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. 2022 Nov:97:None.
doi: 10.1016/j.regsciurbeco.2022.103830.

The response of regional well-being to place-based policy interventions

Antonella Rita Ferrara  1 , Lewis Dijkstra  2 , Philip McCann  3 , Rosanna Nisticó  4
Affiliations

The response of regional well-being to place-based policy interventions

Antonella Rita Ferrara et al. Reg Sci Urban Econ. 2022 Nov.

Abstract

Enhancing the well-being of its citizens is the central remit of the EU's regional policy, but as yet, there is no analysis of the effects of EU regional policy on local well-being. The aim of this paper is to examine this relationship. To do this, we define a novel regionalised well-being measure and we exploit a dataset on regional expenditure in a continuous treatment framework. Based on both parametric and semi-parametric approaches, our analysis demonstrates that the EU regional development policy does influence regional well-being differently from GDP. We find evidence of a linear monotonic response of well-being growth to total transfers, although this effect varies according to the time lag considered and the level of development of the region.

Keywords: Dose-response function; Generalised propensity score; Regional policy; Well-being.

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Conflict of interest statement

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Figures

Fig. 1
Fig. 1
Sensitivity checks on the well-being index. Notes: All results are based on a longitudinal dataset covering the period 2000-2013. Only for panel (b), the analysis is at the country level due to a lack of HPI data at the regional level. Panels (a) and (b) show binned scatterplots absorbing country fixed effects from the x and y-variables before binning and plotting. The blue dots are the median values of the x-axis and y-axis variables within the equal-sized bins grouping the two variables, whereas the dashed linear fit line is estimated using the underlying data, not the binned scatter points. Panel (c) combines a non-binned scatterplot with the linear fit line of the y-axis variable on the x-axis variable, and the shaded grey area is the respective 95% confidence band. Figure (d) plots the Owen value decomposition for regional well-being, and the blue vertical whiskers are the 95% confidence intervals.
Fig. 2
Fig. 2
Geographical distribution of well-being, per-capita GDP and Cohesion Policy expenditure.
Fig. 3
Fig. 3
Well-being and GDP response to total transfers (ESF + ERDF).
Fig. 4
Fig. 4
Generalised Propensity Score estimation of the Dose-Response Function (DRF) to Cohesion Policy Transfers (IW kernel method).
See this image and copyright information in PMC

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