Purpose: Timber export is an important economic development pillar in Ghana, which has a direct effect on Ghana’s domestic forestry industry development, local communities’ income and sustainable forest management and deforestation. China, as the Ghana’s largest timber export destination, brought significant impacts on Ghana’s timber export. However, there is a lack of quantitative analyses on impact factors of timber trade between the two countries in the past, which this paper sought to do.Design/methodology/approach: The authors first collected Ghana’s timber exports to China from 1997 to 2017, and then based on the literature review and trade theories, the authors set up a least squares estimate (LSE)-based multiple linear regression (MLR) model to analyse the specific impact factors. In addition, multi-collinearity, autocorrelation and heteroscedasticity issues of the impact factors were checked to guarantee the accuracy of the results.Findings: The results showed China timber import volume, Ghana cedi (GHC)/US$ exchange rate, Ghana’s gross domestic product (GDP) and China timber consumption volume in construction sector had positive impacts; Ghana timber production volume and Ghana average timber export price had negative impacts. The results confirmed that China’s timber consumption had a positive linkage with Ghana’s timber export. The article also reviewed possible impacts caused by change in timber trade policies, which proved important but was hardly directly quantified. The authors pointed out the importance of optimizing these impact factors to make sure Ghana’s timber export to China went on the sustainable track.Originality/value: There is no literature about timber trade and its impact factors between Ghana and China, which used econometric models. This paper provided new perspectives on the impact factors in timber trade between the two countries.

In this paper, the daily data of SSE 50 stock index futures and SSE 50 index in the past two years from April 16, 2015 to March 16, 2017 are selected as the research object to study the lead relationship between SSE 50 stock index futures and corresponding stock spot price with the methods of co-integration test, Granger causality test, impulse response and variance decomposition etc. The results show that SSE 50 stock index future has a one-way effect on SSE 50 index, and SSE 50 stock index future has reflected the price discovery function.

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.