Regional mobility in the European Union

Abstract

Regional mobility in the spatial distribution of per capita income in the European Union is examined over the period 1977 to 1999. The methodology used to investigate this issue combines a series of measures taken from the literature devoted to the dynamic study of personal income distribution with a non-parametric analysis. The results show limited mobility in the distribution considered, and a decline in mobility over time. The empirical evidence presented indicates, moreover, that mobility patterns vary as a function of regional development levels. Additionally, the analysis carried out investigates the role played in explaining intra-distribution mobility by variables such as per capita income, population density, per capita expenditure in investment, market potential, and the share in total employment of agriculture, advanced services and non-market services.

Acknowledgements

The authors thank Emilio Domínguez and an anonymous referee for their helpful comments. Financial support from MCYT (Project BEC2002-03941) and the Fundación BBVA is gratefully acknowledged.

Notes

¹ Article 2 of the Treaty of the EU specifically states that ‘The Community shall have as its task (…), to promote (…) a harmonious, balanced and sustainable development of economic activities, (…) sustainable and non-inflationary growth, (…) a high degree of competitiveness and convergence of economic performance (…)’.

² The properties of symmetry and scale independence do not constitute a major limitation. Indeed both are basic properties that any inequality index can reasonably be expected to fulfill (Cowell, 1995). In any event, for the purposes of the example, the need for the inequality index to satisfy the property of scale independence can be overcome by simply assuming the average per capita incomes of A and B to be equal.

³ See Durlauf and Quah (1999) for further details on the theoretical basis for the dynamic analysis of spatial distributions.

⁴ Lack of complete series, however, has meant that the Member States incorporated into the EU in May 2004, the Länder of former East Germany, the French overseas departments and the Spanish territories in North Africa to be eliminated from the analysis.

⁵ The most outstanding exception is the variance of the logarithms.

⁶ If , it follows that .

⁷ The mobility measure proposed by Shorrocks (1978b) is given by: SM(Π) = m - tr(Π) / m - 1 where tr(Π) denotes the trace of the matrix Π. Note that, in contrast to what occurs with SM*(Π, ρ), this index assigns identical weight to each of the m classes. Indeed, if ρ _j  = (1/m) for any j = 1, 2, … , m, then SM*(Π) = SM(Π).

⁸ The medium- and full-term transition matrices are included in the Appendix. The rest, which are not shown for lack of space, are available from the authors upon request.

⁹ In order to test the robustness of the above results, SM*(Π, ρ) and BM*(Π, ρ) were recalculated for an eight-category classification of the European regions, based on the following per capita income levels: [0, 50), [50, 75), [75, 90), [90, 100), [100, 110), [110, 125), [125, 150) and [150, +∞). The results, which are available from the authors upon request, are very similar to those just discussed.

¹⁰ Note that, for a given level of inequality, high mobility would be a sign of strong cyclical variability in regional incomes. In this kind of context, regional policy should switch the focus away from the objectives of traditional convergence policies and direct it towards the need to mitigate the adverse effects of economic cycles.

¹¹ In order to test the robustness of the results, it was decided to repeat the above analysis using data only for the subperiods 1977–1988 and 1988–1999. The results, shown in the Appendix, are very similar to those discussed in this section.

¹² It was necessary to exclude Denmark and Luxembourg from this analysis, given that these two countries are formed by a single NUTS2 region according to the Eurostat territorial classification.