Identifying Technical Efficiency of Dairy Cattle Management in Rural Areas Through a Non-Parametric Method: A Case Study for the East Mediterranean in Turkey

2009 ◽  
Vol 8 (5) ◽  
pp. 863-867 ◽  
Author(s):  
Erdal Dagistan . ◽  
Besir Koc . ◽  
Mevlut Gul . ◽  
Oguz Parlakay . ◽  
M. Goksel Akpinar .
2018 ◽  
Vol 11 (2) ◽  
pp. 188-201
Author(s):  
Teguh Santoso

This study aims to measure the technical efficiency of banks (BUKU I and BUKU II categories). The efficiency calculation in this study uses Non-Parametric method, Data Envelopment Analysis (DEA). This research uses an operational approach in performing input and ouput specifications. The inputs are interest expenses, labor expenses, and other expenses. The result of technical efficiency calculation shows that both banks in BUKU I and BUKU II have less efficient in technical efficiency value, either with the assumption of CRS or VRS. However, the value of technical efficiency indicates that BUKU II banks have greater technical efficiency value than the banks in BUKU I category.


2021 ◽  
Vol 9 (1) ◽  
pp. 7
Author(s):  
Mirpouya Mirmozaffari ◽  
Reza Yazdani ◽  
Elham Shadkam ◽  
Seyed Mohammad Khalili ◽  
Leyla Sadat Tavassoli ◽  
...  

The COVID-19 pandemic has had a significant impact on hospitals and healthcare systems around the world. The cost of business disruption combined with lingering COVID-19 costs has placed many public hospitals on a course to insolvency. To quickly return to financial stability, hospitals should implement efficiency measure. An average technical efficiency (ATE) model made up of data envelopment analysis (DEA) and stochastic frontier analysis (SFA) for assessing efficiency in public hospitals during and after the COVID-19 pandemic is offered. The DEA method is a non-parametric method that requires no information other than the input and output quantities. SFA is a parametric method that considers stochastic noise in data and allows statistical testing of hypotheses about production structure and degree of inefficiency. The rationale for using these two competing approaches is to balance each method’s strengths, weaknesses and introduce a novel integrated approach. To show the applicability and efficacy of the proposed hybrid VRS-CRS-SFA (VCS) model, a case study is presented.


2018 ◽  
Vol 9 (1) ◽  
pp. 51-58
Author(s):  
Arbia Hlali

AbstractThis paper applies a non-parametric method to provide level technical efficiency for 7 Tunisian ports during 18 years (1998-2015). These ports represent different data set. The use of the model of variable returns to scale (VRS) has led to interesting results. The results show that the most ports are characterized by low levels of technical efficiency, with the exception port of Rades. In addition, the result shows the variation of variable returns to scale and constant returns to scale of technical port’s efficiency. Furthermore, we concluded that the panel data improves the efficiency estimates.


2020 ◽  
Vol 19 (1) ◽  
Author(s):  
Remco Oostendorp ◽  
Lia van Wesenbeeck ◽  
Ben Sonneveld ◽  
Precious Zikhali

Abstract Background The impact of diet diversity—defined as the number of different foods or food groups consumed over a given reference period—on child nutrition outcomes strongly interacts with agro-ecological, institutional, and socio-economic drivers of child food and nutrition security. Yet, the literature on the impact of diet diversity typically estimates average treatment effects, largely ignoring impact heterogeneity among different groups. Methods In this paper, we introduce a new method of profiling to identify groups of treatment units that stand to gain the most from a given intervention. We start from the ‘polling approach’ which provides a fully flexible (non-parametric) method to profile vulnerability patterns (patterns in ‘needs’) across highly heterogeneous environments [35]. Here we combine this polling methodology with matching techniques to identify ‘impact profiles’ showing how impact varies across non-parametric profiles. We use this method to explore the potential for improving child nutrition outcomes, in particular stunting, through targeted improvements in dietary diversity in a physically and socio-economically diverse country, namely Zimbabwe. Complex interaction effects with agro-ecological, institutional and socio-economic conditions are accounted for. Finally, we analyze whether targeting interventions at the neediest (as identified by the polling approach) will also create the largest benefits. Results The dominant profile for stunted children is that they are young (6–12 months), live in poorer/poorest households, in rural areas characterized by significant sloping of the terrain and with one-sided emphasis on maize cultivation and medium dry conditions. When moving from “need” to “maximal impact”, we calculate both the coverage in “need” as well as the impact coverage, and find that targeting on need does not always provide the largest impact. Conclusions Policy-makers need to remain alert that targeting on need is not always the same as targeting on impact. Estimation of heterogeneous treatment effects allows for more efficient targeting. It also enhances the external validity of the estimated impact findings, as the impact of child diet diversity on stunting depends on various agro-ecological variables, and policy-makers can relate these findings to areas outside our study area with similar agro-ecological conditions.


2018 ◽  
Vol 10 (1) ◽  
pp. 58-73 ◽  
Author(s):  
Nicola Galluzzo

AbstractThe Bulgarian countryside has suffered a significant phenomenon of rural emigration since the early 1970s. The main consequence of rural depopulation has been a decline of investments in Bulgarian farms and in their own level of technical and economic efficiency. The aim of this research was to assess afterwards the enlargement of the European Union in 2007, the technical efficiency by a non-parametric approach such as the Data Envelopment Analysis (DEA), using some findings and variables investigated in the Farm Accountancy Data Network annual survey from 2007 till 2015. Farms have been stratified into functions of their typology of farming and their geographical localization. Research findings have pointed out that specialized farms as dairy farms and granivores ones have had the highest levels of technical efficiency compared to mixed farms and wine farms. To sum up, financial subsidies allocated by the Common Agricultural Policy have had a positive impact towards farmers, both increasing the technical efficiency and also in reducing the socio-economic marginalization of Bulgarian rural areas.


Author(s):  
Anna Nowak

The purpose of this paper was to evaluate the changes in total productivity of agriculture in 16 regions of Poland after its accession to the European Union, i.e. in the years 2005-2014. The changes were studied using a non-parametric method based on the Malmquist index of productivity supplemented with decomposition into technological changes and changes in technical efficiency. The results showed that in the studied period the average total productivity of agriculture increased by 5%. In particular regions also an increase in the total productivity of this sector was observed. It ranged from 1.8% in Podkarpackie province to 8% in Pomorskie province. The source of improved productivity in all regions was positive technological changes, whereas an increase in technical efficiency contributed to improvement in productivity in 11 regions. In two of the regions technical efficiency did not show any changes (Wielkopolskie, Zachodniopomorskie), and in three of them (Dolny Śląsk, Lubuskie, Podkarpackie) the changes had a destimulating effect on the improvement in total productivity.


Sign in / Sign up

Export Citation Format

Share Document