Resource allocation and productivity of cereal state farms in Ethiopia (original) (raw)
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Sources of productivity growth in Ethiopian agriculture
In Ethiopia, agricultural production and productivity are very low, and hence increase in production and productivity are vital to meet increasing food demand. This study identifies and quantifies the main sources of productivity growth in Ethiopian agriculture using the translog (TL) stochastic input distance function and the Ethiopian Rural Household Survey (ERHS) panel dataset. The true fixed effects (TFE) panel data estimator is used to separate inefficiency effects from observed and unobserved heterogeneity. The parametric Malmquist productivity index (MPI) is used to decompose total agricultural growth into three major sources. The average technical efficiency score was 0.875; this finding indicates that on average a farmer produces 87.5% of the value of the output that is produced by the most efficient farmer using the same technology and inputs. This implies that they can reduce the inputs required to produce the average output by 12.5% if their farming operation becomes technically efficient. MPI shows that the average annual productivity growth was 17.9% between 1994 and 2009. Further decomposition of the index shows that scale efficiency change is the most important source of this growth, and accounts for about 14.5%. Technological improvement accounts for approximately 4.8% while the contribution of technical efficiency change is negative, leading to an annual productivity decline of 1.3%. This finding suggests that increasing productivity is possible via improving these components by improving training to the farmers, extension services, research and development, and agronomic practices.
Impact of Agricultural Inputs Use on Productivity of Major Crops in Southern Ethiopia
Research Square (Research Square), 2022
This invention describes that the rate of input utilization is decisive for productivity growth of considered crops. The invention enhances the productivity of major crops like maize, teff, wheat, barley and sorghum crops. The sample was based on a panel data of (2011, 2013, and 2015) acquired from the Ethiopian socioeconomic survey was used. The invention was scientifically analyzed using the basic fixed effect model and dose-response function under exogenous and endogenous treatment models. In the exogenous and endogenous treatment cases, households applying fertilizer have achieved actual different levels of higher outputs than their counterparts. In endogenous treatment, the household applying fertilizer harvested much higher output than those in the counterfactual condition. Moreover, inputs: fertilizer, seed, labor force, and farm capital utilization have a critical impact on the aggregate outputs of considered crops.
Abdella Mohammed Ahmed (M.Sc.), 2024
In an effort to boost agricultural productivity the Ethiopian government has embarked on implementing policy reforms since 1991. Assessing the performance of this sector after the introduction of these policies can help to evaluate the real impact of the reforms on agricultural productivity and to design future policy reforms or take corrective measures. In this paper we employ the stochastic frontier production function to examine technical, allocate and economic efficiency in crop production using farm level data from 1993/94 and 2000/01 production years in post-reform Ethiopia. In addition, we decompose the growth in agricultural production to examine the contributions of the changes in efficiency, technology and inputs to the total factor productivity (TFP) in agriculture. Results show that there are inefficiencies attributable to household and farm characteristics and the policy environment. There was a decline in TFP, allocates and economic efficiency during the period resulting in poor performance of the sub-sector and indicating an adverse impact of the reform. There was no significant change in technical efficiency.
Technical Efficiency of Agricultural Production in Ethiopia
Journal of Natural Sciences Research, 2020
Farmers faced low productivity due to lack of knowledge on maximizing level of output at the given level of inputs. Technical efficiency of agricultural production in the Ethiopia were assessed by using cross-sectional secondary data collected from Ethiopia socioeconomic survey in 2015/16 production year. Cobb-Douglas stochastic frontier production function model was used to estimate technology and determinants of technical inefficiency simultaneously using the maximum likelihood estimator (MLN). MLN estimation results showed that increasing input use like area, seed, oxen, fertilizer and labor would increase yield of agricultural production. The coefficients of elasticity for area, seed, oxen, fertilizer and labor were 0.21, 0.29, 0.38, 0.12 and 0.10 respectively. Consequently, agricultural production exhibits increasing return to scale because the sums of input elasticity's were greater than one which is 1.1. The mean technical efficiency of farmers in the agricultural production was about 36%. The implication is that there is an opportunity to increase output on average by 64% through efficient use of inputs given the current input use and technology. The discrepancy ratio gamma (γ) which measures the relative deviation of output from the frontier due to inefficiency was about 86 percent indicating that about 86% of variation in agricultural production among the farmers was attributed to technical inefficiency effects. Thus, it is possible to improve technical efficiency through better use of these factors.
Determinants of Cereal Crops Productivity: In Case of Kecha Birra Woreda, Snnpr, Ethiopia
2019
This study conducted to investigate the determinants of cereal crop productivity of small household farmers in southern region, a case of Kecha Birra woreda.To study the determinants of cereal crop productivity descriptive and econometrics analysis was carried out, a positive increasing trend was found in agricultural productivity and data collection was from rural household farmers selected through random sampling techniques for the collected cross-sectional data on 100 samples of the farmers at household level. Agriculture plays prominent role in the process of economic development for a country. Without achieving substantial increase in agricultural production, no country has moved to take off stage of economic development. The general objective of the study is to assess the determinants of cereal crop productivity in Kecha Birra Woreda. The study found that improved seed, farm size, fertilizer, education, family size, age, and irrigation have the positive effects in the product...
Production Efficiency and Agricultural Technologies in the Ethiopian Agriculture
1993
Stochastic frontier production function analysis was performed to examine relative crop and milk production efficiency among peasants in Ada and Selale districts of the Central highlands of Ethiopia. The results indicate that Ada farmers exhibit relatively higher efficiency scores in cereal production compared to Selale producers. Farmers who adopted cross-bred cows attained higher efficiency scores than farmers who did not adopted. Production efficiency scores are higher in enterprises that enjoys experience and location specific comparative advantages. The magnitude of the impacts of knowledge-related variables (i.e., production knowledge and schooling) on production efficiency are higher relative to other variables. Adoption of one or two innovations show a consistently large, positive and significant effect on all measures of production efficiency in the Selale region. Higher production efficiency is attained in Ada region if producers adopt two or more technologies. Development...
Sustainability, 2021
(1) Background: Even though agriculture is the backbone of the Ethiopian economy, the improvements made regarding crop productivity appeared insufficient and had slow progress. Several studies suggest possible ways to identify the challenges in the productivity of the crop sub-sector. Nevertheless, there are gaps in the empirical literature in both knowledge and methods. The current study intends to identify the factors that affect growth in the productivity of teff, maize, barley, wheat, and sorghum crops. (2) Methods: Cobb-Douglass stochastic production function is estimated using a panel data set of the Living Standard Measurement Survey. To address the objectives of the study, a parametric estimation with a time-varying decay model with deterministic and stochastic components was adopted. (3) Results and Discussion: The effect of inputs on aggregate output was positive and significant at the 1% significance level, implying the presence of economies of scale. Variation in the inefficiency term explained 46.4% of the total variance in the composed error term. The average productivity of major crops was 6.19 per year. This study implied that technical change in the production of major crops increased by 22% with better use of available technology. (4) Conclusion and Policy Implication: The findings pinpoint that farmers should focus on technical change and intensification of improved agricultural inputs.
Agricultural Transformation in Africa? Assessing the Evidence in Ethiopia
World Development
Despite significant efforts, Africa has struggled to imitate the rapid agricultural growth that took place in Asia in the 1960s and 1970s. As a rare but important exception, Ethiopia's agriculture sector recorded remarkable rapid growth during 2004-14. This paper explores this rapid change in the agriculture sector of this important country-the second most populous in Africa. We review the evidence on agricultural growth and decompose the contributions of modern inputs to growth using an adjusted Solow decomposition model. We also highlight the key pathways Ethiopia followed to achieve its agricultural growth. We find that land and labor use expanded significantly and total factor productivity grew by about 2.3% per year over the study period. Moreover, modern input use more than doubled, explaining some of this growth. The expansion in modern input use appears to have been driven by high government expenditures on the agriculture sector, including agricultural extension, but also by an improved road network, higher rural education levels, and favorable international and local price incentives.
Factors affecting agricultural production in Tigray Region, Northern Ethiopia
2015
This study investigates the factors affecting agricultural production of farm households in the National Regional State of Tigray, Ethiopia. The major primary sources of data for the study were farm household surveys, focus group discussions and key informant interviews. The study revealed that the annual average crop production of respondents was found to be below the standard annual food requirement recommended by the international organizations. The proportion of irrigated land to total cultivated land was only 11per cent. The proportion of irrigated land in the two districts is lower than 11.27 per cent at the regional level. The utilization of chemical fertilizers for the majority of the respondents was below the recommended standard for the region. Although the farmers were interested in using improved seeds, the supplied varieties were not based on their preferences. Extension agents were mainly engaged in activities which were not related to their professions. The farm income model result showed that landholding size (p<0.0001), possession of oxen(p<0.0001), amount of fertilizer(p=0.010), improved seeds(p=0.002), irrigation(p=0.028), soil quality(p=0.019), village distance to the district market(p=0.066), average distance of plots from the homestead (p=0.023) and crop rotation(p=0.016) were determinant variables. Farmers were engaged in off-farm activities to fulfill the cash requirements in credit constrained conditions. The laws of the region do not allow farmers to be out of their localities for more than two years and the farmerswere restricted to renting out only half of their land. This discouraged farmers from off-farm participation for fear of land confiscation. In the Probit model, the determinant variables of off-farm participation were: irrigation (p=0.001), age (p=0.007), amount of money borrowed (p=0.078), village distance to the wereda market (p=0.055), fear of land confiscation (p=0.023) and access to electricity (p=0.044). It is recommended that if farmers are to use chemical fertilizers, they should be supplied with High Yielding Varieties (HYV)and enough water through access to irrigation. Furthermore, farmers should be allowed to have long term off-farm employment to augment the farming sector.