Benchmarking Sustainable Development: A Synthetic Meta-index Approach
AbstractThe need for monitoring countries’ overall performance in Sustainable Development (SD) is widely recognized, but the methods for aggregating vast amounts of empirical data remain rather crude. This paper examines the so-called ‘benefit-of-the-doubt’ weighting method as a tool for identifying benchmarks without imposing strong normative judgement about SD priorities. The weighting method involves linear optimization techniques, and allows countries to emphasize and prioritize those SD aspects for which they perform relatively well. Using this method, we construct a meta-index of SD (MISD), which combines 14 existing aggregate SD indices (developed by well-established organizations and/or expert teams) into a single synthesizing overall SD index. Within a sample of 154 countries, our index identifies 6 benchmark countries (3 high-income countries and 3 upper-middle-income countries), but also a number of seriously under-performing countries. We view this approach as a first step towards more systematic international comparisons, aimed at facilitating diffusion of the best practices and policies from the benchmark countries to the less developed world.
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Bibliographic InfoPaper provided by EconWPA in its series Others with number 0210001.
Date of creation: 08 Oct 2002
Date of revision: 08 Oct 2002
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Sustainable Development; Integrated Assessment; Benchmarking; benefit of the doubt weighting; Data Envelopment Analysis;
Other versions of this item:
- Cherchye, Laurens & Kuosmanen, Timo, 2004. "Benchmarking Sustainable Development: A Synthetic Meta-index Approach," Working Paper Series UNU-WIDER Research Paper , World Institute for Development Economic Research (UNU-WIDER).
- O57 - Economic Development, Technological Change, and Growth - - Economywide Country Studies - - - Comparative Studies of Countries
- C43 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Index Numbers and Aggregation
- C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis
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