Assessment Methodologies: Energy, Mobility and Other Real World Application
DOI: 10.14195/978-989-26-1039-9_1
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Measuring technical efficiency of European Countries using data envelopment analysis

Abstract: A navegação consulta e descarregamento dos títulos inseridos nas Bibliotecas Digitais UC Digitalis, UC Pombalina e UC Impactum, pressupõem a aceitação plena e sem reservas dos Termos e Condições de Uso destas Bibliotecas Digitais, disponíveis em https://digitalis.uc.pt/pt-pt/termos.Conforme exposto nos referidos Termos e Condições de Uso, o descarregamento de títulos de acesso restrito requer uma licença válida de autorização devendo o utilizador aceder ao(s) documento(s) a partir de um endereço de IP da insti… Show more

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Cited by 2 publications
(3 citation statements)
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“…(2013) provide an overview of DEA models [1] for measuring the efficiency of the national economy (Table 1), which differ in part of the output variables, which in most models include the Gini coefficient (Gini) as a measure of income inequality or wealth distribution, while the input variables are more or less the same, as well as the orientation of the model. Taking into account the components of GDP, as well as based on the analysis of papers and publications on the issue of efficiency of national economies (Vaz and Ferreira, 2019; Milner and Weyman-Jones, 2003; OECD, 2001; Lábaj et al ., 2013; etc. ), the DEA model variables for evaluating the efficiency of the Western Balkans national economies include (I1) – Exports of goods and services (% of GDP) , (I2) – General government final consumption expenditure (% of GDP) , (I3) – Gross capital formation (% of GDP) i (O) – GDP growth (annual %).…”
Section: Description Of Variables and Model Structuringmentioning
confidence: 99%
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“…(2013) provide an overview of DEA models [1] for measuring the efficiency of the national economy (Table 1), which differ in part of the output variables, which in most models include the Gini coefficient (Gini) as a measure of income inequality or wealth distribution, while the input variables are more or less the same, as well as the orientation of the model. Taking into account the components of GDP, as well as based on the analysis of papers and publications on the issue of efficiency of national economies (Vaz and Ferreira, 2019; Milner and Weyman-Jones, 2003; OECD, 2001; Lábaj et al ., 2013; etc. ), the DEA model variables for evaluating the efficiency of the Western Balkans national economies include (I1) – Exports of goods and services (% of GDP) , (I2) – General government final consumption expenditure (% of GDP) , (I3) – Gross capital formation (% of GDP) i (O) – GDP growth (annual %).…”
Section: Description Of Variables and Model Structuringmentioning
confidence: 99%
“…Using four macroeconomic indicators, gross national debt, GDP growth rate, inflation rate and unemployment rate, they construct a scalar measure of macroeconomic performance and show that Switzerland, Singapore and the USA are the most economically successful countries. Vaz and Ferreira (2019) propose a framework for the application of the DEA method to assess the technical efficiency of 26 European countries in the last five years, within the current 2020 energy policy. DEA is used to estimate efficiency, along with bootstrapping, to obtain statistical inferences.…”
Section: Theoretical Backgroundmentioning
confidence: 99%
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