Impact of land tenure security on technical efficiency for maize production: the case of Central province in Zambia

Structural Adjustment and Economic Efficiency of Rice Farmers in Northern Ghana

Technical efficiency, technical change and return to scale of rice, maize and agricultural production in Vietnam

Maize is the main staple food and cornerstone of Zambia’s agricultural economy and as such, high productivity and efficiency in its production are critical to food security and poverty reduction in the country. This paper estimates the technical efficiency of maize producers in Zambia using Stochastic Frontier Analysis (SFA) and also determines the factors which influence technical efficiency in maize production. Primary data from 400 households in the Central Province of Zambia were used in this study. Results show that there exists opportunities to increase technical efficiency from the present level of inputs. The average technical efficiency was at 50%, with a minimum of 2% and a maximum of 84%. The distribution of the technical efficiency is such that 14% of the farmers have efficiency scores that are less than 30% while 46% of the farmers have technical scores above 50%, and 14% have technical efficiency scores above 70%. Maximum likelihood results showed that the age of a farmer, use of certified hybrid seed, access to loans and extension advice and off-farm income influence technical efficiency. The study recommends Government and other maize stakeholders to devise strategies for improving access to credit and extension services and promoting use of certified hybrid seed as a way to improve the technical efficiency of maize producers in Zambia.

Using a cross sectional data obtained through a multistage sampling technique this study estimates the technical efficiency of maize producing-farmers in Oyo State, Nigeria and further examined the factors that determines the differential in efficiency index. A multistage sampling technique was used to select 120 maize farmers in the study area. Data were collected and subjected to inferential statistics; stochastic frontier production model was used in the analysis to determine the relationship between the maize output and the level of input used in the study area. The empirical results revealed that farm size and Seed were statistically significant at 10 and 1% level respectively in the study area. The estimated gamma parameter (i§) of 0.12 in the study area, indicates that 12% of the total variation in maize output is due to the technical inefficiencies. The mean technical efficiency (χ) was 0.961 while the return to scale (RTS) was 0.587 in the study, it was therefore concluded that there is scope for increasing maize production by 0.39% with the present technology. Therefore the study confirmed that more land can still be open for maize production in the area with the current level of input used. Key words: Technical efficiency, maize production, Oyo State, stochastic production frontier.

Traditional Food Crop Production and Marketing in Sub-Saharan Africa - The Case of Finger Millet in Western Kenya

This study used the stochastic frontier model to examine the technical, allocative and economic efficiency of maize production in northern Ghana using cross-sectional data for the 2011/2012 cropping season. Conventional inputs such as farm size, seed, fertilizer, labour and weedicides were statistically significant and had positive effects on maize output in northern Ghana using the Cobb-Douglas functional form. The mean estimates were 85.1%, 87.8% and 74.7% for technical, allocative and economic efficiencies respectively. Largely, maize production in the study area exhibited increasing returns to scale. The determinants of technical inefficiency were experience, agricultural extension service and gender. Farmers with many years of experience in maize production were more technically efficient and opportunities that bring the less experienced farmers to tap the accumulated knowledge of the more experienced ones would improve maize production. Farmers who had access to agricultural extension services were more technically efficient than those who did not have access and strengthening the extension service would further enable them improve on their technical efficiency. Male farmers were more technically efficient than females in maize cultivation and efforts that stress gender equality as regards access to economic resources, information and decision-making would help narrow this gap. There is allocative inefficiency relative to all the production inputs under the prevailing prices. Land, seed and weedicides would be allocatively efficient by increasing their use by 26.6%, 10.52% and 39.9% respectively. Fertilizer and labour are currently being over-used and requires 82.8% and 94.5% reductions respectively to reach their allocatively efficient points. Keywords : Stochastic Frontier Analysis, Technical Efficiency, Allocative Efficiency, Economic Efficiency, Maize, Northern Ghana An Errata has been published for this article in vol 14 (2) 2017. You can find the link to this Errata here: https://www.ajol.info/index.php/gjds/article/view/162547 DOI: https://dx.doi.org/ 10.4314/gjds.v14i2.16

This study investigates the relationship between farm size and technical efficiency for the production of maize in Rwanda. Since levels of technical efficiency tend to vary considerably across farms in sub-Saharan Africa, with a mixture of both inefficient and fully efficient farms, the use of the conventional stochastic frontier method is not appropriate. In this paper, we apply a zero-inefficiency stochastic frontier method that manages both efficiency and inefficiency in the studied sample. The average technical efficiency of maize farms for the full sample is estimated at 0.64, demonstrating that maize output can be improved by approximately 36% without increasing the proportion of farm inputs used. Regarding the relationship between farm size and technical efficiency, the study results show a positive relationship between farm size and technical efficiency for maize production in Rwanda. Thus, the enforcement of land reforms such as land consolidation and enhanced aggregate productivity growth is needed. The results also indicate that education, cooperative membership, extension services, access to credit, off-farm income, land tenure, and livestock ownership have significant and positive effects on technical efficiency.

A comparative study on area, production, yield and stability of maize in northern and southern districts of Karnataka was conducted, Northern and southern districts of Karnataka were purposively selected due to their major contribution in maize production. Among the northern districts, Belagavi and Haveri and among southern districts, Davangere and Chitradurga had the highest area and production under maize in 2016. Karnataka state is famous for maize production and industrial glucose extraction. Growth in area, production and yield of maize in northern and southern districts of Karnataka was worked out. Right from 2000 to 2014 it was found that northern Karnataka had higher area, production and yield of maize. Area, production and yield ranged from 26, 613 to 62, 103 ha, 52, 997 to 3, 63, 803 MT and 1.80 to 4.65 tonnes per ha respectively in northern Karnataka in comparison to 17, 289 to 41, 901 ha, 36, 217 to 1, 36, 537 MT and 1.88 to 3.49 tonnes/ha respectively in southern karnataka. The compound annual growth rate of area, production and yield under maize in northern Karnataka was estimated at 6.51, 7.55 and 1.07 per cent respectively. In case of southern Karnataka growth in area, production and yield increased by 6.90, 9.38 and 2.50 per cent respectively. Average instability in area, production and yield of maize in northern and southern Karnataka was worked out and it was estimated to be 58, 65 and 37 per cent for northern Karnataka and 51, 59 and 44 per cent respectively for southern Karnataka. Hence it could be inferred that northern Karnataka had higher instability in production and yield and southern Karnataka in area.

Maize farming in Swaziland is divided into subsistence farming on Swazi Nation Land (SNL) and commercial farming on Title Deed Land (TDL). Maize production on SNL accounts for only 10% of total agricultural output in Swaziland. While almost all households in SNL produce maize, the country has never reached self-sufficient levels in maize production. For the past 40 years, Swaziland has not been able to meet the population's maize requirements. Currently, the domestic shortfalls of maize are covered by imports through the National Maize Corporation. Swaziland continues to experience a downward trend on maize production, while maize demand has been increasing. This study was aimed at estimating technical efficiency of maize production and determining the factors affecting technical efficiency in Swaziland. The stochastic frontier approach was used to estimate the technical efficiency of 127 farmers and the two-limit Tobit model was used to determine the factors affecting technical efficiency of the farmers. The results revealed that there is a wide variability in the production of maize since technical efficiency ranged from 14.5 to 93.3% with a mean of 80.0%. The most important contributors to the maize production process were the amount of seeds, fertilizer, pesticides and labour used per hectare. Technical efficiency was found to be positively associated with farmers' age, having off-farm income, farmers' experience, intercropping and use of hybrid seeds. The gamma, (γ), was 68% and significant at 1% indicating that the variation in maize output was due to factors within the control of the farmers. It is recommended that the government needs to provide input subsidies so that farmers can use more inputs to improve their technical efficiency. Key words: Technical efficiency, maize production, stochastic frontier function, Cobb-Douglas production.

This study contributes to the literature on the impact of farmer contact with agricultural extension services on farm productivity, drawing on a unique panel sample of households residing in three resettlement areas of rural Zimbabwe. It pays particular attention to the potential confounding effects of the biases identified by Birkhaeuser, Evenson, and Feder. Specifically, we exploit the longitudinal nature of our data to estimate the impact of extension on the value of crop production per hectare, with and without controls for unobservable household fixed effects. The attraction of this estimator is that the differencing process rids the specification of the correlation between extension and the disturbance term. We find that after controlling for innate productivity characteristics and farmers' ability using household fixed- effects estimation, access to agricultural extension services, defined as receiving one or two visits per agricultural year, raises the value of crop production by about 15%. This parameter estimate is statistically significant. Another unique feature of these data are, for a subsample, extension worker assessments of farmers' ability. We find that farmers with above-average ability are indeed more productive, producing 40%-50% higher output per hectare of cropped area. Controlling for innate productivity using locality dummies, farm plot characteristics, and farmers' ability using these assessments of ability, we continue to obtain a positive association between access to extension and productivity, an association that is equal in magnitude to our fixed-effects results. However, we also find considerable variability in these parameter estimates across individual crop years.

This study was conducted in Musanze and Bugesera districts of Rwanda .The objective were to estimate the level of technical efficiency in maize production. The study also attempted to determine some socio-economic characteristics which influence technical efficiency in maize production. It used primary and secondary data. Primary data were collected using questionnaire from random sample of 276 farmers, and it covered the socio-economic characteristics of farmers. Secondary data were collected from different sources, e.g., Ministry of Agriculture and livestock, records, books, reports and internet. The Stochastic Production Frontier (SPF) analysis was used to estimate the technical efficiency of producing maize, and to determine the factors behind inefficiency such as age, educational level, marital status, family size, main occupation, type of seeds, and extension services. Also, descriptive statistics were used to analyze the socio-economic characteristics of farmers. The results indicated that the mean technical efficiency for maize production in both districts is 27% which means that farmers can increase their output by 34%, through better use of available resources and existing technology if they are to be technically efficient. The study concluded that age, educational level and access to credit were significant variables leading to technical inefficiency in Rwanda. On the other hand, marital status, family size, main occupation, type of seeds, and extension services, had no significant impact on farmers' inefficiency. To improve technical efficiency for maize production in the Rwanda, the study recommended improvement in education level of the farmers and availability of funds in the optimum time. Key words : maize Productivity; Technical efficiency; stochastic frontier production

This dissertation set out to evaluate the impact of land ownership and role of gender to the Filipino farmers and to investigate gender difference in agricultural productivity and technical efficiency of Malawian rural households. The first essay investigates the impact of land ownership on the productivity and technical efficiency of rice farmers in the Philippines. We use a 2007-2012 Loop Survey from the International Rice Research Institute (IRRI) and analyzed it by using a stochastic frontier function method. Results show that land ownership has a significant impact on technical efficiency. In particular, counter to the theory, the Comprehensive Agrarian Reform Policy (CARP) may have reduced the technical efficiency of leasehold farmers compared with owner operators. Additionally, results show that land area, fuel cost, fertilizer cost, irrigation cost, and labor cost are significant factors that affect rice production. We found a mean technical efficiency score of 0.79—still leaving room for improvement. Finally, educated females and farmers leasing land have higher technical inefficiency. The second essay investigates the effect of gender on rice production using the average treatment effect and farm level data from the Philippines. Results indicate that female-headed farm households, despite having limited access to land, have a higher value of rice production than their male counterparts. However, there is no significant difference between net farm incomes earned by male- and female-headed farm households. Female-headed households have higher fixed costs, consequently earning less total household income. Findings from this study indicate that women are less efficient in farming, but are more likely to adopt improved seed varieties. In addition, female-headed farm households are better at controlling farming costs. The third essay examine how gender affects technical efficiency using a case of maize production in Malawi. Maize is a staple food crop in sub-Saharan Africa. Using the third Integrated Household Survey data from Malawi and stochastic production frontier, we estimate maize productivity and technical efficiency in Malawi for male-headed and female-headed farm households, separately. Results show that, contrary to expectations, technical efficiency is 5% higher for female-headed farm households than for male-headed farm households.

(ProQuest: ... denotes formulae omitted.)1. IntroductionSalinity has emerged as the major factor responsible for low crop production in Iraq (Hatem et al., 2012; Wu et al., 2014a and 2014b). In recent years, various regions have lost significant agricultural productivity due to soil salinity. This situation is particularly critical for the Al-Musayyeb area, which produces an important share of crops for the whole country (Hatem et al., 2012). In the past, the Iraqi economy was heavily dependent on agriculture for employment generation through exports of agricultural goods and agro industries such as the cotton crop for the textile sector. In the last 15 years there has been a phenomenon of increased reliance on women in the agricultural sector. In 2000, women represented more than 50% of all workers in agriculture and were expected to increase to about 60% in 2010 (Telleria et al., 2012).Annual loss of cultivated lands in Iraq is about 5% due to salinization and water logging (FAO, 2003). Of the total land area of Iraq (43 million ha), 8.2 million ha (18.8%) is agricultural area, 4 million ha (9.2%) is arable land, 4 million ha is permanent meadows and pastures, 0.85 million (2%) ha is forest and the rest corresponds to areas not used for agricultural or forest purposes (FAOSTAT, 2014). Of the 3.5 million ha equipped for irrigation (FAOSTAT, 2014), approximately 1.5 million ha is estimated to be moderately salinized, while 0.5 million ha has severe levels of salinity that prevent farming. Due to soil salinity-fallow practices, and the unstable political situation, it is estimated that only 2.8-4.9 million ha is actually cultivated annually.Soil salinity explains up to 50% of lost agricultural productivity in saline-affected areas (Soppe and Saleh, 2012; Dhehibi et al., 2013). Other factors, such as outdated agricultural machinery, poor management practices and lack of fertilizers, certified seeds and pesticides have to a lesser extent negatively affected agricultural productivity growth. From the national context and in historical perspective, there is no doubt that the Iran-Iraq War (1980-1988), the Gulf War (1990-1991), the period of United Nations sanctions (1990-2003) and the Iraqi occupation (2003-2011) have meant about 30 years of conflict for the country and undermined efforts to develop the agricultural system in Iraq, including to improve agricultural productivity. These conflicts have particularly weakened the infrastructure and the whole chain and marketing system of agricultural and livestock commodities.It is clear that salt-induced land degradation occurs in both on and off sites and affects the livelihoods inside and outside the farming communities. However, there would be a need for thinking and acting beyond the classical farm level salinity management. It is within this context that this research paper attempt to fill the gaps identified in the analysis of the impact of salinity on livelihoods by determining the extent to which it is possible to raise efficiency for salt-affected farmers with the existing resources base and available technology.Following this Introduction, Section 2 describes the conceptual framework to measure both technical and allocative efficiency using a production and cost function framework plus the model specifications. The study area and data used are outlined in Section 3. Section 4 deals with the presentation and discussion of our empirical results. In the last section, conclusion and policy implications emerging from the results are presented.2. Conceptual Framework: Efficiency and Frontier Production FunctionsEfficiency is a very important factor of productivity growth, especially in developing agricultural economies where resources are scarce and opportunities for developing and adopting better technologies are essential. Two techniques of estimating a firm's relative position to the frontier are used in empirical studies: non-parametric approaches that involve Data Envelopment Analysis (DEA), and parametric approaches that comprise econometric models (such the Stochastic Frontier Production Function - SFPF) and index numbers. …

The objective of this study was to examine the level of technical efficiency of smallholder maize producers and identify its determinants in Horo Guduru Wollega zone of Oromia Regional State, Ethiopia. A Cobb-Douglass stochastic production function model was used for the analysis. To specify technical inefficiency effects of socioeconomic variables, Maximum Likelihood Estimation (MLE) technique using data collected from 120 randomly selected sample farmers in 2011 was applied. The MLE results reveal that farm size under maize cultivation, chemical fertilizer (DAP) and maize seed are the major factors that are associated with changes in the maize output. The effect of land area on output is positive and the coefficient is found to be significant, implying the economies of scale. The test result indicates that there is inefficiency in the production of maize in the study area. The relative deviation from the frontier due to inefficiency is 85 percent. The average estimated technical efficiency for smallholder maize producers ranges from 0.06 to 0.92 with a mean technical efficiency of 0.66 (66%). The analysis also reveals that the educational level of the farmer, age of household head, land fragmentation, extension services, engagement in off-farm/non-farm activities, and total land holding of the farmer are the major socioeconomic factors influencing farmers’ technical efficiency and maize output. The implication of the study is that technical efficiency in maize production in the study area could be increased by 34 percent through better use of available resources, given the current state of technology.Keywords: Food security, Maize, Technical Efficiency, Stochastic Frontier Analysis, Horo Guduru Wollega

Increasingly, maize is becoming a staple food for many Sub-Saharan Africa (SSA) countries, and hence, it is regarded important in mitigating increasing incidences of hunger and famine in the region. This article reviews and compares literature related to farm level technical efficiency of small-scale maize production among countries of the SSA. A total of 17 studies from 11 different countries were examined. At least 2 studies related to small-scale maize farmers' technical efficiency were drawn from 6 countries, East African region being the most represented. Presentations of discussions were divided into three regions namely the West Africa, the East Africa, and the Southern Africa regions, respectively. Maize productivity in the Sub-Saharan region seem to be low, South Africa scoring only 4.37 tonnes/ha of maize far less than the potential grain yield of maize ranging between 7 tonnes/ha to 12 tonnes/ha. This prompts the region to import more grains to meet its domestic demand. The average technical efficiency (TE) index from all the studies reviewed is 70%. Although South Africa as a country had the highest average score of technical efficiency index (98%), West Africa as a region had the highest score of 82%, followed by Southern Africa region with 72%, and East African region scored only 57% on average. Overall technical efficiency scores suggest that there is considerable room to maximize agricultural output with the available resources and without changing the existing technologies. All reviewed studies sought to explain socioeconomic factors responsible for farm level variation in TE. Family farm labour (household size), availability of maize markets, improved seed variety, use of agro-chemical, access to farm credit, off-farm incomes and group membership were key outstanding socioeconomic factors that had a positive and significant impact on technical efficiency in the SSA region. For increased maize output and reduced budgets on maize imports, the region needs to focus and catalyse policies related to strengthening research and dissemination of technologies on maize breeding, labour saving technologies, growth in agro- industry, strengthening farmer cooperatives and maize markets, and strengthening of farmers' savings and credit facilities.