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dc.creatorHalkos, G. E.en
dc.creatorTzeremes, N. G.en
dc.date.accessioned2015-11-23T10:29:46Z
dc.date.available2015-11-23T10:29:46Z
dc.date.issued2010
dc.identifier10.1016/j.envsoft.2010.04.014
dc.identifier.issn1364-8152
dc.identifier.urihttp://hdl.handle.net/11615/28384
dc.description.abstractThis paper uses a methodological framework based on the new advances of Data Envelopment Analysis (DEA) and a sample of 71 developed, developing and under-developed countries to model and evaluate their biodiversity performance. Specifically, by using conditional DEA, bootstrapping and kernel density estimations, the efficiency levels of these countries are compared and analysed in such a way as to show whether the countries environmental policies have been used efficiently in order to enhance biodiversity. Our empirical results indicate that there are major inefficiencies among the countries considered in terms of their biodiversity performances revealing that population level is the dominant threat of countries' biodiversity performance followed up by GDP per capita and income inequalities. At the same time CO(2) per capita, population, income inequalities and GDP per capita have different impact on developed, under-developed and developing countries which implies that environmental policies must be adopted and implemented accordingly. (C) 2010 Elsevier Ltd. All rights reserved.en
dc.source.uri<Go to ISI>://WOS:000282655200035
dc.subjectBiodiversityen
dc.subjectConditional DEAen
dc.subjectBootstrap techniquesen
dc.subjectConvexity testen
dc.subjectKernel density estimationen
dc.subjectNONPARAMETRIC FRONTIER MODELSen
dc.subjectDATA ENVELOPMENT ANALYSISen
dc.subjectENVIRONMENTALen
dc.subjectPERFORMANCEen
dc.subjectPRODUCTIVE EFFICIENCYen
dc.subjectGLOBAL BIODIVERSITYen
dc.subjectEXPERIENCEDen
dc.subjectUTILITYen
dc.subjectKUZNETS CURVEen
dc.subjectTIME-SERIESen
dc.subjectMANAGEMENTen
dc.subjectINDEXESen
dc.subjectComputer Science, Interdisciplinary Applicationsen
dc.subjectEngineering,en
dc.subjectEnvironmentalen
dc.subjectEnvironmental Sciencesen
dc.titleMeasuring biodiversity performance: A conditional efficiency measurement approachen
dc.typejournalArticleen


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