Long-term regional economic disparities

Within-country regional economic gaps have increased in half of OECD countries since 2000.

While the exact impact of the COVID-19 pandemic on regional economies remains to be seen, the last two decades offer important insights for the whole OECD area. Regional economic disparities show different trends depending on the geographical level observed. Overall, within-country disparities in GDP per capita tend to be starker when assessed across small regions (TL3), as small regions might capture the differences between cities and low-density areas more precisely. Within-country disparities in GDP per capita across large regions (TL2) have followed a bell-shaped pattern over the last two decades and are at the lowest level since 2000. They reached their peak in 2010, in the aftermath of the global financial crisis, after which they started to decline slowly (Figure 2.8, panel A). Disparities across the whole set of large regions have declined, mainly reflecting a process of convergence in economic development between OECD countries during the years before the global financial crisis. Some champion regions drove the convergence process, which initially raised disparities within their respective countries. However, when looking at economic gaps across small regions (TL3), it emerges that within-country disparities have slightly and almost constantly increased since 2000, reflecting both an increasing concentration of economic activities in cities and the difficulties of small remote regions to keep pace with the national frontier (Figure 2.8, panel B).

The moderate fall and rise of economic disparities across large and small regions respectively, in the OECD area taken as a whole, masks a substantial heterogeneity in how regional economic gaps have changed within countries. Half of OECD countries experienced an increase in the GDP per capita gap between the top and bottom 20% of regions, no matter whether small or large regions are taken into account. That increase has been particularly high in France, Italy, Poland and the United States. Estonia and the United Kingdom experienced a faster increase in economic disparities between small regions compared to that observed between large regions. Measuring GDP gaps between the richest and poorest regions in each country helps to capture the extent of economic polarisation across space. In 2018, the top 20% of large regions in terms of GDP per capita (i.e. the TL2 regions with highest GDP per capita representing 20% of the national population) recorded, on average, twice the level observed in the 20% bottom regions. Colombia, Hungary, Mexico and Turkey show the starkest regional gaps in GDP per capita (Figure 2.9).

Different geographic patterns of economic growth help to explain the observed changes in regional disparities across OECD countries. Most countries where regional economic disparities have increased since 2008 experienced faster economic growth in the richest regions. This pattern is particularly evident in Poland, where the richest 20% of regions grew by 4% per year over the period 2008-18. Greece and Italy are two exceptions characterised by economic stagnation in practically all regions but with poorer regions declining faster than richer regions.

Regional economic growth in OECD countries also differed by regions’ location and access to markets and economic activity. Regions near metropolitan areas of at least 250 000 inhabitants have grown faster than other regions in terms of GDP per capita, including faster than metropolitan regions. On the other hand, regions far from metropolitan areas have increased their gap in GDP per capita with both metropolitan regions and regions near metropolitan areas since 2009 (Figure 2.10).Such an increase in disparities reversed the developments between 2000 and 2008 when regions far from metropolitan areas – potentially due to a natural resource boom – were growing faster than metropolitan regions on average.

Fadic, M. et al. (2019), "Classifying small (TL3) regions based on metropolitan population, low density and remoteness", OECD Regional Development Working Papers, No. 2019/06, OECD Publishing, Paris, https://doi.org/10.1787/b902cc00-en.

OECD (2020), OECD Regional Statistics (database), OECD, Paris, http://dx.doi.org/10.1787/region-data-en.

Figure 2.9: 2008-18, except last available year for COL, LVA, LTU, NZL and CHE: 2017; JPN: 2016. Panel A: TL2 regions except for EST, LVA and LTU: TL3.

Figure 2.8 to Figure 2.10: Indicators based on GDP per capita values expressed at 2015 constant prices.

Figure 2.8: Theil index 3-year moving averages. 29 countries considered in panel A, 25 countries in panel B.

Figure 2.9: Unweighted average of TL3 regions by type metropolitan/non-metropolitan typology. 1 507 regions across 27 countries are considered.

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