Abstract
The reproducibility and generality of the Pilot Environmental Performance Index (EPI) 2006 is investigated. Initially, the most accurate means of deriving the Pilot EPI 2006 scores and rankings of the countries which participated in the creation of the index from the various constructs of the Pilot EPI 2006 dataset is identified using a variety of traditional and computational intelligence tools. Use-all and leave-one-out cross-validation are subsequently employed for recreating the index values of the participating countries from the entire, as well as from parts only of the, dataset; parametric as well as non-parametric methodologies are used to this end, consequently establishing the accuracy with which the Pilot EPI 2006 scores and rankings of participating countries can be predicted from these relationships. The optimal means (combination of traditional and computational intelligence methodologies) of estimating the Pilot ESI 2006 scores and rankings of the participating countries is tested and verified; the results raise some questions concerning the reproducibility and generality of the Pilot EPI 2006.
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Notes
- 1.
As the BOs do not constitute a functional part of the Pilot EPI 2006 hierarchy [2], but are rather conceptual, they are not considered further in this investigation.
- 2.
The use of weights between PCs and BOs as well as between BOs and the Pilot EPI 2006 (as shown in Table 2), denotes that the relationship between PCs and the Pilot EPI 2006 is linear.
- 3.
The extensive range of polynomial degrees employed amply accommodates for any rounding errors and/or non-linearities of each relationship.
- 4.
According to [2], the relationship results from a non-linear and a linear relationship between the RD and PTD and between PTD and PC, respectively.
- 5.
This is expected as the relationship constitutes the combination of two linear relationships.
Abbreviations
- (ANN):
-
Artificial neural network
- (BO):
-
Broad objective
- (COI):
-
Country of interest
- (CV):
-
Cross-validation
- (EPI):
-
Environmental performance index
- (ES):
-
Environmental sustainability
- (GRNN):
-
General regression artificial neural network
- (PC):
-
Policy category
- (PTD):
-
Proximity-to-target tata
- (RD):
-
Raw data
References
Hammond, A., Ariannse, A., Rodenburg, E., Bryant, D., Woodward, R.: Environmental indicators: a systematic approach to measuring and reporting on environmental policy performance in the context of sustainable development, World Resource Institute Report (1995)
Yale Center for Environmental Law & Policy: Center for International Earth Science Information Network (CIESIN), Pilot 2006 Environmental Performance Index (2006)
Devijver, P.A., Kittler, J.: Pattern Recognition: A Statistical Approach. Prentice-Hall, London, GB (1982)
Box, G.E.P., Cox, D.R.: An analysis of transformations (with Discussion). J. Roy. Stat. Soc. B 26, 211–252 (1964)
Jolliffe, I. T.: Principal component analysis. In: Springer Series in Statistics, 2nd edn. Springer, New York (1986) (ISBN 0-387-95442-2)
Atkinson, K.A.: An Introduction to Numerical Analysis, 2nd edn. John Wiley and Sons (1988)
Specht, D.F.: A General Regression Neural Network. IEEE Trans. Neural Netw. 2, 568–576 (1991)
Tambouratzis, T., Bardi, K.S., Mathioudaki, A.G.: How Reproducible - and Thus Verifiable - Is the Environmental Performance Index?, Recent Advances in Environmental Sciences and Financial Development. In: Proceedings of the 2nd International Conference on Environment, Ecosystems and Development (EEEAD 2014) Athens, Greece, 28th–30th Nov 2014, pp. 27–33 (2014)
Tambouratzis, T., Bardi K.S., Mathioudaki A.G.: Comprehending the pilot environmental performance index. In: Proceedings of the 15th UK Workshop on Computational Intelligence (UKCI 2015), Exeter, UK, 7th–9th Sept 2015
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Tambouratzis, T., Mathioudaki, A., Bardi, K. (2019). Investigating the Reproducibility and Generality of the Pilot Environmental Performance Index (EPI 2006). In: Vasant, P., Zelinka, I., Weber, GW. (eds) Intelligent Computing & Optimization. ICO 2018. Advances in Intelligent Systems and Computing, vol 866. Springer, Cham. https://doi.org/10.1007/978-3-030-00979-3_49
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