<abstract xmlns="http://www.w3.org/1999/xhtml">

Contemporary development policy concentrates predominantly on reducing noticeable economic differences in a spatial system, and an important role in this respect is played by EU Cohesion Policy. Owing to the considerable scale of financial exposure of Cohesion Policy, the assessment of effectiveness of the implemented measures and their greater reliance on evidence are of major significance. Despite numerous attempts to empirically verify the effects of EU funds spending, the problem remains unresolved, and the results of recent studies lead frequently to ambiguous conclusions.
The article aims to verify the <italic>β</italic>-convergence process in EU regions in the years 2007–2015 allowing for the impact of the received EU funds and the spatial effects determining economic growth. In the research, use was made of a convergence approach consisting in the regression modelling of per capita GDP growth. Spatial econometrics methods were applied, by adding variables determining spatial interactions that can influence the economic growth rate to the specification of the estimated models.
The estimated econometric models show that in the years 2007–2015 EU funds positively affected economic growth. At the same time, the process of reducing economic disparities between EU regions was observed. Moreover, the existence of spatial effects for a dependent variable was confirmed. The results also show that the value of the EU funds received in the surrounding area generally did not translate into the dynamics of growth in a given location. The research presented is one of the few in which spatial interaction was verified by using weights matrices based on contiguity, distance, flows and affiliation.
</abstract>

Contemporary development policy concentrates predominantly on reducing noticeable economic differences in a spatial system, and an important role in this respect is played by EU Cohesion Policy. Owing to the considerable scale of financial exposure of Cohesion Policy, the assessment of effectiveness of the implemented measures and their greater reliance on evidence are of major significance. Despite numerous attempts to empirically verify the effects of EU funds spending, the problem remains unresolved, and the results of recent studies lead frequently to ambiguous conclusions.
The article aims to verify the β-convergence process in EU regions in the years 2007–2015 allowing for the impact of the received EU funds and the spatial effects determining economic growth. In the research, use was made of a convergence approach consisting in the regression modelling of per capita GDP growth. Spatial econometrics methods were applied, by adding variables determining spatial interactions that can influence the economic growth rate to the specification of the estimated models.
The estimated econometric models show that in the years 2007–2015 EU funds positively affected economic growth. At the same time, the process of reducing economic disparities between EU regions was observed. Moreover, the existence of spatial effects for a dependent variable was confirmed. The results also show that the value of the EU funds received in the surrounding area generally did not translate into the dynamics of growth in a given location. The research presented is one of the few in which spatial interaction was verified by using weights matrices based on contiguity, distance, flows and affiliation.

European Funds and the Dynamics of Economic Growth Among Eu Regions: A Spatial Modelling Approach

Quaestiones Geographicae

This work is licensed under the Creative Commons Attribution 4.0 International License.

Contemporary development policy concentrates predominantly on reducing noticeable economic differences in a spatial system, and an important role in this...

European Funds and the Dynamics of Economic Growth Among Eu Regions: A Spatial Modelling Approach

Pubblicato online: 21 giu 2024

Pagine: 67 - 80

Ricevuto: 11 feb 2024

DOI: https://doi.org/10.14746/quageo-2024-0020

© 2024 Wojciech Kisiała et al., published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.