Farm Level Technical Efficiency Research Articles

Impact of climate change on farm-level technical efficiency in Punjab, Pakistan

This paper assessed the impact of climate change on farm-level productivity and technical efficiency in the Punjab province of Pakistan. The stochastic production frontier model was employed at the farm household level for 3 yr of panel data (n = 537) covering 3 cropping systems (rice-wheat, cotton-wheat, and mixed wheat) from 3 different agro-ecologies and 17 of 36 districts of Punjab. Though the use of inputs was found to have a positive impact on farm production, results highlight the strong negative impacts of the increase in the long-run temperature normals and fluctuating precipitation across the crop production seasons. Weather shocks and socioeconomic factors of the farm family significantly contributed to the farm’s technical efficiency. A mean technical efficiency score of 0.82 suggests that with the use of climate-smart technologies and improving farm management involving better use of production inputs, there is potential for improvements in farm-level technical efficiency. The declining trend in the mean technical efficiency due to weather shocks necessitates the adoption of climate-smart agricultural practices. However, this requires that farmers should be supported with targeted coping options for expected weather shocks differentiated by crop production zones. A well-coordinated climate and extension service can support the adoption of climate-smart agriculture for sustainable crop production.

Technical efficiency of early variety country bean cultivation in selected areas of Bangladesh: a stochastic frontier approach

The present study was undertaken to measure the profitability and technical efficiency of early variety country bean cultivation in selected areas of Chatmohar upazila of Pabna district. A total of 60 early variety country bean-growing farmers were selected from three villages of Chatmohar upazila using a simple random sampling technique. Stochastic frontier production function was applied to determine the technical efficiency of the country bean growers. Technical inefficiency effects model was also applied to identify the demographic and socio-economic factors by which inefficiency effects are influenced. The study revealed that Benefit Cost Ratio (BCR) was the highest (2.29) for large farmers followed by medium (2.27) and small farmers (2.21). The result of the Maximum Likelihood Estimates (MLE) showed that human labor, fencing and manure had significant positive impact whereas the irrigation and insecticides had a negative impact on the production of country bean. The results of technical inefficiency effect model showed that farmer’s age, farm size had negative impact while education, family size and farm credit had positive impact on technical efficiency. The inefficiency analysis results indicated that farm level technical efficiency ranged between 43.06% and 98.01% with a mean technical efficiency of 91.9% implied that there was potential to increase country bean production among smallholder farmers in the study area by 8.1% through efficient use of present technology. The main constraints to country bean (early variety) production were identified as- infestation of pest and disease, high price of inputs, paucity of quality seed and fertilizer, scarcity of human labor, lack of technical knowledge, limited access to institutional credit etc. Despite the constraints, there is a great prospect of early variety country bean production in the study areas. Country bean (early variety) production could be increased in a sustainable manner if farmers would be provided with government support regarding lower price of input, fair price of output, marketing facilities, training for farmers and farm credit at low interest rate, reducing the activities of syndicate of middlemen. Government should provide necessary support to the farmers for ensuring sustainable production of early varieties of country bean. Res. Agric. Livest. Fish. Vol. 10, No. 2, August 2023: 155-164

Spatio-temporal performance of major edible oilseeds in Andhra Pradesh

The current analysis examines the spatio-temporal performance of major edible oilseed crops viz., groundnut, sesame and sunflower in Andhra Pradesh using time series data from 1970-71 to 2018-19. The total period wasdivided into three sub-periods viz., Period I (1970-71 to 1985-86), Period II (1986-87 to 1999-2000) and Period III (2000-01 to 2018-19). Agro-climatic zones, in which these crops were consistently grown, were selected and theirperformance was evaluated using compound annual growth rates and decomposition analysis. Growth of area and production of groundnut and sunflower exhibited frequent declined growth rates, particularlyin Period III, signifying the underperformance of these crops. The performance of sesame was better vis-a-vis groundnut and sunflower. There was no significant decline in growth rates of yields, which could be partly attributed to efforts from the research community and government to increase the yield through various oilseeds development programmes. Although efforts were made towards increasing area, production and yield, the positive growth momentum of area and production could not be sustained. Shift of major oilseeds' cultivation towards competing crops, low profitability, unremunerative market prices, low farm level technical efficiency, increased costs of inputs, higher biotic and abiotic stresses etc., could be some of the reasons for this scenario. Location specific research with focus on hybrids and HYVs with high oil content, addressing the constraints to technology adoption, favourable price policies, enhancing capacityutilization of processing units, creatingmore efficient supply and value chains mayhelpin meeting the oil and oilseed requirements in the country.

Determinants of technical efficiency of smallholder farmers’ bread wheat production and implications of seed recycling: A stochastic frontier approach

Background: Due to decreasing productivity trends, enhancing farm level technical efficiency (TE) in bread wheat production (BWP) is central to Ethiopia's food security strategy. This requires increased BW productivity through the use of improvements in seeds and TE. However, there is some empirical research that examines the institutional, socio-demographic, economic, and agronomic determinants of the TE of BWP simultaneously. Therefore, the purpose of this study was to analyze determinants of TE and the implication of seed recycling on TE. Methods: The data was gathered from 450 randomly selected sample respondents via structured interviews, focus groups, and interviews with key informants. Data collection took place from December 15, 2021 to January 15, 2022. BW growing smallholder farmers were the major respondent of the study. Quantitative type of data including the number of inputs used, amount of wheat produced, and socio – demographic, economic, agronomic, and institutional variables were gathered and analyzed. The TE and factors affecting it were examined using a stochastic frontier production analysis with a trans-log functional specification. Results: The coefficients for labour (0.086), capital (0.22), fertilizer (0.042), weedicide (0.014), and machinery (0.005) were significantly positive at p<0.001 implying that an optimum increase to these inputs would increase BWP. The mean TE was found to be 79.99% indicating that farmers in the study operate 20.01% less than their potential. Nine of the hypothesized variables (69.2%) had significantly affected TE. Moreover, seed recycling reduced TE by 2.34%. Conclusion: Findings suggest that few farmers are able to grow BW either on the frontier or very close to it, which denotes high TE and poor access to improved seeds leading to seed recycling. Therefore, the farmer-to-farmer (F2F) extension method, which enables farmers to learn from their neighbors and create wider access to improved seeds through seed loans and vouchers are strongly suggested.

The effect of crop insurance in Ecuadorian rice farming: a technical efficiency approach

PurposeThe aim of this study is to estimate the technical efficiency of the massive and economically important crop of rice in Ecuador, and then conduct a comparison between groups of farmers with and without insurance.Design/methodology/approachThe authors use an input-oriented data envelopment analysis approach (DEA) to estimate technical efficiency scores. The DEA is combined with the double bootstrap approach in Simar and Wilson (2007) to study factors that may affect technical efficiency. This method overcomes the traditional two-stage DEA approach frequently used in the efficiency literature. The authors thus research the role of insurance on rice efficiency production using this technique and sizeable field-level survey data from 376 rice farmers distributed in five provinces during the 2019 winter cycle in Ecuador.FindingsMost uninsured rice farmers operate with increasing returns to scale, which means that farms improve their resource use efficiency by increasing their size. However, since scale efficiencies are relatively high, it appears that inefficiencies are explained by inadequate input use. Also, the authors find evidence that insured farmers have a negative relationship with technical efficiency in rice production. In other results, when exploring the influence of additional variables on efficiency, the authors find that parameters related to transplanting, high education, farm size and some locations are positive and statistically significant.Social implicationsThe results of this work are relevant for policymakers interested in evaluating technology performance, risk management instruments and farm efficiency in an industry in a developing country such as rice production in Ecuador.Originality/valueThis paper is the first attempt to estimate farm-level technical efficiency employing the double bootstrap approach to assess the efficiency and its determinants of Ecuadorian rice producers.

Measuring the impact of pesticide exposure on farmers’ health and farm productivity

The motivation of this paper stems from the growing concern of heavy pesticide use in developing countries such as Sri Lanka. Its excessive use affects the environment, the economy and farmers’ health and yet farmers still seem unaware of its ill-effects. More worrying is the lack of appropriate government efforts to address this problem. If neglected, heavy use of pesticide eventually renders land useless, reduces future farm output and productivity and can severely affect farmers’ health. This paper investigates pesticide use in agriculture and its impact on farm level technical efficiency using a metafrontier framework with stochastic frontier analysis. Data are collected through surveys of two groups of farmers in Sri Lanka. The first (described as the ‘non-hospitalized farmers’) are farmers who perceive that their ill-health is due to exposure to pesticides and obtained treatment but are not hospitalized. The second group (described as the ‘hospitalized farmers’) are farmers whose ill-health has been diagnosed by doctors and have been treated in hospital for exposure to pesticides. The results show that farmers overuse pesticides because of higher expectations of future returns which has led to an increase in inefficiency and remains unknown to the farmers. Determinants of inefficiency supports the argument that pesticide induced health problems reduce the health capital, while increasing farm level inefficiency.

Analysis of Levels and Determinants of Technical Efficiency of Teff Producing Farmers: The Case of East Gojam Zone, Amhara Region, Ethiopia

This study explores Technical Efficiency level of smallholder teff production and also investigates socioeconomic determinants explaining the variation in Technical Efficiency among smallholder teff farmers using 396 random sample farm households in East Gojam Zone of Amhara regional state, Ethiopia. Cobb-Douglas Stochastic Frontier Model was fitted to estimate farm level technical efficiency and the associated efficiency scores since the function has been one of the most widely used models among the potential algebraic forms of production function in most empirical studies of agricultural production analysis. Both Maximum Likelihood (ML) and quantile regression (QR) techniques were employed to conduct the analysis of technical efficiency determinants. And the study revealed that a one % increase in the input level of plot size, seed, fertilizer, man-days and oxendays respectively produce a return of 0.30, 0.11, 0.02, 0.28 and 0.14% increase in output, keeping all other factors constant. In general, the result had underlined farmer’s opportunity to boost their productivity by optimizing the level of the inputs they are using. On this study the mean levels of the actual and potential output during the production year were 14.00 qt/ha and 21.07 qt/ha and, hence, with 7.07Qt/ha yield gap. Therefore, the ratio of the average yield gap to the average actual yield entails the possibility to increase the average plot level output by 50.5% through improving producers TE under the prevailing production input and technology level. The study also identified that farmers with more fertile plots are technically efficient as compared to those who cultivate marginal lands, keeping all other factors constant. Besides, those teff farmers who use compost have lower inefficiency as compared to those farmers who do not utilize compost in the study area. Moreover, education level influenced efficiency of teff farmers positively. Therefore, the study recommends the concerned bodies to give emphasis to promote education, and to have integrated soil fertility management policy targeting soil fertility enhancement to move the marginalized smallholder farmers TE closer to the frontier. Keywords: Technical efficiency, Stochastic frontier model, Quantile regression, Teff, Amhara, Ethiopia DOI: 10.7176/JESD/13-9-02 Publication date: May 31 st 2022

Farm-Level Technical Efficiency and Its Determinants of Rice Production in Indo-Gangetic Plains: A Stochastic Frontier Model Approach

This research was conducted to explore the factors affecting the technical efficiency (TE) of rice producers and its determinants at the farm level. We used a multi-stage sampling procedure to collect cross-sectional data from 800 rice growers in the Uttar Pradesh state of India, and a stochastic frontier model (SFA) was applied. The results showed that the mean technical efficiency was 72%, suggesting scope for a substantial increment in rice productivity exists while using the current level of inputs and technologies. Furthermore, the MLE results revealed that labor, irrigation, and hybrid seeds had a constructive impact on technical efficiency, while experience and tenure status showed a negative impact on technical efficiency. As unraveled by the results of the study, it can be concluded that the technical efficiency of rice farmers can be improved through timely access to credit and agricultural information delivered to them via extension services. The study, therefore, recommends that the government provide subsidized agrochemicals and focus on developing a robust network of extension services throughout the local districts for proper dissemination of inputs. About 12% of India’s rice is produced in the Uttar Pradesh state. So, this study could be an essential tool for the agriculture sector, which could help to solve rice productivity problems for future generations.

Technical Efficiency of Ginger Production in Ilam District of Nepal: A Stochastic Production Frontier Approach

This study measured the level of technical efficiency among smallholder ginger growers and examined the determinants of inefficiency by employing the stochastic frontier production function. The paper used a simple random sampling technique to interview 100 ginger farmers in Ilam, a leading ginger-producing district in Nepal, with the help of a pretested interview schedule. The STATA.13 software was used to obtain both stochastic frontier estimates and the determinants of technical inefficiency. The results revealed that the average farm-level technical efficiency is 67.8% which shows the scope of increasing the technical efficiency by 32.2%. The coefficients of seed and farmyard manure were positive and showed significant relation to ginger output at a 1% and 5% level of significance, respectively. Education level, training, and membership in cooperatives had a negative and significant impact on technical inefficiency, whereas areas under ginger production had a positive impact on technical inefficiency. Hence, improving the technical knowledge of farmers through training on optimum input use complemented with motivation to join agriculture cooperatives and farmer’s associations may increase the technical efficiency of ginger growers in the study area.

Analyzing the Impact of Subsidies on Beef Production Efficiency in Selected European Union Countries. A Stochastic Metafrontier Approach

The European Union Common Agricultural Policy reforms since the early 2000s allowed for the implementation of different types of agricultural subsidies, such as direct support in the form of decoupled and coupled payments, or agri‐environmental payments. As a result, there are significant differences in agricultural subsidies granted in each member state of the European Union. However, there is limited cross‐country comparative empirical evidence regarding the effects of the implementation of different levels and types of subsidies on farm efficiency. Using farm level data for beef farms in Ireland, France, Great Britain, and Germany between 2005 and 2012, we implement the stochastic metafrontier proposed by Huang et al. (2014) and attempt to correct for endogeneity applying the method in Shee and Stefanou (2015). Using these approaches, we contribute to the literature by consistently comparing cross‐country farm performance, as well as exploring the disaggregated effects of different types of subsidies on farm level technical efficiency and on the technology gaps. Our estimates show that although beef farms included operate on average close to the global frontier, there is scope to improve farm level managerial performance. However, they do operate close to the global frontier, although not on it. We also find evidence that implementing full decoupling benefited efficiency, whereas implementing partial decoupling might have hindered technical efficiency improvements for beef farms, as well as technology catch up.

Farm Level Technical Efficiency of Paddy Production in Andhra Pradesh: An Empirical Evidence from the Cost of Cultivation Survey Data

The study calculated technical efficiency, Data Envelopment Analysis technique was employed, one of the non-parametric linear programing techniques to estimate the farm level technical efficiency of paddy production in Andhra Pradesh. This secondary data set contained 541 paddy producing farms/units across Andhra Pradesh state under five agro climatic zones viz North coastal, Godavari, Krishna, Southern and Scarce rainfall zones was studied. The results showed that the overall technical efficiency of the entire sample is 86.8 per cent inferring that about 13 per cent of the potential paddy yield is lost because of technical inefficiency in Andhra Pradesh. The yield gap was found to be 981.10 kg/ha in Godavari zone and a minimum yield gap of 335 kg/ha in North coastal zone with an average yield gap of 663 kg/ha for Andhra Pradesh indicating domestic paddy production could be significantly increased only by improving farmers practices with the current amount of resource they are using. The study suggested that there should be exposure to improved technologies, frequent trainings and experience sharing mechanisms with efficient resource management practices.

Determinants of technical efficiency of potato farmers and effects of constraints on potato production in Northern Ethiopia

AbstractTo improve the national average yield of potato in Ethiopia, which is very low as compared to its potential, factors that influence technical efficiency of potato production need to be determined. Therefore, the objective of this study was to investigate the determinants of technical efficiency using a cross-sectional data collected from 368 randomly selected potato producers in Northern Ethiopia using a multi-stage sampling technique. The study employed Cobb–Douglas stochastic frontier model to get farm-level technical efficiency scores. Tobit model and principal component analysis were used to determine the factors that influence technical efficiency of farm households. The results revealed that chemical fertiliser, seed potato, plot size and labour are statistically significant factors that affect potato yield. The average technical efficiency score was estimated to be 75%; and education, experience, off-farm income, household size, membership in a farmers’ association, use of irrigation water, extension contact, use of improved seed, access to product market and weak coordination of stakeholders’ were significant factors influencing technical efficiency. The findings of the study suggest that there is a need for government intervention to create strong market linkage between producers and buyers and to give appropriate training to agricultural extension agents.

Analysis of technical efficiency among rice farmers in Ebonyi State of Nigeria: A stochastic frontier approach

This paper analysed the technical efficiency of rice farmers in Ebonyi State, Nigeria. It specifically analysed the levels and determinants of technical efficiency. A multistage sampling technique was adopted for sample selection. A total of 150 well-structured questionnaires were distributed but only 91 were returned. The Cobb-Douglas production function model was used to predict the farm level technical efficiency. Results from the Cobb- Douglas Regression showed a sigma square (σ2) of 0.06584 which was statistically significant at 1 percent. The technical efficiency scores among the rice farmers ranged from 0.012 to 1.000 with a mean of 0.350. Farm size, quantity of rice seedlings, quantity of fertilizer and quantity of agrochemical all were showed positive correlation with coefficients of 0.93511, 0.08310, 0.11200 and 0.14345 respectively while farm labour showed a negative correlation with technical efficiency. The determinants of technical inefficiency were age, household size and extension visits. This paper advocates the strengthening of existing extension system for timely sourcing of highly improved rice varieties and subsidized fertilizer. There is the need to enhance farmers’ technical efficiency through adequate training on optimum input mix.
 Keywords: Rice production, technical efficiency, cobb-douglas production function

Technical Efficiency of Irish Potato (Solanum tuberosum L.) Production in Molo Sub County, Kenya

This study focused on measuring farm level technical efficiency among smallholder Irish potato farmers in Molo Sub County and its determinants. Descriptive research design was applied. Cross-sectional data was collected through multistage sampling from smallholder Irish potato farmers located in Molo Sub County from April to June 2019. A Stochastic frontier approach assuming a Cobb-Douglas production function was adopted to analyze the level of technical efficiency and explain variations in this technical efficiency across farmers and estimation was done by applying the maximum likelihood method. Mean technical efficiency was 70.7%. The statistically significant variables with respect to the farm inputs were land (0.262), seed (0.629), fertilizer (-0.299) and fungicide (0.131) variables respectively. However, fertilizer variable had negative effects on Irish potato production. Education (-0.061), gender (-0.262), access to extension services (-0.078) and farmer group (-0.217) variables were significant and influenced technical inefficiency negatively.Increase in smallholder farmers’ literacy level, accessibility to extension services and farmer groups may improve Irish potato production technical efficiency. However, gender contribution towards Irish potato production technical efficiency needs a deeper understanding.

English

The aim of the study was to determine the farm level technical efficiency and its determinants among smallholder sugarcane farmers in Malava Sub-county, Western Kenya. Primary data were collected using questionnaires from a sample of 384 farmers through systematic random sampling.  The study applied stochastic frontier analysis and Tobit regression analysis using computer software STATA. The results found that technical efficiency of sugarcane farmers ranges from almost zero to 0.9829, with mean value of 0.7069, implying that an average farmer could increase sugarcane productivity by 29.31% at the existing level of resources. Maximum likelihood estimate of technical efficiency depicted that the use of fertilizer, labour, seed-cane and farm size are positive and significant at 1% level in determining technical efficiency. Tobit regression analysis showed that education, farming experience, family size, credit access and extension services were positive and significant in contributing to technical efficiency. However, age of the farmer, farm distance from home and contract engagement was negatively influencing technical efficiency. The study recommends the Kenyan government to formulate policies that ensure provision of quality extension services, increased credit access and education among smallholder sugarcane farmers. The results also recommended the need for a review of the existing contract engagement policies among sugarcane farmers. Key words: Technical efficiency, stochastic frontier analysis, tobit, sugarcane. &nbsp

Do farm-level technical efficiency and welfare complement each other? Insight from Ghana\u2019s cocoa industry

Technical inefficiency persists in Ghana’s cocoa farms. Farm-level guidelines from empirical studies are essential to inform programmes dealing with this challenge and subsequently improves farmers’ welfare. This study evaluates the two-way effects of technical efficiency and welfare using Data Envelopment Analysis (DEA) and Conditional Mixed-process (CMP). The study reveals that, with no additional inputs, farmers have the potential of increasing their output by an average of 56% (overall technical efficiency) with mean pure technical and scale efficiencies estimated at 76% and 58%, respectively. Observed inefficiency in the Ghanaian cocoa farms is due to both inefficient utilization of inputs and farmers’ inability to operate at the most productive scale size. Furthermore, findings from the study indicated that improved technical efficiency and welfare of smallholder cocoa farmers are crucial for the sustainable growth of Ghana’s cocoa sector as farmers’ efficiency and welfare significantly complement each other. In other words, improved welfare enhances technical efficiency, and higher technical efficiency score translates into better welfare. Hence, farm-level policies such as inputs subsidy programmes, training farmers on the proper application of agrochemicals, among others to enhance farm efficiency should be strengthened since efficiency is tied to household welfare. Moreover, investment in education targeted at farmers to improve their managerial and technical capacities will enhance their ability to optimize the operational size of the cocoa production system, and subsequently improve their welfare.

Estimation of Farm Level Technical Efficiency in Maize Production at the High Mountain North Region of Pakistan

Estimation of Farm Level Technical Efficiency in Maize Production at the High Mountain North Region of Pakistan

TECHNICAL EFFICIENCY IN ARABLE CROP PRODUCTION UNDER GORONYO IRRIGATION PROJECT OF SOKOTO STATE, NIGERIA

The study examined the technical efficiency in arable crop production under Goronyo irrigation project of Sokoto State, Nigeria. Multi-stage sampling technique was used to sample 246 farmers and the limited cost-route approach was used with the aid of questionnaire. Stochastic frontier production function (SFPF) model was used in estimating farm level technical efficiency. The study also revealed the average technical efficiency index of rice, maize, cowpea and tomato farms to be 0.87, 0.79, 0.45 and 0.76, respectively and that technical inefficiency effect existed among the farmers. Estimates of technical efficiency of farmers revealed that average sampled farms operate 13%, 21%, 55% and 24% below the frontier output levels for rice, maize, cowpea and tomato farms under consideration. Farmers are fairly efficient technically in deriving maximum output from rice, maize and tomato farm and less technically efficient in the production of cowpea. Extension contact was one of the major factor that influences technical efficiency in the area, therefore, sustained farmers extension contact should be encourage by increasing frequency of contact where new techniques will be disseminated to the farmers to improve the use of available resource.

Measuring Technical Efficiency and Returns to Scale in Indian Agriculture Using Panel Data: A Case Study of West Bengal

The study investigates farm level technical efficiency (TE) and its determinants in the state of West Bengal in India. A stochastic production frontier model has been applied for determining technical efficiency by using panel data on 17 agricultural production units over a period of 23 years. Maximum-likelihood estimates of the Cobb-Douglas stochastic frontier production function in a time-variant truncated normal distribution is appropriate for the measurement of technical efficiency of West Bengal agriculture in India. The estimated variance ratio indicates that 48.90 percent of the differences between the observed and the estimated output is caused by differences in farms’ technical inefficiencies. However, the remaining variation is due to factors beyond farmers’ control. The study shows that the agricultural farms in West Bengal exhibit increasing returns to scale in production. The study finds that farmers’ education and agricultural extension are important determinants of technical efficiency. Other prominent determinants that have a significant contribution are farm size, crop diversification, number of available agricultural markets, the proportion of small landholders and input intensity. All these determinants, excluding the proportion of small landholders, have a largely positive impact on technical efficiency. The maximum-likelihood estimation (MLE) and principal component analysis (PCA) are applied to determine the effects of determinants on TE. Both methods give similar results.

Productivity and Resource Use Efficiency in Wheat: A Stochastic Production Frontier Approach

Farm level technical efficiency and its determinants in wheat production in the state of Bihar has been studied using stochastic frontier production function model. The average productivity of wheat was reported 28.43 q/ha which was below the national average of 30.33 q/ha during 2016-17. The resource inputs were found inelastic and not being properly utilized. All the resource inputs were found positive and significant at 1 per cent and 5 per cent level of probability except machine labour used which was negatively significant, indicating overuse of machine labour or costly machine labour. The mean input efficiency in production of wheat in the state was estimated to be 94 per cent, emphasizing that efficiency may be enhanced by 6 per cent. The factors influencing efficiency were identified as education, family size and landholding size. The mean technical efficiency was found to be 0.94 indicted that optimal and sustainable use of resource inputs may further raise the input use efficiency in wheat production by 6 per cent and consequently boost up the income of the wheat cultivators in the state.