scholarly journals Technical efficiency of agriculture in EU countries

2020 ◽  
Vol 8 (1) ◽  
pp. 151-168
Author(s):  
Robert Rusielik ◽  
Beata Szczecińska
Keyword(s):  
Technical Efficiency ◽  
Linear Ordering ◽  
Agricultural Activity ◽  
Data Envelopment ◽  
Access To Information ◽  
Analysis Method ◽  
Eu Countries ◽  
Selection Of Variables ◽  
European Union Countries ◽  
Selection Of

The study attempts to assess the technical efficiency of agriculture in European Union countries. Two methods were used for this purpose. One was to establish a ranking and separate typological groups of countries similar to each other in terms of technical efficiency of agriculture, using the Hellwig’s taxonomic measure of development. The second one concerned the measurement of technical efficiency of EU countries using the DEA (Data Envelopment Analysis) method. A set of 6 variables determining the technology of agricultural activity was adopted for the model. The model assuming the variable effects of the BCC scale was adopted for the study. Based on the variables adopted for the DEA model, a set of diagnostic indicators was defined, which finally included 5 indicators. Based on these indicators, by means of a linear ordering method based on a synthetic variable, countries were grouped into 4 groups bringing together countries from the lowest to the highest efficiency. The results of both methods overlap in the part concerning the countries with the best efficiency. In other groups there are slight discrepancies that may result from limited access to information and selection of variables for research.

scholarly journals A Comparison of Ensemble and Dimensionality Reduction DEA Models Based on Entropy Criterion

Algorithms ◽  
2020 ◽  
Vol 13 (9) ◽  
pp. 232
Author(s):  
Parag C. Pendharkar
Keyword(s):  
Dimensionality Reduction ◽  
Returns To Scale ◽  
Data Envelopment ◽  
Objective Functions ◽  
High Entropy ◽  
Selection Of Variables ◽  
Dea Models ◽  
Entropy Criterion ◽  
Selection Of ◽  
Normally Distributed

Dimensionality reduction research in data envelopment analysis (DEA) has focused on subjective approaches to reduce dimensionality. Such approaches are less useful or attractive in practice because a subjective selection of variables introduces bias. A competing unbiased approach would be to use ensemble DEA scores. This paper illustrates that in addition to unbiased evaluations, the ensemble DEA scores result in unique rankings that have high entropy. Under restrictive assumptions, it is also shown that the ensemble DEA scores are normally distributed. Ensemble models do not require any new modifications to existing DEA objective functions or constraints, and when ensemble scores are normally distributed, returns-to-scale hypothesis testing can be carried out using traditional parametric statistical techniques.

scholarly journals Performance Evaluation in the UEFA Champions League

2015 ◽  
Vol 18 (5) ◽  
pp. 448-470 ◽  
Author(s):  
Fabíola Zambom-Ferraresi ◽  
Lucía Isabel García-Cebrián ◽  
Fernando Lera-López ◽  
Belén Iráizoz
Keyword(s):  
Performance Evaluation ◽  
Data Envelopment Analysis ◽  
Technical Efficiency ◽  
Estimation Methods ◽  
Data Envelopment ◽  
Sports Performance ◽  
Management Implications ◽  
European Football ◽  
High Level ◽  
Selection Of

This article aims to evaluate the sports performance of teams that have participated in the Union of European Football Associations (UEFA) Champions League (UCL) during the last 10 seasons (2004-2005 to 2013-2014). Technical efficiency is estimated using well-known data envelopment analysis (DEA) approaches and a bootstrapped DEA model. To solve the problem of measuring sporting results as output in knockout competitions, we propose the use of the coefficients applied by the UEFA from UCL revenue distribution. The results obtained show first that there is a high level of inefficiency in UCL over the period studied: Only 10% of the teams seem to be efficient. Also, the teams have many problems in maintaining their efficiency during the seasons. Second, the champion is always efficient. Third, we identify two sources of inefficiency: waste of sports resources and the selection of sporting tactics. Finally, from a methodological perspective, the output measure proposed seems to be suitable to represent reliably the sports results achieved by clubs in this qualifying competition type. Furthermore, our results are robust when applying alternative estimation methods. Regarding the results, some management implications are discussed and suggestions are made to boost the efficiency in inefficient clubs.

State- Owned Forest Tenure Reform Efficiency Evaluation of Heilongjiang Province

2011 ◽  
Vol 66-68 ◽  
pp. 1917-1922
Author(s):  
Wei Wei Zhong ◽  
Yu Kun Cao
Keyword(s):  
Data Envelopment Analysis ◽  
Technical Efficiency ◽  
Scale Efficiency ◽  
Data Envelopment ◽  
Efficiency Evaluation ◽  
Heilongjiang Province ◽  
Analysis Method ◽  
Tenure Reform ◽  
Forest Tenure ◽  
Forest Farm

This dissertation adopts Data Envelopment Analysis method, in accordance with principles of comprehensiveness, concise, relevance and relativity as well as decision package requirements on quality and quantity, it selects four input indexes as woodland area, stuff, technical stuff proportion and fund; two output indexes as live stumpage and output value of state-owned forest farm, and takes use of DEAP2.1 software based on input-oriented BCC model to make an efficiency evaluation of 11 state-owned forest farms which participate in forest tenure reform and 19 which does not. The result shows no matter it's technical efficiency, scale efficiency or pure technical efficiency, forest farms which carries out reform are more efficient that those which does not.

A MONTE CARLO EVALUATION OF SEVERAL TESTS FOR THE SELECTION OF VARIABLES IN DEA MODELS

2005 ◽  
Vol 04 (03) ◽  
pp. 325-343 ◽  
Author(s):  
INMACULADA SIRVENT ◽  
JOSÉ L. RUIZ ◽  
FERNANDO BORRÁS ◽  
JESÚS T. PASTOR
Keyword(s):  
Statistical Tests ◽  
Returns To Scale ◽  
Nonparametric Tests ◽  
Model Specification ◽  
Data Envelopment ◽  
Selection Of Variables ◽  
Dea Models ◽  
Observed Behaviour ◽  
Monte Carlo Evaluation ◽  
Selection Of

Data Envelopment Analysis (DEA) is a recently developed methodology that is widely used for estimating relative efficiency scores of Decision Making Units (DMUs) that use several inputs to produce several outputs. Model specification in DEA includes aspects such as the choice of inputs and outputs or the adoption of a returns to scale assumption. As pointed out by many authors, it is obvious that the specification of a model is the key to having reliable efficiency scores. In this paper, we are particularly concerned with the selection of variables in DEA models. To be specific, we investigate the performance of several statistical tests existing in the literature that can be used for the selection of variables. In particular, the behaviour of the well-known tests proposed by Banker2 and the nonparametric tests recently developed by Pastor et al.13 is analyzed in relation to several factors such as sample size, model size, the specification of returns to scale and the type and level of inefficiency. We have drawn some conclusions that will be of help for practical uses, since the observed behaviour of the tests in the different scenarios determined by the specifications of the mentioned factors may provide some useful insight into the choice of an adequate statistical test in the particular context of a given DEA application.

Selection of Variables in Data Envelopment Analysis for Evaluation of Stock Performance

2021 ◽  
pp. 0258042X2110025
Author(s):  
B. Senthil Arasu ◽  
Desti Kannaiah ◽  
Nancy Christina J. ◽  
Malik Shahzad Shabbir
Keyword(s):  
Data Envelopment Analysis ◽  
Stock Exchange ◽  
Secondary Market ◽  
Data Envelopment ◽  
Stock Performance ◽  
The Past ◽  
Financial Strength ◽  
Selection Of Variables ◽  
Selection Of ◽  
Past Price

Data envelopment analysis (DEA) is a relative measurement technique used to evaluate the efficiencies of a homogeneous group of samples with multiple inputs and/or outputs. DEA can be highly effective when right variables are chosen. The objective of this study is to identify the most appropriate variables for DEA to evaluate stock performance and find the efficient ones from a pool of stocks. Evaluation of stocks are carried out either by assessing their financial strength or by assessing their past price behaviour in the secondary market or both. In any case, it is imperative to use suitable variables to evaluate the performance of stocks. For this purpose, three different combinations of variables were tested on 69 non-financial stocks listed in the National Stock Exchange (NSE), which were selected based on their market capitalization. The results obtained suggest that all the three sets of variables taken for the study help in the identification of efficient stocks. The average returns of the stocks selected in all the three cases are higher than the market return. Among the three sets, stocks identified using the past price behaviour give a higher return when compared to the other two sets. The study can help academicians and investors to percolate efficient stocks from a large pool of stocks. The selected stocks can be further analysed to construct an effective portfolio.

scholarly journals The Use of Data Envelopment Analysis for Selection of Investment Objects

Ekonomika ◽  
2004 ◽  
Vol 66 ◽  
Author(s):  
Daiva Rimkuvienė
Keyword(s):  
Data Envelopment Analysis ◽  
Information Technologies ◽  
Policy Support ◽  
Data Envelopment ◽  
Analysis Method ◽  
Effective Work ◽  
The Past ◽  
Use Of Data ◽  
Enterprise Activity ◽  
Selection Of

Due to limited resources the State support can be delivered only to part of the enterprises that apply for it. To increase the effectiveness of investment policy, support has to be provided for enterprises having not only good financial results, but also perspectives of effective work in future. Commonly, more attention is paid to analysis of financial results. However, financial indexes describe the enterprise’s position in the past and do not reflect its possibilities of development. The estimation of an enterprise’s future effectiveness requires accounting for not only its financial results, but also for the efforts of employees to improve their qualification, to use information technologies, to use rationally natural resources. Those who analyse the enterprise’s activity in different aspects encounter problems of the object’s intercomparison due to the variability of the indexes. Data Envelopment Analysis allows to put the objects into a line according to a lot of criteria expressed in various measures, and to choose a number of input and output indexes. The paper presents the aspects estimating the future of an enterprise, the results of enterprise activity effectiveness evaluation using the Data Envelopment Analysis method, and a discussion about the possibilities to use this method.

scholarly journals Analysis of Technical Efficiency of Paddy and Maize Farming

2021 ◽  
Vol 4 (1) ◽  
pp. 1
Author(s):  
Surojudin Sodiq ◽  
Tri Haryanto
Keyword(s):  
Data Envelopment Analysis ◽  
Technical Efficiency ◽  
Average Level ◽  
Data Envelopment ◽  
Analysis Method

This study aims to determine the level of technical efficiency of paddy and maize farming in Gorontalo Province in 2019. The data used comes from the 2019 Ubinan Survey conducted by BPS Gorontalo Province. The total samples studied were 833 farming units, consisting of 392 paddy farming units and 441 maize farming units. The analysis method used is Data Envelopment Analysis (DEA). The results showed that most of the paddy and maize farming in Gorontalo Province in 2019 had not yet reached the full level of technical efficiency. The average level of technical efficiency in paddy farming was 68.7 percent, while the average level of efficiency in maize farming was only 56.7 percent. 

scholarly journals Evaluation of Technical Efficiency in Financial Dimension of Private Medical Entities in Podkarpackie Voivodhip – DEA Approach

2021 ◽  
Vol 17 (2) ◽  
pp. 24-31
Author(s):  
Małgorzata Leśniowska-Gontarz
Keyword(s):  
Data Envelopment Analysis ◽  
Technical Efficiency ◽  
Functional Form ◽  
Research Study ◽  
Maximum Output ◽  
Data Envelopment ◽  
Analysis Method ◽  
Medical Entity ◽  
Dea Approach

Abstract The major aim of this paper is to assess technical efficiency of private medical entities. Technical efficiency refers to the capacity of a medical entity to obtain the maximum output for a particular set of inputs. The article presents results of research study on technical efficiency of 33 medical entities using the Data Envelopment Analysis method (DEA) which allows the use of multiple inputs/outputs without imposing any functional form on data or making assumptions of inefficiency. The research study was carried out in years 2011–2016 on medical entities from Podkarpackie voivodship. The analysis was conducted based on the CCR input-oriented model.

scholarly journals Selection of the method of linear ordering using the example of assessing the level of socio-economic development of European Union countries

2020 ◽  
Vol 64 (7) ◽  
pp. 118-129
Author(s):  
Agnieszka Sompolska-Rzechuła
Keyword(s):  
European Union ◽  
Economic Development ◽  
Rank Correlation ◽  
Linear Ordering ◽  
Diagnostic Features ◽  
European Union Countries ◽  
Socio Economic Development ◽  
Optimal Ordering ◽  
Selection Of ◽  
Diagnostic Variables

The aim of the article is to present the issues of choosing the optimal procedure for the linear ordering of objects and assessing the correctness of the selected methods of the linear ordering. The goal was achieved by creating linear ordering of objects using various methods for normalizing the value of diagnostic features. An aggregate measure based on various properties of the synthetic feature was used to select the optimal ordering, among others, the compatibility of the mapping, the correlation of the synthetic line variable with diagnostic variables, the rank correlation of the synthetic variable with diagnostic variables and the variability of the synthetic variable. The study was conducted based on the example of data concerning 28 European Union countries according to the level of socio-economic development in the context of sustainable development concerning society, economy and the environment. The linear ordering of countries using the quotient transformation with an arithmetic mean turned out to be the most correct ordering

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