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FP5

TRANSUST Informe resumido

Project ID: EVG3-CT-2002-80012
Financiado con arreglo a: FP5-EESD
País: Germany

Cross-cutting paper, measurement of indicators for sustainable development (Christoph Boehringer)

Sustainability Impact Assessment (SIA) of economic, environmental, and societal effects triggered by governmental policies has become a central requirement for EU policy design. The three dimensions of SIA are inherently intertwined and subject to trade-offs. Quantification of trade-offs for policy decision support requires numerical models in order to assess systematically the interference of complex interacting forces that affect economic performance, environmental quality, and societal conditions.

This paper investigates the use of energy-economy-environment (E3) models within the TranSust project for measuring the impacts of policy interference on policy-relevant economic, environmental, and social (institutional) indicators. We find that operational versions of E3-models have a good coverage of central economic indicators. Environmental indicators such as energy-related emissions with simple direct links to economic activities are widely covered, whereas indicators with complex natural science background such as water stress or bio-diversity loss are hardly represented. Societal indicators stand out for very weak cover-age, not at last because they are vaguely defined or incommensurable. Our analysis con-firms prospects for future modelling in the field of integrated assessment that link standard E3-models to theme-specific complementary models with environ-mental and societal focus.

The objective of SD needs a comprehensive methodology to perform SIA quantitatively. An issue that cannot be clearly measured will be difficult to improve. In this paper, we have investigated the use of energy-economy-environment (E3) models within the TranSust project for measuring the impacts of policy interference on policy-relevant economic, environmental, and social (institutional) indicators: Operational versions of E3-models have a good coverage of central economic indicators, whereas environmental indicators with complex natural science background and - in particular - social indicators are hardly represented. Our cross-model evaluation confirms the need for future modeling activities in the field of integrated assessment that link standard E3-models to theme-specific complementary models with environmental and societal focus.

A final caveat applies: Our focus on quantitative analysis should not exaggerate the role numerical approaches can play in SIA. Policy decisions are the outcome of a broader participatory process where stakeholders and other interested parties communicate a wide range of values, perceptions and judgments to policy makers (Tamborra, 2002). Quantitative analysis if available at all can at best strengthen or weaken policy arguments, putting decision making on a more informed basis.

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ZEW
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