The Integration of Border Regions in the European Union: A Model Approach

ABSTRACT

This study analyzes the problems related to the integration of border regions in the EU. Existing literature on the subject presents a range of models that specify different types of border regions based on the intensity of their interactions and accounting for the causes of their development. It has been suggested that these models may help in evaluating the intensity of cross-border interaction, but such assumptions have not been empirically verified. Moreover, most of the presented models also fail to fully account for integration processes in the EU. Thus, the stages of cross-border integration defined in the literature seem insufficient. The current paper proposes a five-category model for border regions, listing the stages of integration between them: from regions that demonstrate no interaction whatsoever, to cross-border regions – covering at least two border regions – with the most intense interaction. The model has been empirically verified on the basis of selected Polish-German pairs of cities.

KEYWORDS:

• Border regions
• cross-border cooperation
• European Union

Disclosure Statement

No potential conflict of interest was reported by the author(s).

Notes

1 This study also uses the typologies and models offered by Stiglbauer and Lackinger (1980), Sanguin (1983), Leimgrüber (1991), Strassoldo (1974, 1989), Minghi (1991), and Decoville et al. (2010, 2013).

2 The 2+3+2 principle enables EU member states to apply a maximum of a 7-year period of restrictions in opening their labor markets (for more details, see Wiktor 2005; Brücker 2009; Wróblewski 2017).

3 The intensification of cross-border relations can also take place outside of the currency areas, but only when the exchange rate is relatively stable.

4 The formalization of the border formally determines the time, place, conditions, and manner of border crossing. Permeability is understood as the degree to which the border constitutes a barrier to various types of flows.

5 Cultural ties are crucial for border regions and their populations. However, at the level of conceptualization, certain simplifications were adopted in this regard due to the perspective taken and the academic field (economics). The outlined model undoubtedly invites more extensive consideration in other academic fields, such as sociology or cultural studies.

6 The phenomenon is determined by the diversity of labor costs in regions on both sides of a state border: the greater their diversity, the more intense the free movement of labor. In this context, however, the underlying problem is the limited flexibility of the local labor market and the low extent of labor mobility; both in terms of geography and market sectors.

7 The method of classification proposed in this study allows for the determination of classes characterized by an even scope of divisions. One undeniable advantage of the proposed method is its objectivity, since the respective class divisions are independent of the researcher's opinion.

8 $maxR$ = 55; $minR$ = 0; $c$ = 5; h = 11; Class division: $minR$:$maxR$-4h = closed border regions; $maxR$-4h:$maxR$-3h = transitional border regions; $maxR$-3h:$maxR$-2h = open border regions; $maxR$-2h:$maxR$-1h = integrated border regions; $maxR$-1h:$maxR$ = cross-border region.

9 A simplified assumption was made in this study that the information about the ties between the residents of border regions can be drawn from studies conducted by their respective local governments.

10 $maxR$ = 1; $minR$ = 0; $c$ = 5; h = 0.2.

11 From a methodological standpoint, it is impossible to use more rigid synthetic measurements when, in the course of analysis, other such measurements have already been applied; in this case the Euclidean distance. However, it is possible to use simple measurements of central tendency, i.e., averages, dominants, and medians. For the purposes of this analysis, an average value was used.

12 $maxR$ = 4; $minR$ = 0; $c$ = 5; h = 0.8.

13 $\alpha$ = 0.05; $u_{\alpha }$ = 1.96.

14 Conducting the sample size procedure for each city individually would have significantly increased the cost of the analysis. Therefore, for the purposes of this study, the author decided to determine the sample size for companies, allocating it proportionately to each examined city.

15 The value of all synthetic variables (X21–X50) rendering social and economic ties amounted to 0. Therefore, they are marginal ties. This, however, does not indicate that none of the examined business entities manifested any ties or that they only manifested limited ties. There were businesses operating within the examined population that demonstrated high levels of relations. Yet the differences in the Euclidean distances between particular diagnostic variables were not significant enough to affect the value of the synthetic variable. For editorial purposes, the table was limited to a concise breakdown.

16 For example, the mobility of individual customers rarely exceeds a radius of 100 km from their place of residence, and the further away from the border, the lower the potential impact of this phenomenon on the examined regional ties. Conversely, one may assume that other phenomena – for example, capital ties between businesses – are more intensive in the regions located further away from the border.