Measurement of total factor productivity of green agriculture in China: Analysis of the regional differences based on China

The impact of data factor-driven industry on the green total factor productivity: evidence from the China

Data factors have become an essential factor of production in today's digital era, and provided renewed energy for China's green and high-quality development. This study analyses the impact of data factor-driven industries on green total factor productivity (GTFP) and the underlying mechanisms using panel data of 277 Chinese cities from 2008 to 2020. The results show that: First, the urban data factor-driven industry can enhance GTFP. Second, the data factor-driven industry can increase the input-output ratio and enhance GTFP by promoting AI technological innovation and AI technological entrepreneurship. Third, the heterogeneity analysis show that in regions with high levels of digital technological innovation, the market size of data factor-driven industries is larger and the effect of data factor-driven industries in enhancing GTFP is more significant. And in regions with low levels of savings, the data factor-driven industry has limited capital availability and is more efficient in using capital, which has a stronger effect on GTFP enhancement. This study provides valuable empirical evidence on the relationship between data factor-driven industries and urban GTFP, and important policy implications for fully leveraging the green economic effects of data factors, and promoting green and high-quality urban development.

Synergistic study of the green efficiency and economic resilience of agriculture from a sustainable development perspective: evidence from Northeast China

Under the scenario of the complex external environment and internal structural changes in agricultural development, exploring the synergistic relationship between agricultural green efficiency (AGE) and agricultural economic resilience (AER) can offer a new path for fostering sustainable regional agricultural development. This paper fills the research gap in the interaction between efficiency and resilience in agriculture. We explore the synergistic mechanism of the two based on the perspective of sustainable development, providing a reference for constructing a synergistic theoretical system of AGE and AER. Moreover, we apply the Haken model to the field of the agricultural economy and scientifically evaluate the level of AGE and AER synergy in Northeast China from 2010 to 2020. Finally, we analyze the influencing factors of AGE and AER synergy in Northeast China from three dimensions: economic, social, and natural. The results show that AER is dominant in the AGE-AER synergistic system. The synergy level of AGE and AER in Northeast China is mainly in the higher and advanced synergy stages, with obvious spatio-temporal differences and insufficient inter-regional radiation effects. Social factors are the main factors of spatial differentiation of AGE and AER synergy.

Does farmland inflow improve the green total factor productivity of farmers in China? An empirical analysis based on a propensity score matching method

Promoting the "double security" of agricultural economy and ecology is the key to the agricultural modernization strategy, and the large-scale development of agriculture is an essential way for modern agriculture. Based on the micro-survey of 697 corn growers from August to September 2020 in China, the super-efficiency SBM model was used to calculate farmers' green total factor productivity. We further used the propensity score matching method to identify the impact of farmland inflow on farmers' green total factor productivity and dissect the internal mechanism. The study found that: firstly, compared with the non-inflowed households, the green total factor productivity of the inflowed households increased by 14.66%; secondly, farmland inflow can significantly improve farmers' green total factor productivity through the marginal output leveling effect, transaction benefit effect, and technology adoption effect; thirdly, the influence of farmland inflow on the green total factor productivity of farmers has heterogeneity in age, identity, and geographical location. Therefore, governments should establish a differentiated farmland inflow mechanism according to local conditions, enhance factor mobility and soil fertility monitoring capabilities, and drive a "win-win" between economic development and ecological protection.

How Does Agricultural Mechanization Service Affect Agricultural Green Transformation in China?

Agricultural mechanization service (AMS) is a critical path to achieving agricultural green transformation with smallholders as the mainstay of agricultural production. Based on the panel data of 30 Chinese provinces from 2011 to 2020, this paper measures the AGTFP using the Super-SBM model and examines the effects of different AMS supply agents on AGTFP and spatial spillover effects through the spatial Durbin model. The main conclusions are as follows: First, China's AGTFP showed a stable growth trend, with the mean value increasing from 0.1990 in 2011 to 0.5590 in 2020. Second, the specialization (SPO) and large-scale (LSO) of AMS supply organizations have significantly positive effect on the AGTFP of the local province. However, SPO has a significantly positive effect on the AGTFP of the neighboring provinces, while LSO has the opposite effect. Third, the specialization of AMS supply individuals (SPI) has significantly negative effect on the AGTFP of the local province. In contrast, the large-scale AMS supply individuals (LSI) has the opposite effect. Furthermore, the spatial spillover effects of both are insignificant. Fourth, the spatial spillover effect of AGTFP shows asymmetry among different regions and indicates that AMS resources flow from non-main grain production and economically developed regions to main grain production and less developed regions. These findings provide helpful policy references for constructing and improving the agricultural mechanization service system and realizing the agricultural green transformation in economies as the mainstay of agricultural production.

Spatial-temporal evolution and convergence analysis of agricultural green total factor productivity-evidence from the Yangtze River Delta Region of China

Measuring regional differences in agricultural green total factor productivity (AGTFP) provides a basis for policy guidance on agricultural green development in the Yangtze River Delta (YRD) region. By constructing a two-period Malmquist-Luenberger index under the carbon emission constraint, we measure the AGTFP of cities in the YRD region from 2001 to 2019. Furthermore, adopting the Moran index method and the hot spot analysis method, this paper analyzes the global spatial correlation and local spatial correlation of AGTFP in this region. Moreover, we investigate its spatial convergence. The results show that the AGTFP of 41 cities in the YRD region is on an increasing trend; the growth of AGTFP in the eastern cities is mainly driven by green technical efficiency, while this growth in the southern cities is mainly stimulated by green technical efficiency and green technological progress. We also find a significant spatial correlation between cities' AGTFP in the YRD region from 2001 to 2019, but with certain fluctuations, showing a U-shaped trend of "strong-weak-strong". In addition, absolute β convergence of the AGTFP exists in the YRD region, and this convergence speed is accelerated with the addition of spatial factors. This evidence provides support for implementing the regional integration development strategy and optimizing the regional agricultural spatial layout. Our findings offer implications for promoting the transfer of green agricultural technology to the southwest of the YRD region, strengthening the construction of agricultural economic belts and agricultural economic circles, and improving the efficiency of agricultural resource use.

Does Agricultural Credit Input Promote Agricultural Green Total Factor Productivity? Evidence from Spatial Panel Data of 30 Provinces in China

Improving agricultural green total factor productivity is crucial to promoting high-quality agricultural development. This paper selects the panel data of 30 provinces in China from 2009 to 2020 and uses the super-efficiency SBM model with undesirable outputs to measure the agricultural green total factor productivity of all regions in China. On this basis, this paper uses the panel data fixed-effect model and spatial Durbin model to empirically discuss the impact of agricultural credit input on agricultural green total factor productivity and its spatial spillover effect. The main conclusions are as follows: First, from 2009 to 2020, the average values of agricultural green total factor productivity in national, eastern, central, and western regions are 0.8909, 0.9977, 0.9231, and 0.8068, respectively, and the agricultural green total factor productivity needs to be further improved. Second, the agricultural green total factor productivity presents a significant and positive spatial correlation, and the spatial distribution of agricultural green total factor productivity is not random and irregular. Third, agricultural credit input can significantly promote agricultural green total factor productivity in the local region, but it hinders the improvement of agricultural green total factor productivity in the adjacent regions. Fourth, the impact of agricultural credit input on the agricultural green total factor productivity and its spillover effect has a significant regional heterogeneity. This paper believes that paying attention to the spatial spillover effect of agricultural total factor productivity, optimizing the structure and scale of agricultural credit input, and formulating reasonable agricultural credit policies can improve agricultural green total factor productivity.

Does Cleaner Household Energy Promote Agricultural Green Production? Evidence from China

Cleaner household energy for agricultural green production can significantly alleviate energy poverty and food security, thus contributing to global sustainable development. Using survey micro-data collected from Sichuan Province, the ordered probit model, OLS model, and instrumental variables approach were applied for empirical analysis. The results show that: (1) cleaner household energy significantly enhances farmer's agricultural green production awareness and improves agricultural green production levels, which is still significant after treating endogenous issues with the conditional mixing process estimation method and 2SLS model; (2) health plays a partially mediating effect of cleaner household energy on agricultural green production awareness and agricultural green production levels; (3) environmental protection awareness and digital literacy have a moderating effect and reinforce the positive impact of cleaner household energy on agricultural green production awareness and agricultural green production levels. This research suggests that governments can enhance the impact of cleaner household energy on agricultural green production through price and subsidy mechanisms.

Indicators for Evaluating High-Quality Agricultural Development: Empirical Study from Yangtze River Economic Belt, China

Agriculture is the foundation of the national economy, and achieving high-quality agricultural development is an important support for strong economic development in the post-pandemic era. Based on the new development philosophy of the Chinese government, this study constructs an evaluation framework of "innovation-coordination-green-openness-sharing" for high-quality agricultural development, and quantitatively assesses the level of high-quality agricultural development in China's Yangtze River Economic Belt with a systematic integration model, and explores the spatial evolution characteristics and obstacles of the level of high-quality agricultural development in Yangtze River Economic Belt. It reveals that the level of high-quality agricultural development in the Yangtze River Economic Belt shows a fluctuating upward trend in general, but there is variability among regions. The green dimension has the fastest development rate, followed by innovation and sharing. In terms of spatial characteristics, it gradually shows a pattern dominated by high levels and shows the characteristics of agglomeration, but the spatial correlation is not high. In terms of obstacle factors, openness and coordination are the main obstacle factors. Considering the different agricultural development models, it is suggested that international cooperation, new agricultural cooperation, and differentiated policies can be considered to promote high-quality agricultural development. This study provides a more complete evaluation framework for government policy-making authorities to measure the level of regional agricultural development and help regional agriculture achieve sustainable development at a higher quality level.

Agricultural Services: Another Way of Farmland Utilization and Its Effect on Agricultural Green Total Factor Productivity in China

Improving agricultural green total factor productivity (AGTFP) is an important aspect of sustainable agricultural development. Agricultural services, a new way of farmland utilization in agricultural production, solved the problem of ‘who and how to farm’ in the context of labor off-farm migration. The literature has analyzed different factors that affect AGTFP, but there is a relative dearth of research into agricultural services and AGTFP. Therefore, based on the panel data of 31 provinces from 2011 to 2020, this study firstly measured carbon emissions in agricultural production and then took it as an unexpected output to measure the AGTFP by using the global Malmquist–Luenberger (GML) productivity index. Finally, the effect of agricultural services on AGTFP and its decomposition were empirically verified. The main findings are as follows: (1) Between 2011 and 2020, agricultural carbon emissions increased from 85.63 million tons to 90.99 million tons in the first five years and decreased gradually to 78.64 million tons in 2020; the government policy significantly affects carbon emissions reduction. (2) AGTFP has been increasing for the past decade, and the average growth rate of AGTFP reached 1.016, and agricultural services promoted AGTFP growth significantly, in which technological progress was the crucial driving factor. (3) Taking the Heihe–Tengchong line as the demarcation, the improving effect of agricultural services on AGTFP in the eastern region is better than the western region.