Going NUTS: The effect of EU Structural Funds on regional performance

Abstract

The European Union (EU) provides grants to disadvantaged regions of member states to allow them to catch up with the EU average. Under the Objective 1 scheme, NUTS2 regions with a GDP per capita level below 75% of the EU average qualify for structural funds transfers from the central EU budget. This rule gives rise to a regression-discontinuity design that exploits the discrete jump in the probability of EU transfer receipt at the 75% threshold. Additional variability arises for smaller regional aggregates -so-called NUTS3 regions -which are nested in a NUTS2 mother region. Whereas some relatively rich NUTS3 regions may receive EU funds because their NUTS2 mother region qualifies, other relatively poor NUTS3 regions may not receive EU funds because their NUTS2 mother region does not qualify. We find positive growth effects of Objective 1 funds, but no employment effects. A simple cost-benefit calculation suggests that Objective 1 transfers are not only effective, but also cost-efficient.

Does medieval trade still matter? Historical trade centers, agglomeration and contemporary economic development

“…If this is the case, it could provide a new explanation for the uneven distribution of economic activity and significant spatial concentration of industries throughout Europe (e.g., Chasco et al 2012, Koh and Riedel 2012, Roos 2005. Furthermore, it can contribute to the understanding of the persistent differences in regional economic development (Becker et al 2010, Maseland 2012, Tabellini 2010or Waidlein 2011. Finally, this study contributes to a growing literature reporting on the persistence and pathdependent nature of spatial equilibria (e.g., in industry concentration) and city growth processes (Bosker et al 2007, Bleakly and Lin 2012, Davis and Weinstein 2002, Davis and Weinstein 2008, Miguel and Roland 2011and Redding et al 2011.…”

Too much of a good thing? On the growth effects of the EU's regional policy

“…Due to a lack of administrative capacity, part of the funds is not spent as intended but used for consumption purposes or subject to corruption. 8 If there are diminishing returns to EU regional transfers, knowing that they foster growth on average, as in Becker, Egger, and von Ehrlich (2010), is not enough. 9 In fact, it is important to understand how a varying treatment intensity (different amounts of EU transfers relative to GDP) affects regional growth.…”

Econometric Evaluation of EU Cohesion Policy: A Survey

“…Despite some criticism due to its strict assumptions (Dall'erba and Le Gallo, 2008), the use of the neoclassical growth model might be explained by the limited data availability at the regional level. 14 Possible approaches to this problem have been proposed by Becker, Egger, von Ehrlich and Fenge (2008) as well as by Hagen and Mohl (2008), who avoid strict functional form assumptions by using treatment effect methods (for a recent survey for applied researchers see Austin, 2007). These studies will be summarised in section 5 in greater detail.…”

“…18). Becker, Egger, von Ehrlich and Fenge (2008) use up to 3301 NUTS-3 regions and apply "regression discontinuity design" techniques. 20 They make use of the relatively clear-cut rule that defines an Objective 1 region: NUTS-2 regions with a GDP per capita level below 75 percent of the EU average.…”

“…However, it may be argued that the goal of Cohesion Policy is to promote convergence of GDP per capita, implying that this variable is more appropriate. Nevertheless, Esposti and Bussoletti's argument points to the fact that it is necessary to evaluate the labour market effects of Cohesion Policy, an undertaking that has been neglected so far (exceptions are Becker, Egger, von Ehrlich and Fenge, 2008;Bouvet, 2005;Dall'erba and Le Gallo, 2007).…”