(Balassa, 1965) but also trade balances with rising real income (Hatsopoulos, Krugman and Summers, 1988 and Markusen, 1992), and market shares or market share increases (e.g. Sharpe, 1986; Fagerberg, 1988, Krugman and Hatsopoulos, 1987, Mandeng 1991, etc.).

A second view is based on relative prices. In competitive economies, equilibrium factor prices will be lower than those of international competitors, irrespective of the source of cost advantage (input abundance, technology, scale or a combination of the above). The real exchange rate and the real effective exchange rate are a measure of competitiveness based on relative prices that has been used by many authors and by literature as old as Lipshitz and McDonald (1991), Durand and Giorno (1987) and Helleiner (1989). Other authors use the unit labor costs criterion with the idea that these indicators are a good basis of international comparison among countries using similar technologies, as they are a function of important underlying determinants of competitiveness, i.e. wage rates, labor productivity and exchange rates (see for example Turner and Golub, 1997 or Hickman 1992). Obviously, there are important shortcomings in using unit labor cost indicators. In particular, they abstract from the cost function. A low labor cost component not necessarily signals competitiveness as it may result from high capital intensity or high intermediate input intensity. Hence there are also attempts to compute full unit costs (Siggel and Cockburn, 1995 and Siggel, 2007). Besides the limits of unit labor cost measures, there are also shortcomings more generally applicable to measures of price and cost competitiveness, including the failure to account for market and product composition differences and changes. Finally, such measures also lend support to a view of competitiveness as a zero-sum game, where the improvement of a country is seen as corresponding to a loss of opposite sign by other countries. This criticism however is applicable to all measurements (including market share changes) that do not account for world export growth.

Finally there are multi-dimensional definitions of competitiveness, such as Porter (1990), the World Economic Forum’s World Development Indicators (2004), or Buckley, Pass and Prescott (1988). These have the advantage to capture several aspects of the debate on competitiveness. However it is difficult to derive robust quantitative measures without incurring in a typical problem of composite indices, namely the lack of guidance from theory as to the choice in underlying data and aggregation techniques (Ravallion, 2010).

Reflecting the concepts discussed in Box 1, there are three two main types of publicly available data on competitiveness besides measures world market share changes and other trade-based indicators.

First, there are databases with indicators measuring the institutional characteristics of each country that may influence competitiveness. This is the case, for example, of the Swiss-based World Economic Forum’s “Global Competitiveness Index” (GCI) and of the World Bank’s “Doing Business” Report. The GCI provides country rankings based on a weighted average of many different components, each informing on a different aspect of competitiveness, and grouped into 12 pillars of competitiveness, spanning what they call the “basic requirements” (institutions, infrastructure, macroeconomic conditions, health and education), and “efficiency enhancers and innovation and sophistication factors” (technological readiness, innovation, financial market development, and market and labor conditions). The “Doing Business” report on the other hand focuses on comparing business regulation environments across economies and over time, based on surveys on the ease of doing business in each country. Three important dimensions along which our data set differs from the existing databases of institutional characteristics are the following. First, it is not a composite index. As such it avoids key criticisms to composite indices, namely about the lack of guidance from theory as to the choice in underlying data and aggregation techniques (Ravaillon, 2010). Second, it allows to benchmark countries without the need of reasoning in terms of rankings, which have the drawback to focus the policy makers and media 12