Technical Efficiency Of Farmers Research Articles

The adoption of cotton combine services and farm technical efficiency: evidence from Kazakhstan and Uzbekistan

PurposeThis study examines the adoption of cotton combine services and its impact on farm technical efficiency in Kazakhstan and Uzbekistan. The research aims to determine whether mechanisation influences productivity and economic output at the farm level.Design/methodology/approachUsing farm-level data from 511 cotton growers in Kazakhstan and Uzbekistan collected in 2019, this study employs stochastic frontier analysis to measure potential output and technical inefficiency among cotton farmers. The analysis includes a translog functional form to account for the use of cotton combine services and other farming variables.FindingsThe findings indicate that while mechanisation through cotton combines can potentially increase technical efficiency by optimising the harvesting process, the benefits are not uniformly experienced across all farms. Variations in farm characteristics, such as labour availability and existing agricultural practices, influence the efficiency of technology adoption. Institutional factors and historical legacies also play a significant role in the adoption and impact of mechanisation.Research limitations/implicationsThe study is based on cross-sectional data from 2019, and the findings may not capture longer-term trends or recent developments in mechanisation policies in the study countries.Originality/valueThis research provides a nuanced understanding of the conditions under which cotton combine services enhance or hinder technical efficiency. It highlights the necessity for carefully tailored policies for mechanisation, especially in Uzbekistan, where rural labour is abundant and predominantly female. The study contributes to the broader discourse on agricultural mechanisation in developing countries by focusing on the specific context of Central Asia.

Effects of exposure on adoption of agricultural smartphone apps among smallholder farmers in Southwest, Nigeria: implications on farm-level-efficiency

BackgroundWhen considering new technologies that are not widely known such as agricultural smartphone apps, exposure plays a significant role in facilitating farmers’ decision to use the agricultural smartphone apps. In this study, we examine the role of exposure to agricultural smartphone apps on adoption of agricultural smartphone apps among smallholder farmers in Southwest, Nigeria and also evaluates the effect of use of agricultural smartphone apps on total factor productivity and technical efficiency of farmers. Through counterfactual framework evaluation approach, we used a multistage sampling procedure to select 380 farmers in Southwest, Nigeria through well-structure questionnaire.ResultsWe found that the agricultural smartphone apps user rate in 2022 for the sub-sample of the exposed farmers was higher in both Oyo and Osun State, indicating that exposure to agricultural smartphone apps played an important and significant role in increasing the adoption and use of agricultural smartphone apps in Nigeria. We also found that the mean TFPI and TE of the treated (users of agricultural smartphone apps) is higher than the non-treated and control group (non-users) implying that the users of agricultural smartphone apps have higher productivity margin than the non-users.ConclusionBased on the result of the study, it was concluded that exposure to the technology has a higher chances of increasing the use of agricultural smartphone apps across farmers populations in Southwest, Nigeria.

Technical Efficiency of Smallholder Oil Palm Farms in Batanghari District Jambi Province, Indonesia

Smallholder oil palm farming is the main livelihood in Batanghari District, although its productivity has not shown maximum results. Maximum productivity achieved, it is necessary for farmers to do their business efficiently. This study aims to analyze technical efficiency and socio-economic factors that affect the technical efficiency of smallholder oil palm farming in Batanghari District. The research sample was determined using the multistage sampling method, which was used to sample farmers using simple random sampling. The number of respondents was 100 farmers. The stochastic frontier production function was used for data analysis. The results showed that the average technical efficiency of oil palm farming was 0,89 and had reached efficiency. However, this level can still be increased by 0,11 to achieve the highest level of technical efficiency. The technical efficiency of farming is affected by socio-economic factors, namely farming experience, distance from home to the farm, and the existence of partnerships. Based on the study's results, the technical efficiency of oil palm cultivation can be improved by utilizing production parameters precisely and accurately and increasing farmers' resources to achieve maximum production. For sustainable agricultural development, further research is needed to analyze the economic efficiency of oil palm farming so that the overall picture of both technical and economic efficiency can be seen.

Impacts of soil and water conservation measures on farm technical efficiency in the semi-arid tropics of central India

SummaryNatural resources such as soil and water are essential to agriculture, especially in arid and semi-arid rain-fed areas, yet the impacts of managing these crucial natural resources on farm technical efficiency are little known. Using data from 400 households with 1031 plots, we examined the impacts of soil and water conservation measures (SWCMs) on the technical efficiency of farmers in the semi-arid Bundelkhand (central India). We estimated stochastic production frontiers, considering potential self-selection bias stemming from both observable and unobservable factors in the adoption of SWCMs at the farm level. The farm technical efficiency for adopters of SWCMs ranged from 0.68 to 0.72, and that for non-adopters ranged from 0.52 to 0.65, depending on how biases were controlled for. As the average efficiency is consistently higher for adopter farmers than the control group, promoting SWCMs could help to increase input use efficiency, especially in resource-deprived rain-fed systems in the semi-arid tropics.

Impact of Agricultural Technical Efficiency on Farm-Gate Emission: An Implementation of Environmental Kuznets Curve in Asian Developing Countries

<p>The Environmental Kuznets Curve (EKC) explains that economic activities in developing countries, including agriculture, increase environmental damage. Increased technical efficiency is one approach that is frequently suggested for reducing the negative impacts of farming practices. Unfortunately, there are no studies that investigate this at the macro (national) level. This study examines the impact of technical efficiency on farm-gate emissions in Asian developing countries. Data were collected from 25 developing countries in Asia from 1992 to 2021 and were analyzed using frontiers and the generalized method of moments. The findings demonstrate that technical efficiency is insufficient to prevent increases in CO<sub>2</sub>, CH<sub>4</sub>, and N<sub>2</sub>O emissions. This finding is consistent with the EKC. Gas emissions also rise because of gross domestic product (GDP) and population growth. Human development is the only way to prevent a rise in emissions of these 3 gases. Meanwhile, renewable energy and food prices have varying impacts on CO<sub>2</sub>, CH<sub>4</sub>, and N<sub>2</sub>O emissions reduction. Therefore, based on these findings, it is suggested that developing countries increase the utilization of natural production factors and organic farming, improve human capital development, and conduct a wise selection of renewable energy sources.</p>

Economic Efficiency of Banana Production in Uttara Kannada District of Karnataka, India

Aim: Banana cultivation holds significant agricultural importance, contributing substantially to global dietary staples. This study Examines the economic efficiency of banana production in Uttara Kannada district.
 Sampling Design: Employed purposive and multistage sampling, the study focuses on Sirsi and Siddapur taluks, selecting 80 farmers through random sampling.
 Methodology: The research examines resource utilization by employing the Cobb-Douglas production function and evaluate efficiency levels by Data Envelopment Analysis (DEA).
 Results: Allocative efficiency in banana cultivation is apparent through positive MVP/MFC ratios for inputs like suckers (15.89), manure (1.91), fertilizers (7.21), machine labor (1.75), and propping material (6.66), indicating underutilization. Conversely, plant protection chemicals (-22.35) and human labor (-1.20) show negative ratios, signifying overutilization. The ratio of MVP to MFC was differed from unity indicating scope for reallocation of expenditure among various resources. Using Data Envelopment Analysis, individual farm technical and economic efficiency was assessed. Banana, Crop I had a mean technical efficiency of 70.30, while Crop II had 49.40. The results highlight room for improvement, especially in Crop II, emphasizing the need for better resource allocation. Major production constraints include labour scarcity, poor planting material, and pest issues. Marketing hurdles encompass price fluctuations, limited storage, and distant markets.
 Conclusion: The study emphasizes the banana cultivation revealed significant impacts of resource utilization on yield, with suckers, fertilizers, and plant protection chemicals showing substantial effects. Allocative efficiency analysis indicated underutilization of resources, suggesting potential for yield improvement. However, farmers face challenges including labour scarcity, quality planting material, price fluctuations, and inadequate storage facilities in production and marketing.

How Does Land Fragmentation Affect Agricultural Technical Efficiency? Based on Mediation Effects Analysis

The scientific revelation of the mechanism underlying land fragmentation’s influence on agricultural technical efficiency is extremely important. This study utilized survey data from 305 villages across 12 provinces in Southern China in 2020 to assess technical efficiency through the application of the stochastic frontier production function. Moreover, we investigated the direct impact of land fragmentation on technical efficiency and the indirect impact transmitted through crop diversification and part-time farming by employing Tobit and mediating effect models, respectively. The key findings are as follows: (1) The sampled farmers, on average, operated 0.614 hectares of land with 17.395 plots, and the mean of their technical efficiency was 0.630. (2) The overall effect of land fragmentation on technical efficiency demonstrated a “U”-shaped relationship. (3) Crop diversification and part-time farming were mediating factors in the impact of land fragmentation on technical efficiency. Specifically, an “inverted U”-shaped relationship existed between land fragmentation and crop diversification, whereas a negative linear relationship was observed between land fragmentation and part-time farming. Conversely, crop diversification presented a positive linear relationship with technical efficiency, and part-time farming had an “inverted U”-shaped relationship with technical efficiency. (4) The impact of land fragmentation on technical efficiency varied across altitude zones. It is recommended to control land fragmentation based on local conditions, encourage crop diversification, and strengthen employment guidance and skills training for farmers to ensure the orderly transfer of land.

Multiple roles of agricultural cooperatives in improving farm technical efficiency: A case study of rural Gansu, China

AbstractThe establishment of agricultural cooperatives is widely viewed as an institutional arrangement to remove constraints that prevent smallholders from accessing profitable business opportunities in agriculture. Agricultural cooperatives in China offer a wide range of services within the framework of contract farming and vertical integration. This study empirically examines the multiple roles of China's cooperatives in improving farm production efficiency and conserving the agricultural environment. Considering that agricultural cooperatives' services can be broadly divided into biological and machinery services, we specify a stochastic frontier production function in a special form, called the separated Cobb–Douglas. The empirical results present clear evidence that Chinese agricultural cooperatives play essential roles in increasing biochemical technical efficiency and protecting the agroecological environment. However, the involvement of cooperatives as vertical integrators is demonstrated to have a detrimental effect on biochemical technical efficiency. The pressing challenge for agricultural cooperative development in China is to accommodate the conflicting consequences that their entry into farming has on biochemical and machinery technical efficiencies. This has strong policy implications, although our study has certain limitations in terms of the narrow focus on a single specific region. [EconLit Citations: C26, Q12, Q13, Q15, Q18].

Strategic resilience: Integrating scheduling, supply chain management, and advanced operations techniques in production risk analysis and technical efficiency of rice farming in flood-prone areas

Farmers face various risks such as production risks in the use of technology, pests, climate change and natural disasters. Farmers in disaster-prone areas have different responses depending on their behavior towards the risks posed. The main problem in this research is how farmers behave towards production risks due to flooding and the technical efficiency of rice farming in flood-prone areas. The aim of this research is to analyze farmers' behavior towards production risks due to flooding and the technical efficiency of rice farmers in flood-prone areas. The results of this research will provide important information for policy simulations that the government can implement towards farmers affected by natural disasters and for sustainable disaster mitigation strategies. The novelty of this research is that it combines two theories, namely risk behavior and agricultural technical efficiency in producing disaster mitigation strategies. The research location was determined purposefully in Pasuruan and Bojonegoro Regencies. The data in this research are primary and secondary data with the sample in this research being farmers. The sampling technique in this research is a multi-stage cluster sampling technique. The analysis method in this research uses Just Pope. and the Cobb-Douglas production function model with the Stochastic Production Frontier approach. The target of these research findings is a model of the types of behavior regarding the risks of farmers who are flood victims, as well as the level of technical efficiency of rice farming and the factors that influence it. The expected findings are policy recommendations regarding disaster mitigation from economic and agricultural risk aspects to create sustainable agriculture.

TECHNICAL EFFICIENCY IN BITTER MELON PLANTS USING DATA ENVELOPMENT ANALYSIS (DEA) MODEL IN TANAH LAUT DISTRICT

Farm technical efficiency involves maximizing output while minimizing input costs. In Tanah Laut Regency, bitter melon production fluctuates annually due to climatic factors and inefficient input use. On average, farmers use 0.47 hectares of land, 166 grams/ha of seeds, 2,659 kg/ha of organic fertilizer, 208 kg/ha of inorganic fertilizer, 7.08 liters/ha of liquid pesticides, 7.24 kg/ha of solid pesticides, and 339 HKSP of labor. Data Envelopment Analysis (DEA) indicates that farmers are technically inefficient, with average technical efficiencies of 80.8% (CRS-DEA), 89.9% (VRS-DEA), and 89.8% (SE-DEA). Among the farmers, 32% operate under increasing returns to scale (IRS), 26% under constant returns to scale (CRS), and 42% under decreasing returns to scale (DRS). A logit regression model reveals that education level, farming experience, and number of family members significantly impact technical efficiency, while age, land ownership status, and off-farm income do not. To enhance efficiency, farmers should reduce input use by emulating the practices of their more efficient peers.

Do agricultural technical efficiency and technical progress drive agricultural carbon productivity? based on spatial spillovers and threshold effects

Do agricultural technical efficiency and technical progress drive agricultural carbon productivity? based on spatial spillovers and threshold effects

Power Mechanism and Practical Path of Agricultural Insurance to Help Rural Revitalization

Abstract This paper firstly explores the power mechanism of agricultural insurance to help rural revitalization from three aspects of agriculture, farmers and rural three farmers, respectively, and constructs the rural revitalization development index system by combining the entropy power method. Then, the three-stage DEA model and the three-stage Malmquist index model are used to measure the efficiency of agricultural insurance boosting rural revitalization by combining the selected agricultural insurance boosting indicators. Finally, taking province A as an example, after descriptive statistical analysis, the method of this paper is combined with empirical analysis, and the practical path of agricultural insurance to help farmers is proposed from the three aspects of the insurance system, publicity as well and supply. The results show that after the optimization of agricultural insurance, the value of technical efficiency is distributed in [0.600, 0.738], the value of pure technical efficiency is distributed in [0.716, 0.826], and the value of scale efficiency is distributed in [0.738, 0.833] from 2010 to 2019. The mean value of the agricultural technical efficiency index in each city is 1.091, the mean value of the progress index is 1.033, and the mean value of total factor productivity is 1.029, which is an upward trending technology, and all of them have a growth rate of more than 5%. Based on this study, agricultural insurance can help improve the efficiency of rural revitalization.

Migrant Labor and Farm technical Efficiency of Paddy Production in North Bihar

"It has long been known that migration and remittances contributed to the growth of agriculture. This study was conducted in East Champaran and West Champaran for paddy production. Multistage random sampling was applied to the study area. The study area was selected based on the annual production of Paddy in Bihar. Stochastic Frontier Analysis was applied to get an appropriate result for remittance on paddy farming. Our findings have important policy ramifications because they suggest that smallholder paddy production may become more technically efficient by using migrant labour’s remittances more frequently. By providing small-holder growers with continuously growing support from extension services, enough market access for selling their product, and farmer empowerment for women, the government may be able to increase the technical efficiency of smallholder rice farmers. Instructing farmers on correct weeding schedules, for instance, would be one way that effective extension services might enhance crop management practises."

The role of rational decisions in technical inefficiency analysis of Spanish pig farms: The influence of water use management

There has been limited research on the degree to which rational inefficiency arises when environmental factors are considered. Thus, our goal is to contribute to the literature by applying the concept of rational inefficiency to pig farming and investigating the relationship between water use and farm technical efficiency levels. This research aims to provide a better understanding of the complex interactions between pig farming production, the natural environment, and economic performance. The stochastic frontier analysis is applied to a cross-section dataset of 523 Catalan farms specialized in pig production in 2018. The main findings of this study are as follows: First, Catalan pig farming exhibits high levels of technical efficiency with an average score of 0.94, which is consistent with the high intensity and concentration of Spanish pork production. Second, there is no compelling evidence to support the rational inefficiency hypothesis, particularly when comparing the rational efficient and multi-efficient groups.

Internet use and technical efficiency of grain production in China: a bias-corrected stochastic frontier model

Internet technology has unique advantages, such as rich information, rapid dissemination, and overcoming spatial limitations. It is considered an effective approach to promote agricultural technology application and enhance agricultural technical efficiency. However, it is still unclear how Internet use affects the technical efficiency of smallholders in grain production. Based on the grain production data of 1699 smallholders in China, this study uses the bias-corrected stochastic production frontier and propensity score matching to obtain an unbiased estimate of the impact of Internet use on technical efficiency and examines its channels of action. The empirical results indicate that the decision of households to use the Internet is influenced by the individual characteristics of the household head, household characteristics, and village characteristics. The age of the household head has a significant negative impact on Internet use, while the education level and health status of the household head, household income and size, and the topography of the village have significant positive effects on Internet use. We also find that Internet use has a statistically significant positive effect on technical efficiency, and the selection bias leads us to underestimate this effect. Furthermore, we verified the channels of Internet use affect technical efficiency by alleviating financial constraints, broadening social capital, and improving the level of mechanization. Therefore, policymakers must strengthen the construction of Internet infrastructure in rural areas and improve the Internet penetration rate in rural areas. Furthermore, policymakers can establish technical training centers to help farmers learn Internet technology and new agricultural production techniques. Lastly, policymakers can collaborate with banks, research institutions, cooperatives, agricultural enterprises, and other entities to develop diverse policy measures that provide farmers with financial support, technology assistance, and production services.

Retracted: The Impact of Agricultural Land Rights Policy on the Pure Technical Efficiency of Farmers' Agricultural Production: Evidence from the Largest Wheat Planting Environment in China.

[This retracts the article DOI: 10.1155/2022/3487014.].

Technical efficiency and its determinants on lentil (Lens culunaris) production in Nepal

Lentil is one of the important pulse crops of Nepal and has high export potential. This study aimed to analyze the technical efficiency of the lentil production system and its determinants. A multistage sampling technique was employed to select respondent farmers from four districts representing three provinces in Nepal. Primary data were collected through face-to-face interviews with randomly selected 473 respondents using a semi-structured interview schedule. To derive the results, the stochastic production frontier and Tobit model were adopted. The average lentil output in the study area was found 672.6 ​kg ha-1 and the input variables such as seed, labor, tractor use, and area were the significant inputs increasing the output of lentils. The mean technical efficiency percentage for the pooled sample was 61.5% with a range between 23.0% and 89.9%. Further, the result revealed that average-performing farmers and least-performing farmers need to reduce their costs by 42.82% and 85.65%, respectively to attain the status of the most efficient farmer. Education, membership in groups and cooperatives, weeding practice, use of improved seed, and lentil farm size were found as determinants of technical efficiency in lentil production and unit increment of those variables favor lentil yield by 0.3%, 2.6%, 21.5%, 3.1%, and 3.1% respectively. As there is room to increase lentil output by using inputs efficiently, the government and related stakeholders should motivate farmers to get involved in groups and cooperatives to pool resources together and share information. Based on the results, with the application of current available resources farmers are strongly recommended to maintain their lentil farm size between 0.5 and 1 ​ha, use improved varietal seed, and also follow at least one weeding operation to increase their farm technical efficiency level by 21.5%.

Some Theoretical and Practical Aspects of Technical Efficiency—The Example of European Union Agriculture

The main objective of this article is to better understand the category of technical efficiency of agriculture. To achieve this goal, empirical research was carried out, the subject of which was to estimate the average technical efficiency of agriculture in the European Union in the years 2004–2020. The technical efficiency of agriculture was estimated using the Data Envelopment Analysis method–Cooper Rhodes Input Oriented model. In order to estimate the level of technical efficiency, the value of Total output was adopted as the output, and the following inputs were adopted: Total Utilized Agricultural Area, Fertilizers, Plant protection products, Total livestock units, Feed for grazing animals, Labor inputs, Machinery and equipment, and Gross expenditure on fixed assets. The conclusions from the literature review indicate that technical efficiency is the main determinant of economic efficiency. The conclusions from empirical research have shown that agriculture in the European Union is characterized by a high level of technical efficiency for 2004–2020, TE = 90.24%. Moreover, the technical efficiency of farms was checked according to classes of economic size. The obtained results only partially confirm that the increase in the economic size of a farm increases its technical efficiency, because the highest level of technical efficiency is characteristic of farms that belong to the classes very small and very large.

Farmers’ Technical Efficiency and their Adoption to New Variety of Sorghum: Evidence from East Java of Indonesia

Objective: The study delves into the technical efficiency of sorghum cultivation and evaluates the effects of the adoption of the new superior variety on the efficiency of farmers. Methods: The research employs a methodology that involves the use of stochastic frontier analysis and propensity score matching to examine cross-sectional data obtained from a sample of 150 farmers located in Lamongan Regency, East Java, Indonesia. Results: The findings indicate that sorghum farmers exhibit suboptimal levels of technical efficiency. The adoption of the bioguma variety has a positive impact on the technical efficiency of farmers. Farmers who choose to implement bioguma demonstrate superior levels of efficiency in comparison to their counterparts who utilize alternative varieties. Suggestions: The study suggests that policymakers should take steps to enhance access to high-quality seeds and encourage farmers to adopt improved varieties. This can be accomplished through measures such as targeted subsidies, favorable credit schemes, or collaborations with seed companies to ensure the availability and affordability of the bioguma variety.

Analysis of Technical Efficiency and Determinants of Cereal Production on Family Farms in the Dogon Plateau in Mali

The area of the Dogon plateau located in central-eastern Mali is an arid agricultural region with difficult morpho-pedological and climatic conditions where peasant populations derive their income and especially their food from agriculture. The objective of this study was to determine the level of technical efficiency of family farms in this area and subsequently to identify the factors explaining their inefficiency. Data were collected from a sample of 400 farms through a quantitative survey. The stochastic frontier production method was used to determine their efficiency scores. Truncated regression was used to identify farm inefficiencies.
 The results of the study show that in the Dogon Plateau area family farms have an average efficiency score of 72.75%, which means an overall loss of 27.25% of production factors. The maximum efficiency score is 92.60% against a minimum of 0.21%. In addition, it appears that less than 20% of farms in the area have a below-average technical efficiency score.
 The analysis of the determinants of the technical inefficiency of farms shows that the association of agriculture with livestock, the possession of agricultural land with a land title and the cultivation of onion/shallot positively and significantly influence the level of technical efficiency of family farms in the Dogon Plateau area. Contrary to our expectations, the decrease in cultivated areas due to the residual insecurity of our study area has no significant effect on the technical efficiency of the farms.