Agricultural Total Factor Productivity Research Articles

Intra-Africa Agricultural Trade, Governance Quality and Agricultural Total Factor Productivity: Evidence from a Panel Vector Autoregressive Model

Intra-Africa Agricultural Trade, Governance Quality and Agricultural Total Factor Productivity: Evidence from a Panel Vector Autoregressive Model

DIGITAL INITIATIVES OF HARYANA GOVERNMENT AND FARMER'S WELFARE

The agricultural landscape in Haryana, India, has undergone a transformative shift with the advent of digital technologies, specifically E-Portals encompassing social media and mobile applications. Digitalization presents the opportunity to assist in tackling the agricultural sector's challenges and improve productivity and sustainability. Digital initiatives (E-commerce and E-Portals) in agriculture have a significant positive impact on agricultural production efficiency. It encourages rational allocation of agricultural factors and promotes sustainable development.Based on Available data from national surveys and existing literature on the implementation and effects of digital portals, Mobile applications, and social media in agriculture utilization of digital technologies. The study adopted a mixed-methods approach, data taken from different sources like combining surveys, national surveys, existing literature, and data analytics to evaluate the adoption and utilization patterns of E-Portals, mobile applications and social media among farmers. The study aims to analyze the impact of E-Portals on farmers lives in Haryana. The research paper will focus on the E-Portals, Mobile apps and social media initiatives run by Government of Haryana. This research paper explores the multi-sided impact of these technological involvements on farmers in the region. Through a comprehensive study, we investigate how E-Portals have influenced various facets of farming practices, socio-economic conditions, and overall welfares of farmers in Haryana.Findings of this study reveal the extent to which farmers have integrated digital platforms into their daily routines for tasks such as market information access, crop management, financial transactions, and community engagement. Furthermore, the research explores the implications of E-Portals on improving market linkages, enhancing agricultural productivity, and contributing to sustainable farming practices.In addition to the positive outcomes, challenges and barriers faced by farmers in adopting and adapting to E-Portals are also analyzed. Issues such as digital literacy, connectivity constraints, and the socio-economic divide are examined to provide a holistic understanding of the technology's impact on different segments of the farming community.The research contributes valuable insights for policymakers, technology developers, and stakeholders aiming to enhance the effectiveness of E-Portals in agriculture. By understanding the dynamics of technology adoption among farmers in Haryana, this study aims to inform strategies that can bridge existing gaps, promote inclusivity, and ensure sustainable development in the agricultural sector. The study finds that regional digitalization can significantly raise agricultural total factor productivity, particularly in economically underdeveloped areas.

Increasing overall agricultural productivity in the Yellow River Delta Eco-economic Zone in China

AbstractImproving the efficiency of agricultural production in infertile areas contributes to reducing hunger, ensuring food security, and promoting eco-economic development. This study examines the effects and mechanisms of the Yellow River Delta High Efficiency Ecological Economic Zone policy on agricultural total factor productivity. The data from prefecture-level cities and a difference-in-difference model were used, and descriptive statistics and multiple regression analysis were conducted. The results show that the establishment of the zone increased agricultural total factor productivity by 40%. Heterogeneity analysis reveals that this positive effect is particularly pronounced in regions with a high proportion of agriculture and high per capita disposable income. However, this effect has diminished year by year since 2010. Mechanism tests suggest that the increase in agricultural R&D, the improvement in mechanization, and the application of ecological technologies have boosted agricultural total factor productivity. The results confirm the positive effects of the ecological economic zone policy and highlight the need for further measures to maintain and increase these positive effects in the long term. Future research should explore specific micro-management and technological measures to improve agricultural performance.

Impact of digital inclusive finance on agricultural total factor productivity in Zhejiang Province from the perspective of integrated development of rural industries.

Improving agricultural total factor productivity is crucial for comprehensive rural revitalization and building a strong agricultural nation. Digital inclusive finance amalgamates the benefits of digital technology and inclusive finance, mitigating financial exclusion in agricultural production. It fosters rural revitalization and the modernization of agriculture by bolstering farmers' innovation, entrepreneurship, and agricultural technology advancements. Consequently, it significantly enhances overall agricultural total factor productivity. This study uses panel data from 2011 to 2020 to empirically investigate the impact and mechanism of digital inclusive finance on agricultural total factor productivity in Zhejiang Province, China. The research results show that digital inclusive finance significantly enhances agricultural total factor productivity in Zhejiang Province, which holds true even after a series of robustness tests. Analysis of the mechanism reveals that the integrated development of rural industries plays a crucial mediating role in empowering agricultural total factor productivity through digital inclusive finance. Furthermore, heterogeneity analysis indicates that the positive effect of digital inclusive finance on agricultural total factor productivity is more pronounced in the northeastern region of Zhejiang Province and in areas ranked in the second tier of agricultural development. Therefore, we recommend comprehensively enhancing the development of digital inclusive finance in rural areas, fostering a financial ecosystem that integrates rural industries, promoting the coordinated development of digital inclusive finance in different regions, and comprehensively improving agricultural total factor productivity.

The effect of restricting groundwater exploitation on agriculture: Evidence from Huang-Huai-Hai region, China

Food security and groundwater conservation may conflict with each other due to high irrigation demands. This study aims to identify how groundwater conservation policies affect agriculture and the mechanisms of long-term adaptation. Our framework aggregates the stochastic frontier analysis, dynamic panel fixed effects model, and long-difference approach to evaluate the impact of restricting groundwater exploitation on agricultural total factor productivity, agricultural inputs, and outputs in the Huang-Huai-Hai area of China. The results demonstrate that, in the short run, the reduction in groundwater exploitation has a negative impact on agricultural total factor productivity, fertilizer and machines but promotes water input, which results in a more negative effect on agricultural output measured by yield. In the long term, restricting groundwater exploitation still implies a loss of agriculture. However, the long-run adaptation offsets 75% and 64% of the short-run effects on total factor productivity and yield, respectively. Despite more flexible adjustment in fertilizer and machines, long-term adaptation mitigates yield losses to a lesser extent than TFP due to water use constraints.

Integrating the rent gap into the ground rent theory. Measurement and implications for different models of agriculture

The aim of this paper is to establish a conceptual framework for the rent gap theory in agriculture and to identify potential implications of the rent gap for socio-economic processes occurring in agriculture and rural areas. From an empirical perspective an attempt was made to determine the state and dynamics of the rent gap phenomenon in agriculture in Poland, considering the regional division. The authors used income approach and Capital Asset Pricing Model (CAPM) for estimating the capitalization rate. It was found that rent gap is a permanent phenomenon in Polish agriculture, the dynamics of which largely depends on macroeconomic factors. A widening rent gap may result in the withdrawal of land from farming and a decline in total factor productivity in agriculture. Thus, the implications of the rent gap may relate to food security. Measuring the rent gap can be a step towards determining the quasi-market value of environmental amenities of land.

Agricultural Total Factor Productivity Based on Farmers' Perspective: An Example of CCR, BCC, SBM and Technology Optimization Malmquist-Luenberger Index

Agricultural Total Factor Productivity Based on Farmers' Perspective: An Example of CCR, BCC, SBM and Technology Optimization Malmquist-Luenberger Index

Does internet use promote agricultural green development?Evidence from China

Based on the panel data of CFPS2016, 2018 and 2020 as samples, this paper empirically investigates the green development effect of internet use on farmers from the perspective of agricultural green total factor productivity. The research shows that farmers' internet use has significantly promoted the improvement of agricultural green total factor productivity. The mechanism analysis shows that farmers' internet use promotes the improvement of agricultural green total factor productivity in two ways: land transfer and adoption of agricultural production services. The threshold effect analysis shows that it is only when the level of human capital exceeds the threshold that farmers' internet use can have a positive impact on agricultural total factor productivity. The expansion analysis shows that in the context of urbanisation and marketization development, there is a substitution effect between urban development and internet use by rural households in the eastern region, and a complementarity effect between urban development and internet use by rural households in the central and western regions.

Can Agricultural Industry Integration Reduce the Rural–Urban Income Gap? Evidence from County-Level Data in China

The improvement in urban production efficiency has led to income distribution being skewed towards urban labor, thereby widening the urban–rural income gap. However, integration of the agricultural industry at the county level can accelerate the flow of production factors between industries. Therefore, this study evaluates the degree of agricultural industry integration at the county level using the entropy weight method and explores its impact on the urban–rural income gap, based on sample data from 1122 counties in China spanning from 2014 to 2021. The research findings reveal the following: (1) The fixed model demonstrates that enhancing agricultural industry integration can significantly narrow the urban–rural income gap; (2) The mediating model indicates that this narrowing effect can be achieved by improving the green total factor productivity of agriculture; (3) Regional heterogeneity analysis indicates that the impact of agricultural industry integration is more pronounced in the central region and main crop production areas; (4) The results of the spatial Durbin model demonstrate that agricultural industry integration also exhibits a significant positive spatial spillover effect on neighboring areas. The outcomes of this study contribute to enriching the research on agricultural industry integration for green and low-carbon agricultural development, further promoting the development of county-level agricultural industry integration, and providing valuable insights for other similar countries.

New evidence of the driving forces behind Brazil's agricultural TFP growth—A stochastic frontier analysis with climatic variables and land suitability index

AbstractUsing panel data from 510 Brazilian micro‐regions in three census years (1995, 2006 and 2017), this study presents a productivity decomposition for the Brazilian agricultural sector using stochastic production frontier methods that account for the effects of rainfall, temperature and the land suitability index. We also calculated the total factor productivity (TFP) index and decomposed it into technical efficiency, technological change, scale efficiency and environmental efficiency. This article thus provides a new and more realistic assessment of recent Brazilian agricultural productivity growth. In recent decades, Brazilian agriculture has become widely known for presenting fast productivity growth; however, our results suggest that a lower TFP growth rate than previous estimates (1.96% per annum) and the overall effects of climate change could potentially compromise Brazilian agricultural TFP growth in the long run. Our findings might thus generate insights for agricultural and regional policies to increase efficiency in the sector and promote sustainable agricultural development in Brazil, which will contribute to the sector's competitiveness in international markets, the country's social and economic welfare, and environmental conservancy.

How does the development of rural broadband in China affect agricultural total factor productivity? Evidence from agriculture-related loans

IntroductionThe construction of digital villages is widely acknowledged as a way to achieve the “dual goals” of high quality of the agricultural and rural economy and common prosperity under the digital China strategy. Studies have explored the socio-economic benefits of different aspects of rural digitization, but few have focused on the productivity role of rural broadband development in the context of the urban-rural broadband divide. The purpose of this paper is to explore the relationship between rural broadband development and agricultural total factor productivity (TFP) and the intrinsic mechanism of action, and to provide empirical evidence on the productivity effect of promoting digital transformation in rural agriculture.MethodsUsing panel data from 31 provinces in China from 2011 to 2020, this paper investigates the impact and mechanism of rural broadband development on agricultural TFP from the perspective of agriculture-related loans by setting up a two-way fixed effects model, a mechanism effects model and a threshold effects model.ResultsThe results find that rural broadband development has a significant role in enhancing agricultural TFP. Heterogeneity analysis indicates that the productivity-enhancing effect of rural broadband development is remarkable only in the central region and the region with higher rural disposable income. Mechanism analysis points out that rural broadband development can increase agricultural TFP by influencing the share of farm-related loans. Threshold analysis further reveals that the role of increasing the share of farm-related loans on agricultural TFP is marked only after rural broadband development reaches a certain level.DiscussionThese findings can provide practical guidance for other developing countries in accelerating the digital transformation of villages and optimizing factor allocation to achieve high-quality agricultural development.

A framework for quantification and integration of green development of cultivated land in China: From the perspective of adaptability‐vitality‐resistance

AbstractExploring the green development of cultivated land (GDCL) and solving the problem of “high consumption and high pollution” caused by the traditional model are of great significance for achieving sustainable use of cultivated land and green agricultural growth. However, the existing consensus on action lacks theoretical support and quantitative analysis. To this end, the objective of this study was to develop a new multidimensional framework considering as an integrated capacity to adaptability‐vitality‐resistance (A‐V‐R) assess GDCL according to the essential requirement of green development. The analytical framework and evaluation system proposed in this study are expected to provide empirical support for the green transition of cultivated land use in China or worldwide. This study determines spatiotemporal differentiation and influencing mechanism of GDCL in China from 2000 to 2020. The results demonstrated that the GDCL level of China was low and characterized by a W‐shaped fluctuation. The regional difference in GDCL is greater than that within the regions and the evolution of different types of regions showed significant path dependence and spatiotemporal inertia. The reason behind this phenomenon is that agricultural technology and socioeconomic development factors such as agricultural mechanization level, urban–rural income equity index and extensively influenced GDCL in different regions. The interaction among driving factors forms a complex multi‐resultant force to construct a comprehensive action mechanism at the GDCL level driven by demand, economy, technology, and ecology. Therefore, this study suggests coordinating the relationship between technological progress, technological diffusion, agricultural total factor productivity, and the GDCL path, in order to effectively reduce the internal and external contradictions of GDCL.

Spatio-temporal differentiation on China’s green agricultural total factor productivity guided by digital technology and fuzzy systems

Spatio-temporal differentiation on China’s green agricultural total factor productivity guided by digital technology and fuzzy systems

Retracted: Analysis Method of Agricultural Total Factor Productivity Based on Stochastic Block Model (SBM) and Machine Learning

Retracted: Analysis Method of Agricultural Total Factor Productivity Based on Stochastic Block Model (SBM) and Machine Learning

The nexus of foreign direct investment and agricultural productivity: does absorptive capacity matter?

PurposeThis study aims to examine the complex effects of foreign direct investment (FDI) on China’s agricultural total factor productivity (TFP) from 2005 to 2020. It also explores the role of absorptive capacity as a moderating factor during this period.Design/methodology/approachEmploying provincial panel data from China, this research measures agricultural TFP using the Stochastic Frontier Approach (SFA)-Malmquist method. The impact of FDI on agricultural productivity is further analyzed using a nondynamic panel threshold model.FindingsThe results highlight technological progress as the main driver of agricultural TFP growth in China. Agricultural FDI (AFDI) seems to impede TFP development, whereas nonagricultural FDI (NAFDI) shows a distinct positive spillover effect. The study reveals a threshold in absorptive capacity that affects both the direct and spillover impacts of FDI. Provinces with higher absorptive capacity are less negatively impacted by AFDI and more likely to benefit from FDI spillovers (FDISs).Originality/valueThis study provides new insights into the intricate relationship between FDI, absorptive capacity and agricultural productivity. It underscores the importance of optimizing technological progress and research and development (R&D) to enhance agricultural productivity in China.

Impact of relaxing internal-migration restrictions on agricultural TFP of rural households: evidence from China

ABSTRACT In this paper, we study how a significant relaxation of internal migration restrictions affects the agricultural total factor productivity of rural households, taking advantage of the 2014 Hukou reform in China. This reform completely removed the migration restrictions for cities with an urban population of less than 0.5 million (towns and small cities) but left the migration restrictions in megacities unchanged. We find that the reform has significantly contributed to the off-farm transfer of rural labour and increased the agricultural TFP of rural households. Further mechanistic analysis shows that the reform increased the level of agricultural mechanization of rural households and facilitated the subcontracting of land by low productivity farmers.

Does Land Fragmentation Affect the Effectiveness of Fiscal Subsidies for Agriculture: Evidence from China

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.

Rural E-Commerce and Agricultural Carbon Emission Reduction: A Quasi-Natural Experiment from China’s Rural E-Commerce Demonstration County Program Based on 355 Cities in Ten Years

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.

The spatiotemporal pattern of surface ozone and its impact on agricultural productivity in China.

The slowing of agricultural productivity growth globally over the past two decades has brought a new urgency to detect its drivers and potential solutions. We show that air pollution, particularly surface ozone (O3), is strongly associated with declining agricultural total factor productivity (TFP) in China. We employ machine learning algorithms to generate estimates of high-resolution surface O3 concentrations from 2002 to 2019. Results indicate that China's O3 pollution has intensified over this 18-year period. We coupled these O3 estimates with a statistical model to show that rising O3 pollution during nonwinter seasons has reduced agricultural TFP by 18% over the 2002-2015 period. Agricultural TFP is projected to increase by 60% if surface O3 concentrations were reduced to meet the WHO air quality standards. This productivity gain has the potential to counter expected productivity losses from 2°C warming.

Can development of large scale agricultural business entities improve agricultural total factor productivity in China?: an empirical analysis

Large scale agricultural business entities (hereinafter referred to as “the large scale entities”) are newly sprouted in the process of China’s agricultural transformation from traditional production to modern mode, while the improvement of agricultural total factor productivity is an important driving force to realize agricultural transformation in China. Therefore, it is of great significance to explore whether the former has a promoting effect on the latter. First of all, the effective improvement of agricultural total factor productivity by the large scale entity development is analyzed from the two aspects of scale effect and technology utilization effect, and the effect mechanism is discussed in depth in this paper. Secondly, empirical test was carried out by using the panel data of prefecture-level cities from 2015 to 2020. The benchmark regression results show that the development of large scale entities can significantly improve agricultural total factor productivity. The mechanism test results indicate that the development of large scale entities improves the agricultural total factor productivity by raising the agricultural mechanization level. The results of heterogeneity analysis show that the difference between large scale entities would affect the benchmarking results. Therefore, it is believed through the study as discussed in this paper that devoting greater effort to support the development of large scale entities is an important measure to improve agricultural total factor productivity and promote China’s agricultural transformation, but it is necessary to act according to local conditions based on the difference of entity types in the process.