Search Results (38)

The main purpose of this study is to understand the potential determinants of sustainable field crop farm productivity. This paper considers a multi-input, multi-output production technology to estimate the effects of aridity on farm-level productivity using a stochastic input distance function. By isolating the respective weather components of agricultural total factor productivity (TFP), we can better assess the impact on productivity of adopting various technologies and farm practices that might otherwise be masked by changing climate conditions or weather shocks. We make use of data from Phase 3 of the United States Department of Agriculture (USDA) Agricultural Resource Management Survey (ARMS) between 2006 and 2020. We supplement this estimation using field crop farm productivity determinants, including technology adoption and farm practice variables derived from the ARMS Phase 2 data. We identify several factors that affect farm productivity, including many practices that help farmers make more sustainable use of natural resources. The results show that adopting yield monitoring technology, fallowing in previous years, adding or improving tile drainage, and contour farming each improved farm productivity. In particular, during our study period, conservation tillage increased by over 300% across states on average. It is estimated to increase productivity level by approximately 3% for those adopting this practice. Critically, accounting for local weather effects increased the estimated productivity of nearly all farm practices and increased the statistical significance of several variables, indicating that other TFP studies that did not account for climate or weather effects may have underestimated the technical efficiency of farms that adopted these conservation practices. However, the results also show the impacts can be heterogeneous, with effects varying between farms located in the U.S. northern or southern regions. Full article

As the primary force driving the sustainable development of the rural economy, the improvement of the total factor productivity (TFP) of agricultural enterprises (AEs) is of great strategic significance. This study innovatively zeroes in on AEs, leveraging micro-level data from agricultural listed companies in China’s A-share market spanning from 2007 to 2023. It aims to investigate the impact of supply chain finance (SCF) on the TFP of these enterprises and elucidate the underlying mechanisms. Uniquely, this study incorporates enterprise digital transformation and innovation capability as moderating variables into the mechanism analysis framework. Furthermore, it examines the heterogeneous effects across different characteristics of AEs. The findings reveal that SCF significantly boosts the TFP of AEs. Specifically, a one-standard-deviation increase in the level of SCF is associated with a 0.2658% increase in TFP relative to the mean. This conclusion holds robustly across various tests. Moreover, the interaction terms of SCF with both enterprise digital transformation and innovation capability are significantly positive. This indicates that greater digital transformation and stronger innovation capability amplify the positive effect of SCF on TFP. The heterogeneous analysis further indicates that for AEs with highly optimized human capital, higher financing constraints, and more efficient credit resource allocation, the positive impact of SCF on TFP is particularly pronounced. Full article

Land, as the foundation of all productive activities, plays a crucial role in achieving high-quality development across regions. China’s current land allocation model, which focuses on land quota distribution, has several drawbacks and does not address the conflict between limited land availability and increasing demand. To maximize land use benefits, it is essential to develop scientifically sound allocation plans that effectively adjust land structure and layout. However, existing research often relies on single-attribute geographic or linear programming models which do not meet the multidimensional needs of modern territorial planning. Additionally, commonly used CGE models often overlook the critical role of construction land. To address these gaps, this study introduces a multi-scale, multi-type China Territorial Spatial Planning Simulation Model (CTSPM). This model integrates cultivated, forest, grassland, and construction land, simulating the land use changes driven by socioeconomic impacts through price mechanisms. By employing a land use transition matrix, the CTSPM enhances practical applicability and improves predictions for residential and non-agricultural construction land. It provides a scientific tool for evaluating land policies, supporting interdepartmental negotiations on land quotas, and contributing to natural resource governance and territorial spatial planning. Using the CTSPM, we simulated various high-quality development scenarios and derived the following conclusions: (1) An increase in Total Factor Productivity (TFP) significantly boosts regional economic development and the demand for non-agricultural land; a 1% increase in TFP leads to a 1.48% rise in actual GDP and a 0.19% increase in total non-agricultural land demand. (2) At the regional level, eastern regions experience a greater impact on total land demand compared to central and western regions. (3) In terms of land use types, cultivated and grassland areas show a decreasing trend, while forest and construction land areas are increasing. Full article

After the merger of China’s Ministry of Culture and the National Tourism Administration into the Ministry of Culture and Tourism in 2018, there was a strong push to advance the strategy of culture–tourism integration, which has shown significant effects on the economy and society. Building on this success, the Chinese government proposed the strategy of agriculture–culture–tourism integration in 2023. However, its impact on the agricultural sector remains unclear. This study employs field theory to explain the impact of culture–tourism integration on the agricultural sector. Drawing from the relevant literature, we construct and statistically analyze the Culture–Tourism Coupling Coordination Degree (CTCCD). Utilizing provincial panel data from China from 2000 to 2022, we employ two-way fixed-effects panel regression to empirically estimate and analyze the effects of the CTCCD on the agricultural GDP, Total Factor Productivity (TFP), and various aspects of crop farming. Our findings reveal several key insights: (i) the CTCCD exhibits a significant negative impact on both agricultural GDP and TFP; (ii) the CTCCD negatively affects the proportion of crop farming within the agricultural sector, suggesting that culture–tourism integration results in weaker development of crop farming compared to forestry, animal husbandry, and fisheries; (iii) the CTCCD demonstrates significant negative effects on the sown area, yield per unit area, and total production of food crops, while positively influencing the per capita income of agricultural workers. These empirical results highlight the complex relationship between culture–tourism integration and agricultural development. Our analysis provides quantitative evidence of the trade-offs involved in pursuing integrated development strategies, adding to the existing research on rural development. The findings indicate that promoting agriculture–culture–tourism integration should be balanced with efforts to accelerate agricultural technological progress. Full article

The digital economy (DE) is a new driver for enhancing total factor productivity (TFP). Using panel data from 30 provinces in China between 2011 and 2022, this study measures DE and TFP using the entropy-weighted TOPSIS method and the Global Malmquist–Luenberger method and further examines the impact of DE on the TFP of industries. The main findings are as follows: (1) DE can significantly improve TFP, though the extent of improvement varies. DE has the greatest impact on the TFP of the service industry, followed by the manufacturing industry, with the weakest effect on the agricultural industry. (2) The enhancement effect of DE on agriculture and the service industry is more pronounced in the central and western regions, while the improvement effect on manufacturing is more evident in the eastern region. (3) DE has facilitated the improvement of TFP in manufacturing industries such as textiles and special equipment manufacturing, as well as in service industries like wholesale and retail. However, it has not had a significant impact on the TFP of industries such as pharmaceutical manufacturing and real estate. This study has significant theoretical value and policy implications for China and other developing countries in exploring DE and achieving high-quality industrial development. Full article

The impact of climate change on agricultural quality development under the constraint of China’s “Double Carbon” target has been widely discussed by policy practitioners and academic theorists. This paper attempts to deconstruct the logic of how climate change affects agricultural total factor productivity (TFP) in three dimensions—the structure of agricultural input factors, the change in the cropping system, and the stability of crop supply. This paper also reveals the mechanism through which biased technological progress increases agricultural TFP by weakening the magnitude of climate change and empirically tests it by using China’s provincial-level data from 2000 to 2021. This study showed that average annual temperature and annual precipitation had significant negative effects on agricultural TFP, that the number of sunshine hours had a significant positive effect on agricultural TFP, and that obvious regional differences existed in the effect of climate change on agricultural TFP. Further mechanism tests revealed that biased technological progress positively moderated the effect of climate change on agricultural TFP. Based on these findings, the appropriate countermeasures for improving climate early warning mechanisms, promoting the progress of appropriate technology, and fostering new agricultural management bodies. Full article

The urgency of enhancing agricultural productivity within the Yellow River Basin cannot be overstated, given its critical role in ensuring food security amidst the challenges posed by climate change, natural disasters, and the increasing demand for food crops. Utilizing panel data from nine provinces within the Yellow River Basin for the period 2001 to 2020, this study examines the temporal characteristics and spatial distribution of Total Factor Productivity (TFP) for key grain crops—namely wheat, corn, and soybean—through the application of the Malmquist index which can be decomposed through the DEA-Malmquist index methodology. The empirical results demonstrate that TFP growth rates for these crops have exhibited significant phase variations, with soybean recording the highest TFP growth rate in the basin. Additionally, this study underscores marked regional disparities in soybean productivity. TFP decomposition reveals that the primary drivers of TFP improvement across these crops are attributed to technical progress, with gains in overall technical efficiency largely due to scale efficiency enhancements, whereas pure technical efficiency has shown limited progress. Regional analysis indicates that Inner Mongolia leads in TFP growth for all crops, while Ningxia, Sichuan, and Shaanxi lag behind in wheat, corn, and soybean. Additionally, our analysis delineates natural disasters as a significant barrier to Total Factor Productivity (TFP), notably obstructing technological advancements in wheat cultivation. The investigation further reveals a positive relationship between regional per capita income and the growth of wheat TFP, in contrast to a negative relationship with the TFP growth of corn and soybeans. Moreover, investing in agriculture, forestry, water management, and road infrastructure supports the growth of wheat TFP, while urbanization levels pose constraints. Conclusively, an uptick in annual rural electricity usage, along with improved per capita postal and telecommunication services, exerts a favorable influence on TFP for corn and soybeans. Full article

Fiscal and land policies are important tools in developing agriculture in China. Understanding how agricultural subsidies and land fragmentation jointly affect agricultural Total Factor Productivity (TFP) is crucial for building a strong agricultural nation. This paper utilizes microdata from fixed observation points in rural China from 2003 to 2017 and employs panel bidirectional fixed-effect models and moderation-effect models to empirically analyze the impact of agricultural subsidies and land fragmentation on agricultural TFP. The research finds: (1) Agricultural subsidies positively affect agricultural TFP, while land fragmentation leads to decreased agricultural TFP. (2) Land fragmentation hinders the positive effects of agricultural subsidies on agricultural TFP. A 1% increase in land fragmentation could lead to approximately a 3% decrease in the enhancement effect of agricultural subsidies, with significant impacts on households in major grain-producing areas and those primarily engaged in agriculture. (3) There is no evidence that reforms in the “three agricultural subsidies” would alter the combined effect of agricultural subsidies and land fragmentation on agricultural TFP. The obstructive role of land fragmentation cannot be mitigated through the “three agricultural subsidies” reform. The study indicates that the incentivizing role of agricultural subsidies has not been fully realized, and land fragmentation remains a key bottleneck in agricultural development. Fiscal support for agriculture should be coupled with effective land reform policies for synergistic efforts. Full article

Reducing carbon emissions is of paramount importance to the accomplishment of the 2030 Sustainable Development Goals. The effect of rural e-commerce on agricultural carbon emissions (ACEs) is controversial, and particularly the mechanism behind the effect is unknown. To identify the impact of rural e-commerce on agricultural carbon emissions and its mechanisms, we take advantage of China’s Rural E-Commerce Demonstration County Program (REDCP) as a quasi-natural experiment and use the multi-period difference-in-difference (DID) model to investigate the relationship between rural e-commerce and agricultural carbon emissions. Our data are based on panel data of 355 prefecture-level cities from 2010 to 2019 in China. We identify that rural e-commerce can reduce agricultural carbon emissions by an average of 14.4%, but this effect is not long-lasting. Mechanism analyses suggest that the reduction effect of rural e-commerce on agricultural carbon emissions is mainly due to fostering agricultural economic growth, increasing the share of low-carbon industry, and improving agricultural total factor productivity (TFP). Further heterogeneity analyses demonstrate that rural e-commerce has better carbon emissions reduction performance in eastern cities as well as in non-major grain-producing cities in China. Full article

Under the condition of opening up, participation in international specialization and global value chains (GVCs) has become the main source for more and more countries to obtain foreign resources and advanced technologies, thereby promoting productivity improvement and technological progress. What are the pathways of agricultural GVC participation that affect agricultural total factor productivity (TFP)? Is the impact of agricultural GVC participation on agricultural TFP consistent across different statuses and modes of agricultural GVC participation? This paper elaborates on the theoretical mechanism of agricultural GVC participation affecting agricultural TFP, and then empirically estimates the impact of different statuses and modes of agricultural GVC participation on agricultural TFP by taking 58 countries as examples. The results show that agricultural GVCs affect agricultural TFP by several direct and indirect pathways. There was a U-shaped relationship between agricultural GVC participation and agricultural TFP, which means that after crossing a certain threshold, the former has a positive impact on the latter. By participating in agricultural GVCs, agricultural TFP in high-income and upper-middle-income countries was significantly improved, while in lower-middle-income countries it was not. Both forward and backward agricultural GVC participation were conducive to improving agricultural TFP in high-income and upper-middle-income countries, but only backward agricultural GVC participation was conducive to improving agricultural TFP in lower-middle-income countries. Therefore, every country needs to actively explore its optimal pathway to participate in agricultural GVCs in order to maximize the participation benefits and promote the improvement in agricultural TFP, simultaneously. Full article

This study undertakes a comprehensive analysis of vegetable production efficiency in China using input–output data from 30 provinces spanning 2011 to 2017. By incorporating environmental pollution costs as undesirable outputs alongside vegetable output value, we employ Data Envelopment Analysis (DEA) with the Banker, Charnes, and Cooper (BCC) model and the Malmquist index model. Our assessment reveals both annual and inter-period efficiency changes. The findings highlight a modest overall efficiency in China’s vegetable production and significant regional disparities. Technical progress emerges as a pivotal determinant of total factor productivity (TFP). Recognizing these dynamics, we propose policy recommendations that prioritize technical innovation, sustainable practices, rural infrastructure enhancement, and specialized cultivation methods. Implementing these recommendations could bolster China’s position in international trade negotiations due to increased exports and potentially drive broader environmental policy reforms. As vegetable production becomes more efficient and sustainable, there might be a shift in labor needs, potentially leading to migration patterns or changes in employment structures. These insights contribute to the sustainable development of China’s vegetable industry, offering a broader understanding of the dynamics of agricultural efficiency in the context of environmental sustainability. Full article

The study focuses on examining how the total factor productivity (TFP) of China’s agriculture-related enterprises is affected by the reform of “County Administrated by Province” (CAP). Using panel data from 1998 to 2013, with a sample size of 292, 423 agriculture-related enterprises, the study investigates the influence of CAP reform on the TFP. The findings reveal a significant dampening effect of the CAP reform on the TFP of agriculture-related enterprises. These results are further supported with a series of robustness tests including placebo test, multidimensional fixed effects test, and clustering of cities or counties. Heterogeneity analysis reveals that the CAP reform has significantly restrained the TFP of agriculture-related enterprises in high level cities, while showing no significant impact on cities with lower administrative levels. In the eastern region, the impact of the CAP reform on the TFP of agriculture-related enterprises is significantly negative, whereas it is not statistically significant in the central and western regions. the study on mechanisms elucidates that the inhibitory impact of CAP policy on the TFP of agriculture-related enterprises is enhanced by urban property prices, labor resource allocation, and banking competition. The research conclusion is of significance in guiding the practices of agriculture-related enterprises and deepening the reform of “County Administrated by Province”. Full article

The study investigated the impact of temperature extremes on carbon emissions (CE) from crop production. (1) Background: Many scholars have studied climate extremes. However, the research on the relationship between temperature extremes and CE is not extensive, which deserves attention. (2) Methods: The study adopted a fixed-effect model to analyze the impact of temperature extremes on CE from crop production, and the moderating effect was tested using total factor productivity (TFP) in agriculture. (3) Results: Temperature extremes in Hebei Province were mainly reflected in a decline in the cold day index (TX10p) and a rise in the warm spell duration index (WSDI) and the number of summer days (SU25). Additionally, TX10p was positively correlated with CE. For every 1% reduction in TX10p, CE dropped by 0.237%. There was no significant correlation between WSDI and CE. Finally, the agricultural TFP had a significant moderating effect on CE, with each 1% increase resulting in a corresponding 0.081% decrease in CE. (4) Conclusions: The results indicated a warming trend in Hebei Province, which resulted in a decrease in the number of winter days, and reduced CE from crop production. The improvement of input efficiency in agricultural production factors helped moderate the CE. Full article

This paper studied the total factor productivity (TFP) of agriculture in the Bohai Rim region. The agricultural TFP showed the dependence of agricultural development on chemical fertilizers, pesticides, labor, science, technology, etc. By coordinating the inputs of various production factors, production efficiency can be improved, reducing the over-reliance on chemical fertilizers and pesticides and achieving the development and sustainability of agriculture. In this study, the sectional data of three provinces (Shandong, Hebei, and Liaoning) and two cities (Beijing and Tianjin) in the Bohai Rim region of China from 2011 to 2020 were collected, and the envelope analysis was performed on the collected data using the Malmquist index model. The results showed that the TFP of agriculture in the Bohai Rim region was greater than one, and agriculture was generally well-developed. Regionally, the agricultural productivity in Shandong Province was generally lower than in other provinces and cities. In addition, the scale efficiency was the most important factor restricting agricultural TFP in the Bohai Rim region, indicating that there was still room to improve investment in the agricultural production scale. Based on the analysis results, suggestions were made for sustainable and high-quality development of agriculture. Full article

This study evaluates the impact of industrial energy efficiency on agricultural development in the 31 member countries of the Organization for Economic Cooperation and Development (OECD) from 2015 to 2019. Using dynamic network slack-based measures (DN-SBM) and dynamic network total factor productivity (DN-TFP) indicators, dynamic cross-period information is used to assess the changes in efficiency and productivity of the industrial and agricultural sectors. The empirical results show that the industrial sector of the OECD is more efficient than the agricultural sector, and while some countries have low efficiency, productivity tends to improve. The study has three contributions: 1. Using the concept of the water–energy–food (WEF) nexus as a framework and combining its elements with variables to evaluate the efficiency performance of OECD countries; 2. using a dynamic two-stage DN-SBM model to objectively assess the overall efficiency value and provide improvement suggestions for different stages; 3. a comprehensive analysis of efficiency and productivity; the results can serve as a reference for OECD countries when formulating policies Full article