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The aim of this article is to research on forestry green total factor productivity and explore the impact of financial support on forestry green total factor productivity.

The methods used in this study are super efficiency SBM model of undesired output and empirical model. SBM model is a kind of Data Envelopment Analysis (DEA). The SBM model with non-expected outputs (slacks-based measure) can be used to deal with the problem of efficiency measurement with multiple input and output variables and can be used to analyze the efficiency of green development of forestry economy.

First, the overall green total factor productivity of the authors’ country's forestry has shown a trend of first decline and then an increase from 2008 to 2018, and there are significant spatiotemporal differences; second, financial support has a significant positive impact on forestry green total factor productivity; third, environmental regulation has a significant threshold effect in the process of financial support on forestry green total factor productivity, and the role of financial support shows a trend of first increasing and then decreasing.

Secondly, taking the data of 30 provinces and cities in the authors’ country from 2008 to 2018 as the research object, using the super-efficiency SBM-Malmquist index to measure the country's forestry green total factor productivity and analyze its temporal and spatial changes; finally, a dynamic panel model was established to explore the impact of financial support on forestry green total factors quantitative impact on productivity, and adding environmental regulation as a threshold variable to establish a dynamic threshold regression, and found that financial support has a nonlinear impact on forestry green total factor productivity.

Agricultural carbon productivity considers the dual goals of “agricultural economic growth” and “carbon emission reduction”. Improving agricultural carbon productivity is a requirement for promoting green and low-carbon development of agriculture. Agricultural production agglomeration is widespread worldwide, but the relationship between agricultural production agglomeration and agricultural carbon productivity is inconclusive. This paper aims to study the impact of agricultural production agglomeration on agricultural carbon productivity, which is conducive to a better understanding of the relationships among agglomeration, agricultural economic development and carbon emission, better planning of agricultural layout to build a modern agricultural industrial system and achieve the goal of carbon peaking and carbon neutrality.

Based on China's provincial data from 1991 to 2019, this paper uses non-radial directional distance function (NDDF) and Metafrontier Malmquist–Luenberger (MML) productivity index to measure total factor agricultural carbon productivity. Subsequently, using a panel two-way fixed effect model to study the effect and mechanism of agricultural production agglomeration on agricultural carbon productivity, and the two-stage least squares method (IV-2SLS) is used to solve endogeneity. Finally, this paper formulates a moderating effect model from the perspective of the efficiency of agricultural material capital inputs.

The empirical results identify that Chinese provincial agricultural carbon productivity has an overall growth trend and agricultural technological progress is the major source of growth. There is an inverted U-shaped relationship between agricultural production agglomeration and agricultural carbon productivity. The input efficiency of agricultural film, machine and water resources have moderating effects on the inverted U-shaped relationship. Agricultural production agglomeration also promotes agricultural carbon productivity by inhibiting agricultural carbon emissions in addition to affecting agricultural input factors and its internal mechanisms are agricultural green technology progress and rural human capital improvement.

This paper innovatively adopts the NDDF–MML method to measure the total factor agricultural carbon productivity more scientifically and accurately and solves the problems of ignoring group heterogeneity and the shortcomings of traditional productivity measurement in previous studies. This paper also explains the inverted U-shaped relationship between agricultural production agglomeration and agricultural carbon productivity theoretically and empirically. Furthermore, from the perspective of agricultural material capital input efficiency, this paper discusses the moderating effect of input efficiency of fertilizers, pesticides, agricultural film, agricultural machines and water resources on agricultural production agglomeration affecting agricultural carbon productivity and answers the mechanism of carbon emission reduction of agricultural production agglomeration.

The research objective of this paper is to investigate the direct and indirect impacts of green finance on agricultural carbon total factor productivity (ACTFP) within the framework of the carbon peaking and carbon neutrality (dual carbon) goals, while also identifying the driving factors through an exponential decomposition of ACTFP, aiming to provide policy recommendations to enhance financial support for low-carbon agricultural development.

In this paper, the Global Malmquist Luenberger (GML) Index method was employed to analyze and decompose the ACTFP, while the direct and spillover effects of China’s green finance pilot policy (GFPP) on ACTFP were assessed using the difference-in-differences (DID) method and the spatial differences-in-differences (SDID) method, respectively.

After the implementation of the GFPP, the ACTFP in the pilot area has experienced significant improvement, with the enhancement of technical efficiency serving as the main driving force. In addition, the GFPP exhibits a positive low-carbon spatial spillover effect, indicating it benefits ACTFP in both the pilot and adjacent areas.

Within the framework of the dual carbon goals, the paper highlights agriculture as a significant carbon emitter. ACTFP is assessed by considering the agricultural carbon emission factor as the sole non-desired output, and the impact of the GFPP on ACTFP is investigated through the DID method, thereby providing substantial validation of the hypotheses inferred from the mathematical model. Subsequently, the spillover effects of GFPP on ACTFP are analyzed in conjunction with the spatial econometric model.

At present, China’s forestry development is mainly driven by the traditional production factors such as forestry labor force, land resources and capital and thus the top priority of forestry development is to optimize forestry production factors. Scientific and effective forestry labor input has a significant role in promoting the development of forestry industry. Given that the actual input to forestry labor is not clear, the accuracy of the forestry industry development may be slightly affected. Based on the monitoring project of collective forest tenure reform (RCFT), this paper uses the survey data of 3,500 rural households in seven provinces of China from 2010 to 2014 and 2016 to 2017 to measure the actual labor force in China, and empirically analyzes and studies the factors influencing the development of forestry industry based on the provincial data of forestry in China, and further discusses the heterogeneous impact of forestry production factors on the development of forestry industry.

In this paper, the generalized least squares estimation model is used to calculate the actual number of forestry labor in China, and then the Cobb–Douglas production function is selected to explore the influencing factors of forestry industry development.

The results show that the actual number of forestry labor force in China continues to decline and the degree of reduction varies from different regions. The forestry labor is a major factor that promotes the development of the forestry industry, but this promotion is affected by the low matching degree between the forestry production factors and thus further inhibits the development of the forestry industry. Due to the time lag of the reform, the implementation of RCFT first weakens and then promotes the development of forestry production. Further on, the forestry labor input is heterogeneous in land resource endowment, forestry investment source and the proportion of management personnel.

Therefore, researches show that the feasible way to promote the development of forestry industry is to expand the scale of forestry labor force, optimize the mutual allocation of forestry production factors, enhance the input of human capital in forestry and deepen the RCFT.

The forest products processing industry is a key component of the forestry economy, and the level of companies’ operating efficiency directly affects its profitability and market competitiveness.

In order to deeply study the operation status of forest product processing industry, this paper takes the panel data of 70 listed forest product processing companies from 2015 to 2022 as the basis, and adopts BBC, CCR and DEA-Malmquist models to measure the operating efficiency of these companies. Meanwhile, the Tobit model is applied to deeply explore the impact of innovation input on operating efficiency.

The results of the paper show that: (1) the overall operating efficiency of listed forest product processing companies performs well, and the improvement of technology level promotes the growth of total factor productivity; (2) innovation input plays a significant positive role in listed forest product processing companies, which positively affects the operating efficiency.

A scientific and reasonable evaluation of the operating efficiency of listed forest product companies is of great practical significance to the development of the forestry industry The study of forest product processing industry is of key significance to the social economy.

This paper explores the improvement of production and operation efficiency of forest products processing enterprises for the purpose of in-depth analysis of the current situation of China's forest products processing enterprises, which is conducive to improving the innovation and operation efficiency of China's forest products processing enterprises, and realizing the high-quality development of China's forest products processing industry.

The island areas, in particular, are characterized by a more fragile ecological carrying capacity and higher value of resources and environment, which requires us to take Xi Jinping's green ecological development view as the theoretical basis and adhere to the high-quality development path of gradual development and ecological environment priority. Taking Shengsi and Daishan counties as examples, on the basis of their high-quality development evaluation and identification of the main influencing factors, this study explores the specific path of Xi Jinping's ecological development view in the high-quality development of typical island counties in China.

This paper applies the interpretative structural model to construct an evaluation index system for the high-quality development of the island. In determining the factor weights of the index layer, the AHP hierarchical analysis method was combined with the Delphi method to increase the objectivity of the assignment process as much as possible. This study used the technique for order of preference by similarity to ideal solution to calculate island high quality development index. To measure the main obstacle factors, the index factor contribution rate, the index factor deviation, and the index factor obstacle degree were applied in this research.

As China intensifies its maritime strategy, the sustainability of coastal and island regions is critical, particularly given their fragile ecosystems and high resource value. Our study reveals a declining trend in the high-quality development index for Shengsi, peaking at 0.4262 in 2010 and dropping to 0.3261 in 2012. To reverse this, it's essential to align with President Xi Jinping's green ecological development framework and commit to a high-quality development pathway.

The connotation and extension of Xi Jinping's view of ecological development should be continuously studied in depth and enriched, with green development as the core idea to guide the correct direction of the high-quality development of the island. In this paper, it is suggested that researchers are supposed to focus on these problems, such as the changes of sea water quality, the reduction of urban greening, the continuous negative growth of population in island areas, the decline of forestry added value and air quality protection, so as to ensure the sustainable high-quality development of example islands.

This paper aims to analyze the spatiotemporal heterogeneity of regional total factor productivity (TFP) growth and explores how haze pollution and different levels of new-type urbanization affect China’s economic growth.

This paper constructs an index for evaluating the TFP growth of China’s 31 provinces by integrating slack-based measures and the Global Malmquist (GM) productivity index. Meanwhile, the panel threshold estimation method is used to examine the complex relationships among haze pollution, new-type urbanization and TFP growth.

The results reflect conspicuous spatiotemporal heterogeneity in TFP growth in China. Interestingly, the influence of haze pollution on TFP growth is limited by the “critical mass” of new-type urbanization in China. When new-type urbanization does not cross the first threshold, haze pollution has a negative but non-significant effect on TFP growth. When new-type urbanization crosses the first threshold but not the second, haze pollution has a significant positive impact on TFP growth. When new-type urbanization crosses the second threshold, haze pollution significantly and positively affects TFP growth with the strongest positive effect.

This study innovates by combining haze pollution and TFP growth and proposing an integrated framework from the perspective of new-type urbanization, providing insight into how different degrees of new-type urbanization impact the mechanism between haze pollution and TFP growth. Using panel data in China and emphasizing green development, a sustainable economy and new-type urbanization, this study contributes to the current studies on haze pollution and economic development based on developed countries.

The purpose of this paper is to analyze the influence of different factors on forestry production, with an aim to explore the degree of connection between forestry economic growth and influencing factors such as forestry investment, labor input, afforestation area, scientific and technologies progress, and the reform of property-rights regimes.

According to the data of China Forestry Statistical Yearbook from 1978 to 2017, this paper uses the grey correlation analysis to observe and analyze the factors influencing China’s forestry economics growth.

The results show that capital investment demonstrates the largest impact on the forestry output value, followed by property system, afforestation area, labor input and technologies progress. The correlation coefficients of the above factors are 0.874451654,0.85827468,0.835138412,0.832985604 and 0.825747493. This means that forestry capital investment plays a major role in contributing to forest economic growth; forest property system also plays a positive role in the growth of forestry economy.

This paper uses continuous data collected during 1978‒2017, which are quite extensive as compared to data used in the existing research, considering the influencing factors are comprehensive, especially the impact of property right system reform on forestry economic growth.

The purpose of this study is to examine the spatial fluctuation spillover effect of green total factor productivity (GTFP) under the influence of Internet development.

Using panel data from 283 cities in China for the period 2003–2016, this paper explores the spatial fluctuation spillover effect of internet development on GTFP by applying the spatial autoregressive with autoregressive conditional heteroscedasticity model (SARspARCH).

The results of Moran's I test of the residual term and the Bayesian information criterion (BIC) value indicate that the GTFP has a spatial fluctuation spillover effect, and the estimated results of the SARspARCH model are more accurate than the spatial autoregressive (SAR) model and the spatial autoregressive conditional heteroscedasticity (spARCH) model. Specifically, the internet development had a positive spatial fluctuation spillover effect on GTFP in 2003, 2011, 2012 and 2014, and the volatility spillover effect weakens the positive spillover effect of internet development on GTFP. Moreover, Internet development has a significant positive spatial fluctuation spillover effect on GTFP averagely in eastern China and internet-based cities.

The results of this study provide digital solutions for policymakers in improving the level of GTFP in China, with more emphasis on regional synergistic governance to ensure growth.

This paper expands the research ideas for spatial econometric models and provides a more valuable reference for China to achieve green development.

This research aims to examine the moderating role of green chief executive officer (CEO) in the effect of managerial ability (MA) on environmental performance (ENV).

This research’s sample consists of 197 manufacturing firm-years that are listed on the Indonesian Stock Exchange and the Program Penilaian Peringkat Kinerja Perusahaan Dalam Pengelolaan Lingkungan Hidup (PROPER) participants. Data analysis use industry- and year-effect regression analysis.

The result shows that MA improves ENV when led by a green CEO. It indicates that a green CEO with higher MA considers environmental responsibilities as a valuable investment to create business competitive advantages and sustainability.

First, this research only uses the PROPER participants as the research sample. Second, by nature, MA measurement errors might still exist because it is hard to determine the MA with qualitative factors. Third, this research does not split the environmental responsibilities into a wider spectrum, such as environmental–business, environmental–regulation or environmental–ethical spectrum.

This research provides new evidence that higher MA by green CEO increases ENV in Indonesia. This research also gives a contribution to fill the inconsistent previous findings of MA and ENV.