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Change in new registered cars 2019-2020

The map shows the change in new registered passenger cars from 2019 to 2020. In most countries, the number of car registrations fell in 2020 compared to 2019. On a global scale, it is estimated that sales of motor vehicles fell by 14%. In the EU, passenger car registrations during the first three quarters of 2020 dropped by 28.8%. The recovery of consumption during Q4 2020 brought the total contraction for the year down to 23.7%, or 3 million fewer cars sold than in 2019. In the Nordic countries, consumer behaviour was consistent overall with the EU and the rest of the world. However, Iceland, Sweden, Finland, Åland, and Denmark recorded falls of 22%–11% – a far more severe decline than Norway, where the market only fell by 2.0%. The Faroe Islands was the only Nordic country to record more car registrations, up 15.8% in 2020 compared to 2019.  In Finland, Iceland, Norway, and Sweden, there were differences in car registrations in different parts of the country. In Sweden and Finland, the position was more or less the same in the whole of the country, with only a few municipalities sticking out. In Finland and Sweden, net increases in car registrations were concentrated in rural areas, while in major urban areas, such as Uusimaa-Nyland in Finland and Västra Götaland and Stockholm in Sweden, car sales fell between 10%–22%. Net increases in Norway were recorded in many municipalities throughout the whole country in 2020 compared to 2019.

Population change by component 2010-2019

The map shows the population change by component 2010-2019. The map is related to the same map showing regional and municipal patterns in population change by component in 2020. Regions are divided into six classes of population change. Those in shades of blue or green are where the population has increased, and those in shades of red or yellow are where the population has declined. At the regional level (see small inset map), all in Denmark, all in the Faroes, most in southern Norway, southern Sweden, all but one in Iceland, all of Greenland, and a few around the capital in Helsinki had population increases in 2010-2019. Most regions in the north of Norway, Sweden, and Finland had population declines in 2010-2019. Many other regions in southern and eastern Finland also had population declines in 2010-2019, mainly because the country had more deaths than births, a trend that pre-dated the pandemic. In 2020, there were many more regions in red where populations were declining due to both natural decrease and net out-migration. At the municipal level, a more varied pattern emerges, with municipalities having quite different trends than the regions of which they form part. Many regions in western Denmark are declining because of negative natural change and outmigration. Many smaller municipalities in Norway and Sweden saw population decline from both negative natural increase and out-migration despite their regions increasing their populations. Many smaller municipalities in Finland outside the three big cities of Helsinki, Turku, and Tampere also saw population decline from both components. A similar pattern took place at the municipal level in 2020 of there being many more regions in red than in the previous decade.

Net internal migration rate, 2010-2019

The map shows the annual average internal net migration in 2010-2019. The map is related to the same map showing net internal migration in 2020. The maps show several interesting patterns, suggesting that there may be an increasing trend towards urban-to-rural countermigration in all the five Nordic countries because of the pandemic. In other words, there are several rural municipalities – both in sparsely populated areas and areas close to major cities – that have experienced considerable increases in internal net migration. In Finland, for instance, there are several municipalities in Lapland that attracted return migrants to a considerable degree in 2020 (e.g., Kolari, Salla, and Savukoski). Swedish municipalities with increasing internal net migration include municipalities in both remote rural regions (e.g., Åre) and municipalities in the vicinity of major cities (e.g., Trosa, Upplands-Bro, Lekeberg, and Österåker). In Iceland, there are several remote municipalities that have experienced a rapid transformation from a strong outflow to an inflow of internal migration (e.g., Ásahreppur, Tálknafjarðarhreppurand, and Fljótsdalshreppur). In Denmark and Norway, there are also several rural municipalities with increasing internal net migration (e.g., Christiansø in Denmark), even if the patterns are somewhat more restrained compared to the other Nordic countries. Interestingly, several municipalities in capital regions are experiencing a steep decrease in internal migration (e.g., Helsinki, Espoo, Copenhagen and Stockholm). At regional level, such decreases are noted in the capital regions of Copenhagen, Reykjavík and Stockholm. At the same time, the rural regions of Jämtland, Kalmar, Sjælland, Nordjylland, Norðurland vestra, Norðurland eystra and Kainuu recorded increases in internal net migration. While some of the evolving patterns of counterurbanisation were noted before 2020 for the 30–40 age group, these trends seem to have been strengthened by the pandemic. In addition to return migration, there may be a larger share of young adults who…

Cross-border commuting as share of employment

The map illustrates the average share of employees who commuted to another Nordic country between between 2015 and 2018 in Nordic regions (NUTS 2). Between 2015 and 2018, an average of approximately 49,000 people held a job in a Nordic country in which they were not residents. This indicates that, on average, 0.5% of the Nordic working-age population commuted to a job in another Nordic country. This is below the EU27 average of 1%, with the highest numbers found in Slovakia (5.1%), Luxembourg (2.8%) and Estonia (2.6%). Some of these people cross borders daily. Others work in another country by means of remote working combined with occasional commuting across borders.  Within the Nordic Region, the largest cross-border commuter flows are in the southernmost parts of Sweden, regions in the middle of Sweden and in Åland, where more than 1% of the working population commutes to another Nordic country. However, there may be individual municipalities where cross-border commuting is substantially higher. For example, the employment rate in Årjäng Municipality, Sweden, increases by 15 percentage points when cross-border commuting is taken into account. These municipalities are not reflected on NUTS 2 level when averages are calculated. In terms of absolute numbers in 2015, the highest numbers of commuters were from Sweden: Sydsverige (16,543), Västsverige (7,899) and Norra Mellansverige (6,890). The highest number of commuters from a non-Swedish region were from Denmark’s Hovedstaden (2,583).   Due to legislative barriers regarding the exchange of statistical data on cross-border commuting between the Nordic countries, more recent data is not available. 

Travel time by train from Copenhagen or Malmö

The travel times indicate the fastest morning connection outbound from Copenhagen Central Station or Malmö Central Station, departing after 6:30AMand arriving before 9:00AM. The station catchments are calculated by bicycle travel time for any time remaining beyond train travel. For instance, a 35-minute train ride and a 10-minute cycle ride results in a 45-minute total travel time. The shades of green indicate the travel time to other train stations and their surrounding areas in four main classes: up to 15 minutes, 16 to 30 minutes, 31 to 45 minutes and 46 to 60 minutes. The areas not highlighted in green on the map are further than one hour by train from either Copenhagen or Malmö main train stations. The map clearly shows that the vast majority of areas within the Capital Region of Denmark, a number of stations and areas which are part of the region of Zealand, for instance Slagelse and Næstved, as well as areas located along four main train corridors in Skåne (Malmö-Helsingborg, Malmö-Hässleholm, Malmö-Trelleborg and Malmö-Ystad) are within the one-hour travel time by train from/to Copenhagen and/or Malmö, thanks to the different train types (Öresund trains, regional trains and intercity trains). Areas of the GCR which are beyond the one-hour travel condition are the most northern part of the Capital Region of Denmark, the southern and western parts of Zealand (e.g. Kalundborg and Vordingborg) as well as most of the eastern half part of Skåne. In terms of population, the current situation provides this possibility to almost 3 million out of 4.3 million inhabitants, corresponding to 69% of the total population living in the Greater Copenhagen Region in 2020. The proportion of the total population increases to 75% when the region of Halland is excluded (as this was not initially part of the GCR when the…

At-risk-of-poverty rate 2011-2018 change

The map shows the “at-risk-of-poverty” (AROP) rate in the Nordic Region. For the period from 2004 to 2018, the AROP rate increased in all Nordic countries except Iceland. This trend was strongest in Sweden. In Finland the AROP rate has been decreasing during the past few years, in line with what has previously been indicated – namely, on account of economic turmoil. This points to one of the weaknesses of using the AROP rate alongside several other measures of inequality. That is, while people have become poorer due to the economic crisis, the at-risk-of-poverty rate has paradoxically gone down. In addition, the AROP rate for Finland is higher in 2018 than it was in 2004. Looking at these trends on a regional level over a period of time (between 2011 and 2018), we can see that the AROP rate has decreased in almost all areas of Finland, whereas the pattern is rath er more varied in the other Nordic countries (we can also see a cohesive area in the south of Denmark where the AROP rate has decreased.) Again, Sweden has the most regions displaying increases in the AROP rate. Finland and Sweden contain the largest differences between the regions with the highest and lowest AROP rate. Hence the greatest regional differences are to be found in Sweden and Finland. Sweden also has the highest average AROP rate. About the At-risk-of-poverty The at-risk-of-poverty rate is a common measure of relative poverty and social inclusion. Most notably, it has been used for monitoring the EU2020 goal of inclusive growth. The at-risk-of-poverty rate is normally defined as “the share of people with an equivalised disposable income (after social transfer) below the at-risk-of-poverty threshold, which is set at 60% of the national median equivalised disposable income after social transfer.” (Eurostat). The indicator is…

Internal net migration of 30 to 39 years-of-age, by gender, in 2010-2019

This map shows a typology that divides the Nordic municipalities and regions into four migration categories: positive net migration for both males and females (green on the map), positive male net migration (blue on the map), positive female net migration (yellow on the map), and negative net migration for both males and females (red on the map). These migration flows on 30 to 39-year-olds are of particular interest since it is often assumed that the future of rural regions is dependent upon their capability both to retain their populations and to attract newcomers, returning residents and second home owners. In this context, the map provides a rather positive picture, because a considerable proportion of rural municipalities have experienced positive net migration among females, males, or both sexes across all the Nordic countries. Even so, there is negative net migration among both females and males in many municipalities in northern Sweden, north-eastern Norway and eastern Finland, in addition to several inland municipalities within these countries. Interestingly, there is negative net migration among both sexes across all the capital city municipalities of the Nordic Region. According to the regional map, the capital city regions of Denmark, Iceland and Norway all experienced negative net migration of young people aged 30-39 years between 2010 and 2019. The capital city region of Sweden experienced positive net migration of males and negative net migration of females while the capital city region of Finland experienced positive net migration overall. Despite the majority of peripheral regions experiencing negative net migration of 30 to 39-year-olds during the time period studied, there are also several interesting examples of rural regions which experienced positive female net migration, for example Nordjylland (Denmark), Pohjois-Savo (Finland), Austurland (Iceland), Møre og Romsdal (Norway), and Jämtland (Sweden).

Internal net migration of 20 to 29 years-of-age, by gender, in 2010-2019

This map shows a typology that divides the Nordic municipalities and regions into four migration categories: positive net migration for both males and females (green on the map), positive male net migration (blue on the map), positive female net migration (yellow on the map), and negative net migration for both males and females (red on the map). These migration flows of 20 to 29-year-olds are of interest since there is a particularly high level of internal migration among young adults across the Nordic countries compared to other EU countries. While the map shows that the great majority of municipalities experience negative net migration of young adults in favour of a few functional urban areas and some larger towns, it is possible to observe a number of exceptions to this general rule. The rural municipalities of Utsira, Moskenes, Valle, Smøla, Ballangen and Lierne in Norway have the highest positive net migration rates both for men and women. There are also positive net migration rates for males and females in the peripheral municipalities of Jomala, Kittilä, Lemland and Finström in Finland and Åland. There is positive male net migration but negative female net migration in Gratangen, Loppa, Gamvik, Drangedal and a few other Norwegian rural municipalities, plus Mariehamn in Åland, while several municipalities in remote areas of Finland have positive female net migration but negative male net migration. Some of these patterns may be related to specialised local labour markets, such as fisheries in Loppa, or recreational tourism in Kittilä. In general, the pattern of net migration among young adults is more diverse in Finland (where 72.0% of all municipalities have negative net migration), compared with 84.6% in Norway, 88.9% in Denmark and 89.0% in Sweden. However, it is important to remember that Danish, Finnish and Norwegian municipalities are smaller in size…

Mobility changes due to COVID-19

This map shows the difference in mobility to workplaces between a weekday (April 23rd, 2020) and the corresponding weekday during the period January 7th to February 6th, 2020 (in percent). The data highlights the percent change in visits to workplaces within each administrative region in Denmark, Finland, Norway and Sweden. Data is not available for the Faroe Islands, Greenland, Iceland and Åland. Read more about the data here. The average value of the Nordic regions included in the map is a reduction by 34% of the number of visits to workplaces on April 23rd (in comparison to a baseline). This average value hides large variations within the Nordic Region with the most modest change occurring in Gotland (-12%) and the most severe change in Oslo (-57%). More generally, variations can be identified both between and within countries. The variations between countries reveal differences in recommendations and restrictions from published by the different national governments. Details for each country have been gathered by Info Norden and can be found here. As a result, the change in visits to workplaces decreased by 26% in Sweden, 39% in Denmark, 41% in Norway and 47% in Finland. The variations within countries also reveal differences in government´s decisions (e.g. lockdown of the Helsinki-Uusimaa region reducing the mobility to workplaces by 53%), but not only. There are indeed a number of local characteristics of the labour markets that contribute at explaining that the largest changes in mobility to workplaces are found in capital city regions. These local characteristics are a greater dependency on public transport for commuters, who are adviced to avoid using such means of transportation under the COVID-19 context; and having a higher share of jobs that can be done by teleworking, among others.