotes technological innovation that contributes to energy conservation. Fiscal decentralization plays an important regulatory role, while the digital economy independently increases energy consumption but can weaken the adverse effects of CPU through interaction effects. Research limitations/implications This study relies on aggregate city-level energy data and does not directly observe forest bioenergy consumption. Future research could incorporate disaggregated forest bioenergy data and micro-level evidence to further explore heterogeneous effects and transmission mechanisms, particularly the energy rebound effect within the forest bioenergy sector. Originality/value This study provides novel empirical evidence on the relationship between CPU and energy consumption from the perspective of the forest bioeconomy. By integrating policy uncertainty, industrial upgrading, technological innovation and institutional factors into a unified analytical framework, the paper offers new insights into how climate governance affects forest-based energy transitions.