Search Results (25)

In contemporary discourse, Nigeria’s reliance on its oil sector is proving insufficient for sustained economic growth. The volatility of oil prices, geopolitical tensions, technological advancements, and environmental sustainability concerns have exposed the vulnerabilities of an oil-dependent economy, emphasizing the need for diversification and a renewed focus on agriculture. This study investigates the relationship between technological innovation and agricultural productivity in Nigeria, contrasting it with the oil sector. Using the ARDL estimation technique, our findings reveal a significant negative influence of immediate lagged agricultural productivity (AGTFP(−1)), indicating technological constraints. Technological innovation, proxied by TFP, shows a substantial impact on agricultural productivity, with a negative long-term effect (−90.71) but a positive, though insignificant, impact on agricultural output (0.0034). The comparative analysis underscores that the agricultural sector tends to benefit more from technological innovation than the oil sector. This highlights the critical need to prioritize technological advancements in agriculture to drive sustainable growth and economic resilience in Nigeria. 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

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

Resource misallocation is one of the important manifestations of agricultural supply-side distortion and an important causal factor that hinders food production increase and affects food security. Did the COVID-19 pandemic intensify China’s food production misallocation? The extent and consequences require quantitative assessment and scenario analysis. In this paper, we use a combination of input-output model and computable general equilibrium (CGE) model, and further incorporate the most important input factor in agriculture—intermediate inputs—into the model. At the same time, simulation of the pandemic impact from the demand and supply sides, respectively, and scenario analysis of the impact of the COVID-19 pandemic on China’s food production. The results of the study show that: first, compared with the baseline level before the epidemic, the overall TFP growth of China’s food industry chain decreased, and the TFP growth rate of the food distribution sector decreased most significantly. Second, there are significant factor misallocation distortions of capital, labor, and intermediate inputs. Third, in the short term, the period of the COVID-19 pandemic led to a decline in the vitality of the national labor market, but the return of non-farm employed labor in rural areas instead reduced the degree of labor misallocation in the food sector. Fourth, the demand side has a greater impact on China’s food production, among which the consumer demand has a particularly strong impact on the resource allocation of food production, and the short-term shock will mainly have a more obvious impact on the allocation of labor factors and the allocation of intermediate input factors in the food industry chain. Accordingly, this paper proposes that in order to guarantee China’s food security and adapt to the short-term characteristics of the era when the COVID-19 pandemic is rampant, China should make efforts in four areas: rational allocation of food production resources and factors, solid construction of the whole food industry chain, stable guarantee of the food market system and transfer to enhance social expectations. Full article

Due to the trend of global warming, individuals from all walks of life have paid close attention to how climate change affects food security. China is a sizable nation with a rich climate and a diverse range of food crops that are of interest to researchers. Additionally, there is little mention of agricultural technology and farm irrigation facilities in academic research on climate change and agricultural economic growth in China. As a result, this study uses the SBM model, panel fixed effect model, and SYS-GMM model to examine the development trend of climate change and food security based on the panel data of Chinese provinces from 2000 to 2020. The study found that China has maintained an average annual growth rate of 4.3% in agricultural total factor productivity (TFP) in recent years, despite the impact of extreme weather. The average annual precipitation has a depressing influence on the TFP in agriculture, while the average annual temperature has the opposite effect. The farm irrigation facilities and agricultural technology’s moderating impact is mostly shown in how well they attenuate the impact of climate change on the TFP in agriculture. Food crops have thereby improved their ability to survive natural risks and attain higher yields as a result of advancements in agricultural technology and increasing investment in contemporary farm irrigation facilities. The study’s conclusions are used in the article to make the suggestion that strengthening climate change adaptation is necessary to ensure food security. The strategic policy of “storing grain in technology and storing grain in the soil” and the advancement of contemporary agricultural technology must be put into reality while the management system for grain reserves is being improved. Full article

Previous research on agricultural productivity in Africa has focused on conventional Total Factor productivity (TFP) growth rather than Green Total factor productivity (GATFP) growth, thus ignoring the effect of undesirable outputs such as emissions. This has raised concerns about the sustainability of agricultural productivity growth in the continent. The study was designed to examine GATFP growth in agricultural productivity for 49 African nations from 2000 to 2019. We apply the Global Malmquist–Luenberger (GML) Productivity Index, which complies with the sustainable development agenda that promotes greater production of desirable outputs and minimising unwanted outputs. This approach is also compared to Global Malmquist (GM) Productivity Index which ignores unwanted outputs, yielding to conventional TFP growth. We found an average GATFP growth of 0.6% and TFP growth at 0.9% suggesting that the actual agricultural productivity growth is overstated if agricultural emissions are disregarded. Both estimates fell short of the desired annual target of 7% from the Comprehensive African Agriculture Development Programme (CAADP). Regional growth is mostly characterised by high (low) GATFP and TFP except in Southern Africa and East Africa. The two regions represent an ideal situation where GATFP exceeds TFP. At country level growth can be divided into three scenarios: desired growth, where GATFP exceeds TFP; balanced growth with both estimates equivalent; and undesired growth, where TFP exceeds GATFP. Unfortunately, most African nations fall in the last scenario. We conclude that policies must be developed to encourage sustainable agricultural productivity growth in Africa. Full article

Narrowing the rural–urban income gap is an important challenge in achieving sustained and stable economic and social development in China. The present study investigates the role of farmers’ education and agricultural productivity growth in influencing the rural–urban income gap by applying mediation, interaction, and quantile regression models to provincial panel data of China from 2003 to 2017. Results show that, first of all, China’s agricultural productivity (TFP) continues to improve, and it is mainly driven by technical change (TC), with no significant role of technical efficiency change (TEC) or stable scale change (SC). Improving farmers’ education not only directly narrows the rural–urban income gap but also indirectly improves agricultural productivity to further narrow the rural–urban income gap. Due to differences in income sources of farmers, the corresponding impacts of farmers’ education and agricultural productivity growth on the rural–urban income gap also differ. Policy recommendations include continued investments in farmers’ education and training as well as modernization of agricultural for higher productivity growth. Full article

This study investigates the impact of climatic variability on both agricultural production and total factor productivity (TFP) in the Southern United States (US). It also aims at identifying the drivers of productivity in this region. The analysis is tailored to inform decision makers about effective policy options to increase and sustain productivity in this important agricultural region. We use data from the US Department of Agriculture, National Climatic Data Center, and US Geological Survey to estimate alternative stochastic production frontier models. The estimated parameters are then analyzed and used to compute and decompose TFP into several measures of efficiency. The results show that agricultural production in the Southern US is more responsive to labor and has been increasing at a 1.13 percent rate annually. The findings also suggest that while precipitation, on average, has a positive and significant impact on productivity, intra-annual variation in both temperature and precipitation, which can be considered as anomalies, has a negative and significant impact on production. The impact of climatic effects on productivity across states is mixed and technological progress has been the main driver of TFP growth. Findings indicate that climatic variability is having a negative impact on agricultural productivity in the Southern US, similar in magnitude to the positive impact of irrigation. Full article

The effort to increase agricultural productivity continues to receive interest in Africa as low productivity levels, poverty and food insecurity remain or even increase. This study used the Färe-Primont Index to estimate agricultural total factor productivity growth for 49 African countries. Panel data consisting of 833 observations for the period 2000 to 2016 were obtained from the United State Department of Agriculture Economic Research Service database. The results show that the average growth rate for agriculture in Africa is 0.73% per annum. The sector experienced increased growth after the Maputo Declaration, which was sustained during the global financial crisis. West Africa experienced the largest growth while Southern Africa suffered a substantial decline. The study also discovered that growth differed between countries indicating that customization of the Comprehensive Africa Agriculture Development Programme into regional and country-specific policy interventions is important to boost agricultural productivity. Finally, the growth was achieved through technical change, while efficiency change constrained growth. Policy-makers should increase investment in agricultural extension services, education and training to enhance managerial capacity (efficiency change) because improved managerial capacity could increase agricultural growth and thereby increase food security and alleviate poverty in Africa. Full article

This article proposes a new lifetime-generated family of distributions called the sine-exponentiated Weibull-H (SEW-H) family, which is derived from two well-established families of distributions of entirely different nature: the sine-G (S-G) and the exponentiated Weibull-H (EW-H) families. Three new special models of this family include the sine-exponentiated Weibull exponential (SEWE${}_x$), the sine-exponentiated Weibull Rayleigh (SEWR) and sine-exponentiated Weibull Burr X (SEWBX) distributions. The useful expansions of the probability density function (pdf) and cumulative distribution function (cdf) are derived. Statistical properties are obtained, including quantiles ($Q_U$), moments ($M_O$), incomplete $M_O$ ($I{M}_O$), and order statistics ($O_S$) are computed. Six numerous methods of estimation are produced to estimate the parameters: maximum likelihood ($M_L$), least-square ($L_S$), a maximum product of spacing ($M{P}_R{S}_P$), weighted $L_S$ ($W{L}_S$), Cramér–von Mises ($C_{R}VM$), and Anderson–Darling ($A_D$). The performance of the estimation approaches is investigated using Monte Carlo simulations. The total factor productivity (TFP) of the United Kingdom food chain is an indication of the efficiency and competitiveness of the food sector in the United Kingdom. TFP growth suggests that the industry is becoming more efficient. If TFP of the food chain in the United Kingdom grows more rapidly than in other nations, it suggests that the sector is becoming more competitive. TFP, also known as multi-factor productivity in economic theory, estimates the fraction of output that cannot be explained by traditionally measured inputs of labor and capital employed in production. In this paper, we use five real datasets to show the relevance and flexibility of the suggested family. The first dataset represents the United Kingdom food chain from 2000 to 2019, whereas the second dataset represents the food and drink wholesaling in the United Kingdom from 2000 to 2019 as one factor of FTP; the third dataset contains the tensile strength of single carbon fibers (in GPa); the fourth dataset is often called the breaking stress of carbon fiber dataset; the fifth dataset represents the TFP growth of agricultural production for thirty-seven African countries from 2001–2010. The new suggested distribution is very flexible and it outperforms many known distributions. Full article

Population growth, food shortages, and low levels of human development have been longstanding issues confronting many African countries. Agricultural productivity remains a critical goal for mitigating these challenges and ensuring overall economic development. Total factor productivity (TFP) is a crucial metric for determining a sector’s overall growth. However, due to a lack of comprehensive assessments of the trends and determinants of TFP growth in African agriculture, there are disagreements. Within the context of inclusive human development, the impact of agricultural productivity is frequently misrepresented in the current literature. This paper estimated TFP growth and assessed its impact on human development in Africa. Due to technological improvement, TFP increased moderately at a 5.4% growth rate across African countries over the period (2001–2019). Empirical evidence indicates that TFP growth enhances human development in the long run, but the effect varies according to levels of human development (HDI) and the nature of growth over time. For instance, higher levels of human development tend to mitigate the impact of TFP. Further analysis revealed that technical efficiency improvement is critical for enhancing food safety and human development. Policy recommendations for improving TFP for food security and human development in Africa are provided. Further investigation into agricultural TFP’s impact beyond the poverty measure in Africa is encouraged. Full article

Growth in total factor productivity (TFP) indicates the sustainable and/or judicious use of scarce resources, including non-renewables. This paper identifies sources of growth in global agricultural TFP and its finer components, ranging from climate, production environment, and socio-economic factors, using a panel data of 104 countries, covering a 45-year period (1969–2013); and, finally, projects changes in TFP from increased climate variability. The results revealed that global agricultural productivity grew consistently at a rate of 0.44% p.a., driven by technological progress and mix-efficiency change, with negligible contributions from technical- and scale-efficiency changes; albeit with variations across regions. Both long-term and short-term climatic factors and the natural production environment significantly reduce global agricultural productivity, whereas a host of socio-economic factors have a significant but varied influence. The projected increased level of future climate variability will significantly reduce future agricultural productivity. Policy implications include investments in crop diversification, education, agricultural spending, number of researchers, and country specific R&D. Full article

Innovation adoptions in agriculture sustain high total factor productivity (TFP) growth and overcome a potential production gap, which is beneficial for food security. Research and development (R&D) innovation adoption in agriculture sector is dependent on producers’ willingness to adopt, knowledge capital spillovers, and financial capacity. This research aims to investigate the impact of R&D innovation adoption and climate factors on agriculture TFP growth in Pakistan. The annual time series data were collected from different sources for the period of 1972–2020. For measuring the agriculture TFP, this study adopted the Cobb Douglas and Translog production functions. To analyze the impact of R&D innovation adoption and climate change on agricultural productivity, the dynamic autoregressive distributive lag (ARDL) and two-stage least square (TSLS) approaches were applied for regression analysis. The study outcomes highlight that the agricultural innovation adoption has a significantly positive impact on agriculture TFP growth in Pakistan with weak farmers’ absorptive ability. According to the results, agriculture tractors, innovative seed distribution, and fertilizer consumptions make a significantly positive contribution to agriculture TFP growth. Further, rainfall shows a positive and significant impact on agricultural productivity, where a moderate climate is beneficial for agricultural productivity. The estimation results contain policy suggestions for sustainable R&D adoption and agrarians’ absorptive ability. Based on the obtained results, it has been suggested that producers should focus on R&D innovation adoption to attain higher productivity. The government needs to emphasize innovative technology adoption, specifically to implement the extension services to increase farmers’ education, skills based training, and networking among the farmers to enhance their knowledge capital and absorptive ability. The farmers should also focus on the adoption of climate smart agriculture that can be achieved through the proper utilization of rainwater. For this purpose, the government needs to develop small community dams and large-scale dams for better use of rainwater harvesting. Full article

There is an “export productivity paradox” in Chinese enterprises, which has been confirmed in agricultural enterprises. This paper attempts to explain this phenomenon from the perspective of the components of TFP. This paper uses the SFA-Malmquist method to decompose and compare the TFP of China’s agricultural export enterprises based on the data of the state-level leading agricultural enterprises from 2016 to 2017. The conclusions are as follows: firstly, China’s agricultural TFP shows a negative growth trend, and the growth rate of TFP of agricultural export enterprises is less than that of agricultural non-exported enterprises; secondly, the growth rate of TFP of grain and animal husbandry export enterprises is less than that of non-export enterprises; the growth rate of TFP of private agricultural export enterprises is lower than that of non-export enterprises of the same type; the growth rate of TFP of export enterprises in eastern and western regions is lower than that of non-export enterprises; and thirdly, technical progress is an important reason for the change of TFP of China’s agricultural enterprises. However, compared with agricultural non-exported enterprises, improving the technical efficiency of enterprises can more promote the TFP of agricultural export enterprises. Full article

The growth of agricultural total factor productivity (TFP) is seen as a driving force for the sustainable development of agriculture. Meanwhile, the promotion of urbanization in China has exerted a profound impact on agricultural production. This paper calculates the agricultural TFP and analyzes the effect of urbanization. Firstly, the DEA-Malmquist method is used to calculate the dynamic change in agricultural TFP in China from 2004 to 2016. Secondly, the spatial spillover effect of urbanization on agricultural TFP is investigated by the spatial Durbin model. We found that: the average annual growth rate of agricultural TFP in China is 4.8% from 2004 to 2016; and the spillover effect of urbanization on agricultural TFP shows a U-shaped relationship, which means that urbanization has exerted a negative effect first and then a positive effect on agricultural TFP. Finally, the paper puts forward policy suggestions from the perspective of sustainable coordination of urbanization and agricultural production. Full article