Do Decision Variables Improve Microfinance Efficiency? A Stochastic Frontier Analysis for African Countries

2017 ◽  
Vol 26 (2) ◽  
pp. 159-174 ◽  
Author(s):  
Sandra Kendo
Energies ◽  
2021 ◽  
Vol 14 (4) ◽  
pp. 1168
Author(s):  
Victor Moutinho ◽  
Mara Madaleno

This study aims to evaluate the economic and environmental efficiency of Asian and African economies. In the model proposed, Gross Domestic Product (GDP) is considered as the desired output and Greenhouse Gases (GHG), like carbon dioxide (CO2) emissions, as the undesirable output. Capital, labor, fossil fuels, and renewable energy consumption are regarded as inputs, and the GDP/CO2 ratio is the output, by using a log-linear Translog production function and using data from 2005 until 2018, including 22 Asian and 22 African countries. Results evidence cross-countries heterogeneity among production inputs, namely labor, capital, and type of energy use and its efficiency. The models complement each other and are based on different distributional assumptions and estimation methods while providing a picture of Eco-efficiency in Asian and African economies. Labor and renewable energy share increase technical Eco-efficiency, while fixed capital decreases it under time-variant models. Technical improvements in Eco-efficiency are verified through time considering the time variable into the model estimations, replacing fossil fuels with renewable sources. An inverted U-shaped Eco-efficiency function is found concerning the share of fossil fuel consumption. Important policy implications are drawn from the results regarding the empirical results.


2021 ◽  
Vol 41 (1) ◽  
Author(s):  
João Vasco Silva ◽  
Pytrik Reidsma ◽  
Frédéric Baudron ◽  
Moti Jaleta ◽  
Kindie Tesfaye ◽  
...  

AbstractWheat yields in Ethiopia need to increase considerably to reduce import dependency and keep up with the expected increase in population and dietary changes. Despite the yield progress observed in recent years, wheat yield gaps remain large. Here, we decompose wheat yield gaps in Ethiopia into efficiency, resource, and technology yield gaps and relate those yield gaps to broader farm(ing) systems aspects. To do so, stochastic frontier analysis was applied to a nationally representative panel dataset covering the Meher seasons of 2009 and 2013 and crop modelling was used to simulate the water-limited yield (Yw) in the same years. Farming systems analysis was conducted to describe crop area shares and the availability of land, labour, and capital in contrasting administrative zones. Wheat yield in farmers’ fields averaged 1.9 t ha− 1 corresponding to ca. 20% of Yw. Most of the yield gap was attributed to the technology yield gap (> 50% of Yw) but narrowing efficiency (ca. 10% of Yw) and resource yield gaps (ca. 15% of Yw) with current technologies can nearly double actual yields and contribute to achieve wheat self-sufficiency in Ethiopia. There were small differences in the relative contribution of the intermediate yield gaps to the overall yield gap across agro-ecological zones, administrative zones, and farming systems. At farm level, oxen ownership was positively associated with the wheat cultivated area in zones with relatively large cultivated areas per household (West Arsi and North Showa) while no relationship was found between oxen ownership and the amount of inputs used per hectare of wheat in the zones studied. This is the first thorough yield gap decomposition for wheat in Ethiopia and our results suggest government policies aiming to increase wheat production should prioritise accessibility and affordability of inputs and dissemination of technologies that allow for precise use of these inputs.


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