The Influence of Misspecification in Stochastic Frontier Analysis Models: A Simulation Approach

2010 ◽  
Author(s):  
Aljar Meesters
Keyword(s):  
Stochastic Frontier Analysis ◽  
Stochastic Frontier ◽  
Simulation Approach ◽  
Frontier Analysis ◽  
Analysis Models

scholarly journals The Cost Efficiency of the Brazilian Electricity Distribution Utilities: A Comparison of Bayesian SFA and DEA Models

2010 ◽  
Vol 2010 ◽  
pp. 1-20 ◽  
Author(s):  
Marcus Vinicius Pereira de Souza ◽  
Madiagne Diallo ◽  
Reinaldo Castro Souza ◽  
Tara Keshar Nanda Baidya
Keyword(s):  
Cost Efficiency ◽  
Stochastic Frontier Analysis ◽  
Stochastic Frontier ◽  
Fundamental Aspect ◽  
Data Envelopment ◽  
Electricity Distribution ◽  
Frontier Analysis ◽  
Dea Models ◽  
The Cost ◽  
Analysis Models

The purpose of this study is to evaluate the efficiency indices for 60 Brazilian electricity distribution utilities. These scores are obtained by DEA (Data Envelopment Analysis) and Bayesian Stochastic Frontier Analysis models, two techniques that can reduce the information asymmetry and improve the regulator's skill to compare the performance of the utilities, a fundamental aspect in incentive regulation schemes. In addition, this paper also addresses the problem of identifying outliers and influential observations in deterministic nonparametric DEA models.

scholarly journals Wheat yield gaps across smallholder farming systems in Ethiopia

2021 ◽  
Vol 41 (1) ◽  
Author(s):  
João Vasco Silva ◽  
Pytrik Reidsma ◽  
Frédéric Baudron ◽  
Moti Jaleta ◽  
Kindie Tesfaye ◽  
...  
Keyword(s):  
Stochastic Frontier Analysis ◽  
Stochastic Frontier ◽  
Wheat Yield ◽  
Farming Systems ◽  
Smallholder Farming ◽  
Yield Gap ◽  
Frontier Analysis ◽  
Ecological Zones ◽  
Relative Contribution ◽  
Yield Gaps

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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