Measuring efficiency of cotton cultivation in Pakistan: a restricted production frontier study

We estimate the efficiency of groundwater use in cotton production in the Punjab province of Pakistan. We use a survey data of 189 cotton producers comprising 98 tube-well owners and 91 water buyers in order to get the differential impact of tube-well ownership on groundwater use efficiency. We use data envelopment analysis to compute the technical, scale, cost and allocative efficiencies for tube-well owners and water buyers relative to a meta-frontier and groupfrontiers. The DEA sub-vector and slack-based models are used to compute groundwater use efficiency. The results indicate low levels of technical inefficiencies with water buyers being more inefficient relative to tube-well owners. However, groundwater use inefficiency is more pronounced than the respective technical efficiency. The sub-vector and slack-based estimates are highly correlated suggesting the robustness of the results. The results on returns to scale indicate that the majority of cotton growers are operating at increasing returns to scale, suggesting that efficiency can be improved by expanding the scale of operation. We use a second-stage bootstrap truncated regression to investigate the factors that influence technical efficiency and groundwater use efficiency. We find that the level of education, seed quality and extension services have positive significant impacts on technical and groundwater use efficiency. We suggest that knowledge of crop water requirements and the use of improved crop varieties can play role in improving the efficiency of groundwater use.

The depletion of groundwater aquifers has raised serious concerns about the sustainability of groundwater resources with serious repercussions to irrigated agriculture in Pakistan. Within the context of diminishing water resources, it is important to improve agricultural water productivity by making efficient use of the available water resources. This study uses bootstrapped metafrontier data envelopment analysis to investigate technical and irrigation water use efficiency (IWE) of wheat farming in Pakistan. The study uses a cross‐sectional dataset of 200 groundwater‐irrigated wheat farms comprising 100 tube‐well owners and 100 non‐owners (water buyers). The study results suggest considerable improvements in technical and IWE in wheat production among the surveyed farms. The tube‐well owners, on average, are 82% and the water buyers, on average, are 77% technically efficient under the metafrontier framework with slightly higher estimates under the group frontier estimations. The IWE estimates indicate, on average, 66% and 65% IWE among tube‐well owners and water buyers when assessed under the metafrontier specification. As technical efficiency, the group frontier estimates indicate slightly higher IWEs compared to the metafrontier estimates. The most influential factors affecting technical and IWE include farmers’ education, improved seed variety, and farmers’ perceptions about groundwater resource quality and availability.

Diminishing irrigation water supplies are threatening the sustainability of irrigated agriculture in Pakistan. Within the context of dwindling water resources and low agricultural water productivity, it is imperative to improve efficiency in agricultural production and to make efficient use of available water resources. This study employs a non-parametric approach to estimate the extent of technical and irrigation water efficiency in sugarcane cultivation in Pakistan. The mean technical efficiency score is 0.96 for tube-well owners whereas it is 0.94 for water buyers. The mean irrigation water efficiency score is 0.86 for tube-well owners whereas it is 0.72 for water buyers. We find that across all farms, 59% of the tube-well owners and 45% of the water buyers are fully technically efficient, whereas only 36% of the tube-well owners and 30% of the water buyer are fully efficient in irrigation water use. This study finds that sugarcane growers are operating at fairly high technical efficiency levels. But, there is considerable potential to improve irrigation water efficiency. This study proposes expanding the role of agricultural extension services from merely agronomic grounds to guide farmers to undertake cost benefit analysis of the available production technology, would help achieve higher efficiency levels.

Assessing the efficiency of smallholder sugarcane production: The case of Faisalabad, Pakistan

Utilizing the stochastic frontier approach, this paper estimates output and input-oriented technical and scale efficiency levels for a sample of cotton-growing farms in Thessaly, Greece. The empirical results suggest that Greek cotton farm operations are technically and scale inefficient. There is a considerable scope for improvement in resource use and thereby in farm income of cotton farms; Greek cotton farmers could reduce production costs by 20.4%, making more efficient utilization of the existing production technology. Factors responsible for the technical efficiency differentials observed among cotton-growers include the farmer’s age and education as well as the farm’s land fragmentation and output specialization. JEL codes : C33, D24, O13 Key words : Technical and scale inefficiency, stochastic frontier models, cotton production, Greece. Introduction European Union agriculture appears to be at the crossroads. It can no longer continue to depend on the current support schemes as the financial costs of its Common Agricultural Policy – C.A.P. have boomed; the world marketplace is turning increasingly more competitive; and, potential new member-states with huge farm sectors are about to join the union. In this new environment, effective input use and rational utilization of farming techniques, that is, efficient exploitation of existing technologies is far more important than artificially high prices and farm import controls for the viability of farm operations. It follows that the measurement of existing inefficiencies in the agricultural production of the E.U. becomes of interest for at least two reasons: first, it can provide useful information on the technical efficiency of E.U. farm operations achieved in the context of current C.A.P. measures. And second, it can be used as a guideline for effective policy reforms in the direction of technical efficiency improvements in E.U. farming. In Greek agriculture, cotton has been a crop of major importance for domestic producers and a politically sensitive issue in resent years because, as explained in the next section,

Abstract. Olatidoye MS, Alimi T, Akinola AA. 2018. Quality assessment of the physico-chemical properties of vermiwash produced from different sources during successive storage periods. Asian J Agric 2: 58-63. The study investigated on socio-economic factors and estimated the technical efficiency indices and factors influencing technical efficiency of the sampled cotton farmers in the Southern Cotton growing zone of Nigeria. A multistage sampling technique was employed to select a total sample of 300 cotton farmers. The study made use of only primary data which was collected through the aid of a well-structured questionnaire. The data were analyzed using descriptive statistics and stochastic frontier production parametric model. The results of the descriptive statistics showed that majority (83%) of the cotton farmers in the study area were males while the mean age of the respondents was 49 years. The average household size was 8 persons per household and majority (69%) of the respondents had formal education. Majority of the respondents (59%) had no access to credit facilities while majority (80.4%) of the cotton farmers had reasonable years of experience ranging between 11 and above in cotton production. Furthermore, the study found that the technical efficiency of the farmers range from 0.35 and 0.99 with a mean of 0.79. This indicates ample opportunity for farmers to increase their productivity through improvement in their technical efficiency. Seed, fertilizer, pesticides and farm size were found to be statistically significant and positively related to farmers’ output while education, credit, extension contact and farming experience of the respondents negatively influenced farmers’ technical inefficiency. The farmers therefore need to increase their output through more intensive use of seed, land, pesticides and fertilizers.

In Pakistan, excessive lowering of the groundwater table has made crop irrigation costlier and without improving production efficiency, Pakistan’s rural economy will be adversely affected. This study estimated the technical, allocative, and groundwater use efficiency of wheat producers, identified the factors affecting their allocative efficiency, and suggested policy implications from these results. The data were collected from 84 tubewell owners, 65 tubewell shareholders, and 75 water buyers. The technical, allocative, and groundwater use efficiency were estimated by the Data Envelopment Analysis (DEA) method, and the important factors affecting the allocative efficiency were identified by two-limit tobit regression analysis. The results highlighted that the tubewell owners, tubewell shareholders, and water buyers had above 90% technical and groundwater use efficiency. However, allocative efficiency was substantially lower for all groups, indicating that wheat production costs could be significantly reduced by the optimal allocation of inputs. The allocative efficiency of wheat farmers decreased significantly with the increasing capacity of the tubewells, with the sharing of tubewells, and with the use of tractor-operated tubewells. The results imply that wheat farmers should be provided with technical and decision-making support to select an appropriate tubewell system that minimises their cost of production and improves their allocative efficiency. Furthermore, the resource allocation system of tubewell shareholders should be further studied to improve the allocative efficiency of wheat farmers.

This study investigates the technical efficiency and production constraints of hybrid and local cotton varieties in Kushtia district, Bangladesh, using primary survey data from 60 farmers (30 hybrid and 30 local). A Cobb–Douglas stochastic frontier production function was applied to estimate technical efficiency and identify determinants of inefficiency. Results indicate that hybrid cotton farmers achieved a mean technical efficiency of 92 percent, compared with 81 percent for local farmers, implying potential output gains of 8 and 19 percent, respectively, under existing input levels. For hybrid cotton, human labor, TSP, gypsum, and irrigation exerted significant positive effects on production, while urea showed a negative impact. Farm size, training, and farming experience were found to significantly reduce inefficiency. Local cotton farmers exhibited similar patterns, with human labor, TSP, and irrigation positively influencing yield. The analysis further identified key production constraints, including long cultivation duration (91.67 percent of farmers), low output prices (90 percent), insect infestations (83.33 percent), and adverse climatic conditions (75 percent). These findings suggest that targeted interventions—such as farmer training, improved resource management, expansion of farm size, and strategies to address systemic production constraints—can enhance cotton productivity and efficiency. Strengthening these areas could reduce Bangladesh’s heavy reliance on cotton imports and support the long-term sustainability of its textile sector.

Agriculture in Sub-Sahara Africa is considered as an engine of economic growth and has the potential to reduce rural poverty of smallholder farmers through increased food security and household income. However, most of Sub-Sahara Africa countries are faced with low agricultural productivity and this has undermined the potential to reduce rural poverty. The study focused on smallholder cotton producers in Zambia. Cotton is grown in Central, Eastern and Southern Provinces of Zambia and is an important cash crop which contributes over $60 million to the economy. It also supports over 150,000 households. However, productivity of smallholder cotton farmers in Zambia is low, around 800 kg per hectare or less. While in West Africa productivity is over 1000 kg per hectare. Agricultural productivity is defined as a measure of value of output for a given level of inputs. Efficiency is defined as the actual productivity of a farm relative to a maximal potential productivity. This shows that efficiency is related to productivity though it is productivity at maximum or minimum values. The study used the 2008 supplemental survey data collected by the Ministry of Agriculture and Cooperatives, Central Statistics and Food Security Research Project. Using Data Envelopment Analysis (DEA) this study determines the technical, allocative and economic efficiency indices of a sample of 812 (population estimates 150,801) cotton producers in Zambia. Using the Ordinary Least Squares (OLS) regression, the study determines the factors influencing technical, allocative and economic efficiency variations. Results show that the mean technical, allocative and economic efficiency indices in cotton production are 46%, 37% and 20% respectively. This means that Zambian cotton farmers could reduce input use and production cost without altering the output by improving technical and allocative efficiency by 54% and 63% respectively. Female headed households, number of years spent in school by the household head, leaving crop residues, value of productive assets and off farm income are some of the factors found to positively influence the technical, allocative and economic efficiency. The study found that cotton farmers are relatively inefficient and there is room to improve efficiency among smallholder cotton farmers in Zambia. Some socio-economic and farm specific factors have a positive influence on efficiency. The study recommends that cotton stakeholders should devise strategies of involving more women in cotton production, improve access to productive assets, and encourage adoption of conservation farming crop residue retention as the means to improve cotton production efficiency.

As the process of agricultural modernization accelerates, exploring the impact of agricultural mechanization services on production technology efficiency has become a key issue for enhancing agricultural productivity and promoting sustainable agricultural development. The study focuses on cotton growers in the Tarim River Basin and systematically explores the impact and driving mechanisms of agricultural mechanization services (AMSs) on cotton production’s technical efficiency within the framework of the social–ecological system (SES). By employing a combination of stochastic frontier analysis (SFA) and propensity score matching (PSM), the research indicates that the adoption of AMSs significantly enhances the production technical efficiency of cotton farmers. Among the sample that adopted this service, as much as 53.04% of the farmers have their production efficiency within the range of [0.8, 0.9], demonstrating a high production capability. In contrast, the production efficiency values of the farmers who did not adopt such services are more dispersed, with inefficient samples accounting for 11.48%. Furthermore, while the technical efficiency levels across different regions are similar, there are significant efficiency differences within regions. A further analysis indicates that the age of the household head, their education level, the number of agricultural laborers in the family, the proportion of income from planting, and irrigation convenience have a positive impact on farmers’ adoption of AMSs, while the degree of land fragmentation has a negative impact. Therefore, AMSs are not only a core pathway to enhance cotton production’s technical efficiency but also an important support for promoting agricultural modernization in arid areas and strengthening farmers’ risk-resistance capabilities. Future policies should focus on optimizing service delivery, enhancing technical adaptability, and promoting regional collaboration to drive the high-quality development of the cotton industry and support sustainable rural revitalization.

This paper examines the effects of the institutional environment on West African cotton farmers’ technical efficiency (TE). First, key aspects of the cotton sector institutional environment are discussed, including input and credit access, and producers’ organisations. Then, a stochastic frontier production function, which incorporates technical inefficiency effects, is applied to farm level data collected in Benin, Burkina Faso and Mali. The survey includes farmers’ evaluations of the cotton sector institutional environment. Results suggest that institutional level features influence producers’ TE, besides farm‐level characteristics. Cotton growers who report a negative experience with the joint liability programme, who identify the cotton price mechanism or access to credit as the main constraints to performance, and who cultivate more hectares of cereals are technically more inefficient in producing cotton. Findings suggest that cotton farmers in Mali are less technically efficient in producing cotton than in Burkina Faso and Benin. Agricultural development policies focusing on reducing farmers’ financial stress, particularly through the establishment of adequate price mechanisms (i.e. higher farm‐gate prices and timely payments to farmers) and improvement in the input–credit markets should be encouraged to improve TE in West Africa.

Assessing the current farm-level efforts of climate change adaptation is essential to distinguish their usefulness and implying policy level advance measures for future. The present study investigated cotton farmers' climate change adaptation and its impact on increasing cotton productivity and net cotton income in Punjab province of Pakistan. A pretested and well-structured questionnaire was used for data collection of 480 cotton farmers from three major cotton-producing divisions of cotton-wheat zone of Punjab, Pakistan. Logistic regression analysis approach was used in this study to find out the factors of adaptation and propensity score matching method employed to identify connecting adaptation impact on cotton productivity and cotton income. Empirical estimates of this study indicated as owing to some external and internal constraint farmers were limited focused on adaptation while conscious about adverse effects of climate change. Usage of required and recommended types of fertilizer, variation in planting dates, and changing varieties of crop were main adaptation strategies implemented by cotton farmers. Cotton farmers' adaptation decision was significantly influenced by some major factors as weather forecasting, market information, easy access to agricultural extension services, farming experience, and education of cotton farmer. Farm-level increase in cotton productivity and net cotton crop income was direct while overall increases in national output and improving rural area farmer well-being were indirect and significant outcomes of implementing climate change adaptation of cotton farmers. Cotton farmers were using various combinations of adaptation strategies and achieving more benefits regarding their crop productivity and net returns. Findings of the study suggest need for larger investment in farm-level extension services, farmers' schooling, and develop climate change institutional setup for enhancing farmers' adaptation capability to increasing cotton productivity, improving well-being of farming community, and securing agriculture from future climatic uncertainties. Future policies must deal with farm-level limitations of advanced adaptation measures like making available information and sustaining sponsoring soil conservation practices, launching climate smart varieties and advanced adaptation measures based on various agro-ecological zones.

This paper uses both the stochastic and nonstochastic production function approach to measure technical efficiency in public education in Utah.The stochastic specification estimates technical efficiency, assuming half normal and exponential distributions.The nonstochastic specification uses two-stage DEA to separate the effects of fixed inputs on the measure of technical efficiency.The empirical analysis shows substantial variation in efficiency among school districts.While these measures are insensitive to the specific distributional assumptions about the one-sided component of the error term in stochastic specification, they are sensitive to the treatment of fixed socioeconomic inputs in the two-stage DEA.

The effect of water table decline on soil CO2 emission of Zoige peatland on eastern Tibetan Plateau: A four-year in situ experimental drainage

The effect of water table decline on plant biomass and species composition in the Zoige peatland: A four-year in situ field experiment