Mobility across regions
Most people who change regions within a country move to metropolitan regions.
People relocate across regions for numerous regions, including to access better jobs or education opportunities or to benefit from better amenities. While some of these flows are not necessarily permanent, they can affect the demographic structure of regions by changing the age composition.
In the 28 OECD countries, 29 million people changed their region of residence each year, on average, between 2016 and 2019. While regional data are not yet available for all countries in 2020, it appears that COVID-19 sparked some temporary moves across regions but reduced other types of inter-regional moves, leading to net declines in inter-regional migration in many OECD countries. In 2019, inter-regional movers corresponded to 2.7% of the total population in the OECD area, ranging from around 5% in Korea, the Netherlands and the United Kingdom (UK) to less than 0.7% in Italy, Poland and the Slovak Republic (Figure 3.9).
Inter-regional migration does not affect all regions of a country in the same way. While metropolitan regions and regions close to a city tend to experience positive net inflows, others are often facing net outflows. In the 28 OECD countries with available data from 2016 to 2019, metropolitan regions and regions near a metropolitan area experienced net in-migration flows, gaining an average of 10.5 and 7 persons per every 10 000 inhabitants respectively (Figure 3.11). In contrast, regions far from a metropolitan area faced net out-migration flows, losing an average of 10 persons for every 10 000 people. Looking at individual regions, Parinacota (Chile), Sejong (Korea) and Flagstaff (United States, US) were the regions with the highest positive annual net migration rate during the last 4 years considered, with gains of 9%, 4% and 3% of the regional population respectively (Figure 3.10). In contrast, during the same period, Suhl (Germany), Oost-Go (Netherlands) and Anchorage (US) experienced net out-migration that corresponded to losses of 7.8%, 4.2% and 3.7% of their populations.
Young people between 15 and 29 years old account for more than half of the total within-country flows. In almost all OECD countries for which data is available, young people move almost exclusively to metropolitan regions, with educational and professional opportunities likely driving such flows (Figure 3.12). Greece and Portugal are exceptions, as these two countries were the only ones where regions far from metropolitan regions received net inflows of young migrants since 2016.
Sources
OECD (2022), OECD Regional Statistics (database), OECD Publishing, Paris, https://doi.org/10.1787/region-data-en.
Reference years and territorial level
2016-19; TL3 or TL3 regions classified according to metropolitan access classification (see below for further details).
Inter-regional movers: Data refer to yearly flows of the population from one TL3 region to another TL3 region in the same country (regional migration). Outflows are represented as the number of persons who left the region the previous year to reside in another region of the same country, while inflows are represented as the number of new residents in the region coming from another region of the same country.
The net migration flow is defined as the difference between inflows and outflows in a region. A negative net migration flow means that more people left the region than entered it.
Access to metropolitan areas typology: The proposed classification distinguishes TL3 regions based on the level of access to metropolitan areas (Fadic et al., 2019). At a first level, regions where at least half of the regional population live in a metropolitan area of at least 250 000 inhabitants are considered “metropolitan” regions, and as “non-metropolitan” otherwise. Metropolitan regions are further distinguished as “large metro” regions if they include or they are part of a metropolitan area of at least 1.5 million inhabitants. “Non-metropolitan” regions are sub-classified as regions “with access to a metro” if half of its population can reach a metropolitan area within a 60-minute drive. When half of the regional population can reach only a smaller-sized city (between 50 000 and 250 000 inhabitants), the region is classified as “with access to a small/medium city”. In all other cases, the region is classified as “remote”. The classification relies on the concept of FUAs (Dijkstra et al., 2019; OECD, 2012) to delineate metropolitan areas of at least 250 000 inhabitants or smaller-sized cities.
Further information
Territorial grids and regional typology (Annex B).
Dijkstra, L., H. Poelman and P. Veneri (2019), “The EU-OECD definition of a functional urban area”, OECD Regional Development Working Papers, No. 2019/11, OECD Publishing, Paris, https://doi.org/10.1787/d58cb34d-en.
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 (2012), Redefining “Urban”: A New Way to Measure Metropolitan Areas, OECD Publishing, Paris, https://doi.org/10.1787/9789264174108-en.
Figure notes
3.9-3.12: Average values for 2016-19 (4-year period).
3.12: Regions with a large city includes those with large and very large cities.
