Utilize este identificador para referenciar este registo: http://hdl.handle.net/10400.3/2853
Título: Azorean Agriculture Efficiency by PAR
Autor: Mendes, Armando B.
Noncheva, Veska
Silva, Emiliana
Palavras-chave: Productivity Analysis with R
Data Envelopment Analysis
Efficiency of Azorean Farms
Data: 2013
Editora: Springer Netherlands
Citação: Mendes, Armando B.; Noncheva, Veska; Silva, Emiliana (2013). "Azorean Agriculture Efficiency by PAR", In Mendes, Armando, L. D. G. Soares da Silva, Emiliana, Azevedo Santos, Jorge M. (Eds.), «Efficiency Measures in the Agricultural Sector: With Applications», pp. 117-136. ISBN 978-94-007-5738-7. Dordrecht: Springer Netherlands. http://dx.doi.org/10.1007/978-94-007-5739-4_9.
Resumo: The producers always aspire at increasing the efficiency of their production process. However, they do not always succeed in optimising their production. In the last years, the interest on Data Envelopment Analysis (DEA) as a powerful tool for measuring efficiency has increased. This is due to the large amount of data sets collected to better understand the phenomena under study and, at the same time, to the need of timely and inexpensive information. The "Productivity Analysis with R" (PAR) framework establishes a user-friendly data envelopment analysis environment with special emphasis on variable selection, aggregation, summarisation and interpretation of the results. The starting point is the following R packages: DEA (Diaz-Martinez and Fernandez-Menendez 2008) and FEAR (Wilson 2008). The DEA package performs some models of data envelopment analysis presented in Cooper et al. (2007). FEAR is a software package for computing nonparametric efficiency estimates and testing hypotheses in frontier models. FEAR implements the bootstrap methods described in Simar and Wilson (2000). PAR is a software framework using a portfolio of models for efficiency estimation and also providing results explanation functionality. PAR framework has been developed to distinguish between efficient and inefficient observations and to explicitly advise the producers about possibilities for production optimisation. PAR framework offers several R functions for a reasonable interpretation of the data analysis results and text presentation of the obtained information. The output of an efficiency study with PAR software is self-explanatory. We are applying PAR framework to estimate the efficiency of the agricultural system in Azores (Mendes et al. 2009). All Azorean farms will be clustered into homogeneous groups according to their efficiency measurements to define clusters of "good" practices and cluster of "less good" practices. This makes PAR appropriate to support public policies in agriculture sector in Azores.
Descrição: Copyright © 2013 Springer Netherlands.
Peer review: yes
URI: http://hdl.handle.net/10400.3/2853
ISBN: 978-94-007-5738-7 (Print)
978-94-007-5739-4 (Online)
Versão do Editor: http://link.springer.com/chapter/10.1007/978-94-007-5739-4_9
Aparece nas colecções:DME - Parte ou Capítulo de um Livro / Part of Book or Chapter of Book

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