Determinants Of Technical Efficiency Research Articles

Evaluating bank technical efficiency in SADC region

Efficiency is generally defined as the capacity to deliver desirable results with little effort or input. A bank cannot afford to allocate limited resources at random in a competitive market. Only once the efficiency factors have been identified can resources be allocated in a conscious and effective manner. The study investigates the determinants of technical efficiency of banks in the SADC region. The study is significant in the SADC region as the block is trying to create a robust and stable banking system. This is driven by the desire to stay away from the current global financial system volatility and the region is working to develop an integrated banking system. The results show that the banks are relatively inefficient with the level of inefficiency around 40 percent. The efficiency of the banks is determined by the level of capitalisation, size of the bank, research costs and automation of the banks. The results of the study imply that that there is great scope for the banks in the SADC region to increase their efficiency. Improved efficiency will ensure banks provide services at a lower cost to clients. The study recommends adequately capitalizing banks, increasing the asset base of the banks, investing in research and the automation of the banking systems.

Urbanization Impacts on Rice Farming Technical Efficiency: A Comparison of Irrigated and Non-Irrigated Areas in Indonesia

By 2050, the world population is expected to double, with the majority living in urban areas. Urbanization is a result of population pressure, often emphasized in developing countries. It has various impacts on all economic sectors, among which is agriculture through irrigation, which plays an important role in the production and sustainability of farming. This paper aimed to analyze the effect of urbanization on farm performance using a sequential mixed method. The data of approximately 80,053 farmers were extracted from the Indonesian Rice Farm Household Survey (SPD) dataset. A stochastic frontier was employed to analyze technical efficiency (TE) and its determinants, which consist of farmers’ age, education level, climate change, land ownership, membership status, and pest infestation. The estimation results showed that the mean technical efficiency in both irrigation and non-irrigation rice farming was 64.7% and 66.2%, respectively. Although TE’s achievement in non-irrigated rice farming areas was greater than in irrigated ones, rice productivity in irrigated areas was greater than in non-irrigated. All technical efficiency determinants have significant effects on technical efficiency. The estimation results also showed that rice farming in urban areas tends to decrease technical efficiency.

Determinants of Technical Efficiency in Cow Milk Production in Kurunegala District: An Application of Data Envelopment Analysis

The aim of this study was to determine the level of technical efficiency scores under the assumptions of both constant returns and variable returns to scales on a sample of 150 cow milk producers in Kurunegala District, Sri Lanka. A structured questionnaire was used to gather the data during 2022 in the study and those data were analysed by Data Envelopment Analysis and Tobit regression model. Results of the data envelopment analysis based on input - oriented reveal that, mean technical efficiency scores estimated for constant returns and variable returns to scales were 0.782 and 0.887, respectively, indicating that substantial inefficiencies occurred in operations among the sample farmers. Further, with respect to returns to scale, out of the 150 dairy farmers, 21 were found to be operating at the constant returns to scale while, 122 and 7 were operating at an increasing return to scale and decreasing returns to scale respectively. Tobit regression model was applied to examine the factors influencing the technical efficiency under the specifications of constant returns to scale, variable returns to scale, and scale effects. The study found that age, sex, family size, credit accessibility, and milking frequency were significantly influence the technical efficiencies in dairy farming. These findings could help to increase the milk production and technical efficiency of cow milk production in the study area.

Determinants of Technical Efficiency in Pixie Production in Makueni County, Kenya

Determinants of Technical Efficiency in Pixie Production in Makueni County, Kenya

Determinants of technical efficiency among smallholder upland rice farmers in northern Uganda—a Cobb–Douglas stochastic frontier approach

Determinants of technical efficiency among smallholder upland rice farmers in northern Uganda—a Cobb–Douglas stochastic frontier approach

Determinants of Technical Efficiency and Production Costs in Small-Scale Apple Farms in Albania

Determinants of Technical Efficiency and Production Costs in Small-Scale Apple Farms in Albania

An Empirical Study of Middle-income Farmers on Millet Production in Kano South Nigeria: A Stochastic Frontier Analysis Approach

This paper aimed at assessing the technical efficiency of millet farmers in Kano south Nigeria using the stochastic frontier production function from the parametric perspective. The determinants of technical efficiency, such as, education, extension access, access to loans, farm size, labour etc, which played a great role in technical efficiency level, are assessed to measure the level of efficiency of the middle-income farmers. 227 middle income farmers were selected for the study and provide an empirical analysis of the efficiency determinants which aim to find a way of improving the millet production and productivity. The results show that middle income farmers’ productivity is very weak ranging from 0.023t/ha to 5.62t/ha, averaging 1.07t/ha. While the technical efficiencies of middle-income farmers range from 0.013 to 0.930 with mean of 0.621. However, the results also indicate that most of the above determinants have negative effect on technical efficiency for the farmers. So, there is need by the government at all levels to review the existing agricultural policy that will favour the reality on the ground which will result in improving the output level of the middle-income farmers with their minimum available input. International Journal of Statistical Sciences , Vol. 23(2), November, 2023, pp 39-46

Determinants of Technical Efficiency of Head Cabbage Producer Farmers in West Arsi Zone, Oromia Region, Ethiopia

Determinants of Technical Efficiency of Head Cabbage Producer Farmers in West Arsi Zone, Oromia Region, Ethiopia

Technical efficiency drivers of farmer-led restoration strategies, and how substantial is the unrealised potential for farm output?

CONTEXTIn Ethiopia, similar to other parts of Sub-Saharan Africa, the effects of farmland degradation on ecosystem services and well-being are especially prominent as 85% of the population lives in rural areas and depends on agriculture for their livelihoods. Existing farmer-led restoration activities involve integrating trees on farms (ToF) through traditional agroforestry or woodlots systems. Although ToF practices can potentially bring economic and ecological gains, their production systems and efficiency in terms of input use remain overlooked in the current literature. OBJECTIVEThe study analyses the technical efficiency levels in Ethiopia's home gardens and woodlot systems and examines the drivers contributing to technical efficiency. METHODSThe study estimates the technical efficiency of farmers who implement the ToF strategies, i.e. the extent to which the farmers can achieve the highest output level given their set of inputs. Deviation from the total technical efficiency is then referred to as unrealised potential. We also analyse the drivers of technical inefficiency by controlling for geographical, biophysical, and production system attributes of woodlots and agroforestry patches, as well as household characteristics and institutional settings. We use a one-step Latent Class Stochastic Frontier Modelling approach based on the cross-sectional household data of 543 home gardens and 426 woodlot systems patches in Ethiopia. RESULTS AND CONCLUSIONSAccording to the results, in woodlots, extensive farms lose 38% and intensive farms 22% of the potential output. In home-gardens, intensive farms lose 39%, and extensive farms lose 49% of the output due to technical inefficiency. Significant determinants of technical efficiency in both systems are ecological zones, access to markets, communal carbon payments, forest user groups, training, land title factors, rotation age and product diversification, among others. SIGNIFICANCEOur results help identify priority policy and practical action fields for improving farmer-led restoration strategies' technical efficiency and management in Ethiopia and the global south. Future national reforestation policies could reduce inefficiencies in farmer-led systems across Sub-Saharan Africa by targeting the factors exacerbating technical inefficiency per class in a given strategy. Thus, handling these drivers increases the success of farmer-led restoration strategies and contributes to achieving restoration pledges and AFR100 commitments in mosaic landscapes.

Stochastic Frontier Analysis of Production, Socio-economic and Institutional Factors Affecting Technical Efficiency of Cowpea Production in Chuka Sub-county, Kenya

Cowpea is one of the most important vegetable that ranks third among pulses and top five leafy vegetables consumed in Sub Saharan Africa. In Kenya cowpea contributes to cheap supply of nutritious food, revenue and food security. Despite its importance, cowpea production levels are a fraction of the potential due to low technical efficiency of production which affects the revenue levels and food security of the smallholder farmers. This study aimed to determine the production, socio-economic and institutional factors affecting the level of technical efficiency among smallholder cowpea farmers in Chuka Sub County, Tharaka Nithi County, Kenya. Using semi structured questionnaire in a population of 12905 households and using multistage sampling technique from 389 households cross-sectional data on production factors, socioeconomic and institutional characteristics was collected. Data collected was analyzed using descriptive statistics and stochastic frontier production function. The results indicated that production factors, socioeconomic and institutional characteristics significantly affected cowpea production. The mean technical efficiency index was 0.34. The stochastic frontier analysis revealed that production factor coefficients of labour (0.825), topdressing fertilizer (0.635), manure (0.325), agrochemicals (0.221) and land size (0.628) were all positive and statistically significant at 5% level. The inefficiency model revealed that the coefficients of socio-economic factors age (0.038), education (-0.156) and farming experience (-0.053), and the institutional factors, information sources/extension contact (-0.669) and access to digital financial services (1.527) were negative but statistically significant, except for age and access to digital service that were positive and significant. These variables were the determinants of technical efficiency in cowpea production. The results suggest that there is potential for cowpea farmers to increase production and net profits in the long run by efficient utilization of the existing mix of production inputs and technologies. Formulation of policies revolving around the significant variables, input supply, technology transfer and subsidies; extension services, information exchanges and market linkages are recommended to palliate technical inefficiency in cowpea production among farmers.

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%.

The Impact of Government Food Policy on Farm Efficiency of Beneficiary Small-Scale Farmers in Indonesia

Enhancing self-sufficiency and national food security have been strategic policy goals of the Indonesian government. From 2015 to 2019, a food policy program called Upsus Pajale had been implemented to provide input subsidies and extension assistants to farmers for three strategic commodities: rice, maize, and soybeans, to accelerate productivity and increase production. The study was done by interviewing 374 beneficiary farmers. The objectives were to explore production efficiency and the farmers’ perspectives on the policy programs. By conducting stochastic frontier production function estimation, the results show that the mean efficiency level was 0.866. This study revealed that land size, seed cost, and labor cost were found to be important determinants of technical efficiency. In addition, the results of the inefficiency model indicated that age and farmers’ associations had a significant and positive effect on efficiency scores, whereas education had a negative effect. Contrarily, none of the policy program instruments appear to be essential determinants of efficiency. Furthermore, the research found that farmers prioritized their habits and profitability when deciding which crop to cultivate and that pests were their main concerns. Hence, the government should focus on enhancing research and development for improved seedling pest management control and encourage the establishment of farmers’ association to share experience and transfer information and technology for farmers to improve their efficiency.

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.

Smallholder Tomato Production in Mwanza Region- A Technical Efficiency Analysis Approach.

This study measured technical efficiency and its determinants in maize production by small-scale producers in Mwanza region, using a stochastic frontier production function approach. A randomly selected sample of participants in the two districts was used. The Maximum Likelihood estimation procedure was followed to obtain the determinants of technical efficiency and technical efficiency levels of small-scale tomato producers. The minimum and maximum values of technical efficiency were between 20% and 91%, indicating that the least practices of specific producer operates at a minimum level of 20%, while the best practice producers operate at 91% technical efficiency level respectively. The summary results of the mean technical efficiency was 57%. The results indicate that farmers were not fully technically efficient with a mean technical efficiency score of 0.58. The study also revealed that most of the farmers irrespective of the size of the holdings have shown technical inefficiency problems. Experienced farmers were observed to have good measures of technical efficiency. The findings also indicated that significant variables of technical efficiency included household size, labour, fertilizer, seed, educational level, household size, farming experience, and access to extension services were statistically significant by positively impacted on producers’ technical efficiency in the study area.

Determinants of technical efficiency of coffee production in Jimma Zone, Southwest Ethiopia

Agriculture has been and continues to assume center stage in the economic policy of Ethiopia. Coffee is one of the most vital sources of income for many coffee growers and continues to be still the leading export commodity in the national economy of the country. Despite the economic use, the productivity and quality of the coffee are unsatisfactory. The adoption of coffee yield-enhancing technical efficiency is key to improving coffee productivity and quality. Therefore, this study aims to investigate determinants that influence the technical efficiency of coffee production in Jimma Zone, Southwest Ethiopia. The primary data was collected among 398 coffee growers in research locations during the 2020/21 season. Descriptive statistics and econometric methods were developed for the data analysis. The estimated average value of technical, allocative, and economic efficiencies was 82.63%, 78.35%, and 74.65% respectively, which shows the existence of inefficiency in coffee production in the study area. The findings of OLS regression indicated that technical inefficiency is affected by age, sex, education status, landholding, livestock holding, credit uses, the extension uses, off-farm activity, land ownerships, seed, and variety of coffee planted. Coffee yield technical efficiency was associated with a significantly higher coffee yield and per capita annual income of coffee cultivators. Concerned bodies should give important attention to coffee yield enhancing technical efficiency which is base for improving production. The summary of this coffee production technical efficiency by policymakers and plan designers could bring better enhancement to the coffee cultivator in the study area.

Modeling Linkages among Urban Agglomeration, Construction Industry, Non-Renewable Energy, and Zero-Carbon Future

On the one hand, the twin perspectives of the construction industry and urban agglomeration proliferate economic prosperity. However, on the other hand, construction activities and increased population density give rise to environmental challenges. This study is an initial attempt to explore links between the construction industry, urban agglomeration, non-renewable energy utilization, carbon dioxide emissions (CO2e), and economic output within a system of simultaneous equation modeling. This study develops modeling specifications to include the construction industry as a shifting factor and CO2e as a determinant of technical efficiency. A heterogeneous fully modified ordinary least squares (FMOLS) technique, capable of providing concrete empirical outcomes even in the presence of modern panel-data econometric issues, is utilized for the data of China’s 30 provincial/ city divisions during the 2003–2019 period. It has been revealed that: (i) the influence of urban agglomeration on the economic output was heterogeneous, with an adverse link for China’s western part, neutrality connection for the central part, and favorable for China’s eastern part; and (ii) shifting from China’s western to eastern parts, the expansion of the construction industry has a significant impact on economic output, and, hence, has been described as “the Economic Effects of Urban agglomeration” for the Chinese economy. The policies of this study have crucial lessons for global economies.

Technical efficiency and constraints related to rice production in West Africa: The case of Benin Republic

Rice plays a major role in the fight against food insecurity in developing countries such as Benin. The objective of this research is to evaluate the determinants of technical efficiency, the factors influencing this efficiency, as well as the constraints related to rice production in Benin. The technical efficiency levels were obtained from the Data Envelopment Analysis (DEA) method and were regressed in a Tobit regression model to assess the determinants of the efficiency of rice producers. Production constraints were identified using Kendall’s W concordance test and descriptive statistics. The technical efficiency rate obtained was 51%. Inferential analysis showed that parameters such as the age of the rice producer, household size, the amount of agricultural credit obtained, and the use of inputs impact the technical efficiency of rice production. In addition, most rice producers suffer from limited access to agricultural credit and adequate agricultural equipment, while their production is subject to climatic hazards. Agricultural development policies related to the determinants of the technical efficiency of rice production should be formulated in order to improve the efficiency of the producers in Benin Republic.

A spatial stochastic frontier model introducing inefficiency spillovers

Abstract This paper develops a spatial Durbin stochastic frontier model for panel data introducing spillover effects in the determinants of technical efficiency (SDF-STE). The model nests several existing spatial and non-spatial stochastic frontier specifications and is estimated using maximum-likelihood techniques. Estimates are shown to be unbiased even for small sample sizes and for alternative specifications of the spatial weight matrix implementing different Monte Carlo simulations. Finally, an application to the Italian accommodation sector is provided. Empirical findings suggest the relevance of the SDF-STE model in capturing labour productivity and knowledge spillover effects.

Analysis of factors affecting technical efficiency of A1 smallholder maize farmers under command agriculture scheme in Zimbabwe: The case of Chegutu and Zvimba Districts

In an effort to address the decline in maize productivity, the government of Zimbabwe in 2016/17 endorsed a special program for input support named command agriculture scheme (CAS). Against this background, the study questioned the beneficiaries’ technical efficiency and factors that influence farmers to gravitate towards the frontier using Chegutu and Zvimba districts of Zimbabwe as case studies. The study used a cross-sectional survey of 240 households randomly selected through a three-stage multiple-sampling procedure. The single-stage modelling stochastic frontier approach was applied to assess technical efficiency of A1 smallholder command agriculture maize farmers. The study revealed that A1 smallholder command agriculture maize farmers in Chegutu and Zvimba districts were technically efficient at 85% and 94%, respectively. The major determinants of technical efficiency were basal fertilizer, labour, area allocated to maize production and topdressing fertilizer which all indicated a positive relationship. The main determinants of technical inefficiency were age, maize farming experience, level of education, marital status, occupation status and other sources of income. Results further revealed that farmers from Chegutu district had increasing returns to scale (1.43) while farmers from Zvimba district had decreasing returns to scale (0.54). The study therefore argues that despite the observed high technical efficiencies, Chegutu farmers could bridge their 15% gap between the observed output and the frontier output by focusing more on input usage with increasing returns to scale while Zvimba farmers could bridge their 6% gap by focusing more on socio-economic drivers of technical inefficiency given their decreasing returns to scale.

Determinant of Technical Efficiency of Sugarcane During the Covid 19 Pandemic in Malang Regency East Java Indonesia

Sugarcane farmers in sugar-producing countries are experiencing an economic crisis due to the Covid 19 pandemic. Restrictions on transportation and a scarcity of labor have delayed sugarcane harvesting, increased production costs, decreased productivity, and decreased income. Therefore, our research aims to measure the technical efficiency and the influence of environmental factors on the technical efficiency of sugar cane farming in Malang Regency. The results of the research using the multiple bootstrap regression approach show that the efficiency values based on the VRS and CRS assumptions are 0.854 and 0.834. This value means that sugarcane farmers in Malang Regency must reduce the use of inputs by 16.6% and 14.6% respectively to make sugarcane farming more efficient. The variable age of the head of household reduces technical efficiency, while the variables of sugarcane training experience, organizational experience, ratoon cane, and increases in input prices have the potential to increase technical efficiency. The Covid 19 pandemic has become a momentum for policy makers to create training programs that aim to utilize natural resources to overcome scarcity and rising input prices, as well as realize agricultural sustainability.