Agricultural Productivity Growth Research Articles

Current issues in waste management in hot climate conditions

Abstract The article discusses current issues of waste management in the hot climate of Central Asia. It notes that the development of industry, construction boom, rapid motorization, diversification and growth of agricultural production, combined with a hot climate, along with population growth and its migration to cities, affect the waste situation. At the same time, the region is becoming familiar with the concept of the “green” economy and welcomes the adoption of global experience, modern technologies, and progressive thinking. It emphasizes that waste management is a “complex system” consisting of interconnected parts, each of which can be both a driver and a barrier.

Reconsidering agricultural productivity, comparative advantage and economic growth

ABSTRACT In this article, we reconsider the work of Matsuyama (Journal of Economic Theory, 58(2): 317–334, 1992). Matsuyama (1992) concluded that, for a small open economy, a negative relationship exists between agricultural productivity and economic growth. Our study questions Matsuyama’s (1992) conclusion. We aim to demonstrate a theoretical possibility in which Matsuyama’s (1992) conclusion for a small open economy does not always hold. We extend Matsuyama’s (1992) model by introducing government services that enhance household utility. Unlike Matsuyama’s (1992) model, our model implies that, even in a small open economy, under certain conditions, a positive relationship may exist between agricultural productivity and economic growth when a small country initially has a comparative advantage in agriculture.

A Novel Decomposition Framework for Agricultural Growth Accounting: A Global Supply Chain Perspective

ABSTRACTIn this article, we delve into the traditionally opaque total factor productivity (TFP) “black box” by dissecting it into its constituent elements—technology and efficiency—based on input–output variables from a global supply chain vantage point. Utilizing growth accounting methods, the article seeks to discern the variety of routes through which technology (frontier movement) and efficiency (catch‐up effects) propagate their effects on TFP. Our primary objective is to identify the most potent mechanism for fostering productivity enhancement, a task that previously eluded systematic examination. The methodology involves creating an empirical approximation of the agricultural production frontier from a selection of national data. Bounded‐adjusted linear programming techniques are subsequently employed to disentangle the observed TFP growth within the agricultural sector of each country into its technology and efficiency facets. It is important to note that this study also integrates resource and environmental footprints as additional input–output variables, quantified via the multi‐region input–output (MRIO) model. The analysis, spanning from 2000 to 2016, reveals that the most advanced nations demonstrate the most vigorous growth in agricultural productivity, with a global upward trend in agricultural productivity over the sampled years.

Impact of Agricultural Credit by Commercial Banks on Agricultural GDP

The farming sector in India has always been an essential and significant part of the country’s economy. Agriculture has long been a significant employer of over 43% of the workforce and a large contributor to the nation’s Gross Domestic Product (GDP), (14.39%) but it has also experienced difficulties including exploitation and uneven regulations. Despite these challenges, agriculture remains essential for the country’s development, especially as it shifts towards a more business-oriented approach that requires access to capital. When looking at what factors influence agricultural productivity growth in India, attention to credit, inputs and policies can be signalled. Credit has been a crucial component in supporting agriculture for centuries and its importance has only increased as financial institutions have taken over from traditional non-institutional players such as moneylenders, friends and relatives. A significant factor in agriculture’s expansion, especially in spurring the Green Revolution, has been institutional financing. Institutional lending to the agricultural industry and allied fields has grown significantly over time. Based on regression analysis, this study examines the relationship between direct institutional credit and agriculture and allied services GDP by analysing data covering 19 years (1992-2011) using a Multi Linear Regression model to find determinants of agricultural development. The research has found that a strong correlation exists between credit and agricultural output along with other inputs like seeds, fertilisers, pesticides, tractors, power tillers and electricity. This has been reinforced by government interventions such as offering subsidies, providing extension services and developing infrastructure. Nonetheless, a nagging problem of climate change markets is out of control and gaps in the execution of policies continue to cross the horizons. For India to manage these changes, it will be necessary for the country to shift and take positive measures that will ensure sustainable agricultural growth in rural communities.

Foreign Direct Investment and Its Effect on Agricultural Productivity Kenya

Kenya has historically been one of Africa's top destinations for foreign direct investment. Foreign direct investment is critical for Kenya's agricultural sector, offering capital, technology transfer, and skill development that enhance productivity and economic growth. Despite agriculture being a primary economic driver, challenges such as limited capital, outdated farming techniques, and insufficient infrastructure continue to hinder growth. The research explores the contribution of foreign direct investment on agricultural productivity in Kenya as well as to assess the effect of foreign direct investment on the productivity levels of small-scale and large-scale farmers in Kenya for a period 1993 to 2022. Neoclassical growth theory, Endogenous theory were key in guiding the study. This study adapted the causal research design employing time series data from World Bank spanning from years 1993 to 2022. Data was analyzed the data both descriptively and by inferential statistics. The findings of correlational analysis revealed a moderate positive relationships (r= 0.3213) between Foreign direct investment and agricultural productivity. Multiple regression analysis confirmed the significant positive effect of foreign direct investment on agricultural productivity with a coefficient of 0.3661 and p value 0.0014<0.05. This signifies that, in the short term, a 1% increase in foreign direct investment results in a 36.61% rise in the growth of Agricultural productivity, assuming all other variables remain constant. The findings implied that foreign direct investment inflow has the ability to create employment, technological development and improve access to international markets playing a pivotal role in accelerating the agricultural productivity. The Kenyan government should have more effective foreign direct investment strategies to facilitate technology transfer agreements between foreign investors and local agricultural enterprises, additionally, the government should pursue macroeconomic policies that attract foreign direct investment by providing an investor-friendly environment.

Investigating Transfer Learning based CNN for Multi-Crop Disease Recognition in Horticulture Crops using Wireless Multimedia Sensor Network

Introduction: Achieving sustainable growth in agricultural productivity is crucial for addressing various challenges confronting food systems globally. One of the key aspects is effectively identifying and addressing diseases that can adversely affect crop quality and yield. Method: This research study proposes the use of Wireless Multimedia Sensor Network (WMSN) in conjunction with deep transfer learning model for disease detection in horticulture crops. The proposed system utilizes the image data of horticulture crops obtained using WMSN for performing a comparative assessment of several pre-trained deep learning models, encompassing VGG, ResNet, MobileNet, Inception, Xception, DenseNet, and EfficientNet, to ascertain their effectiveness in identifying diseases across a range of horticultural plants. The models undergo fine-tuning using transfer learning technique and are assessed on different measures, such as accuracy, precision, recall, F1 score, and the number of epochs needed for convergence using the image data obtained from WMSN. Results: Among the compared models, EfficientNetB3 appears as the best performing model, surpassing others in all evaluation metrics while also exhibiting low parameters and a compact size. Notably, EfficientNetB3 achieves a testing accuracy of 93.69% and a training accuracy of 98.85% after only 21 epochs of training. In contrast, DenseNet201, DenseNet169, and EfficientNetB0 demonstrate performance close to the best-performing models, but they have higher parameters or sizes. On the contrary, ResNet50, InceptionV3, and Xception exhibit poorer performance, presumably due to their substantial size in relation to the dataset. Conclusion: This analysis provides valuable insights for optimizing the top-performing models for disease classification across various plant species. Moreover, the fine-tuned EfficientNetB3 model shows potential for integration with mobile devices, facilitating real-time disease classification.

The intermediate role of farmland transfer in the impact of digital financial inclusion on agricultural total factor productivity in China

IntroductionEnhancing agricultural productivity and promoting sustainable development in China are critical priorities, given their significant contribution to food security and rural development. However, achieving consistent agricultural productivity growth across regions and sectors has been challenging, leading to inefficiencies and environmental pressures. To address this, the potential of digital inclusive finance (DIF) as a catalyst for progress has been explored.MethodsThis study investigates the impact of DIF on agricultural total factor productivity (ATFP) through farmland transfer, with implications for rural revitalization and high-quality agricultural development. Using the HMB index method, we calculate and decompose China’s inter-provincial ATFP from 2011 to 2020. Employing the dynamic panel fixed effect model and SYS-GMM method, we empirically test the influence of DIF on agricultural productivity in relation to farmland transfer.Results and discussionOur findings reveal a slow upward trend in China’s ATFP, driven primarily by scale efficiency. Notably, a 1% increase in the general index of DIF correlates with a 0.136% increase in ATFP. We analyze the sub-classification indexes of digital inclusive finance, namely coverage breadth, depth of use, and digitalization degree. Their contributions to agricultural productivity growth are significant, with coverage breadth having the greatest impact, followed by depth of use and digitalization degree. Farmland transfer acts as a crucial intermediary, enhancing agricultural allocation efficiency and driving the relationship between digital finance and total factor productivity growth. Interestingly, the western region exhibits the highest growth rates, followed by the eastern region, while the central region shows no significant effects.ConclusionTo comprehensively enhance ATFP, aligning supply and demand for digital financial services, leveraging service depth, and guiding farmland transfer according to local conditions are essential. These findings offer valuable insights into effective strategies for maximizing the potential of DIF, promoting rural development, and achieving sustainable agricultural growth.

Digitalization and Agricultural Green Total Factor Productivity: Evidence from China

Based on panel data of 31 provinces (autonomous regions and municipalities) in China from 2011 to 2022, this paper empirically examines the impact of digitalization on the inputs and outputs of the agricultural production process, and thereby derives the effects and mechanisms by which digitalization empowers the growth of agricultural green total factor productivity. The study finds that agricultural and rural areas’ digitalization significantly improves agricultural green total factor productivity, and this promotion mainly comes from the improvement of technical efficiency. Further analysis shows that digitalization mainly reduces land input and labor input, increases expected output, and reduces undesired output during the agricultural production process to achieve an improvement in agricultural green total factor productivity, indicating that digitalization has altered the allocation of agricultural factors. Heterogeneity analysis finds that the effect of digitalization on the growth of agricultural green total factor productivity is more pronounced in the eastern regions, southern regions, and areas with higher levels of agricultural digitalization, indicating that the development of digitalization exacerbates the gap in agricultural green total factor productivity among regions.

Agricultural Productivity and Climate Mitigation

Agriculture will play a central role in meeting greenhouse gas (GHG) emission targets, as the sector currently contributes ∼22% of global emissions. Because emissions are directly tied to resources employed in farm production, such as land, fertilizer, and ruminant animals, the productivity of input use tends to be inversely related to emissions intensity. We review evidence on how productivity gains in agriculture have contributed to historical changes in emissions, how they affect land use emissions both locally and globally, and how investments in research and development (R&D) affect productivity and therefore emissions. The world average agricultural emissions intensity fell by more than half since 1990, with a strong correlation between a region's agricultural productivity growth and reduction in emissions intensity. Additional investment in agricultural R&D offers an opportunity for cost-effective (<US$30 per ton carbon dioxide) and large-scale emissions reductions. Innovations that target specific commodities or inputs could even further reduce the cost of climate mitigation in agriculture.

Impact of climate change on agricultural productivity: a combination of spatial Durbin model and entropy approaches

PurposeGlobal climate change characterized by an increase in temperature has become the focus of attention all over the world. China is a sensitive and significant area of global climate change. This paper specifically aims to examine the association between agricultural productivity and the climate change by using China’s provincial agricultural input–output data from 2000 to 2019 and the climatic data of the ground meteorological stations.Design/methodology/approachThe authors used the three-stage spatial Durbin model (SDM) model and entropy method for analysis of collected data; further, the authors also empirically tested the climate change marginal effect on agricultural productivity by using ordinary least square and SDM approaches.FindingsThe results revealed that climate change has a significant negative effect on agricultural productivity, which showed significance in robustness tests, including index replacement, quantile regression and tail reduction. The results of this study also indicated that by subdividing the climatic factors, annual precipitation had no significant impact on the growth of agricultural productivity; further, other climatic variables, including wind speed and temperature, had a substantial adverse effect on agricultural productivity. The heterogeneity test showed that climatic changes ominously hinder agricultural productivity growth only in the western region of China, and in the eastern and central regions, climate change had no effect.Practical implicationsThe findings of this study highlight the importance of various social connections of farm households in designing policies to improve their responses to climate change and expand land productivity in different regions. The study also provides a hypothetical approach to prioritize developing regions that need proper attention to improve crop productivity.Originality/valueThe paper explores the impact of climate change on agricultural productivity by using the climatic data of China. Empirical evidence previously missing in the body of knowledge will support governments and researchers to establish a mechanism to improve climate change mitigation tools in China.

Influence of Rural Road Transportation on Farming Activities in Baruten Local Government Area, Kwara State, Nigeria

Rural road transportation is critical for enhancing agricultural productivity and improving the livelihoods of rural farmers. This paper examines the influence of rural road transportation on farming activities in Baruten Local Government Area (LGA) of Kwara State, Nigeria. Baruten, known for its significant agricultural potential, faces several challenges due to inadequate transportation infrastructure. The study explores the relationship between road access and agricultural productivity, market access, and overall rural development in the region. Using both primary and secondary data, the paper analyzes how improved rural road transportation can support agricultural growth by reducing post-harvest losses, enhancing market linkages, and boosting income levels for local farmers. This research adopts a mixed-methods approach, utilizing both quantitative and qualitative data to analyze how rural road transportation influences farming activities in the region. The findings suggest that improving rural road transportation would enhance agricultural productivity, reduce poverty, and foster economic growth in Baruten. The study recommends strategic investments in rural infrastructure to promote sustainable agricultural development and to equally improve rural road infrastructure to enhance farming activities in Baruten LGA.

The Curse of Plenty: The Green Revolution and the Rise in Chronic Disease

The rising rate of chronic disease is a leading driver of the global disease burden. Yet, its determinants are not fully understood. Exploiting the Green Revolution and its expansion in historically groundwater-rich Indian districts, we examine the unanticipated contribution of agricultural productivity growth to the rise in chronic, diet-related diseases. We find that areas with greater adoption of new staple varieties saw an increase in diabetes in men born after the introduction of high-yield crops. We find suggestive evidence that diet is an important mechanism, such as heterogeneous impacts with respect to dietary habits and increases in household calorie consumption. (JEL I12, O13, O15, O31, Q12, Q16)

Impact of short- and long-term factors on the growth of gross agricultural products in Azerbaijan: ARDL analysis

Purpose. The main purpose of this research is to assess the factors affecting the gross agricultural products in Azerbaijan in the short and long term. Methodology / approach. This study uses an Autoregressive Distributional Lag (ARDL) model to analyse the relationship between gross agricultural output and total government expenditure on agriculture, the volume of credit used in agriculture, direct investment in fixed assets in agriculture, and the country’s net agricultural exports. In our study, unlike most existing research, the variables are integrated in the second order, which increases the importance of this study. Results. The results of the study indicate that, despite the “crowding in” effect created by the state budget expenditures as the main factor in the short term, the effect on the growth of gross agricultural products in the long term is not so important. Credit resources and net exports have a negative effect in this relationship. In the long term, investment in fixed capital is a crucial factor in the growth of production. In general, the positive balance of net exports is a “mirror” reflection of investments, especially innovation-oriented investments. Considering that the predominance of imports in the total demand for agricultural products significantly reduces the multiplier effect that can occur in the field in general, it minimises the multiplier effect of the total expenditure. From this point of view, foreign investments can play an important role in creating a positive balance in the trade balance of agriculture. Originality / scientific novelty. The scientific value of the research is the selection of main factors as direct contributions to the growth of the gross agricultural products and their effects. Through the ARDL program, we determined what factors are short-term and which are long-term, and we analysed the causes and consequences of these dependencies and put forward relevant proposals. Practical value / implications. The practical value of the research lies in the given proposals that can directly affect the net export of agricultural products and create positive changes in its balance. Because, massive investments, especially foreign investments, can modernise the rural economy in a short period of time and, accordingly, not only increase the competitiveness of its products in foreign markets, but also raise the level of self-sufficiency.

The Relationship between Agricultural Production, Agricultural Exports and Economic Growth in Türkiye: Cointegration and Causality Analysis

This study aimed to assess the influence of agricultural production and agricultural product exports on economic growth within the Turkish economy. To achieve this, annual data spanning from 1980 to 2022 were utilized to construct a model, employing the ARDL Bounds Test to discern the long-term cointegration relationship among variables and the Fourier Toda-Yamamoto Causality Test to determine causality relationships. The empirical findings from the ARDL Bounds Test indicate that increases in both agricultural production and agricultural product exports positively impact economic growth. Moreover, results from the Fourier Toda-Yamamoto Causality Test unveil a two-way causal relationship between agricultural production and GDP, while a one-way causality relationship is observed between agricultural product exports and GDP. Despite the declining share of the agricultural sector in GDP over the years in Turkey, these findings underscore the enduring importance of agriculture in driving economic growth and creating value. As potential solutions to Turkey's balance of payments challenges, strategies such as boosting domestic demand, expanding the domestic market, and augmenting agricultural sector contributions to foreign exchange earnings through agricultural export subsidies are proposed. Furthermore, efforts to mitigate income disparities between the agricultural sector and other sectors could foster socio-economic development in rural areas, thus promoting a more equitable distribution of national income across society.

Modelling the nexus between green energy, agricultural production, forest cover, and population growth towards climate change for the transition towards a green economy

Modelling the nexus between green energy, agricultural production, forest cover, and population growth towards climate change for the transition towards a green economy

The unmet demand of food security in East Africa: review of the triple challenges of climate change, economic crises, and conflicts

East Africa struggles with a profound challenge in ensuring food security amidst the convergence of climate change, economic crises, and conflicts. This paper presents a comprehensive review of the interconnected and compounding effects of these three factors on the region’s food security landscape. It investigates the complex ways in which shifting climatic patterns disrupt agricultural systems, exacerbating food scarcity and amplifying vulnerabilities among marginalized communities. The study also examines the intertwined impact of economic downturns, which diminish access to resources, disrupt supply chains, and deepen food insecurity. Furthermore, the paper scrutinizes the ramifications of persistent conflicts, which not only displace populations but also destabilize agricultural production, aggravating food shortages. To achieve the objective of this, review the authors have collected the relevant documents through search engines of Web of Science, Google, Google Scholar, Scopus, and Science Direct databases. This review found that climate change, economic instability, and conflict are the primary challenges to food security in East Africa. Climate change exacerbates extreme weather events, rising temperatures, and pest infestations, reducing agricultural productivity and economic growth. Economic instability stems from a lack of industrialization, dependence on foreign aid, and significant investment gaps, resulting in persistent poverty and underdevelopment. Additionally, conflict and instability disrupt agricultural activities, displace populations, and restrict access to essential resources, further aggravating food insecurity. The study emphasizes the necessity for coordinated efforts among governments, international organizations, and local communities to navigate these intersecting crises and establish sustainable pathways toward enhanced food security in the region.

PS-MTL-LUCAS: A partially shared multi-task learning model for simultaneously predicting multiple soil properties

Soil acts as a foundation for human survival and social development and soil quality has a great effect on the growth of agricultural products. Visible/near-infrared spectroscopy has been acknowledged as a rapid and non-destructive method for predicting soil properties, and multi-task learning is a preferable approach to analyze the correlation between the spectroscopy data and soil properties. However, current multi-task learning models with the soft parameter sharing structure extremely rely on the task relatedness. To tackle this limitation, we proposed PS-MTL-LUCAS, a multi-task learning with a partially shared structure in this study. An additional shared layer was utilized to learn the general informative representations and interact with each task-specific layer. The partially shared structure ensured the maximum information flow between layers, thereby boosting the prediction performance. Also, the SHapley Addictive exPlanations (SHAP) algorithm was adopted to extract the feature wavelengths of each soil property. PS-MTL-LUCAS was validated on the LUCAS topsoil dataset (2009), and the experimental result suggested that PS-MTL-LUCAS dominated state-of-the-art models by achieving the determination of coefficient at 0.945, 0.936, 0.413, 0.624, 0.837, 0.952, and 0.956 for pH, N, P, K, CEC, OC, and CaCO3, respectively. In summary, this study highlighted the use of the soil spectroscopy and multi-task learning techniques in the soil property prediction task and provided a very promising approach for soil studies.

(Invited) Efficient Recycling of Dilute Nitrate to Ammonia Using Cu-Based Electrocatalyst

The use of nitrogen fertilizers has contributed significantly to the growth of agricultural production, but the nitrogen use efficiency is typically lower than 40%, so most of the nitrogen readily leaches into ground water, rivers, and lakes, causing an increase of nitrate (NO3 −) concentration and severe environmental problems. Electrochemical reduction of nitrate has emerged as a promising route for the recycling of nitrate from wastewater and sustainable production of ammonia when powered by renewable electricity. Here I present our recent studies of the intrinsic activity and selectivity of Cu for nitrate electroreduction, as well as a rational design of Cu-based catalysts for single-pass conversion of nitrate to ammonia. Using polycrystalline Cu foils for benchmarking, we elucidated the impact of often overlooked factors on nitrate reduction, including Cu facet exposure, nitrate concentration, and electrode surface area. We find that an electropolished Cu foil exhibits a higher activity and selectivity for nitrate reduction to ammonia than a wet-etched Cu foil, benefiting from a greater exposure of Cu(100) facets that are more favorable for the reaction. The NH3 selectivity shows no apparent dependence on the nitrate concentration, but it increases monotonically with Cu electrode area, which is attributed to a promoted conversion of intermediately produced NO2 − to NH3 on a larger electrode. Based on the understandings, we further developed a Cu/Co-based tandem electrocatalyst, which achieved nearly 100% single-pass conversion of dilute nitrate (5−50 mM) to NH3 at a low overpotential using a flow cell.

DOES IMPROVING TECHNICAL EFFICIENCY INCREASE FOOD PRODUCTION? AN ANALYSIS OF WHEAT FARMS IN AFGHANISTAN

Afghanistan faces serious challenges in terms of food security, which highlights the importance of agricultural productivity growth. This study assessed the impact of technical efficiency (TE) of wheat production on farmers’ household food security by improving food production using ex-post non-experimental data from Takhar Province, Afghanistan. Our empirical approach is based on the Cobb–Douglas stochastic frontier model and the Household Food Insecurity Access Scale (HFIAS). We found that farmers’ TE significantly improved farmers’ households’ food security by improving food production. Furthermore, the average TE score of food-secure farmers was 72.0%, whereas that of food-insecure farmers was 66.2%, and the difference was statistically significant. In conclusion, our findings underscore the essential role of improving farmers’ TE in enhancing food security in farming households in Afghanistan.

Research on the Impact of Digital Green Finance on Agricultural Green Total Factor Productivity: Evidence from China

Green development has become one of the important concepts leading China’s economic developments, and it is extremely meaningful to boost the continuous growth of agricultural green total factor productivity (AGTFP) to achieve the construction of a powerful agricultural country. Using China’s provincial data from 2011 to 2020, this manuscript calculates AGTFP through the SBM–GML model, and the digital green finance (DGF) through a comprehensive indicator system. The double fixed-effect model, quantile model and spatial Durbin model are used for in-depth study of the benchmark influence, the nonlinear effect and spatial spillover effect of DGF on AGTFP. The main research conclusions of the article are as follows: (1) DGF is significantly conducive to the improvement of AGTFP. Along with the continuous growth of AGTFP, the promoting effect of DGF has gradually increased. (2) In terms of impact path, green finance can properly promote the growth of AGTFP, while the role of the degree of digitization is not very significant. Meanwhile, the main channel for DGF to promote AGTFP is through green technology efficiency. (3) The impact of DGF on AGTFP varies spatially, while the role is more effective in regions with a higher degree of economic development and well-developed modernization. (4) There is a spatial spillover effect of DGF’s impact on AGTFP, which means that DGF can simultaneously promote the growth of AGTFP in local regions and neighboring regions.