Identifying and Interpreting Regional Convergence Clusters Across Europe

Abstract

In this paper we test for regional convergence clusters across the EU. We utilise a methodology that allows for the endogenous selection of regional clusters using a multivariate test for stationarity, where the number and composition of clusters are determined by the application of pairwise tests of regional differences in per capita output over time. To interpret the composition of the resulting convergence clusters, the latter are tested against a number of possible groupings suggested by recent theories and hypotheses of regional growth and convergence. Further, our method allows regional convergence clusters to vary over time.Since the mid-1980s, the study of long-term growth has made a major re-appearance on the research agenda in economics. An important stimulus for this revival has been the renewed interest in the empirics of growth, and especially the evidence that rates of long-run convergence of per capita output and incomes between nations, and even between regions within nations, appear to be much slower and far more variable than predicted by the standard Solow-Swan neoclassical growth model (Abramovitz, 1986;Boltho and Holtham, 1992). One consequence has been the emergence of a 'new' growth theory that incorporates increasing returns and technical change within the production function as determinants of the (endogenous) long-term growth rate (Romer, 1986;Lucas, 1988;Grossman and Helpman, 1994;Barro and Sala-i-Martin, 1997). Although several variants of this new endogenous growth theory have been developed, all permit a wider set of possibilities with regard to convergence behaviour. Some variants predict 'conditional' convergence of national (regional) per capita incomes to different long-run steady states that depend on initial national (regional) differences in institutional set-up, economic structure, tastes and so on. Others allow for so-called 'club' convergence among countries (regions) with similar structural and related conditions. Still others, including models that assume that technological advance is highly localised and its diffusion slow, predict persistent or even divergent differences in national (or regional) per capita output and incomes as long run outcomes (Bertola, 1993).At the same time, the emergence over the past decade or so of the so-called 'new economic geography' models of industrial location and agglomeration has highlighted how many sources of increasing returns are associated with Marshalliantype external localisation economies (such as access to specialised local labour inputs, local market access and size effects, local knowledge spillovers, and the like). These models provide a rich set of possible long-run regional growth patterns that depend, among other things, on the relative importance of transport costs and localisation economies (Fujita et al., 1999;Brackman et al., 2001;

Regional Growth and National Development: Transition in Central and Eastern Europe and the Regional Kuznets Curve in the East and the West

“…Evidence of club convergence in the 'old' EU member states has been obtained widely (see, inter alia, Canova, 2004;Corrado et al, 2005;Fischer and Stirbock, 2006;Dall'erba et al, 2008), while more recent contributions highlight the role of spatial processes (proximity, concentration), both for club-formation (spatial heterogeneity) and for the overall speed of convergence (see, for example, Lopez-Bazo et al, 2004;Ertur et al, 2006;Egger and Pfaffermayr, 2006;Arbia et al, 2008;Rey and Le Gallo, 2009;Arbia et al, 2010 -see also the discussion in Fingleton and Lopez-Bazo, 2006). The importance of spatial processes has been also analysed in empirical studies employing the Verdoorn Law equation.…”

Regional economic development in Europe: the role of total factor productivity

“…Most of the existing analyses of productivity differences at the regional level have focused on labour productivity (LP), measured simply as output per worker (Corrado, Martin, & Weeks, 2005;Esteban, 2000;Gardiner, Martin, & Tyler, 2004;Vieira, Neira, & Vázquez, 2011). This is because LP can be calculated easily from available data on output and employment.…”

The Determinants of Economic Growth in European Regions

“…Canova (2004) test for convergence clubs in European regions and finds evidence for convergence poles characterized by different economic conditions. Corrado et al (2005) use an alternative technique to identify clusters of convergence in European regions and sectors. A very recent literature has developed Bayesian tools in the analysis of spatially correlated data.…”