the most important driver of these countries’ gains in market shares also in the wake of the global crisis (2009q1-2013q1 period). Interestingly, in the recent period all emerging and developing regions have on average improved their relative market position. By contrast, OECD countries on average experienced a deterioration of their supply side capacity since 2009.

Turning to compositional effects, South Asia, East Asia and the Pacific, and Sub-Saharan Africa have had the strongest pull from their choice of destination markets, with the effect mostly due to recent developments (2009-2013 period). At the same time, geographical specialization for Latin America and the Caribbean and for the Middle East and North Africa region, which had a negative bearing on export performance before the crisis, is now slightly positive. This is not the case for Eastern Europe and Central Asia, whose export performance was supported by a favorable geographical specialization before the crisis and is instead suffering from it in the most recent period, possibly due to a faltering demand in Western Europe.

Finally we look at sectoral specialization. This has served well Sub-Saharan Africa (AFR), the Middle-East and North Africa (MENA) region, Eastern Europe and Central Asia (ECA), the Latin America and the Caribbean (LAC) region, and – marginally – the OECD countries, particularly in pre-crisis years. Since 2009, however, sectoral specialization has become a less important driver of changes in the relative positioning of the different world regions in the map of global trade.

An illustrative set of results suggests that our measure of competitiveness is significantly correlated with factors that are commonly perceived as influencing countries’ competitiveness, including the nominal effective exchange rate (NEER) and the real effective exchange rate (REER).<sup>1</sup> The present analysis focuses on countries’ overall competitiveness and provides a decomposition of all indicators into prices and volumes. The scope of the analysis can be extended in two important respects going forward. First, indicators can be computed for subsets of countries’ trade. For example indicators for trade with different skill or technological intensity, broad sectors, or specific value chains (e.g. the textiles, auto, electronics, or chemicals value chain) within countries can be produced. Second, the decomposition into prices and volumes can be extended to account fully for the extensive margin of trade (now based on the intensive margin). Expanding the analysis on these three fronts should be the focus of future data collection and research.

In the next section, we provide some theoretical underpinnings to the concept of competitiveness. In Section 3 we describe the scope of the data and the methodology, as well as the relation to other databases. In Section 4 we discuss patterns of export performance across main world regions and for selected major exporting countries. Section 4 also presents some further applications of the indicators. Section 5 concludes and discusses implications for future work.

# **2. DATA AND METHODOLOGY**

Our aim is to provide a new database, the Export Competitiveness Database, computing export market share growth decompositions that quantify country specific performances, and that capture the extent to which these reflect country _i_ ’s market specialization, the sectoral specialization, or other determinants of its ability to improve market shares (see Annex 1 for a theoretical

> 1 A separate note, available from the authors, also tested and found a positive correlation between the indicators presented in this paper and the measures making up the 12 pillars of the World Economic Forum Global Competitiveness Index, as developed by Sala-i-Martin and Artadi (2004).

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