Maps

A map portrays tertiary education attainment level around the Nordics.

The map shows the relative change in single-family house prices from fourth quarter 2019 and first quarter 2020 to second and third quarter of 2021 for Danish municipalities. The map shows that most municipalities experienced high price increases during this period, but the extent to which this change was more pronounced differs between municipalities. The increases are highest in the Copenhagen Region, but also in Aarhus and surrounding municipalities, and the peri-urban areas around Vejle. High relative increases are also found in coastal and island municipalities (e.g.  Bornholm, Lolland, Svendborg and around the Western part of the Limfjord), though it is worth noting that these municipalities had lower relative house prices to begin with. These patterns may reflect changing preferences for houses, demand for more space and access to recreational areas.

The map shows the geographical delimitation of cross-border regions and committees financed by the Nordic Council of Ministers as of December 2021.

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.

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.

The map shows the geographical delimitation of cross-border regions and committees financed by the Nordic Council of Ministers.

The map illustrates the accessibility of highly specialised care in Nordjylland in Denmark. 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. Highly specialised care, being the most professional form of health care service, is also the most restricted in terms of accessibility for the general population in Nordjylland, compared to other types of health care. The six hospitals offering specialised care are located in Aalborg (three hospitals), Vesthimmerlands (one), Mariagerfjord (one) and Thisted (one). To reach a specialised health care service, it takes ten minutes by car for 41.5% of the regional population. Specialised care is particularly accessible for those who live in or near the urban centre of Aalborg. On the other hand, a car ride of longer than 30 minutes is needed for 13.8% of inhabitants in the region to access specialised care.

The map illustrates the accessibility of in-patient care in Nordjylland in Denmark. 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. Accessibility of in-patient care in Nordjylland presents a similar picture to that of out-patient emergency care during non-office hours. Nine health care facilities in the region provide in-patient care services, and outside the region five provide such a service. More than half of the inhabitants (58.7%) can access such health care services within a 10-minute car ride, and a car ride of 40-minute covers 99.5% of the regional population who need such a service. Despite the facilities outside the region being geographically close to the regional border, inhabitants living along that border line tend not to cross it in order to seek inpatient care.

The map illustrates the accessibility of out-patient drop-in care during non-office hours in Nordjylland in Denmark. 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. This map shows that accessibility of out-patient drop-in care during evenings and weekends (24/7) is limited. Such health care services are available in only 13 out of the 174 facilities across the region. Half of the inhabitants in the region (54.2%) are able to access out-patient drop-in care during non-office hours within a ten-minute car ride, while a 40-minute car ride covers 99.5% of the regional population.

The map illustrates the accessibility of out-patient drop-in care during office hours in Nordjylland in Denmark. 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 people of Nordjylland have widespread access to out-patient drop-in care facilities during office. Location of health care facilities in Nordjylland. hours, thanks to the 163 health care facilities in the region which provide such a service. It takes ten minutes by car for 98.7% of the regional population to reach out-patient drop-in care facilities during office hours, 99.8% of the population is covered by a 20-minute car ride.

The map illustrates the accessibility of primary care in Nordjylland in Denmark. 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. Accessibility to primary out-patient health care services in Nordjylland is outstanding. Altogether, 98.7% of the population can access one such service within a ten-minute ride, while a 20-minute ride covers 99.8% of the total population in the region. In total, 165 health care facilities provide primary health care in the region, contributing to an established pattern of extensive accessibility across Nordjylland.

These maps show the number of jobs in the bioeconomy sectors as a share of the total employment in 2017 (left) and 2009-2017 change (right), excluding the NACE A sectors. The non-NACE-A sectors have seen a more moderate decrease in Finland but a noticeable increase in most parts of Sweden, Denmark and the Faroe Islands and a remarkable increase in Iceland with more than 15% (Figure 9.3). The average increase in the Nordic Region is 4.3% in the non-NACE-A sectors. There are also notable differences within the countries, showing that regional differences matter. In Denmark, Greenland and the Faroe Islands, there is a positive trend in most regions, but in Finland, almost all regions are losing jobs in the primary industries. In Norway and Sweden, some regions show positive development while others are in decline. Read the digital publication here.

These map show the number of jobs in the agriculture, forestry and fisheries sectors (NACE A sectors) as a share of the total employment in 2017 (left) and 2009-2017 change (right). The map (left) indicates ranges of people employed in agriculture, forestry and fisheries sectors between below 2% to above 8%, with the highest proportion being in Greenland with 23.5% in 2017. In the EU-28, the overall proportion of the total workforce with jobs in the NACE-A sectors is an average of 4.6%. Overall, the NACE-A sectors show a sharp decline in employment (right map), particularly in Finland, Iceland and Norway (except northern Norway), where the decline was up to 20% between 2009 and 2017. Read the digital publication here.  

These maps show the number of jobs in the bioeconomy sectors as a share of the total employment in 2017 (left) and 2009-2017 change (right). The share of jobs in the bioeconomy varies from below 15% to above 22.5%. For instance, in the western regions of Denmark, the central and southern regions in Finland, Greenland and some mid and northern regions of Norway, over 22.5% of the working population is employed in the bioeconomy. At the same time, most regions in mid-Norway, in all Finnish and some Danish regions witnessed negative development in jobs in the bioeconomy. In Greenland, Iceland, Faroe Islands, Sweden, Northern Norway and other parts of Denmark the situation is very different and the number of jobs in the bioeconomy has increased. These proportions should also be seen in relation to the increase in total number of jobs17 in most regions in the Nordic countries except for the Finnish regions and Åland where there is a decline in most regions. Read the digital publication here.

The map provides an overview of the population change in Arctic settlements with 500 inhabitants or more during the period 2000 to 2017. The purple underlaying layer shows the extent of permafrost across the Arctic. The circles indicate settlements with 500 inhabitants or more and are proportional to the total population in 2017. Blue tones indicate population growth between 2000 and 2017, while red tones indicate population decline. Four zoomed-in maps show areas with high settlement density – Arctic Fennoscandia, Iceland, the Faroe Islands, and Alaska. In Alaska, population increased in the largest settlements between 2000 and 2017. The population decline in small settlements located far from the two large cities – Anchorage and Fairbanks – has been caused by outmigration, which has cancelled out the positive natural population growth. In the Canadian Arctic, most people live in a few settlements. Similar to Alaska, the population increased in the largest settlements and decreased in small settlements. Most of the smaller settlements in Arctic Fennoscandia have witnessed a population decline between 2000 and 2017, except in Norway. The dominant pattern in Fennoscandia is a population growth in larger settlements and a population decline in surrounding smaller settlements. This is similar to the pattern observed in the other Nordic Arctic countries – Iceland, Greenland, and the Faroe Islands. New inhabitants settled in the capitals (Reykjavik, Nuuk, and Torshavn) and regional centres, from both domestic and international locations, while settlements in sparsely populated areas are becoming less attractive to incomers. In the Russian Arctic, the regions can be divided into the oil and gas areas of the Khanty-Mansi and Yamal-Nenets, and other areas. The population is growing in the oil and gas areas and declining slowly in the others. Over 75% of the settlements have been shrinking throughout the 21st century, mainly because…

The map shows the indigenous population as a share of the total population in the Arctic. Approximately one million people, or 9% of the total population in the Arctic is indigenous. Indigenous population reassembles more than 40 different ethnic groups. In terms of statistics there are no circumpolar definition of an indigenous person and therefore the number of indigenous people is based on different national definitions. Official statistics do not necessarily recognize indigenous populations separately. The indigenous population is the highest in the Canadian Arctic and in Greenland, weighing more than 75% of the total population. The Yukon, the southern part of Northern Quebec, and Labrador and Newfoundland (Canada) have the lowest shares of indigenous population. In the remaining part of the Arctic, indigenous peoples represent less than half of the total population, except in Sakha (Russian Federation), Southwest Region and Northern Region (Alaska, USA) where 50-75% of the population is indigenous. There are no indigenous people in Iceland, the Faroe Islands and Svalbard.

This map shows the country of origin of Foreign Direct Investment (FDI) in the Nordic regions between 2003 and 2016. The colours indicate different countries of origin of FDI inflow by number of projects between 2003 and 2016. FDI inflows examined by country of origin, reveal an interesting pattern in terms of intra-Nordic investment inflows, confirming the assumption that proximity, both in terms of geographical distance, and in terms of rules, regulation and business culture is an important driver of FDI. A breakdown at the regional level reveals that 55 out of the 74 Nordic regions received the largest number of FDI projects from a region located in another Nordic country. The largest share of these intra-Nordic flows originates from Sweden (35 regions in total), particularly in the manufacturing sector as well as the ICT sector in Norway. The largest share of FDI projects from Finland are attracted to Sweden’s highly competitive international manufacturing industry. Denmark is the main source country of FDI inflows in both Greenland (mostly in the transportation and storage and business services sectors) and the Faroe Islands (mostly manufacturing and finance and insurance activities sectors). Eighteen Nordic regions have their largest source country in terms of project located outside the Nordic Region, i.e. other European and extra-European countries. FDI inflows from other European countries are the highest in terms of projects in six Nordic regions, most of these regions can be characterised by their relative remoteness and strong industrial profile. Finally, two extra-European countries, namely the United States and Canada, are the largest source country in twelve Nordic regions, that are either capital city regions with a strong and diversified service sector or peripheral industrial regions.

The map shows the change in jobs (growth or decline) at municipal level over a period that can be attributed to local factors (e.g. local policies or local natural or institutional conditions) and is thus not due to national or industry trends. The map is based on shift-share analyses which can help answer why employment is growing or declining in a local or regional industry. This type of analysis can answer questions like: How much of local job growth can be attributed to expected national and sectoral trends and how much is due to local factors Is the local economy growing or declining? How does the community compare with other communities? What are the local strengths and weaknesses in providing jobs and in which sectors? What industries are doing well? What industries should be targeted? There are large differences between municipalities in terms of the change in employment due to local factors. For example some of the municipalities in Mid Jutland in Denmark show a high local employment effect while others in the North of Jutland do not. These differences can be due to access to markets, to industrial culture, to municipal or regional facilitation etc. In-depth research is needed in order to understand the reasons. The map does not show the total change in jobs.

This map shows the employment recovery from the financial crisis, with the employment rate (20-64 years) in European regions in 2016 related to the EU2020 goal of 75%, as well as the change in the employment rate between 2009 and 2016. The green colour indicates regions with employment rates above 75% and an increase in the employment rate between 2009 and 2016. The red colour indicates regions with employment rates below 75% and a decrease in the employment rate between 2009 and 2016. The yellow colour indicates regions with employment rates above 75% and a decrease in the employment rate between 2009 and 2016. The blue colour indicates regions with employment rates below 75% and a decrease in the employment rate between 2009 and 2016. The grey colour indicates regions with no data available. On a European scale, the effect of the financial crisis on employment became noticeable from 2009 onwards when average employment rates started to decline. This continued until 2013 when the average European employment rate reached its lowest level of 68.3% for the age group 20–64 years. After 2013 the employment rate started to rise again but it took until 2016 for the average European employment rate to reach and then surpass pre-crisis levels. In 2016 the average employment rate in the European union was 71%, edging closer to the EU2020 goal of 75%. In some regions, primarily in southern Europe, employment rates have still to recover to pre-crisis levels. This is particularly so for Greece, Spain, Italy and Portugal which were particularly hard hit by the debt crisis and thus had to undertake massive cuts across the public sector. On the other hand, some countries such as Germany, Austria and Switzerland saw rising employment rates even during the financial crisis. The differential nature of outcomes in…

This map shows the total value of Foreign Direct Investment (FDI) in million euros, and the intensity of the FDI in the Nordic regions between 2003 and 2016. The FDI intensity is an index of the value of FDI inflows divided by the gross regional product. The FDI intensity index allows comparing the performance of the Nordic regions in attracting FDI inflows by taking the size of the regional economy into account. A high intensity result reflects a more resilient regional economy, due to a diversity of investors. The brown shading indicates different FDI intensities in the regions between 2003 and 2016. The lighter the shade, the lower the FDI intensity. The grey colour indicates regions with no data. The circles indicate the total value of FDI in million euros (2016 value) in the regions between 2003 and 2016. The larger the circle, the greater the value. The colour in the circles indicate changes in the FDI total value between 2003 and 2016. The pink colour indicates regions with a decrease in the FDI value, the yellow colour indicates stable FDI values, and the blue colour indicates regions with an increase in the FDI value. Large capital city regions tend to be the main beneficiaries of FDI inflows and this pattern is also observed in the Nordic Region. Stockholm region emerges as the clear leader with a total deal value of EUR 110,000m. The Danish capital region attracted about half of Stockholm Region’s deal value – EUR 53,804m followed by Helsinki (EUR 45,000m), Skåne (EUR 30,000m), and Oslo (EUR 29,100m). The total deal value for Reykjavík is rather modest – at around EUR 2,000m, and is comparable to regions such as Dalarna and Jönköping (Sweden), Sør-Trøndelag (Norway) and Lappi (Finland). All Nordic regions have witnessed an increase in FDI inflows…