composite indicators, data envelopment analysis, performance benchmarking, technology,

No abstract

Composite indicators are regularly used for benchmarking countries' performance, but equally often stir controversies about the unavoidable subjectivity that is connected with their construction. Data Envelopment Analysis helps to overcome some key limitations, viz., the undesirable dependence of final results from the preliminary normalization of subindicators, and, more cogently, from the subjective nature of the weights used for aggregating. Still, subjective decisions remain, and such modelling uncertainty propagates onto countries' composite indicator values and relative rankings. Uncertainty and sensitivity analysis are therefore needed to assess robustness of final results and to analyze how much each individual source of uncertainty contributes to the output variance. The current paper reports on these issues, using the Technology Achievement Index as an illustration. * This paper is an offshoot of the KEI-project (contract n° 502529) that is part of priority 8 of the policy orientated research under the European Commission's Sixth Framework Programme (see http://kei.publicstatistics.net/). Laurens Cherchye thanks the Fund for Scientific Research-Flanders (FWO-Vlaanderen) for his postdoctoral fellowship.

The open method of co-ordination (OMC) intends to enhance EU Member States' performance on social inclusion. In this context a set of commonly agreed performance indicators plays an important role. While the communicative power of a synthetic indicator has been recognized, several objections have been raised against such a construction. In this article, we argue that a set of separate indicators can in principle be combined into a meaningful synthetic performance index without giving up on the notion of subsidiarity, and without fundamentally impairing the peer pressure incentives that constitute an important rationale for OMC. We complement the presentation of the conceptual framework with a number of empirical applications, thereby indicating how the basic method may be instrumental for policy benchmarking practice.