Access to fixed broadband at minimum download speed 100 Mpbs
The map shows the proportion of households that had access to fixed-line broadband with download speeds >100 Mbps (superfast broadband) at the municipal level, with darker colours indicating higher coverage. Overall, Denmark has the highest levels of connectivity, with 92% of municipalities providing superfast broadband to at least 85% of households. In over half (59%) of all Danish municipalities, almost all (>95%) of households have access to this connection speed. The lowest levels of connectivity are found in Finland. This is particularly evident in rural municipalities where, on average, less than half of households (48%) have access to superfast broadband. Connectivity levels are also rather low in some parts of Iceland, for example, the Westfjords and several municipalities in the east. Households in urban municipalities are still more likely to have access to superfast broadband than households in rural or intermediate municipalities, but the gap appears to be closing in most. This is most evident in Norway, where the average household coverage for rural municipalities increased by 31% between 2018 and 2020. By comparison, average household coverage for urban municipalities in Norway increased by only 0.7%. In the archipelago (Åland Islands, Stockholm and Helsinki), general broadband connectivity is good; however, some islands with many second homes still have poor coverage.
Change in work travels Jan-Feb 2020 compared to Nov 2021
The map shows changes in number of people travelling to work in the Nordic municipalities with the biggest populations comparing November 2021 to a pre-pandemic baseline. The map compares the average number of people who travelled to work on a weekday in January and February 2020 with the number of people who travelled to work on 11 November 2021 in the ten largest cities of Denmark, Finland, Norway and Sweden. The date was selected as the reference date as it is considered to be a relatively typical Thursday. It also represents a point when few movement restrictions were in place in the Nordic countries. As can be seen from the map, all of the municipalities highlighted recorded a fall in work-related travel on 11 November compared to the pre-pandemic baseline. It was biggest in Stavanger (-36%), followed by Stockholm (-31%), Oulu (-30%), Bærum (adjacent to Oslo) (-29%), Frederiksberg (adjacent to Copenhagen) (-29%) and Helsinki (-29%). In general, the decrease was highest around the capital regions and larger cities, but there were exceptions, for example, Jyväskylä (-26%), Örebro (-25%), Jönköping (-21%), and Randers (-20%). Several large municipalities also stood out because their patterns did not change so much, for example, Helsingborg (-3%) and Västerås (-7%) in Sweden; Viborg (-3%) and Odense (-8%) in Denmark.
Remote work potential
The map shows the share of jobs that can potentially be done from home. At the municipal level it shows that the highest proportion is in, or in the proximity of, the largest urban conurbations. The purple areas show the municipalities that has a remote-work potential above the Nordic average (37%) and the blue areas the municipalities with remote-work potential below the Nordic average. The indicator is based on the methodology of Dingel & Neiman (2020). This method estimates the proportion of jobs that can theoretically be performed from home based on the tasks included in different occupations. Dingel & Neiman’s US classification was translated to the European International Standard Classification of Operations (ISCO-08) codes. The data is based on the 4-digit ISCO-08 and includes 437 occupations. The result was that every 4-digit ISCO occupation was coded as either 1: possible to work from home or not possible to work from home. For more information about the method please look at the State of the Nordic Region 2022 publication. The ten municipalities with the highest proportions are all in capital regions, with seven out of 10 in either Copenhagen (Hovedstaden) or Stockholm Region. In general, people in urban municipalities are more likely to be able to work from home (46.2%) than those in intermediate municipalities (32.3%) and rural municipalities (27.8%). It seems to be the case that the higher proportion of jobs that can be done from home in urban areas relates to the differences in industrial and occupational profiles between urban and rural areas, in particular, a higher concentration of knowledge-intensive occupations in urban areas. These differences are also evident when comparing countries. For example, Denmark has a rather large number of municipalities with high proportions of jobs that can be done from home. This may be due to…
The map shows a typology of European regions by combining information on pre-pandemic unemployment rates with unemployment rates in 2020, based on the annual Labour Force Survey (LFS) that is measured in November. On one axis, the typology considers the extent of the change in the unemployment rate between 2019 and 2020. On the other axis, it considers whether the unemployment rate in 2020 was above or below the EU average of 7.3%. Regions are divided into four types based on whether the unemployment rate decreased or increased and how it relates to the EU average. Regions falling into the first type, shown in red on the map, had an increase in the unemployment rate in 2020 as well as an above-average unemployment rate in general in 2020. These regions were most affected by the pandemic. They are mainly found in northern and central parts of Finland, southern and eastern Sweden, the capital area of Iceland, Latvia, Lithuania, Spain and central parts of France. Regions falling into the second type, shown in orange on the map, had an increase in the unemployment rate in 2020 but a below-average unemployment rate in general in 2020. These regions had low pre-pandemic unemployment rates and so were not as badly affected as the red regions, despite the rising unemployment rates. They are located in Denmark, Iceland, Norway, Åland, southern and western Finland, Sweden (Gotland, Jönköping, and Norrbotten), Estonia, Ireland, northern Portugal and central and eastern parts of Europe.
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.
The share of laid-off employees at municipal and regional level
The map shows the share of employees laid off temporarily at municipal and regional levels in May 2020. According to the map, the highest proportion was in municipalities with a high proportion of people working in manufacturing, tourism and transport. These include the municipality of Sykkylven in Norway, which is home to several large furniture factories, the municipalities of Gnosjö and Oxelösund in Sweden, which both have multiple industries and a high proportion working in manufacturing, and the municipality of Taipalsaari in Finland, which is close to a large paper mill. Municipalities with significant tourism and a high proportion of employees laid off include Aurland, Hemsedal, Hol, and Trysil in Norway and Kittilä in Finland. The highly affected municipalities of Tårnby in Denmark and Härryda in Sweden are close to large airports, and in the municipality of Lemland in Finland, many people may work in the cruise industry. At regional level, the largest proportion of laid-off employees per 1,000 employed was in Oslo. All the other regions of Norway, all regions of Finland, and the regions of Halland, Jönköping, Kronoberg, Stockholm, Södermanland and Västra Götaland in Sweden and Hovedstaden in Denmark also had relatively high shares. The lowest proportions were found in the regions of Nordjylland and Sjælland in Denmark.
Work mobility per municipality and region by quarter
The map shows the percentage change for work mobility in Nordic regions and municipalities compared to a pre-pandemic baseline. The maps compare Nordic mobility patterns in each quarter of 2020 and 2021 with a pre-pandemic baseline. Based on Google data, the panels illustrate the impact of national restrictions and how those restrictions hampered work mobility. As the restrictions were both national and regional in nature, some regions and municipalities were more affected than others. The darker areas in the map show that work mobility decreased the most Q2 and Q3 2020 and in Q3 2021. The panels also show that mobility decreased later in Sweden than in the other Nordic countries. However, the decrease in Q3 in both 2020 and 2021 may partly be explained by the summer vacation months, when work mobility tends to decrease anyway. In Q4 2021, the overall situation seems to improve, although the pattern is mixed. In a few municipalities the situation is almost back to pre-pandemic baseline while in most municipalities, there is still less mobility in the labour market compared to the pre-pandemic situation.
Employment rate 2020
The map shows the employment rate for all Nordic municipalities and regions in 2020. Full employment is one of the cornerstones of what is known as the Nordic model and, historically, the Nordic countries have enjoyed comparably high employment rates, particularly for women and older workers. The employment rate measures the number of people in work as a proportion of the working-age population (aged 15–64) as a whole. The green tones indicate municipalities with employment rates above 75% in 2020, with the darker green representing higher employment rate. The yellow tones indicate municipalities with employment rates below 75% in 2020. The light-yellow colour indicates municipalities with employment rates below 70% in 2020. The highest employment rates were found in the Faroe Islands and in many smaller municipalities in Norway and Sweden, whereas the lowest employment rates were in Greenland and several municipalities in Finland. At regional level, the Faroe Islands, the regions of Halland, Jämtland, Jönköping, Norrbotten and Stockholm in Sweden, and the region of Møre og Romsdal in Norway had an employment rate above 80%. Employment rates below 70% were recorded in Greenland and the regions of Etelä-Karjala, Kainuu, Kymenlaakso and Pohjois-Karjala in Finland.
Nordic cross-border co-operation committees 2021
The map shows the geographical delimitation of cross-border regions and committees financed by the Nordic Council of Ministers as of December 2021.
Cross-border commuters as a share of total employees in the Nordic Region 2015
The map shows the share of cross border commuters in the total employees with residence in a NUTS2 Nordic Region in 2015. The darker the blue, the higher the share. For the most NUTS2 regions in the Nordic, the percent is lower than 0,5%, indicating the commuting workers are the absolute minority in the total employed people. Åland (2,6%) and the South Sweden region (2,7%) stand out with more than 2% of employees in the region commuting cross-border for work. The destination country for Åland workers is Sweden, while for Swedish workers living in the south is Denmark. The commuting pattern is also apparent for the Swedish NUTS2 regions along the border line with Norway, with relatively higher percent of cross border workers commuting to Norway compared with other Nordic NUTS2 regions. At a finer scale (e.g., NUTS3) would show higher percentages in a number of regions, e.g., by taking only the NUTS 3 region – Skåne instead of the NUTS 2 region South Sweden (Skåne+Blekinge) or the border regions between NO and SE.
Cross-border commuters to other Nordic countries for work 2015
The map builds on statistics of cross-border commuters with residence in a NUTS2 Nordic region commute for work in 2015. For each NUTS2 region, the map shows the total number of commuters who commute to other Nordic countries for work. The number of commuters is categorised into three groups visualised in different shades: the darker, the higher the number of commuters. In addition, the most common country these commuters commute to from each region is identified by specific colours. For example, the darkest red indicates a region with at least 2,000 commuters working in another Nordic country, of which the largest group number of commuters works in Denmark. The most commuters were from the region of South Sweden (16 543) in 2015, and the majority of them commuted to Denmark for work. Norway is the most popular destination for work commuters in the Nordic Region, e.g., all Swedish regions except for the South Sweden region, all the regions in Denmark except for the Copenhagen region, and Iceland. Sweden is more attractive for work commuters living in Finland, Copenhagen region, and bordering regions in Norway.
Nordic cross-border co-operation committees 2020
The map shows the geographical delimitation of cross-border regions and committees financed by the Nordic Council of Ministers.
Share of employment in tourism 2017
The map shows the share of employed people in tourism industry in 2017. On a national level the share of tourism is quite similar in the Nordic countries, except for Iceland where the share is more than double as high. In Iceland it is especially the sector “Accommodation and food service activities” that stands out. This category alone stood for 6.9% of the total employment in Iceland in 2017 . On a regional level Åland stands out with 14.7% of employment in tourism. In Åland it is mainly the category “Sea passenger transport” that is big. Only this category stands for 9.8% of the employment. Also other islands such as Gotland and Bornholm have a high share of employment in tourism as well as the capital cities of Copenhagen and Stockholm. Jämtland attracts many tourists in the winter. The regions with the lowest share of tourism employment include the Finnish regions Keski-Pohjanmaa and Etelä-Pohjanmaa (both 2,7%); Københavns omegn (2.9%) and Vestjylland (3.4%) in Denmark; Blekinge (3.3%) and Kronoberg (3.3%) in Sweden and Østfold (3.5%) in Norway. The data on employment by sector is classified using the NACE classification system (“nomenclature statistique des activités économiques dans la Communauté européenne”). To define which sectors that tourism comprise of, we have selected the Eurostat’s definition due to the fact that Eurostat has adapted the definition of UNWTO to a European context to make it more precise and to avoid overestimate certain economic activities (e.g. real estate activities). Their definition is also very close to the definition used by Tillväxtverket. Eurostat thus defines tourism as comprising the following economic activities : H4910 Passenger rail transport, interurban H4932 Taxi operation H4939 Other passenger land transport n.e.c. H5010 Sea and coastal passenger water transport H5030 Inland passenger water transport H5110 Passenger air transport I5510 Hotels and…
Accessibility gains from virtual health rooms in Västerbotten
To secure better access to general practitioners for the rural population, the region of Västerbotten has developed the concept of virtual healthrooms (VHRs). These VHRs are unstaffed, which means that they have no regular health personnel in situ. They are equipped with distance-spanningtechnology, which means that patients can go there to take consultations from a practitioner online, conducting health checks such as measuringblood pressure or heart rate. The coloured patches on the map show those populated areas in Västerbotten where inhabitants can expect a reduction of travel distance to primary health care through the implementation of VHRs. The coloured patches are populated areas in Västerbotten (by 1000*1000m grid) with improved accessibility of health care resulting from the implementation of virtual health rooms. The colour indicates the total distance reduced.Distance is measured as being via the road network. The average distance to the closest primary health care facility (health centre or virtual health room) is 6 km for the overall population in Västerbotten. The implementation of VHRs means that around 3.5% of the 270,000 inhabitants of Västerbotten experience increased accessibility toa primary health care service. The travel distance for this portion of the population has been cut by almost 50%, from 42 km per person to 23 km per person. Patients may also use virtual health rooms to conduct teleconsultations with health professionals at specialised hospitals, which creates even greater potential from an accessibility standpoint.
Accessibility of highly specialised care in Västerbotten
The map illustrates the accessibility of highly specialised care in Västerbotten in Sweden. The colours represent car ride times in minutes from the place of residency to the nearest health care facility within a certain service type, with a travel range of 10 minutes to two hours. The health care facilities are also located on the map. The only hospital offering highly specialised in-patient care is located in Umeå, and half of the regional population (51.0%) can reach the hospital within a 40-minute car ride. For the inhabitants of Storuman, however it takes more than a two-hours car ride to access specialised care in the hospital. The accessibility of health care services for rural dwellers are improved by means of distance-spanning digital solutions. Instead of making the effort of physically visiting a health care facility, they can access video consultations with general practitioners via virtual health care rooms, and then decide whether a follow-up physical visit to the specialised hospital is needed.
Accessibility of in-patient care in Västerbotten
The map illustrates the accessibility of in-patient care in Västerbotten in Sweden. The colours represent car ride times in minutes from the place of residency to the nearest health care facility within a certain service type, with a travel range of 10 minutes to two hours. The health care facilities are also located on the map. The accessibility of in-patient care shares similar characteristics to that of access to dropin out-patient care. The ten facilities mentioned above provide in-patient care, too. The only difference is that two facilities outside the region were included in the analysis. But they did not alter the overall picture, suggesting that inhabitants living along the border line tend not to cross the border to seek in-patient care. These hospitals are accessible to 56.3% of the population within a 10-minute car ride, and 97.1% of the population within a one-hour car drive.
Accessibility of out-patient drop-in care in Västerbotten
The map illustrates the accessibility of out-patient drop-in care in Västerbotten in Sweden. The colours represent car ride times in minutes from the place of residency to the nearest health care facility within a certain service type, with a travel range of 10 minutes to two hours. The health care facilities are also located on the map. Health care facilities offering out-patient drop-in care are characterised by even geographical distribution across Västerbotten. Each inland municipality has one such heath care facility, apart from Norsjö. All ten facilities offer drop-in care during both office hours and evenings and weekends (24/7). According to the results of our accessibility analysis, 56.% of the regional population can access drop-in out-patient care within a ten minute car ride. Within a half-hour car ride, the drop-in care service is available to 83.3% of inhabitants.
Accessibility of primary care in Västerbotten
The map illustrates the accessibility of primary care in Västerbotten in Sweden. The colours represent car ride times in minutes from the place of residency to the nearest health care facility within a certain service type, with a travel range of 10 minutes to two hours. The health care facilities are also located on the map. The 37 health care facilities in the region contribute to widespread coverage of primary outpatient care for the population in Västerbotten. Over 80% of the inhabitants can access such health care services within a 10-minute car ride, and a half-hour car ride can cover 95.8% of the regional population. In general, coastal municipalities have easier access to health care services than inland municipalities. As one of the inland municipalities, Storuman accommodates one health care facility which provides most of the health care services expected in relation to highlyspecialised care.
Labour market impacts of COVID-19
On May 17, 2020, 94% of the world’s workers were living in countries with some form of workplace closure measures in place (ILO, 2020). While it is too early to make predictions about the long-term consequences of this, it is possible to make some observations about the short-term labour market impacts in the Nordic Region. The map shows the number of people who registered as unemployed in April 2020 compared with the number of people who registered as unemployed in April 2019 at the municipal level for Denmark, Finland, Norway and Sweden and Åland Islands and at the national/territory level for Iceland and the Faroe Islands. The shading represents the increase in percent, with darker colours showing higher relative increases compared to the previous year and lighter colours lower relative increases. Municipalities shaded in blue on the map did not experience an increase in unemployment registrations in April 2020 compared to April 2019. Overall, the number of unemployment registrations across the Region was 38.9% higher in April 2020 than in April 2019. This increase equates to a total of 220 354 Nordic workers and has affected almost all Nordic municipalities and regions to some degree. Proportionally speaking, Norway saw the largest increase (69%), followed by Iceland (59%), Denmark (48%), Sweden (41%), and Finland (24%). Though between-municipality variation is evident, the greatest differences appears to be between countries. Interestingly, many Swedish municipalities along the southern coast between Sweden and Norway saw increases more consistent with the overall trend observed in Norway. This may be a reflection of the prevalence of cross-border commuting in these regions. It is important to note that the labour market situation in April 2019 has some baring on the results shown on the map. For example, the appearance of a sharper relative increase in Norway is primarily…
Local labour market areas in the Greater Copenhagen Region 2018
This map shows both the location of the four case studies of the Triborder activity 3 in the Greater Copenhagen Region and the local labour market areas in this cross-border region.