Convergence, innovation and geography : European regional growth since 1980

This thesis contributes to the empirical literature on economic growth across the regions of the European Union, using data from 1980 onwards. It consists of three main chapters that in turn explore the major theoretical approaches relevant to regional economic growth. Chapter 1 studies the cffects of allowing for heterogeneous slope coefficients in the Mankiw, Romer and Weil (1992) model, based on panel data for 193 EU-15 regions from 1980 to 2005. We first estimate the modclnsing conventional pooled panel data estimators, allowing at most intercepts to differ across regions. Then we relax the restriction of homo- geneous slope coefficients by estimating separate time-series models for each region, using Pesaran and Smith's (1995) mean group estimator. To account for spatial dependence, we employ the common correlated effects approach of Pesaran (2006). Our analysis indicates important differences across regions in the speed of adjustment to region-specific long-run paths for the level of income per capita. Allowing for heterogeneous coefficients doubles the speed of adjustment to 22% per year on average compared to the homogenous case, which suggests downward bias in the latter. We also find a positive and significant effect of the rate of investment, although the implied structural parameters are smaller than expected. Chapter 3 investigates two channels through which research and development (R&D) and human capital may affect regional total factor productivity growth in the manufacturing sec- tor, using panel data on 159 EU-15 regions from 1992 to 2005. Based on the endogenous growth model of Griffith, Redding and Van Reenen (2003), we allow R&D and human capi- tal to influence productivity growth both directly, reflecting own innovation, and indirectly, reflecting imitation of frontier technology. Further, the model allows for conditional con- vergence to a long-run level of TFP relative to the frontier, and we develop an extension that captures geographically localised technology spillovers. Our preferred system-GMM es- timates provide significant evidence of a positive direct effect of human capital and a positive indirect effect of R&D on productivity growth. This may be interpreted as lending support to the recent focus of EU regional policy on raising educational attainment and R&D ex- penditures, although their channels of influence appear to differ. Our results also suggest that TFP convergence has taken place over our sample period and that spillovers are to an extent geographically localised. Chapter 4 examines the empirical relationship between agglomeration and economic growth for a panel of 48 Central and Eastern European regions from 1995 to 2006. By agglomeration, we mean the within-regional concentration of aggregate economic activity, which we measure using the "topographic" Theil index developed by Briilhart and Traeger (2005). The transitional growth specification of Mankiw et al. (1992) is augmented with this index and estimated using panel data methods that account for endogeneity and spatial dependence. Our empirical analysis provides evidence of a positive effect of agglomeration as measured by the topographic Theil index on long-run income levels. A one standard- deviation increase in agglomeration is estimated to raise steady-state income per capita by 15%. While this effect is sizeable, it also implies a trade-off between regional development and within-regional equality for Central and Eastern Europe.EThOS - Electronic Theses Online ServiceGBUnited Kingdo