The rapid growth of computing demand poses a material challenge to climate policy, making the productivity effects of green digital infrastructure an urgent empirical question. This study estimates whether China’s National Green Data Center Pilot Program, a policy bundling energy efficiency mandates with renewable energy procurement at the infrastructure layer, generates measurable firm-level effects on digital transformation and total factor productivity (TFP). This study treats the staggered rollout of the program across cities as a quasi-natural experiment and estimates its effect on listed firms using a two-way fixed effects difference-in-differences design over 2016 to 2023, complemented by event study analysis, placebo tests, instrumental variable diagnostics, heterogeneity robust estimators for staggered adoption, and mechanism and moderation analyses. The central finding is that pilot designation significantly accelerates firm-level digital transformation, measured by textual indicators of data value mining capability ($p<0.01$), which remains significant across specifications. Complementary evidence points to a modest positive effect on TFP, with an estimated increase of approximately 2.0 percent under the preferred city-level clustered specification, interpreted as suggestive evidence rather than the sole basis for inference. Exploratory mediation decomposition under the strong assumption of sequential ignorability indicates that digital transformation accounts for approximately 23.5 percent of the total effect, though this estimate should be treated as indicative rather than definitive. Mechanism-consistent analysis finds a marginally significant positive association with corporate ESG performance ($p<0.10$), while the association with green technology innovation is directionally positive but not statistically distinguishable from zero. Moderating effect analysis reveals that financing constraints and leverage significantly attenuate the productivity dividend, while public environmental concern provides a marginally significant amplifying effect ($p<0.10$). These results position green data center policy primarily as an upstream enabler of digital transformation that can generate productivity benefits when firms possess sufficient complementary investment capacity.

Converting the diverse values of forest ecosystems into economic gains is one of the major challenges in advancing the global sustainable development agenda. As China continues to expand its factor inputs in the forestry sector, the question of whether these large-scale inputs into forest ecosystems have generated commensurate economic returns constitutes the central concern of this study. To address this question, this study proposes the concept of forest ecological product value conversion efficiency (FCE). Using provincial panel data from 30 Chinese provinces spanning 2011 to 2023, this study measures FCE and examines its spatiotemporal distribution and evolution characteristics. The findings are as follows. (1) China’s FCE exhibited a fluctuating upward trend, yet scale diseconomies have persisted, indicating that simply expanding factor inputs can no longer sustainably drive FCE gains. (2) Spatially, the economically advanced yet forest-resource-scarce eastern region exhibits the highest FCE, whereas the forest-resource-rich yet economically lagging northeastern region ranks the lowest. This pattern indicates that FCE is not primarily driven by the abundance of forest resources, but rather by the capacity to allocate and convert production factors. (3) A significant catch-up effect among FCE-lagging regions, yet this catch-up potential is contingent on the transferability of successful experiences. When FCE gains in leading regions rely heavily on location-specific resources or exclusive policy support, such experiences tend to resist diffusion, thereby constraining technology transfer and FCE convergence within the region. In summary, this study provides a FCE assessment framework for developing countries facing the dual pressures of forest resource conservation and economic development, and offers empirical evidence for shifting from an input-reliant growth model to a model that prioritizes resource efficiency in the forestry sector.

Against the backdrop of global forest degradation and timber supply constraints, improving green production efficiency in forestry while securing timber supply is an important challenge for sustainable forest management. Treating China’s National Reserve Forest Policy (NRFP) as a quasi-natural experiment, this study uses panel data for 114 prefecture-level cities from 2011 to 2022, including 67 treated and 47 control cities. We employ a staggered difference-in-differences estimator based on group-time average treatment effects, together with transmission-channel analysis, difference-in-difference-in-differences (DDD), and a spatial difference-in-differences–spatial Durbin model (Spatial DID-SDM). The baseline estimates yield an overall ATT of 0.0149, indicating an average increase of 0.0149 index points in forestry GTFP for treated cities relative to the estimated counterfactual without the NRFP. This effect is approximately 1.49% of the sample mean of forestry GTFP (0.998) and remains stable across multiple robustness and sensitivity checks. NRFP implementation is separately associated with increases in capital deepening (CD) and physical labor productivity (PLP), while the lagged values of CD and PLP are each positively associated with forestry GTFP; these results are consistent with CD and PLP as potential transmission channels. The estimated NRFP effect is significantly weaker in resource-based cities and significantly stronger in economy-efficiency-oriented regions. Spatial effect decomposition shows that both the direct and indirect effects of the NRFP are positive and statistically significant. Under the alternative spatial weight matrix, both effects retain their direction and statistical significance, while the magnitude of the indirect effect remains broadly stable, suggesting that the positive spatial spillover effect of the NRFP on forestry GTFP is reasonably robust to the spatial weight matrix specification. These findings provide city-level empirical evidence for evaluating NRFP performance and informing differentiated policy design.