Institutional infrastructure and economic performance: Levels versus catching up and frontier shifts.

We analyze the relationship between institutional infrastructure (capturing political stability, quality of government and social infrastructure) and overall country productivity for a sample of 57 (OECD and non-OECD) countries. Specifically, we compare empirical results for alternative productivity measures: output per worker and total factor productivity (TFP); in addition, we consider both levels and changes, where we decompose TFP changes into efficiency changes and technical changes. This gives us insight into the different channels through which the institutional infrastructure impacts on overall productivity performance: the 'accumulation' of production factors versus the 'accommodation' of production factors, and the 'shifting' of the world productivity frontier versus the 'catching up' with this frontier. In line with the existing literature, our results suggest a substantial accumulation effect: good institutions enhance capital accumulation. In addition, we find significant evidence in favor of an accommodation effect (in terms of both levels and changes), which elicits institutional quality as a 'lubricant' of the economic system: good institutions facilitate complex transactions, specialization and flexibility while reducing transaction costs. Interestingly, we find that good institutions enhance technical change as well as efficiency change. Conveniently, the decomposition of TFP change also allows us to interpret the convergence issue, for which largely inconclusive evidence is obtained on the basis of a combined TFP measure. Our findings reveal that efficiency change is associated with convergence, i.e., countries with lower initial productivity realize higher productivity growth through catching up. By contrast, technical change corresponds to divergence, i.e., countries with higher initial productivity succeed in higher productivity growth through shifts of the technological frontier. One possible rationalization is that greater experience with technological innovation (i.e., a closer situation to the world technology frontier) benefits the implementation of new products and processes (i.e., the cost of additional innovations falls).Performance;

Trust as societal capital: Economic growth in european regions.

Growth; Regions; Trust;

Legitimately diverse, yet comparable: Synthesising social inclusion performance in the EU.

The Open Method of Coordination (OMC) intends to enhance EU member states’ performance with regard to 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 recognised, several objections have been raised against such a construction. In this paper, we argue that a set of separate indicators can in principle be combined into one 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.Performance;

Constructing a knowledge economy composite indicator with imprecise data.

This paper focuses on the construction of a composite indicator for the knowledge based economy using imprecise data. Specifically, for some indicators we only have information on the bounds of the interval within which the true value is believed to lie. The proposed approach is based on a recent offspring in the Data Envelopment Analysis literature. Given the setting of evaluating countries, this paper discerns a ‘strong country in weak environment’ and ‘weak country in strong environment’ scenario resulting in respectively an upper and lower bound on countries’ performance. Accordingly, we derive a classification of ‘benchmark countries’, ‘potential benchmark countries’, and ‘countries open to improvement’.Knowledge economy indicators; Composite indicators; Multiple Imputation; Benefit of the doubt; Weight restrictions; Data Envelopment Analysis; Data impreciseness;

One market, one number? A composite indicator assessment of EU internal market dynamics.

We consider the lack of consensus about an appropriate theoretical framework linking sub-indicators as a defining characteristic of composite indicators. This intrinsic feature implies uncertainties about the appropriate normalisation and aggregation of the raw data. The two are related: index theory offers some valuable guidelines about their connection. Yet these do not fully solve the basic problem of expert disagreement. We embed such (residual) disagreement in the aggregation method itself. Specifically, we apply an impartial benefit-of-the-doubt weighting procedure, where weight restrictions incorporate the available information on experts’ opinions. We apply this procedure to the dynamic performance assessment of EU Internal Market effects, thereby highlighting its capacity to disaggregate member states’ observed performance shifts into changes relative to benchmarks and performance changes of the benchmarks (i.e. catching up versus genuine progress). Our results indicate that the latter factor is more important in explaining the observed progress.Dynamics; Market;

Creating composite indicators with DEA and robustness analysis: The case of the technology achievement index.

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 sub-indicators, 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.Indexes; Indicators; Robustness; Technology;