Technical Efficiency Of Maize Production Research Articles

Impact of Microdosing Practices on Technical Efficiency: An Analysis Accounting for Selection Bias Among Smallholder Maize Farmers in Burkina Faso

Smallholder maize farmers are currently confronted with the arduous challenge of managing limited financial resources while incessantly facing the issue of land degradation. To address this issue, an alternative solution has been implemented to optimize the use of chemical fertilizer by adopting microdosing. This innovative system not only helps them enhance their agricultural productivity but also allows them to protect the environment. However, it is unclear how microdosing adoption could increase the technical efficiency (TE) of maize production. Therefore, this research aims to assess how the adoption of microdosing affects the technical efficiency of maize production as well as identify the key factors that influence the technical efficiency of maize production in Burkina Faso. To achieve this goal, farm household survey data was conducted with 210 randomly selected farmers from the Plateau Central and northern regions of Burkina Faso. To account for potential selection biases that could result from both observable and unobservable factors, we used a sample selection stochastic production frontier model and a propensity score matching approach. A stochastic meta-frontier approach was applied to estimate TE differences and the technology gap between adopters and non-adopters. The findings showed that adopters of microdosing have an average efficiency of 68 percent, which is higher than the 53 percent estimated for non-adopters. Adopters of microdosing have been found to have high TE and better agricultural technology than non-adopters. The meta-frontier estimation revealed that the adoption of improved maize varieties would yield better returns. This study contributes significantly to the literature on how fertilizer microdosing affects maize productivity, as well as the policy implications of targeting and encouraging smallholder maize farmers in Burkina Faso to optimize the use of productive inputs and improve maize output by using microdosing.

Dynamics of Maize Production in Changing Climatic Scenario of Bihar: A Stochastic Frontier Approach

"The study attempted to capture the changing scenario of maize production and its efficiency in Bihar agriculture using an unbalanced panel stochastic frontier model in a dataset of all three agro-climatic zones over a period of 15 years (2006-2020). The findings indicated that increasing crop area, machinery used, and irrigation all had a significant impact on maize productivity. A random effect of the Tobit model for panel data is employed to identify the factors that affect technical efficiency. The technical efficiency of maize production has an influence on the maximum temperature, increasing the maximum temperature limit that is detrimental to maize production. The technical score of the current maize production technology is 0.83 indicates that Bihar’s maize production is 83% technically efficient when accounting for climatic factors like maximum and minimum temperatures and rainfall. Technical efficiency scores for Zones 1 and 2, which are well known for being intensely maize-producing regions, are 0.84 and 0.88, respectively. Since crop leftover is distinct from maize production and may be utilized to increase technical efficiency, crop residue is strongly related to maize’s technical efficiency. The highest levels of technical efficiency were seen in Bihar’s maize production from 2006 to 2020, with an average technical efficiency of 0.88. Bihar’s agricultural Zone 2 has a maximum technical efficiency of 0.97, making it the state’s top producer of maize."

Does sending farmers back to school increase technical efficiency of maize production? Impact assessment of a farmer field school programme in Indonesia

A farmer field school programme aims to impart knowledge and promote new technology. The programme is expected to enhance farmers’ performances. However, the empirical evidence remains unclear. A few studies have examined the impact of this programme on technical efficiency in Indonesia. The current study specifically investigates the causal impact of the Farmer Field School of Integrated Crop Management (FFS-ICM) programme on technical efficiency of maize production in Indonesia. We used a stochastic production frontier model and propensity score matching (PSM) to examine the causal impact of FFS-ICM on the technical efficiency of maize production. The results show that the average farm technical efficiency is 68.3%, which suggests that the production can be further improved. The PSM estimation indicates that FFS-ICM increased the technical efficiency by 1.48%, demonstrating the importance of agricultural extension programmes in rural areas in Indonesia. Nevertheless, the relatively small estimated impact raises the issue of cost effectiveness of the programme.

Economic and Technical Efficiency of Maize Production in the Eastern District of Bhutan: Stochastic Frontier Approach

This research paper seeks to deal with the problem of economic and technical efficiency of maize farmers located in the eastern region of Bhutan. For the objective of this paper, the stochastic frontier parametric approach was employed. The socio-economic and production data were collected from 120 maize growing farmers using simple random sampling technique for the production year 2020-2021. Results show that maize producing farmers are 81.47 % technically efficient and 78.19 % economically efficient in producing maize. Farm size, household size, and training positively influences the maize efficiency. The paper presents supporting evidence for more government policy in terms of provision of subsidies on agrochemicals and providing training for better management skills to the farmers.

Impact of natural resource conservation technology on productivity and technical efficiency in rainfed areas of Southern India

This paper assessed the impact of natural resource management technology (NRCT) on productivity and efficiency in maize production using an endogenous switching regression model in rainfed areas of Southern India. We also identified factors influencing adoption of NRCT, and technical efficiency in maize production. For this study, plot-level primary data from 303 farm households cultivating maize on 419 plots were collected. Results show that adoption of NRCT has resulted in an increase in maize productivity by 490 kg per ha and has also reduced technical inefficiency by 28% as compared to non-adopters. Furthermore, access to credit, better extension services and training on natural resource management are crucial factors positively affecting the adoption of NRCT as well as enhancing the technical efficiency of maize production. Therefore, these factors need to be considered when formulating policies and programmes that aim to improve crop productivity in rainfed areas, as well as sustaining natural resources.

Technical Efficiency of Maize Production and Its Influencing Factors in the World’s Largest Groundwater Drop Funnel Area, China

Improving the efficiency of maize production is of great significance for global food security and the effective supply of agricultural products. Based on the survey data of 381 rural households, this study uses a stochastic frontier analysis to estimate the efficiency value and empirically analyze the factors affecting the technology efficiency of maize production in the Hengshui area of the North China Plain. First, higher costs were found to be related to extensive production methods of fertilization, pesticide application, and irrigation. Second, the results showed that there was an inverted U-shaped relationship between the irrigation cost and maize output. Specifically, when the irrigation cost was about 938 yuan/hectare, the maize output per unit area was optimal. Third, there was also an inverted U-shaped relationship between the fertilizer cost and maize output, and the loss of technical efficiency of maize output was minimal when the fertilizer cost is 2547 yuan/hectare. In addition, the findings of the inefficiency influencing factor model suggested that temperature and humidity were all positively associated with the non-efficiency of maize production. These findings can provide empirical support for improving the efficiency of maize production in North China or arid and semi-arid regions around the world.

Modelling technical efficiency and technology gap in smallholder maize sector in Ethiopia: accounting for farm heterogeneity

ABSTRACT This paper examines the effect of farm heterogeneity on the technical efficiency and technology gap of maize production in Ethiopia. We utilize comprehensive household-level data in 2010, 2013 and 2015 for three major maize producing regions in Ethiopia. We estimate technical efficiency using a bias-corrected stochastic meta-frontier model that accounts for technological differences and the consistent ‘true’ fixed-effects stochastic frontier model, which disentangles unobservable farm heterogeneity from inefficiency. We find that maize farmers produce below their potential output with the technology available and the prevailing environmental conditions in their regions. The results show that Oromia has the highest technical efficiency, followed by SNNP, and Benishangul-Gumuz is the least efficient in maize production. These findings generate important policy implications for achieving increased technical efficiency and reduce the technology gap in maize production. Moreover, the level of education, age of household head, family size, household wealth, and off-farm employment and extension services significantly affect technical efficiency in maize production in Ethiopia.

Adoption of climate-smart agricultural practices and their influence on the technical efficiency of maize production under extreme weather events

Malawi experiences frequent and intense extreme weather events that affect rain-fed household maize production. Thus, households have adopted various climate-smart agriculture (CSA) practices to cushion maize production from the adverse effects of extreme weather events, particularly drought episodes. This study examines the drivers of CSA practices' adoption and their influence on the technical efficiency of maize production among drought-affected households. Based on a conditional logit model, the study finds drought episodes substantively enhancing the adoption of organic manure by 76% and soil and water conservation by 29%. The Cobb-Douglas Stochastic Frontier Analysis reveals that households are 63% technically efficient, implying that they can increase current maize production by 37%. A two-stage Tobit model further shows that concurrent adopting organic manure and inorganic fertilizers in the same farm significantly improves maize production's technical efficiency by 18% and is more noticeable among drought-affected households. This study, therefore, advocates for simultaneous adoption of organic and inorganic fertilizers to enhance the effect of CSA practices on the technical efficiency of maize production under intensifying drought episodes. Besides, the study recommends championing gender-targeting extension services to augment the benefits of CSA practices among female farmers. Ultimately, the study results contribute to the existing literature on improving agricultural productivity under varying weather conditions.

Effects of climate adaptation on technical efficiency of maize production in Northern Ghana

Climate adaptation is an essential strategy for responding to climate change at local levels and required for sustainable food production to meet the growing food demand. In this light, this study analyzed the effects of climate adaptation strategies on technical efficiency of maize farmers in Northern Ghana. This involved a total of 619 maize farmers that were selected through a multistage sampling procedure. A Cobb-Douglas stochastic frontier was fitted to the data. From the result, the major climate adaptation strategies adopted by the farmers include row planting, changing planting date, mixed farming, refilling, and intercropping. The frontier result shows that while climate adaptation significantly leads to higher maize outputs, only crop rotation and row planting significantly improve technical efficiency of maize farmers. Other factors that significantly influence maize output are farm size, labor, seed, and chemicals. The study concludes that climate adaptation, particularly, crop rotation and row planting, remains essential adaptation strategies for sustainable food production in the region. However, further understanding of mechanisms through which majority of the climate adaptation strategies significantly reduce technical efficiency is required.

Does agricultural cooperative membership impact technical efficiency of maize production in Nigeria: An analysis correcting for biases from observed and unobserved attributes.

The formation of agricultural cooperatives has been widely promoted as an agricultural development policy initiative to help smallholder farmers cope with multiple production and marketing challenges. Using a nationally representative survey dataset of smallholder maize producers from rural Nigeria, this study assesses the impact of agricultural cooperative membership on technical efficiency (TE). We based our estimation approach on the combination of a newly developed sample selection stochastic production frontier model with propensity score matching to control for possible selectivity biases from both observables and unobservables. We estimate stochastic meta-frontiers to examine TE differences between cooperative members and non-members. Our results reveal that TE levels of members are consistently higher than that of non-members. This calls for continued policy incentives targeted at encouraging farmers to form as well as participate in agricultural cooperatives.

Economics and Technical Efficiency of Maize Production Among Small Scale Farmers in Abuja, Nigeria: Stochastic Frontier Model Approach

This study evaluated Economics and Technical Efficiency of Maize Production Among Small Scale Farmers in Abuja, Nigeria; Stochastic Frontier Model Approach; Multi-stage sampling technique was adopted and used. Primary data were collected through the use of well-structured questionnaire from one hundred and fifty (150) sampled respondents in the study area. Data were analyzed to achieve the specified objectives using the following tools of analysis, Descriptive Statistics, Stochastic Frontier, Gross Margin Analysis, Financial Analysis, Five Point Likert Scale, and Principal Components Analysis. The results show that majority 40.47% of the sampled respondents were among the age range of 41-50 years of age and 25.33% were within the age bracket of 31-40 years of age. The mean age of the sampled farmers is 44 years. Which indicated that Young and energetic farmers are able to withstand stress and adopt new innovations. Most 88.67% of the farmers were male. Majority 72.67% were married. The mean household size of the sampled respondents is 6 members per family. Majority (67%) of the small-scale maize farmers had 1-2 ha of land and the average farm size cultivated by the farmers was 2.576 ha. The factors influencing total output of maize were seed input (P<0.01), Farm Size (P<0.05), quantity of fertilizer (P<0.05), and labour input (P<0.01) were statistically significant variables. The results of the inefficiency components show that the factors influencing technical inefficiency includes: age (P<0.01), education (P<0.01), access to credit (P<0.05), farming experience, and household size (P<0.05) and were statistically significant. The total revenue realized by the sampled small-scale maize farmers was N238,317 on average. While the total variable costs on average basis was N109,702.93. The gross margin realized was N128667.07. The gross margin ratio was 0.54 while operating ratio calculated was 0.857 and the rate of return on investment (RORI) was 1.17. The retained component from the constraint’s analysis include Lack of Improve Seed, Lack of Transportation, Poor Storage Facilities, Inadequate Capital, and Cattle Herdsmen. The retained components explained 60% of the variation of the component included in the model. The study therefore, recommends that affordable loans and adequate capital should be made available to the small-scale maize farmers, farmers should be properly trained and educated by the non-governmental organizations and extension agents on chemical application, fertilizer use and pests and diseases control measures especially on integrated pest management (IPM). Inputs like improve seeds, fertilizer, and chemicals should be made available to farmers at subsidized rates and at appropriate time coinciding with production periods for proper usage. Provisions should be made for transportation and storage facilities for farmers, the issue of conflict between farmers and herdsmen should be brought to book and resolved amicably for peaceful coexistence.

Analysis of technical efficiency in maize production in Guji Zone: stochastic frontier model

BackgroundThe Guji Zone in particular and Oromia region in general have a huge potential for crop production that can even contribute for the country as a whole in the struggle for achieving food security. Maize is Ethiopia’s largest cereal crop in terms of total production, acreage, and the number of farm holdings. It is one of the staple crops produced in the study area. However, the farm productivity per hectare is low compared to the national average which indicates the presence of farming inefficiency in the study area. Thus, this study was undertaken with the objective of estimating the level of farmers’ technical efficiency in maize production and identifying the factors which determine the variation in the level of technical efficiency among the farmers.ResultsThis study was relied on the primary data collected from a sample of maize producing farm household of Adola Rede and Anna Sorra districts of the Guji Zone using a survey questionnaire. A simple random sampling technique was found appropriate for selecting the respondents, since the populations of these study area are homogeneous. The analysis was relied on a cross-sectional data collected from 234 sample farm households. A one-step stochastic frontier normal/truncated-normal model was used to estimate the farmers’ technical efficiency as well as to identify the determinants of yield per hectare of maize which was estimated by maximum-likelihood method. The empirical result indicates that there are large numbers of inefficient farmers in both districts. The estimated technical efficiency for maize producing farmers is equal to 69.03%. Besides, the current study revealed that 69.23% of maize producing farmers have been operating within a technical efficiency score interval equal to (0.5–0.75) in both districts. In addition, the maize yield per hectare in the study area is very low compared to the national average, i.e., the mean yield is 19.2 quintal per hectare. Moreover, the maximum-likelihood results show that gender of the head of the household, age of the head of the household, farm income, row planting, access to credit, number of active labor force, land size owned, access to improved seed and seed type used, and number of livestock were significantly determine the farmers technical inefficiency.ConclusionThe results of the study revealed that there is an opportunity which is being squandered in maize production in the study area. For instance, with a given technology, it is possible to raise the maize yield per hectare by 30.07% in the study area. Thus, the government and any concerned stakeholders should facilitate access to improved seed and fertilizer, credit, farm technology, and short-term training. Besides, all stakeholders should work in a cooperative and organized manner to implement the full agricultural package on farm level.

Technical Efficiency of Maize Producer Smallholder Farmers in Alefa Woreda, North Western Ethiopia

Efficient uses of the existing resources by farm households improve their productivity and thereby increase their output. Maize is one of the dominant crops in the study area; however its productivity is very low. This shows that it is possible to raise output from existing inputs used if resources are properly used and efficiently allocated. The productivity of maize can be changed due to differences in the efficiency of the production process. Hence, this study aimed to analyzing the technical efficiency of maize production in Alefa District of central Gondar in Ethiopia. The objective of study was to measure the level of technical efficiency of maize producers and to identify the determinants of technical efficiencies in maize production among smallholder farmers in the study area. To address the objective of the study both primary and secondary data were collected. The primary data were collected from 152 maize producer farmers by two- stage sampling technique during 2019/20 production season. For data collection personal interview through a structural interview scheduled was employed. Both descriptive and inferential statistics were used for data analysis. Technical efficiency of sampled farmers in maize production was estimated and analyzed by Cobb-Douglas functional form in stochastic frontier model (SFM) with single stage estimation method. The estimated SFM indicated that input variables (land, labor, oxen and DAP) were found significantly and positively influence maize production. The production of maize by sampled farmers was characterized in constant return to scale (1.08). The estimated gamma (γ) parameter was 0.91, which measures the relative deviation of output from the frontier level due to inefficiency. This implies that about 91% of the total variation in maize output was due to technical inefficiency effects. The estimated mean level of TE of maize producers was 0.82. This implies that production can be increased by 18 percent given the existing technological level. The results of this study indicated that among the farm specific, socioeconomic and institutional factors hypothesized to affect TE, age, family size, education status, frequency of extension contact, off farm income and credit access were significant determinants of the production level of maize. The findings obtained in this study could be quite useful to policy makers. Policy interventions should focus more on timely supply of DAP, and socioeconomic significant variables such as education, age, credit access, off farm income, family size and extension contact improve farmers’ efficiency in production of maize. Key words/Phrase: Maize Production, Single Stage Estimation, Stochastic Frontier Model, Technical Efficiency DOI: 10.7176/JAAS/68-05 Publication date: September 30 th 2020

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

Determinants of Technical Efficiency of Maize Production in Son La Province, Vietnam

Determinants of Technical Efficiency of Maize Production in Son La Province, Vietnam

Technical Efficiency of Maize Production in Fluoride Affected Locales, Tamil Nadu: A Stochastic Frontier Approach

To estimate the technical efficiency of maize production among fluoride affected and non affected locales of Tamil Nadu. A multi-stage sampling method involving a combination of purposive and random sampling procedures was employed in drawing up the samples for collecting primary data. The sample size is about 120. Stochastic frontier production function is used to estimate technical efficiency of maize. The result of stochastic frontier production function indicated that FYM, Potassium, machine power, irrigation and management index have significant influence on yield of maize in less fluoride affected locale, while, seed rate, nitrogen, phosphorous, machine power and irrigation are significantly influence the yield of maize in moderately fluoride affected locale, in case of highly fluoride affected locale, seed rate, nitrogen, phosphorous, potassium and irrigation are significantly influencing the yield of maize, while, nitrogen, potassium, irrigation and management index are significantly influences the yield of maize in non affected locale. The study suggests that awareness of fluoride contamination and averting measures must be disseminated to the farmers.

Agricultural Informatization and Technical Efficiency in Maize Production in Zambia

The cropland productivity gap between Africa and the rest of the world is widening. Fortunately, increasing farmers’ access to useful agricultural information reduces the costs of searching for information, thereby leading to higher agricultural productivity and sustainability. This study investigates the association between the adoption of mobile phones to collect agricultural information and farmers’ technical efficiency (TE) in Zambia. Different from previous studies, we focus on the actual use of mobile phones by farmers rather than mere ownership. Farmers were selected using a two-stage sampling procedure, and the Cobb-Douglas (CD) production function is adopted to estimate the association using two approaches—the conventional stochastic production frontier (SPF) and propensity score matching-stochastic production frontier (PSM-SPF) model. In both cases, we found that the use of mobile phones is significantly and positively associated with farmers’ TE. However, the conventional SFP model exaggerates the TE scores by 5.3% due to its failure to mitigate biases from observed variables. Regarding the agricultural growth indicators (income and output) related to TE, a close inspection reveals that increasing mobile phone use to close the TE gap between the two groups could result in a 5.13% and 8.21% reduction in severity of poverty and extreme poverty, respectively. Additional research is essential to corroborate the findings and analyze the potential causal mechanisms. Our study provides strong evidence to promote mobile phone use in agricultural production in rural Zambia.

Review on Technical Efficiency of maize Production in Ethiopia

The economy of Ethiopia is based on agriculture. Maize (Zea mays) is one of the most important food crops produced by smallholder farmers in Ethiopia and accounted for 28% of total grain production during the 2011/12 Meher season. However, low production and productivity characterizes Ethiopian maize production . The low levels of maize productivity may be the result of technical inefficiencies. Therefore the objective of this review is to review level of technical efficiency and assess the source of technical efficiency in Ethiopia. The review suggested the presence of considerable levels of technical inefficiency in maize productivity. From the empirical estimation, important variables affecting the technical efficiency were found Agro-ecology, oxen holding, farm size and use of high yielding maize varieties, sex, age, membership to cooperatives, training, distance to extension agents and main market, credit, family size, livestock and off-farm income. The most important factor to promote production efficiency is probably access to credit. DOI : 10.7176/FSQM/84-03

Determinants of Technical Efficiency of Maize Production in Ethiopia: An Empirical Review

Ethiopia is an agrarian country where a large majority of the peoples and the poor living in rural areas are deriving their livelihood from agriculture. However, low levels of agricultural productivity and increasing population pressure have been critical problems of Ethiopia. These have aggravated the food insecurity situation by widening the gap between demand for and supply of food. In Ethiopia, information on the levels of productivity of maize and farm household technical efficiency in its production is lacking. This paper is aiming at reviewing the major determinants of technical efficiency of maize in Ethiopia using meta-analysis method. Increasing efficiency in maize production could be taken an important step towards attaining food security. The meta-analysis results revealed that important factors that affects the technical efficiency of maize production in Ethiopia were age, family size, education, land holding, livestock ownership, off-farm income, access to credit, contact with extension workers and distance from the nearest market. Many Literatures also suggests the factors that affect the efficiency variation of smallholder farmers classifying them into different categories. These (in) efficiency factors are classified into demographic such as age and family size; socio-economic like education, land holding, livestock ownership, and off-farm income; institutional factors such as access to credit, and contact with extension workers; and physical factor like distance from the nearest market. Therefore, designing and implementing an appropriate policy intervention by focusing on the above-mentioned factors is important in Ethiopia.

Production efficiency of maize farmers under contract farming in Laos PDR

Maize is the second largest commercial crop in Lao PDR, especially in the northern and southern regions. Traditionally, farmers in Lao PDR produced and distributed products in the market on their own. Recently, however, contract farming has gained in popularity and has become more widely accepted, especially after the country entered international collaborations under the Ayeyawady-ChaoPhraya-Mekong Economic Cooperation Strategy (ACMECS) and the Greater Mekong Sub-region (GMS). This study analyzed the technical efficiency of maize production under the contract farming system. Data were collected from the survey responses of 302 contract farmers in Lao PDR's northern and southern regions and were analyzed using stochastic nonparametric envelopment of data (StoNED). Maize production efficiency estimations were calculated using the Tobit model. The results revealed that the efficiency of contract maize farmers in Lao PDR was on average 0.85 and that the main factors affecting maize production efficiency were the age and education level of the farmer and area of planted land. Age and education level had significantly positive impacts, whereas planted land area had negative impacts.