Frontier Function Research Articles

Economic Efficiency of Potato Production by Smallholder Farmers in West Arsi Zone, Oromia Region Ethiopia

This study investigated Economic Efficiency of Potato Production in West Arsi Zone, Oromia Region, Ethiopia. Structured questionnaires were used to collect data from 117 respondents randomly selected from designated locations in West Arsi Zone. A stochastic production frontier function was fitted to the sample households. The result revealed that the mean TE, AE and EE was about 75.60%, 91.41% and 69.07% of for potato production. The sum of the partial elasticity of all inputs were 1.17 for Potato indicating an increase in all inputs at the sample mean by one percent increase by 1.17%. This indicates that the production function is characterized by increasing returns to scale productions. The result of Tobit model estimation indicated that the technical efficiency of Potato production in West Arsi Zone is significantly influenced by the variables potato farming experience, education level, social participation and Extension contact affect efficiency positively while, distance to FTC affect technical efficiency negatively. The mean potato yield difference between sample farmer due to technical efficiency variation was 31.04 qt per ha. District office of Agriculture, stockholders and concerned bodies should focus on farmers experience sharing, providing technical support and farmers practice different social participation to improve his/her income could jointly contribute to the improvement in efficiency of Potato farmers in West Arsi Zone.

Unleashing Economic Potential: Enhancing Cassava Production Efficiency in Nigeria

Purpose: This study is aimed at determining the economic efficiency of Manihot esculenta Crantz (Cassava) production in Nigeria’s Delta State. The study offers a detailed analysis of how socio-economic characteristics influence production output across both early and late farming seasons. Design/ Methodology/ Approach: This study employed a multi-stage random sampling approach in selecting a diverse cohort of 500 cassava farmers engaged in both early and late-season cultivation. Through rigorous personal interviews, primary data was gathered that was both comprehensive and insightful. Advanced parametric statistics and the Cobb-Douglas stochastic frontier function were used for the analysis. Findings: The mean economic efficiency scores were determined to be 0.63 for early-season farms, 0.78 for late-season farms, and 0.76 when considering all farms collectively. The output elasticities of material inputs, labour, and land were found to be 0.42, 0.61, and 0.05, respectively for all farms. For early-season farms, these values were 0.36, 0.68, and 0.04, whereas, for late-season farms, they were 0.31, 0.7, and 0.03. Research Limitation/Implications: This work concentrated on Cassava production efficiency within and around Nigeria’s Delta area. Practical Implication: Understanding the socio-economic factors that influence production during different seasons can help in designing strategies that maximize output in both early and late farming seasons. Social Implication: This study would help agricultural development economists and policy-makers in addressing the economic problems of Cassava farmers both present and future generations. Originality/Value: By examining both early and late farming seasons, the study provides a comprehensive understanding of how socio-economic factors vary across different agricultural cycles. This dual-season approach is relatively rare and offers more detailed insights into the dynamics of cassava production throughout the year.

Determinants of Profit Efficiency among Rice Farmers in Kilombero Valley, Morogoro, Tanzania

Farmers in the Kilombero Valley are experiencing a growing trend towards commercialization seen through the expansion in the cultivated land area rather than agricultural intensification. There is a modicum of information on whether the observed increase in commercialization in the area is associated with an increase in profit. This study used the stochastic profit frontier function to estimate the profit efficiency of rice commercializing farmers and the respective determinants. The study used data collected from 377 rice farmers who were selected by using a multi-stage stratified sampling method. Results indicate that rice commercialising farmers' mean profit efficiency level was 75.65%. This indicates that rice farmers can improve their efficiency levels by 24.4% without increasing the level of inputs used. Maximum likelihood estimates indicated that wage, price of fertilizer, rice area in hectares, and production assets value were significant in determining the profit efficiency of rice commercializing farmers in Kilombero. The study concludes that commercializing farmers in the study area was profit efficient. The study recommends that more emphasis on early formal education in farmers’ society be emphasized for the literate group is more profit-efficient than the illiterate. With the present national educational policy to support education, farming households should strategically take advantage of it as education has exhibited a positive impact on their efficiency. Different services (marketplaces and inputs dealerships) in the area should be improved further to create more room for rice farmers to improve their productivity and profitability.

A Stochastic Frontier Approach to Study the Relationship between the Hygienic Quality of Bulk Tank Sheep Milk and Technical Efficiency of the Coagulation Process.

Sheep milk from local breeds is important for the production of high-quality cheeses throughout the Mediterranean region, such as Manchego cheese in Spain. To maintain sustainable and efficient production, it is necessary to reach a better understanding of how the composition and hygiene of the milk affect the coagulation process, with the aim of optimizing production yield. This study implemented a stochastic production frontier function to estimate the potential production of curd and efficiency using data from the four seasons of a study of 77 Manchega sheep farms. The Cobb-Douglas production frontier model was estimated using the maximum likelihood estimation method. The results showed that the content of protein, lactose, and fat exhibited increasing returns to scale, with protein content being the most significant factor for curd production. Approximately half of the inefficiency was due to factors related to the technological properties and the hygiene of the milk. The pH, curd firmness, and concentration of lactic acid bacteria improved the efficiency of coagulation, while the concentration of spores of lactate-fermenting Clostridium spp., Pseudomonas spp., staphylococci, and catalase-negative gram-positive cocci favored the inefficiency of the coagulation process. To date, this is the first study to evaluate the effect of different factors, such as microbial groups, milk composition, and technological properties, on the efficiency of the coagulation process in dairy sheep.

Technical and allocative efficiency of crop production using different storage and water‐lifting technologies in Central Rift Valley, Ethiopia

AbstractAssessing the efficiency gains, in terms of crop production and productivity, of using agricultural water management is critical to understanding the comparative advantage of using different storage and water‐lifting technologies in irrigation development. This study aims to compare the efficiency differences among irrigation farmers using various water‐lifting technologies and among users of various technology suites in the Central Rift Valley, Ethiopia. Cross‐sectional data collected from 320 randomly selected smallholder farmers, considering the 2019/2020 production season, were used to analyse a one‐step Cobb–Douglas stochastic frontier function. The results of the study revealed the existence of technical and allocative efficiency differences between gravity and fuel pump users. Factors that positively determine the level of technical efficiency scores are gender, age, education status, technology type and extension contact. Irrigation experience, access to credit, training and technology type positively affected allocative efficiency, while the distance to the irrigation water source had a negative effect. The findings have important implications for agricultural policy and practice as improving efficiency through the adoption of fuel‐powered water‐lifting technology could further improve overall agricultural productivity. Designing small‐scale friendly business models and promoting irrigation extension services, among others, is critical for scaling successful water management technologies.

Measuring Efficiency Performance in Economic Productivity Function: Parametric and Non-Parametric Frontier Approach

The parametric and non-parametric frontier approach is the famous frontier measurement efficiency in economic productivity. Many researches on economics-based has focused on efficiency. Basically, efficiency comprises two important components. First is technical efficiency and second is allocative efficiency. Combination of technical and allocative efficiency called as economic efficiency. In order to measure both components of efficiency, parametric and non-parametric approaches have been utilized to either estimate or calculate the efficiency frontier. Many studies have adopted non-parametric, deterministic approach such as Data Envelopment Analysis (DEA) that impose no functional form on the cost or production function, but parametric estimation of cost, production, or profit functions are more relevant approach in the economics-based literature. Stochastic Frontier Approach (SFA) is the most popular among parametric model approach. Deterministic frontier functions can be solved using either mathematical programming or econometric techniques, while stochastic specifications are estimated solely through econometric methods. This study’s main contribution is a review of efficiency concepts, measurement methods, and the strengths, limitations, and data requirements of parametric and non-parametric models.

An Exploration of Prediction Performance Based on Projection Pursuit Regression in Conjunction with Data Envelopment Analysis: A Comparison with Artificial Neural Networks and Support Vector Regression

Data envelopment analysis (DEA) is a leading approach in performance analysis and discovering newer benchmarks, and the traditional DEA models cannot forecast the future efficiency of decision-making units (DMUs). Machine learning, such as the artificial neural networks (ANNs), support vector machine/regression (SVM/SVR), projection pursuit regression (PPR), etc., have been viewed as beneficial for managers in predicting system behaviors. PPR is especially suitable for small and non-normal distribution samples, the usual cases in DEA analysis. This paper integrates DEA and PPR to cover the shortcomings we faced while using DEA and DEA-BPNN, DEA-SVR, etc. This study explores the advantages of combining these complementary methods into an integrated performance measurement and prediction model. Firstly, the DEA approach is used to evaluate and rank the efficiency of DMUs. Secondly, we establish two DEA-PPR combined models to describe the DEA efficiency scores (also called the production function) and the DEA-efficient frontier function. The first combined model’s input variables are input–output indicators in the DEA model, and the output variable is the DEA efficiency. In the second model, its input variables are input or output indicators in the DEA model, and the output variable is the optimal input indicator for input-oriented DEA or the output indicator for output-oriented DEA. We conducted positive research on two examples with actual data and virtual small, medium-sized, and large samples. Compared with the DEA-BPNN and DEA-SVR models, the results show that the DEA-PPR combined model has more vital global optimization ability, better convergence, higher accuracy, and a simple topology. The DEA-PPR model can obtain robust results for both small and large cases. The DEA-BPNN and DEA-SVR models cannot obtain robust results for small and medium-sized samples due to overfitting. For large samples, the DEA-PPR model outperforms DEA-BPNN, DEA-SVR, etc. The DEA-PPR combined model possesses better suitability, applicability, and reliability than the DEA-BPNN model, the DEA-SVR model, etc.

Do farmers' professional cooperatives improve agricultural technical efficiency? Evidence using a national‐level dataset of China

AbstractThis study examines the impact of farmers' professional cooperatives (FPCs) on agricultural technical efficiency (TE), using panel data from 30 provinces of China from 2015 to 2020 and the stochastic frontier function (SFF) method. The number of members of each cooperative, the proportion of demonstration cooperatives, and the proportion of standard cooperatives are introduced as proxy variables for the development level of FPCs. The results show that although the development of FPCs is imperfect, its development has a significant positive impact on improving China's agricultural TE. Through the continuous increase in the number of cooperative members and the vigorous promotion of standardized production, agricultural TE has been significantly improved. However, the construction of model cooperatives has not played a positive role but inhibited the growth of agricultural TE. It is suggested to expand the cooperative membership and promote standardized production. The government and policymakers should focus on improving the standardization level of cooperatives and the development quality of FPCs from the aspects of innovating cooperation models, standardizing internal governance, and giving full play to the synergistic effect of agricultural science and technology.

Stochastic Frontier Analysis of Technical Efficiency and Profitability of Dry Season OKRA Production in Nigeria

Food production in Nigeria is almost entirely rain fed despite the great potential of irrigation in Nigeria to boost agricultural productivity. The study assessed the profitability and efficiency of dry season irrigated okra farming in Adamawa State using primary data collected from 180 farmers through a simple random sampling technique. Profit efficiency and stochastic frontier function were used in analyzing the data. The result revealed that labor costs accounted for 48% of average variable cost while a farmer’s total revenue from irrigated okra produce was ₦228,642.56K ($408.2), total fixed cost and variable input cost was ₦102,440.37K ($182.93), resulting in a net farm income (NFI) of ₦126,201.63K ($225.36). The coefficients of farm size, household size, and fertilizer were positive and significant at the 1%, 10%, and 5% levels of probability, respectively, as revealed by the OLS results. Empirical estimate shows that the mean technical efficiency value of vegetable farmers was about 0.73 while Technical inefficiency coefficient of farming experience (−0.420), adjusted household size (−0.193), and extension contacts (−0.162) are variables that increased technical efficiency. Lack of access to water, high cost of equipment, and inadequate finance were identified as lead constraints of the okra farmers. Therefore, recommendations by the study are that farmers be encouraged to establish cooperative organizations so that they can pool their resources to create an irrigation system that is affordable. Also, sustainability of small scale irrigation scheme should be promoted by the government through skill enhanced trainings.

Economic Efficiency of Onion Production in East Shewa Zone, Oromia Region, Ethiopia

In an economy where resources are scarce and opportunities for new technologies are lacking, efficiency studies able to show the possibilities to raise productivity by improving efficiency of farms without increasing the resource base or developing new technology. This study investigated Economic Efficiency of Onion Production in East Shewa Zone, Oromia Region, Ethiopia. Both primary and secondary source of data were used. Semi- structured questionnaires were used to collect data from Lume, Bora and Dugda districts. Totally 94 respondents randomly selected from each districts based on sample size determination. A stochastic production frontier function was fitted to the sample households. Tobit model was applied to determine factors affecting economic efficiency of onion production. The result revealed that the mean Technical, Allocative and Economic efficiency of onion production was about and 67.60%, 98.99% and 66.91% respectively. The tobit model result revealed that Onion Technical and Economic efficiency were positively and significantly affected by Experience in Onion production, frequency of Extension contact and Non- and off income activities while land allocated for Onion production affect Technical and economic efficiency negatively and significantly. District office of Agriculture, stockholders and concerned bodies should focus on extension service regarding of full package of production, provision of technical support and farmers should practice different Non-and Off-fam activities to improve his/her income that contribute to the improvement in efficiency of Onion production in the study area.

Research on Technical Efficiency of Feed Use for Sustainable Beef Cattle Breeding in China: Evidence from 169 Beef Cattle Farmers

Sustainable green development, cost saving, and efficiency improvement have become the main theme of the high-quality development of China’s animal husbandry and the problem of overuse of feed should be paid more attention. Based on the 3-year input–output data of 169 beef cattle farmers, a trans-logarithmic stochastic frontier function was used to study the relationship between feed utilization efficiency and beef cattle breeding scale. The results showed that the average technical efficiency of feed utilization was 0.56, and the technical efficiency of feed utilization increased year by year. Simultaneously, it showed that Chinese beef cattle farmers pay more attention to feed utilization efficiency at this stage; the feed utilization efficiency of retail and medium-sized beef cattle farmers was in the best state in 2015 and 2016. In 2017, the feed utilization efficiency of small-scale beef cattle farmers was the best; the technical efficiency of beef cattle breeding will increase with the expansion of scale. The technical efficiency of beef cattle breeding will increase with the expansion of the scale, and the feed utilization efficiency of large-scale farmers is also better than that of retail farmers, and the scale of beef cattle breeding can bring better benefits. However, from the perspective of feed utilization efficiency, it is not the largest scale that represents the best efficiency, and from the perspective of breeding technology efficiency, the gap between various scales is gradually narrowing. This should also prove that under the condition of hard resource constraints, the large-scale development of beef cattle breeding is in line with the basic national conditions of China at this stage.

Cassava: Farmers Adoption and Livelihood in Bono Region Performance of Stochastic Frontier Functions

The objective is to analyze the stochastic frontier function in comparing the performance of the Cobb-Douglas and Translog Frontier functions in the cultivation of cassava in the Bono Region of Ghana. The assumption is that given the same level of productive inputs of farmers at any given farming season, across heterogeneous farmlands, both functions are likely to produce the same results. The interview was used as the instrument for obtaining plot-specific data from 120 cassava farmers across six districts and data was analyzed using the quantitative technique. Direct predictors of output include plot size, labor, hoes, cutlasses, and cassava stems. Using a half-normal distributional assumption, the study evaluates variance parameters of the composed error terms. The results showed that the estimated functions produced comparable results in terms of magnitude and signs of input variables. While efficiency appeared to be much higher in Cobb-Douglas than in the Translog function, the variance parameter score for the CD function is significantly different from those of the Translog function, and the maximum output attainable for the given productive inputs was 40% and 15% respectively. This means that farmers can scale up their current crop yield by 60% and 85% respectively of their frontier functions using the same inputs and technology if the appropriate interventions are carried out. The limitation of the study is the non-inclusion of environmental factors such as rain as productive input and the study is limited to comparing frontier functions. The results underscored the importance of examining the current production behavior of farmers for reliability and policy inferences

Planning feasible and efficient operational scenarios for a university hospital through multimethodology

The COVID-19 pandemic required managerial and structural changes inside hospitals to address new admission demands, frequently reducing their care capacity for other diseases. In this regard, this study aims to support the recovery of hospital productivity in the post-pandemic context. The major challenge will be to make use of all the resources the institution has obtained (equipment, beds, temporarily hired human resources) and to increase production to meet the existing repressed demand. To support evidence-based decision-making at a major university hospital in Rio de Janeiro, hospital managers and operations research analysts designed an approach based on multiple methodologies. Besides multimethodology, one important novelty of this study is the application of a productivity frontier function to future scenario planning through the quantitative DEA methodology. Concept maps were used to structure the problem and emphasize stakeholders’ perspectives. In sequence, data envelopment analysis (DEA) was applied, as it combines benchmarking best practices and assigns weights to inputs and outputs. To guarantee that the efficiency measurement considers all inputs and outputs before any inclusion of expert judgment, the scope was redirected to full dimensional efficient facet, if any, or to maximum efficient faces. The results indicate that production scenarios proposed by stakeholders based on the Ministry of Health parameters overestimate the viable production framework and that the scenario that maintains temporary human resource contracts is more compatible with quality in health provision, teaching, and research. These findings will serve as a basis for decision-making by the governmental agency that provided temporary contracts. The present methodology can be applied in different settings and scales.

Regional differences and influencing factors of the carbon emission efficiency from public buildings in China

The rapid development of the tertiary industry has made the energy consumption of public buildings grow too fast during the operation stage, which has become a key area of energy conservation and emission reduction in China’s construction industry. This study uses the Minimum Distance to Strong effective Frontier function (MinDS) and Malmquist-Luenberger (ML) index analysis methods to measure the public building carbon emission efficiency (PBCEE) of 30 provincial-level units in China’s eight economic regions from 2010 to 2019, and analyze regional differences and evolution. Then, the influencing factors of PBCEE in different regions were analyzed using the fixed-effect panel data model. The results show that: 1) China’s PBCEE is generally low, with an average efficiency value of only 0.74, and there are great differences among regions, showing the spatial characteristics of “high in the east and low in the west.” 2) Relying on the positive impact of technological progress, the PBCEE in the eight regions increased year by year, with an annual growth rate of 1.82%. 3) The influence results and degrees of various factors on PBCEE are different in different economic zones, but increasing the proportion of electricity consumption has a certain positive effect on improving PBCEE. The same influencing factor has obvious threshold characteristics for PBCEE in different regions, so the government needs to consider the actual situation of the region when formulating carbon emission reduction policies for public buildings.

Improving Rice Production Efficiency in Myanmar by Controlling for Environmental Production Factors

Rice is the dominant crop in Myanmar and central to the agricultural economy. To increase rice productivity, farmers’ production performance is vital. This requires adjusting the availability of physical production inputs in response to environmental conditions. Very few studies have focused on the effects of relevant environmental conditions in Myanmar, including the impact of weather shocks during the rice production. This study aimed to the improve rice production based on the present performance of rice farmers, while controlling the impact of adverse environmental conditions. Information on rice production was extracted randomly from in-depth interviews with rice farmers in the Ayeyarwady Delta region. The Cobb-Douglas stochastic production frontier function was applied to examine the effects of the underestimated environmental factors. Erratic rainfall and excessive temperature during early growth stage have a significant negative impact on monsoon rice productivity. During the 2018-2019 monsoon cropping season, different levels of yield loss due to weather shock negatively affected rice farmers’ production efficiency. Controlling the environmental conditions improved technical efficiency from 88% to 93%. Based on these findings, policy makers and stakeholders should invest in climate services development, thus enhancing farmers’ understanding of weather variability and upscaling the use of local climate adaptation strategies in accordance with the Myanmar Climate Smart Agriculture Strategy.

ANALISIS EFISIENSI DAN FAKTOR-FAKTOR YANG BERPENGARH TERHADAP HASIL PRODUKSI USAHATANI PADI ORGANIK DI PROVINSI JAWA BARAT (Suatu kasus di Kelompok Tani Sari Alam Desa Cibatu Kabupaten Sukabumi dan Kelompok Tani Terlaksana Kelurahan Sukakarya Kota Sukabumi)

This study aims to analyze what production factors affect organic rice production and how efficient the use of these production factors is in the Sari Alam Farmer Group, Cibatu Village, Sukabumi Regency and the Implemented Farmer Group, Sukakarya Village, Sukabumi City. The research area method was carried out purposively (deliberately). The number of samples was 40 farmers from the Sari Alam Farmer Group, Cibatu Village, Cikembar District, Sukabumi Regency and 40 farmers from the Implemented Farmer Group, Sukakarya Village, Warudoyong District, Sukabumi City, the data used was for one planting season. The first hypothesis is analyzed by multiple regression analysis, the second hypothesis includes technical efficiency, price efficiency and economic efficiency using the frontier function. The results of the analysis of the two statistical test sample areas showed that simultaneously the independent variables consisting of land area, seeds, compost, liquid organic fertilizer and labor had a significant effect on the dependent variable, namely organic rice production. The classical assumption test shows that the research data is normally distributed, free of multicollinearity symptoms and there is no strong correlation between independent variables. The results of organic rice farming calculations show that in the Sari Alam Farmer's Group technical efficiency (ET) is 0.997, price efficiency (EH) is 7.266 and economic efficiency (EE) is 7.204 and in Implemented Farmers Group technical efficiency (ET) is 0.998, price efficiency ( EH) of 5.960 and economic efficiency (EE) of 5.948. The economic value in both farmer groups is more than 1, meaning that organic rice farming activities in both groups are very efficient.

Yield gap analysis of rainfed alfalfa in the United States.

The United States (US) is the largest alfalfa (Medicago sativa L.) producer in the world. More than 44% of the US alfalfa is produced under rainfed conditions, although it requires a relatively high amount of water compared to major field crops. Considering that yield and production of rainfed alfalfa have been relatively stagnant in the country for decades, there is a need to better understand the magnitude of yield loss due to water limitation and how far from yield potential current yields are. In this context, the main objective of this study was to estimate the current yield gap of rainfed alfalfa in the US. We collected 10 year (2009–2018) county-level government-reported yield and weather data from 393 counties within 12 major US rainfed alfalfa producing states and delineated alfalfa growing season using probabilistic approaches based on temperature thresholds for crop development. We then calculated county-level growing season rainfall (GSR), which was plotted against county-level yield to determine attainable yield (Ya) using frontier function analysis, and water-limited potential yield (Yw) using boundary function analysis. Average and potential water use efficiencies (WUE) were estimated, and associated yield gap referring to attainable (YGa) or water-limited yields (YGw) were calculated. Finally, we used conditional inference trees (CIT) to identify major weather-related yield-limiting factors to alfalfa forage yield. The frontier model predicted a mean Ya of 9.6 ± 1.5 Mg ha−1 and an associated optimum GSR of 670 mm, resulting in a mean YGa of 34%. The boundary function suggested a mean Yw of 15.3 ± 3 Mg ha−1 at the mean GSR of 672 ± 153 mm, resulting in a mean yield gap of 58%. The potential alfalfa WUE was 30 kg ha−1 mm−1 with associated minimum water losses of 24% of mean GSR, which was three times greater than the mean WUE of 10 kg ha−1 mm−1. The CIT suggested that GSR and minimum temperature in the season were the main yield-limiting weather variables in rainfed alfalfa production in the US. Our study also revealed that alfalfa was only limited by water availability in 21% of the environments. Thus, future research on management practices to narrow yield gaps at current levels of water supply is necessary.

A spatial stochastic frontier model including both frontier and error-based spatial cross-sectional dependence

ABSTRACT Spatial dependence in stochastic frontier models is usually handled by modelling the frontier function or the inefficiency error term through the introduction of some spatial components. The model proposed in this paper (SDF-CSD) combines the two different modelling approaches, obtaining a full comprehensive specification that introduces four different sources of spatial cross-sectional dependence. The most appealing feature of the model is that it allows capturing global and local spatial spillover effects while controlling for spatial correlation related to firms’ efficiency and to unobserved but spatially correlated variables. Moreover, it can be estimated using maximum likelihood techniques. Finally, some Monte Carlo simulations were run to test the final sample properties of the new spatial estimator and an application to the Italian agricultural sector is provided.

Energy Use Pattern and Its Efficiency in Paddy Cultivation in Tamil Nadu, India

The purpose of this study was to identify the socio-economic characteristics of paddy cultivating farmers of various size groups selected from the sample; to examine the resource use pattern of paddy cultivating farmers of various farm size groups; and to evaluate the farm level technical efficiencies in the production of paddy in Thadappalli ayacut of Erode District in Tamil Nadu. The study was conducted in Thadappalli ayacut of Erode District in Tamil Nadu. The research was conducted solely on a representative sample of 150 paddy farmer households drawn from five different villages located within the Thadappalli ayacut in the Erode District. A straightforward proportion, the Cobb-Douglas type stochastic production frontier function model, was utilised in order to arrive at the conclusions. The findings of the study have policy implications because they not only provide empirical efficiency indicators that can be used to plan farm production but also help us identify the potential for crop production improvement across a variety of farming systems based on efficiency. In other words, the findings not only provide policymakers with a tool that can be used to plan farm production, but they also provide policymakers with a tool The findings of the study also provide insight into long-term techniques to improve production that do not require the addition of additional resources. Because education has a big impact on how well people can use technology, it is important to help farmers in the region get both formal and informal education. Keywords: Cost & Returns, Technical Efficiency, OLS, Stochastic Frontier Function

Brooding Technology Use and Technical Efficiency among Egg Producers in Oyo State, Nigeria

This paper investigated the types of brooding technology used by egg producers in Oyo State, Nigeria and its effect on technical efficiencies of the producers. The study was carried out in two Local Government Areas (LGAs) of Oyo State with data obtained from a total of 139 egg producers (farmers). Descriptive statistics was used to profile the farmers, probit model was employed to analyse the determinants of choice of brooding management technology, Cobb-Douglas stochastic frontier function was used to estimate technical efficiency among the farmers and Tobit regression model was also employed to ascertain technical efficiency determinants. The results show that only 9.4% of the farmers used modern brooding technology and over 50% of them employed unskilled labour. Sex of the farmer (p<0.10), household size (p<0.05) and having a secondary income (p<0.05) were the significant factors influencing adoption of modern brooding technology. Farmers who adopted the traditional brooding technology were found to be 4.3% more efficient than those using modern technology. Age (p<0.00), sex (p<0.05) and production experience (p<0.05) significantly affected their technical efficiencies. It was therefore recommended that technology subsidies, adequate extension training and skill acquisition be injected into the poultry industry to improve production efficiency.