The existing state of over-utilization of input resources affected the efficient production of the agricultural output, which created a challenge for the profitability of the farming community as w...

Systematic Review and Meta- regression Analysis of Technical Efficiency of Agricultural Production Systems:

espanolEn esta investigacion, se desarrollo un metodo para evaluar y predecir la eficiencia de pequenas empresas exportadoras tomando como variables de entrada o recurso los rubros financieros total activos, patrimonio, total pasivo, gastos operacionales, costos de ventas y como variables de salida o resultado las ventas netas, utilidad neta y utilidad operacional. Para esto se utilizo el analisis envolvente de datos en la evaluacion de la eficiencia, el analisis discriminante en la valoracion de la clasificacion de empresas eficientes y no eficientes y las redes neuronales artificiales para evaluar su capacidad de prediccion clasificatoria en 90 empresas del sector de la ciudad de Barranquilla-Colombia. Los resultados permitieron clasificar las empresas segun nivel de eficiencia mostrandose una eficiencia tecnica promedio del 41,38% del sector con 11 empresas representativas de la eficiencia. Los resultados muestran la relevancia de la metodologia propuesta para clasificar y pronosticar correctamente la eficiencia tecnica en las pequenas empresas exportadoras. EnglishIn this research, a method was developed to evaluate and predict the efficiency of small exporting companies taking as input or asset variables the total assets, equity, total liabilities, operating expenses, sales costs and as output or result variables. net sales, net income and operating income. For this, the envelopment data analysis was used in the evaluation of the efficiency, the discriminant analysis in the evaluation of the classification of efficient and inefficient companies and the artificial neural networks to evaluate its capacity of classification prediction in 90 companies of the sector of the city of Barranquilla-Colombia. The results allowed to classify the companies according to level of efficiency showing an average technical efficiency of 41.38% of the sector with 11 representative companies of efficiency. The results show the relevance of the proposed methodology to correctly classify and forecast technical efficiency in small exporting companies.

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Método Análisis Envolvente de Datos y Redes Neuronales en la Evaluación y Predicción de la Eficiencia Técnica de Pequeñas Empresas Exportadoras

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. 

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

Tobacco is considered as one of the most important industrial cash crop and source of livelihood to many families in Pakistan. Considering the contraction of land under tobacco cultivation, the present study is intended to evaluate the production efficiency of tobacco growers in southern Punjab, Pakistan. The Data Envelopment Analysis model was used to investigate energy usage efficiency of tobacco farmers based on seven energy inputs; human labour, farm machinery, irrigation, diesel, fertilizers, chemicals, seeds, and a single output. Moreover, the current study also used DEA – super efficiency to identify and rank efficient and inefficient tobacco producers; and to suggest optimum energy requirements and energy savings potentials. The primary data from 210 tobacco growers were collected in-person interviews by random sampling technique. The findings of the study revealed that average energy consumed in the form of inputs and yield obtained in tobacco production was 52,703.58 MJ/ha-1 and 3,096.98 MJ/ha-1, respectively. Average technical, pure technical, and scale efficiency score was calculated to be 0.902, 0.961, and 0.938, respectively. Likewise, the energy-saving ratio in tobacco production was estimated to be 13.83%, which implies that by adopting the proposed recommendations about 7,121.66 MJ/ha-1 energy could be saved without compromising the output. Also, fertilizers, chemicals, irrigation, and diesel had the highest share in the consumption of energy inputs. The findings of the study provides pinpoint options to the agricultural polices makers to launch the technical training programs for the tobacco farmers to adopt better management practices to optimize the application of energy inputs to reduce the cost of tobacco production. The agricultural extension department should also visit the tobacco fields to assist the farmers about timely application of inputs and with extension services.

/pdf/evaluating-energy-consumption-efficiency-in-tobacco-1v50sh9pw0.pdf

Evaluating energy consumption efficiency in tobacco production: applying data envelopment analysis

The aim of the article was to evaluate production efficiency changes of agricultural enterprises specialized in livestock production and identify its determinants. The total factor productivity (TFP) was used to analyse the changes as determined by the DEA Malmquist index. Evaluated sample contained panel data of 440 farms (114 organic and 326 conventional) based on FADN survey in the period 2011 - 2015. The results showed very little difference in technical efficiency between groups and relatively negligible changes over the time. About 69% of organic farms reached the productivity growth with the change in TFP of 3.17%. A total of 59% of conventional farms were managed with increasing productivity and the TFP change by 1.48%. Differences between groups were given mainly by Utilized agricultural area per farm, level of Total production, Livestock output, sum of Current subsidies per hectare, and by FNVA / AWU.

/pdf/farms-productivity-developments-based-on-malmquist-3eor6stdit.pdf

Farms Productivity Developments Based on Malmquist Production Indices

The objective of this study was to determine the economic efficiency of resource utilization in broiler production farms using a non-parametric production function, data envelopment analysis (DEA). Data for the analysis were collected from a cross section of 44 farmers using a multi-stage sampling procedure. In DEA models the farmers that produce their level of output with the least amount of input serve as benchmarks against which the input use inefficiency of all other farmers can be measured. The total variable costs, net return and benefit cost ratio were calculated to be 3506.29 $ (1000 bird)-1, 1386.53 $ (1000 bird) -1 and 1.38, respectively. The average values of technical and scale efficiencies of farmers were found to be 0.92 and 0.93. The results also revealed that about 10% of the total input resources could be saved if the farmers follow the input package recommended by the DEA.

/pdf/using-nonparametric-analysis-dea-for-measuring-technical-39nhvlfm05.pdf

Using nonparametric analysis (DEA) for measuring technical efficiency in poultry farms

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Using nonparametric analysis (DEA) for measuring technical efficiency in poultry farms