This chapter provides a diagnostic of the region of Upper Norrland in Sweden, its two TL3 regions, Västerbotten and Norrbotten, and its mining municipalities. By comparing with national trends and a benchmark of TL2 and TL3 OECD mining regions, the analysis identifies major trends, strengths and bottlenecks to development and diversification of the nature-based economy. The chapter begins with an overview of the main megatrends affecting regions specialised in mining and extractive activities. The second section sets up the scene and provides a profile of Upper Norrland, Västerbotten and Norrbotten. The third section analyses the demographic labour market trends across the regions. The fourth section describes the main economic trends and the relevance of mining in the regional economies. Finally, the chapter describes the enabling factors for development in Upper Norrland.
Mining Regions and Cities Case of Västerbotten and Norrbotten, Sweden
2. Strengths and challenges in the regional development of Västerbotten and Norrbotten
Abstract
Assessment and findings
Assessment
Upper Norrland is Sweden’s northernmost region and has the largest land area and lowest population density in the country (3.4 inhabitants per square kilometre). It is a key mining region at the national and European levels, concentrating 9 of the 12 active mines in Sweden and providing 90% of the iron ore production in Europe. Upper Norrland includes two Territorial Level 3 (TL3) regions (Västerbotten and Norrbotten). Amongst the two, Västerbotten is more densely populated (4.8) and hosts the largest city in the region (Umeå with 24% of Upper Norrland’s population). Norrbotten, in turn, has the largest land area in Upper Norrland (64%) and is the traditional mining region in the north, concentrating most of the active mines and relatively larger production volumes than in the rest of Sweden. Large Swedish companies dominate Upper Norrland’s mining ecosystem. In Norrbotten, the state-owned company LKAB is the main player, working closely with networks of local suppliers. In contrast, Västerbotten’s ecosystem is relatively more diverse, complemented by the presence of a number of junior mining companies and small- and medium-sized enterprises (SMEs). In both regions, the Swedish private company Boliden is highly active.
This chapter identifies some important findings for Upper Norrland and its TL3 regions by comparing them with the OECD mining regions:
Upper Norrland has the third-highest level of gross domestic product (GDP) per capita (USD 44 290) across the 8 TL2 regions in Sweden and surpasses the average of TL2 benchmark of mining regions (USD 42 087). Over the last 20 years, Upper Norrland has been closing the GDP-per-capita gap with the national average by 22% (from USD 5 097 in 2001 to USD 3 975 in 2017), mainly driven by a faster recovery after the financial crisis. During the post-crisis period (2010-17), the region registered the largest GDP per capita growth (3.0% annual average) across Swedish regions (average growth of 1.7%) and exceeded the average growth of the OECD TL2 mining regions (0.4%). This performance was mainly driven by Norrbotten, that experienced a peak growth right after the crisis (29% annual growth in 2009) following the rebound of international commodity prices. The region is dominated by industrial activities linked to natural resources (including energy and mining) and benefits from a higher share of tradeable activities than the national level. Yet, services represent just a small share of the tradeable sector, which can limit the gains from international trade as services tend to be linked with higher-value-added activities in global value chains (GVCs).
The region also benefits from high labour productivity due to its vibrant industrial sector. Labour productivity of the 2 TL3 regions, Västerbotten (USD 78 729 in 2015) and Norrbotten (USD 87 743) is higher than the comparable OECD TL3 mining regions (USD 78 557). Historically, Norrbotten’s labour productivity has been higher than in Västerbotten and after the crisis, the productivity gap among the regions doubled (from an average of USD 7 478 during 2000-07 to an average of USD 14 384 during 2009-15).
Upper Norrland also has a relatively lower unemployment rate (5.1%) than Sweden (6.9%) and the TL2 OECD mining regions (7.3%). Västerbotten, in turn, exhibits a lower unemployment rate (5.5% in 2019) than Norrbotten (6.0%) but the rate of both regions remains below the average of TL3 OECD mining regions (7.4%). In particular, the rural and mining municipalities have a lower unemployment rate than urban centres of the region, mainly associated with the high-income growth and the shrinking of the workforce.
Nevertheless, the high reliance on the mining sector has exposed Upper Norrland’ economy to external shocks. The GDP of Upper Norrland has experienced higher volatility (USD 3 640 standard deviation during 2001‑16) than the one of Sweden (USD 2 800) and the OECD TL2 mining regions (USD 2 185). At the TL3 level, Norrbotten has proven to be a more volatile economy (USD 4 963 standard deviation) than Västerbotten (USD 2 600), experiencing a more severe drop during the crisis and then a faster recovery. Such vulnerability to external shocks is associated with greater specialisation in mining activities than Västerbotten. Furthermore, the high reliance on mining activities and the low unemployment rate has hampered the creation of new businesses in the region. While the absolute growth of companies in Upper Norrland is positive, the rate of creation of new businesses is lower than in the rest of the country, with the size of companies in term of employees getting smaller. Reducing the reliance on mining and the consequent volatility of its economy should be of interest to the entire Upper Norrland region in order to ensure sustainable and sustained growth.
Despite the rapid economic growth, Upper Norrland has faced a high shrinking of its workforce (from a share of 64.2% of the total population in 2001 to 61% in 2019). Between 2000 and 2019, population growth in Upper Norrland (1.7%) was far below the growth rates of Sweden (15.2%) and the TL2 benchmark of mining regions (17.5%). This phenomenon is driven by a high rate of outmigration, especially from young women. The net amount of people leaving Upper Norrland (7.5% of its population between 2001 and 2018) is the highest across all Swedish regions (2.4%) and above the level experienced by the TL2 benchmark of mining regions (2.6%). The population decline in Norrbotten (-2.9%) explains most of the negative demographic trend in the region, which contrasts with the positive trend in Västerbotten (3.6%) and the benchmark of TL3 mining regions (19.4%). International migration has helped mitigate the population decline but the region still needs to accelerate the intake of foreign people.
Alongside outmigration, the elderly dependency ratio of Upper Norrland (36.6% in 2019) has increased almost twice as fast as Sweden as a whole (9.2 percentage points vs 5.2 percentage points between 2001‑19), reaching levels above the national average (31.9%) and the OECD TL2 mining regions (20.5%). At the TL3 level, Norrbotten is experiencing higher outmigration and population ageing than in Västerbotten and the benchmark of TL3 mining regions. Within the region, mining municipalities are the most affected by population decline (-3.8% in average between 2000-19), which contrasts with the population growth of the regional urban centres (17.5%), driven mainly by rural-urban outmigration of the young population.
Upper Norrland has a number of assets to support new growth opportunities. The region has a relatively high-educated workforce, an innovative environment and high standards of public services. The share of the labour force with tertiary educational attainment in Upper Norrland has risen from 30.1% in 2010 to 35.7% in 2017, reaching a higher level than the average of TL2 OECD mining regions (34.5%). The large coverage of quality broadband has also allowed the sparse population to access health and education services. Overall, the share of households connected to broadband in Upper Norrland (99% in 2019) is above the average of European (98% on average in 2019) and OECD TL2 mining regions (70% on average in 2017). The region also stands out across OECD TL2 regions and OECD TL2 mining regions thanks to its high environmental quality, security rate and level of the population engaged in politics.
The 2020 coronavirus pandemic is causing a global slowdown with containment measures, halting economic activity and mobility. As was the case during the 2009 global financial crisis, rural economies are particularly vulnerable to the crisis due to their less diversified economic base, a greater dependency to fluctuations in external demand and a shrinking workforce. The effects of the slowdown in Upper Norrland were amplified given its specialisation in the mining industry – a sector hardly hit by the drop of global demand from the manufacturing and construction sectors. The challenges facing Upper Norrland in this new crisis are being to demonstrate its resilience in the face of the slowdown, retain the young population and high-skilled workers and attract the skilled migrants while adapting its labour force to new ways of working through technological changes. Specific measures are needed to ensure that the potential of the innovative mining sector in the Upper Norrland region is harnessed and that diversification efforts are deepened to sustain economic growth in the medium and long term.
Introduction
This chapter provides a diagnosis of Upper Norrland, Sweden, and its two Territorial Level 3 (TL3) regions Västerbotten and Norrbotten, by comparing with national trends and a benchmark of TL2 and TL3 OECD mining regions. This analysis identifies major trends, strengths and bottlenecks to development and diversification of their nature-based economy. The chapter begins with an overview of the main megatrends affecting regions specialised in mining and extractive activities. The second section sets the scene and provides a profile of Upper Norrland, Västerbotten and Norrbotten. The third section analyses the demographic labour market trends across the regions. The fourth section describes the main economic trends and relevance of mining in the regional economies. Finally, the chapter describes the enabling factors for development and the quality of life in Upper Norrland.
To better understand the current context in the mining regions, the analysis presented in this section adopts the OECD regional framework to selected OECD regions specialised in mining. The aim is to identify trends specific to mining regions and investigate how outcomes in different dimensions have evolved over time. The regional classification (TL2 and TL3 level) follows the new OECD territorial classification (Box 2.1).
The analysis first identifies 40 OECD TL2 regions specialised in mining. To identify these comparable regions specialised in mining, two methods are applied. As a first step, OECD TL2 regions are selected according to their sectoral employment share in the industry and location quotient (the ratio of the regional share in industry – excluding manufacturing – to the national share). Only regions with a location quotient higher than 1.9 are selected. A value above 1 in the location quotient implies that the region is more specialised in that sector than the rest of the economy. As a second step, desk research was undertaken to identify the regions with a specialisation in industry (mining, energy and water) that currently have mining activities. Annex 2.A provides a full list of elected OECD TL2 mining regions.
However, the analysis at the TL2 level needs a more local approach. Therefore, a second benchmark was built at the TL3 level. It aims to analyse the performance of the TL3 regions of Upper Norrland, Västerbotten and Norrbotten, against national trends and other OECD TL3 regions specialised in mining and extractive activities. The analysis identifies 11 OECD TL3 regions with similar characteristics to Västerbotten and Norrbotten according to two aspects: the degree of rurality and the share of industrial activities linked to natural resources. The selection of the TL3 benchmark of mining regions follows three criteria:
Each TL3 rural remote region in the European Union (EU) was ranked according to its sectoral share in industry and location quotient (the ratio of the regional share in industry to the national share).
Regions with comparable population size to Västerbotten and Norrbotten were selected.
Desktop research was carried out to identify the regions with a similar level of specialisation and population size with current mining activities and/or legacy of mining.
Based on the procedure, the following 14 regions were selected for comparison to Västerbotten and Norrbotten:
1. Karlovy Vary (Czech Republic)
2. Oder-Spree, 3. Celle, 4. Görtlitz, 5. Anhalt-Bitterfeld and 6. Saaleskreis (Germany)
7. Carbonia-Iglesias (Italy)
8. Noord-Drenthe, 9. Overig Zeeland and 10. Zuidoost-Drenthe (Netherlands)
11. Rogaland (Norway)
12. León (Spain)
13. Kalymnos, Karpathos, Kos, Rhodes and 14. Heraklion (Greece).
Box 2.1. OECD TL3 revised typology
The OECD regional database collects and publishes regional data at two different geographical levels, namely large regions (Territorial Level 2, TL2) and small regions (Territorial Level 3, TL3). Both levels encompass entire national territories. With some exceptions, TL2 regions represent the first administrative tier of sub-national government (i.e. states in the United States, estados in Mexico, or régions in France). TL3 regions are smaller territorial units that make up each TL2 region.
The OECD has adopted a new typology to classify administrative TL3 – Territorial Level 3 - regions. This classification allows measuring socio-economic differences between regions, across and within countries. It is based on the presence and access to functional urban areas (FUAs), a concept defining cities and the urban hinterland, in other words, urban economic agglomerations.
By controlling for these regional characteristics, the typology classifies TL3 regions into two groups, metropolitan and non-metropolitan regions. Within these two groups, five different types of TL3 regions are identified. Metropolitan regions (MRs) adopt 50% of the population of the TL3 (small) region living in an FUA of at least 250 000 people as a threshold; non-metropolitan regions (NMRs) use 60‑minutes’ driving time as a threshold, a measure of access to a FUA.
The methodology follows the criteria below:
Metropolitan TL3 region, if more than 50% of its population live in a FUA of at least 250 000 inhabitants. MRs are further classified into:
Large metropolitan TL3 region, if more than 50% of its population live in a FUA of at least 1.5 million inhabitants.
Metropolitan TL3 region, if the TL3 region is not a large metropolitan region and 50% of its population live in an FUA of at least 250 000 inhabitants.
Non-metropolitan TL3 region, if less than 50% of its population live in a FUA. NMRs are further classified according to their level of access to FUAs of different sizes into:
With access to (near) a metro TL3 region (NMR-M), if more than 50% of its population lives within a 60-minute drive from a metropolitan area (a FUA with more than 250 000 people); or if the TL3 region contains more than 80% of the area of a FUA of at least 250 000 inhabitants.
With access to (near) a small/medium city TL3 region (NMR-S), if the TL3 region does not have access to a metropolitan area. Fifty percent of its population has access to a small or medium city (a FUA of more than 50 000 and less than 250 000 inhabitants) within a 60‑minute drive; or if the TL3 region contains more than 80% of the area of a small or medium city.
Remote TL3 region, if the TL3 region is not classified as NMR-M or NMR-S, i.e. if 50% of its population does not have access to any FUA within a 60-minute drive.
The described procedure leads to more statistical consistency and interpretable categories that emphasise urban-rural linkages and the role of market access.
Megatrends affecting regions specialised in mining and extractive activities
A number of megatrends have the potential to alter the future development of mining regions. Global megatrends including demographic change, climate change and the transition to a low-carbon economy as well as digitalisation and automation modify the way people live and consume and, consequently, how industries produce. As mining industries need to adapt to change, so do the regions where extraction is taking place. In light of these megatrends, the geographically concentrated nature of mining, as well as the usually high economic specialisation within mining regions, poses particular challenges and opportunities for prosperity and well-being in mining regions. For instance, regions specialised in hydrocarbons will face the challenge of transition and diversification towards a climate-neutral economy, while others might experience growth from the increased demand for materials needed to produce sustainable energy. Furthermore, regional mechanisms to retain attract and upskills workers will need to be adjusted in light of digitalisation and automation in the mining industry. This section outlines the key opportunities and challenges mining regions face concerning three global megatrends: demographic, climate change as well as technological shift and automation.
Mining regions will likely face a shrinking labour force
Demographic trends are increasingly changing the labour market structure in rural regions. In developed counties, mining is largely concentrated in rural and remote regions, far from large cities (OECD, 2017[1]; Moritz et al., 2017[2]). These regions face a relatively high degree of outmigration and ageing population compared to urban regions (OECD, forthcoming[3]). In most OECD countries, populations have increasingly concentrated in large cities, driven by younger people seeking education and job opportunities (OECD, 2019[4]). The trend in mining regions is exacerbated by the outmigration of women, who tend to leave because of the lack of equal employment opportunities in the mining industry (Abrahamsson, 2006[5]). These structural changes have led to a shrinking labour force in rural and mining municipalities, which pose challenges in terms of meeting the industrial demand for labour, delivering quality services and sustaining local fiscal revenues. Consequently, attracting people and retaining them in the long-term –especially women – is a key challenge for many mining regions. Enhancing regional attractiveness requires an integrated approach that goes beyond economic incentives such as high salaries and job security and includes connectivity, safety, cultural vitality, quality of goods and services as well as social networks.
On the upside, increased agglomeration around cities will boost the demand for minerals and materials from construction. Especially cities in Africa and China are expanding rapidly and demanding an increasing amount of materials such as coal, copper and steel, both for construction and consumption (OECD, 2019[4]). This will maintain the demand for minerals and opportunities for income flow into mining regions. Increased urbanisation will also require more sustainable ways of living to reduce the large carbon footprint of cities. Many of the needed technologies (i.e. electric batteries, solar panels) as well as low-carbon infrastructure (i.e. intelligent buildings, zero-carbon transport systems) require rare metals and minerals (i.e. cobalt, lithium). These rare minerals can be extracted using unexploited deposits as well as the use of new technology that enable sourcing materials from waste or recycling them (Chapter 3).
Mining regions need to prepare for a transition to a low-carbon economy
Increased impacts of climate change have led governments to accelerate the transition towards a low or even zero-carbon economy (UNFCC, 2015[6]). The transition requires increasing energy supply from renewable sources and the development of materials and technologies that reduce carbon emissions. Such transition represents important opportunities and challenges for mining regions. Phasing out of hydrocarbons (coal, oil and gas) as a power source is key to advance in energy transition objectives. Carbon intensive mining is often important for employers in regions with low economic diversity. The phasing out can thus threaten local livelihoods and prosperity in these regions. On the upside, the development of renewable energy and green technologies requires an increasing amount of traditional (iron, copper) and rare (lithium, cobalt) minerals (Olsson, Rasmus and Larsen, 2019[7]). This is an opportunity to grow for mining regions and will provide opportunities to promote innovation and create new economic opportunities from sustainable resource use.
Mining operations also have environmental impacts and contribute to greenhouse emissions. The extraction and primary processing of metals accounts for 26% of global carbon emissions (UNEP, 2019[8]). In light of growing demand for minerals and metals – the world consumption of raw materials is set to double by 2060 –, the extractive industry is required to contribute to the mitigation of climate change and become more sustainable. Many companies address this by investing in electrified vehicles, reducing CO2 emissions throughout their value chains and increasing recycling. The circular economy, for instance, will present new business opportunities and productivity improvements in mining by linking production processes. This way, the value of products, materials and resources is maintained for as long as possible and waste is significantly reduced or even eliminated (OECD, 2019[4]). Further, there is an increasing demand from certain parts of the civil society to conserve the current stocks of natural capital and preserve the landscape (Olsson, Rasmus and Larsen, 2019[7]). This requires an improved process for social engagement and license to operate for existing mines and new mining projects.
Technological change and digitalisation will open new opportunities for mining regions
Technological change and digitalisation can further reduce the cost of moving people and goods and delivering services. They can help rural areas to address demographic shifts by promoting innovative ways to provide public services (e-Health, e-Education) and work (teleworking, meetings through augmented reality) (OECD, forthcoming[3]). Automation also brings positive and negative disruptive effects on local economies. On the upside, automation offers a path to revive productivity growth by creating new jobs and allocating low-skills workers to new sectors (Autor and Dorn, 2013[9]). On the downside, automation can lead to large-scale job losses and high unemployment (Cosbey et al., 2016[10]). Overall, the effect of new technologies on the local labour markets will very much depend on the readiness and adaptability of regional policies (see Chapter 3).
Technological progress can make mines more productive and environmentally friendly while offering new work opportunities to the local workers. The transition to a future digital mine will change core-mining processes and will encompass the automation of physical operations and digitalising assets. Autonomous vehicles, drones, GPS (global positional system) and wearable technologies, can operate through a connected network that uses the Internet of Things (IoT), allowing part of the mining operators to work primarily from above ground or distant centralised control centres (OECD, forthcoming[3]). Yet, a share of tasks will still need human service around the core production, including asset maintenance or logistics services. Hence, automation will lead to the creation of new types of jobs, for example in the development and monitoring of remotely controlled autonomous equipment and in data processing. These new tasks have the scope to offer higher income and quality of life to mining workers as well as involve a larger share of women in mining activities. At the same time, they will demand different skills and up-to-date training to manage technological changes. However, automation is likely to threaten the number of operational jobs in mining. Occupations with a high share of repetitive tasks in mining face the highest risks of job automation. These areas include drilling, blasting and train and truck driving, and typically constitute over 70% of employment in mines (Cosbey et al., 2016[10]).
Upper Norrland is likely to be affected by these megatrends. As this chapter and the rest of the review will show, some of the structural challenges underlying demographic changes, pressures to transition to zero-carbon economy and effects from technological progress are already occurring within the mining ecosystems of Västerbotten and Norrbotten. Ultimately, Chapters 3 and 4 will stress that the type of impact from the megatrends on mining municipalities will very much depend on the policies in place to address the changes and prepare local businesses and communities for future changes.
Table 2.1. Opportunities and challenges of megatrends for the mining industry and regions
Upper Norrland, the mining region of Sweden
Geography and climate shape a low-density settlement structure
Upper Norrland is the northernmost region of Sweden and the largest region by land area. It borders Finland, Norway and Middle Norrland. It includes two TL3 regions, Västerbotten and Norrbotten. The TL3 region of Västerbotten is 1 of the 21 administrative regions that constitute Sweden. It shares the counties of Jämtlands, Norrbotten and Västernorrlands.
Västerbotten is home to 268 465 inhabitants, making it the biggest region of Upper Norrland. Its population is spread out in 15 municipalities, including the capital of the TL3 region Umeå (84 761 inhabitants), which is the largest city in Upper Norrland and ranks as the 13th largest city in Sweden. Norrbotten, on the other hand, is the northernmost TL3 region in Sweden. It is also the largest region of Upper Norrland in terms of land area (64% of Upper Norrland’s area). It shares a regional border with Västerbotten and a frontier with Finland and Norway. There are 14 municipalities within Norrbotten and its main city is Luleå with 77 832 inhabitants. Consistent with the OECD regional typology, Västerbotten and Norrbotten are classified as remote TL3 region.
Upper Norrland has the smallest share of built-up land area in Sweden. Upper Norrland is Sweden’s largest heathland and herb meadow region. In particular, Norrbotten is the TL3 region with the largest land area dedicated to heathland and herb meadow (19% of total land area) and the smallest built-up area (including housing and industry, 0.7%) in the country (Figure 2.2). A similar effect occurs in Västerbotten. It is the third lowest TL3 region in terms of build-up area (1.3%), with forest covering most of its territory (73%). It represents a great environmental asset and an important economic sector in the region.
Figure 2.1. Västerbotten, Norrbotten and mining municipalities (selected)
Figure 2.2. Land use in Sweden’s TL3 regions, 2018
Note: Total forest includes productive and non-productive forest. Others include arable and grazing land, land used for golf courses and ski runs, bare rock and other land, and open mine.
Source:Statistics Sweden (2019[11]), Statistical Database, http://www.statistikdatabasen.scb.se/pxweb/en/ssd/START__BE__BE0101__BE0101A/?rxid=3a012fe9-414f-47c2-8b84-25feb829e48d (accessed on 5 June 2019).
Upper Norrland has five local labour markets (LLMs) that represent an economic enclave within the region (Jokinen et al., 2020[12]). Identifying the LLMs is important to understand the labour dynamics and the centres of economic activity in a region (Box 2.2). LLMs contain at least two contiguous municipalities where there is a significant degree of commuting across municipal borders and a central municipality where most workers of the LLM commute daily to work. Västerbotten has three of Upper Norrland’s LLMs, with Lycksele, Skellefteå and Umeå as central municipalities for each of them (Table 2.2). As the biggest city in the region, Umeå is the centre of the largest LLM in terms of population in Upper Norrland (127 119 inhabitants in 2018). In Norrbotten, there are two LLMs with Kiruna and Luleå as the main centres. Some municipalities form self-contained or independent LLMs, which are characterised by single municipalities that have a particularly strong – location-specific – advantage that offsets its high degree of geographic isolation or/and limits opportunities for commuting. Gällivare in Norrbotten is one example of a self-contained LLM with most of its inhabitants working in the same municipality and relatively low daily commuting from other areas.
Table 2.2. LLMs and municipalities in Upper Norrland
Source: Jokinen, J. et al. (2020[12]), State of the Nordic Region 2020, http://dx.doi.org/10.6027/no2020-001.
Box 2.2. Local labour markets in Northern Sparsely Populated Areas
LLMs are relevant units of analysis for sparsely populated areas as Upper Norrland, given that they offer the best opportunity for additional economic growth and demographic stability. This does not mean that municipalities that are not integrated into an LLM should be ignored, nor that economic growth takes place in all current LLMs, but that the LLMs offer the best opportunity to understand how and where economic progress is currently taking place in the Northern Sparsely Populated Areas (NSPA). Special characteristics of LLMs are:
LLMs correspond to where economic activity is concentrated because the size of an LLM is related to the size of the local economy.
The size of the LLM is a rough proxy for demographic sustainability as larger LLMs are associated with in-migration, while self-contained LLMs are associated with demographic decline.
LLMs correspond to a local economy since they capture both the aggregate local demand for labour that comes from a particular set of employment opportunities and the available local supply of labour that consists of workers who are prepared to travel for work.
LLMs for the NSPA regions were built by fulfilling at least the following criteria:
Municipalities belonging to an LLM should have a single out-commuting flow to another municipality that is more than 7.5% of its employed population. The central municipality in the LLM is determined by having more internal employment than commuting employees and an out-commuting rate of less than 20% of the employed population.
In the case where a municipality has less than the threshold level of out-commuting, it is described as a self-contained LLM.
Source: Jokinen, J. et al. (2020[12]), State of the Nordic Region 2020, http://dx.doi.org/10.6027/no2020-001; Freshwater, D., A. Simms and J. Ward (2014[13]), “LLMs as a new way of organizing policies for stronger regional development in Atlantic, Canada”.
Northern Sweden is one of the most mineralised areas in Europe
Mining is a relevant sector for the national economy and Upper Norrland is the region with the largest mining production and number of mines in the country. The mining sector represents 4.2% of the national gross value added (GVA). Upper Norrland concentrates 9 of the 12 active mines in Sweden, focused mainly on metal extraction including, copper, iron ore and gold. Mining in Upper Norrland represents 19% of its regional GDP, ranking as the second TL2 Swedish region with the highest share of mining in the regional GDP. As a share of the national economy, Upper Norrland represents 4.8% of Sweden’s GDP (2018).
Figure 2.3. GDP share of mining, quarrying and manufacturing over total GDP, 2017
Note: GDP current prices, million SEK by region calculated as a percentage.
Source: Statistics Sweden (2019[11]), Statistical Database, http://www.statistikdatabasen.scb.se/pxweb/en/ssd/START__BE__BE0101__BE0101A/?rxid=3a012fe9-414f-47c2-8b84-25feb829e48d (accessed on 5 June 2019).
At the TL3 level, Norrbotten is the largest region in mining production (Figure 2.3). The TL3 region has five of the active mines in Sweden, focusing its mining extraction on copper and iron ore. Norrbotten has all the iron ore mines of Sweden and the largest underground iron ore mine in the world (in Kiruna municipality). The region has also Europe’s largest copper mine, Sweden’s largest gold mine (Aitik in Gällivare) and iron ore open-pit operations in Kiruna, Pajala and Svappavaara.
The case of Västerbotten has many similarities, as the backbone of the regional economy has been mining, forestry and energy. Its capital, Umeå, has emerged as a port to trade timber from the interior and goods from Lapland. Västerbotten has a large mining industry, which includes the extraction and processing facilities of gold, copper and zinc from its four active mines.
Figure 2.4. Value of annual production in SEK millions by TL3 region, 2018
Note: Aggregate is the name for gravel, sand and crushed bedrock. Aggregates are used in concrete and asphalt as a filler and as railway track ballast, among other things.
Source: Geological Survey of Sweden (2018[14]), Fact about Minerals & Metals 2018, https://www.sgu.se/globalassets/mineralnaring/facts-about-minerals-and-metals-2018.pdf.
Within these regions, mining is mainly concentrated in rural municipalities. The municipalities with the most mining activity in Norrbotten are Gällivar, Kiruna and Pajala, between three- and four-hours’ drive by car from Luleå respectively. Luleå is a key player for the mining value chain of Norrbotten by hosting one of LKAB’s harbours and the processing facilities for iron and steelmaking of the manufacturing company SSAB, earlier called Svenskt Stål AB. In Västerbotten, the main mining municipalities are Lycksele, Malå and Skellefteå, which are relatively closer to the regional urban centre, at less than two hours ride to Umeå. This chapter includes analysis on the performance of Upper Norrland’s mining municipalities in comparison with the main urban centres of the region, Luleå and Umeå. The chapter will take Kiruna as a proxy of the dynamics in Gällivare due to the similar number of inhabitants in these municipalities. Jokkmokk in Norrbotten has been included in the analysis as this municipality has experienced an important interest in mining exploration in recent years (Chapter 4). Table 2.3 describes the main municipalities that will be analysed in this chapter.
Table 2.3. Cities and mining municipalities selected in Upper Norrland, 2018
Note: Number of inhabitants in 2018.
Source: Statistics Sweden (2019[11]), Statistical Database, http://www.statistikdatabasen.scb.se/pxweb/en/ssd/START__BE__BE0101__BE0101A/?rxid=3a012fe9-414f-47c2-8b84-25feb829e48d (accessed on 5 June 2019).
At the TL3 level, Norrbotten is particularly focused on mining and forestry. Mining is vital to the economic performance of the region and accounts for 90% of the iron ore production of Europe, owning all the iron ore mines of Sweden. Production in 2018 from Kiruna, Malmberget and Svappavaara amounted to 26.9 million tonnes, while Boliden Aitik 2019 produced 38.4 million tonnes. The case of Västerbotten has many similarities; the backbone of the regional economy has been mining, forestry and energy. The city emerged as a port to trade timber from the interior and goods from Lapland. The region has a large mining industry, which includes the extraction and processing of gold, copper and zinc.
Settlements patterns have low density and are shrinking
Inhabitants and population density
Upper Norrland has the lowest population density in Sweden. In 2018, the region of Upper Norrland was home to 519 760 people (Table 2.4), which represents 5.1% of the national population. Measured by population, Upper Norrland is the second smallest region in the country but it is the largest region in Sweden in terms of land area, covering more than one-third of Sweden’s land area (37%, 151 929 square kilometres). Upper Norrland’s population density is 3.4 inhabitants per square kilometre, far below the national average of 24.54 inhabitants per square kilometre.
Despite the low density, Upper Norrland’s demographic patterns, as in Sweden, are relatively more concentrated in comparison to other OECD regions. According to the geographic concentration index applied to all OECD TL3 regions,1 Sweden records one of the highest concentrations of population in the OECD, just below Portugal (OECD, 2010[15]). In Upper Norrland, four municipalities (Luleå, Piteå, Skellefteå and Umeå) cover 16.0% of total land area, concentrating 60% of the population.
At the TL3 level, Västerbotten hosted 268 465 inhabitants in 2018, which represent approximately 51% of Upper Norrland’s population and 2.7% of the Swedish population. In the past decade, the population grew at an average annual rate of 0.32% compared to the national average of 0.93%. The same year, the population density of Västerbotten was 4.86 inhabitants per square kilometre, higher than the figure for Upper Norrland (3.4).
The population of Norrbotten was around 251 295 inhabitants in 2018, accounting for approximately 48.4% of Upper Norrland’s population and 2.5% of the Swedish population. The share of the female population (48.8%) is slightly higher than in Västerbotten (48.0%) (Statistics Sweden, 2019[11]). There are 14 municipalities within Norrbotten whose population size range from 76 088 in Luleå to 2 877 in Arjeplog. Its population density is 2.6 inhabitants per square kilometre, which is relatively low compared to the regional and national figure (3.4 and 24.2 respectively). In the past decade, the population experienced a decline (-0.052% annual rate) in contrast with the growth at the national average (0.93%).
Table 2.4. Population by region, capital and municipality, 2018
Source: Statistics Sweden (2019[11]), Statistical Database, http://www.statistikdatabasen.scb.se/pxweb/en/ssd/START__BE__BE0101__BE0101A/?rxid=3a012fe9-414f-47c2-8b84-25feb829e48d (accessed on 5 June 2019).
The population of Upper Norrland is shrinking
The population growth in Upper Norrland has been significantly slower than in Sweden and the benchmark TL2 regions. Between 2000 and 2019, the population in Upper Norrland grew 1.7%, which contrast with the population growth rate in Sweden (15.2%) and benchmark TL2 regions (17.5%) during the same period (Figure 2.5).
Within Upper Norrland, the population trend varies across the TL3 regions. While the population in Västerbotten has increased steadily, reaching a total increase of 3.6% between 2000 and 2017, the population in Norrbotten decreased by 2.9% during the same period. The population growth in both TL3 regions has been far below the growth in the TL2 benchmark mining regions (19%) (Figure 2.5). The population growth in Västerbotten has being supported by inflow migration, mainly into the regional capital Umeå (see next section). Within Västerbotten, the population is concentrated in cities, while rural areas face population declines. Between 1990 and 2017, the regional centre of Umeå has increased its share in the region’s population from 36% to 46%, while the population share of the 8 inland municipalities of Västerbotten has experienced a decline from 21% to 15%.
In Norrbotten, the population has been decreasing since 1990. The region experienced a total population drop of 5% between 1990 and 2017. During this period, only the 2 main cities, Piteå (5.2%) and Luleå (13.7%) have experienced a net population growth, which resulted in a higher population density in these areas. All of the other 12 municipalities, mostly rural areas, have faced a population drop. Between 2000 and 2017, the population decline has varied between the least affected municipalities that experienced one single drop including Boden (-2.1%) and Kiruna (-5.4%), to municipalities that have lost more than one-fifth of their population, Överkalix (-21.5%) and Övertorneå (-21.7%).
Figure 2.5. Population growth rate, 2001-18
Note: 2001 = 100.
Source: OECD (n.d.[16]), “Regional Demography”, http://dx.doi.org/10.1787/a8f15243-en (accessed 27 January 2019).
Mining municipalities face a greater population decline than the regional average (Figure 2.6). In terms of gender, there is one constant in all mining municipalities: overrepresentation in favour of men over the total number of young people under 25. On average, across all Upper Norrland municipalities, young women represent 13.2% of the total population, below the proportion of males (14.5%), with one exception, Umeå, where the gender gap in the young population is almost non-existent.
Between 2000 and 2019, the main mining municipalities in Upper Norrland experienced an average population decline rate of 13.8% (Figure 2.6). In some municipalities such as Pajala, this population has fallen by 19% in this period. This contrasts with the performance of the main cities of the region, Luleå and Umeå, whose population increased by about 0.5% during the same period.
Figure 2.6. Population growth in cities and mining municipalities, 2000‑19
Note: 2000=100.
Source: Statistics Sweden (2019[11]), Statistical Database, http://www.statistikdatabasen.scb.se/pxweb/en/ssd/START__BE__BE0101__BE0101A/?rxid=3a012fe9-414f-47c2-8b84-25feb829e48d (accessed on 5 June 2019).
In summary
Upper Norrland is situated in the north of Sweden and is the largest region in the country. Its population is decreasing year by year, at a faster pace than in Sweden and the benchmark of TL2 mining regions. The negative demographic trend in Upper Norrland is mainly explained by the population decline in Norrbotten (-3%) – especially women – that contrasts with the positive trend in Västerbotten (4%) and the benchmark of TL3 mining regions (19%). This effect is further aggravated when we look at the mining municipalities, where the rural exodus is a tangible reality; the big cities such as Luleå and Umeå are receiving a large part of the population that migrates, especially at working age.
Economically speaking, its activity revolves around its five LLMs, located in the regional capitals of Luleå and Umeå, and around the specialised mining municipalities of Gällivare, Kiruna, Pajala and Skellefteå. Its economic activity is based on extractive and mining activities, concentrating 9 of the 12 active mines in Sweden and providing much of the income for the local population.
Upper Norrland faces outmigration of young population
Upper Norrland has been the largest net emitter of migrants to other regions in Sweden, mainly of persons below 30 years old. Between 2001 and 2018, inward migration to Upper Norrland (persons coming from other Swedish regions) was 159 660 individuals, while outward migration (people leaving for other regions of Sweden) was 198 386, for a net stock of 38 726 people leaving the region, or 7.5% of the total population (Figure 2.7). Of the people leaving Upper Norrland, 60% are aged between 15 and 29 years old. While the phenomenon of negative net migration is common across OECD rural regions (OECD, forthcoming[3]), the net amount of people leaving Upper Norrland is the highest across all Swedish regions (followed by Central Norrland with 7% of its population) and above the level experienced by the TL2 region benchmark region (2.6% of the population during 2001 and 2017).
At the TL3 level, during the last 20 years, Västerbotten and Norrbotten have been also net emitters of migrants to other Swedish regions (Figure 2.7). However, the trend in Västerbotten has improved in recent years, getting closer to a balance between inward and outward migration. In 2019, this region received 1 204 new residents from other Swedish regions. This performance is better than in the TL3 benchmark regions and in Norrbotten, where net migration from these regions has implied increasing population loss in recent years.
The trend in regional youth migration (under 25-year-olds) is uneven across regions. Between 2000 and 2018, both regions accumulated a negative balance of young people outmigrating to other regions in Sweden. The numbers in Västerbotten (-4 725 people) are substantially lower than Norrbotten (-14 488). However, recent data shows significant trend changes. While in 2018, Västerbotten achieved a positive balance (+15 people) in young people, Norrbotten still experienced outmigration from the region (-1 254 in 2018). A more diversified economy, together with increased attractiveness from prestigious university centres, has made it possible to offer environments that are more prosperous for young people in Västerbotten.
Figure 2.7. Ratio of net migration to the total population, 2000‑18
Source: OECD (n.d.[16]), “Regional Demography”, http://dx.doi.org/10.1787/a8f15243-en (accessed 27 January 2019).
International migration is an important factor to mitigate the regional outmigration in Upper Norrland. Since 2000, both TL3 regions of Upper Norrland have shown a positive trend of the foreign-born population. However, the inflow pace of population is below the need of the region, with a share of the foreign-born population (12%) that is still far lower than the Swedish average (19.8%). From 2001 to 2017, Västerbotten experienced an important growth of international migration (29%), almost twice the growth in Norrbotten (14%).
In 2019, the foreign-born population of Västerbotten represents 10.8% of the total population, equally distributed by gender. During the same year, this figure was positively reinforced by a positive influx of 2 376 international migrants, 35% significantly above other regions of Sweden. In the same year, the foreign-born population in Norrbotten represented 11.8% of the total population, with 1 599 more women than men. In 2019, the region received 2 164 international migrants (slightly lower than Västerbotten), mainly young people 15-35 years old, which helped compensate the outflow of people from Norrbotten to other regions. The share of foreign-born women on Norrbotten’s population is 0.8 perceptual points more than in Västerbotten (Figure 2.8).
Figure 2.8. Foreign-born population, ratio, 2000‑19
Note: Calculated as the ratio between Swedish and foreign-born population.
Source: Statistics Sweden (2019[11]), Statistical Database, http://www.statistikdatabasen.scb.se/pxweb/en/ssd/START__BE__BE0101__BE0101A/?rxid=3a012fe9-414f-47c2-8b84-25feb829e48d (accessed on 5 June 2019).
Despite the positive trend of international migration to Upper Norrland, the influx of new people was threatened by the COVID-19 crisis posing an uncertain outlook in the medium term. In the early stages of the health crisis, countries adopted policies to restrict the mobility of their citizens. This implied a drastic contraction in the movements of individuals between countries, with a consequent impact on the migration flows of all countries in the world.
One of the great challenges for the region is to increase its fertility rate. Västerbotten (1.67) and Norrbotten (1.71) is below the minimum fertility value (2) needed to maintain a natural year-to-year replacement. In 2019, Västerbotten had 2 934 births, while it lost population by death in 2 622 individuals, maintaining a positive balance as in the last 15 years. In a different way, Norrbotten lost 2 840 people in the same year, only replaced by 2 457 births, not being able to staunch the negative trend of the last decade (7 853 individuals accumulated since 2000).
In summary
As in many rural areas, Upper Norrland has difficulty retaining its population, especially young people. In fact, Upper Norrland is the largest emitter of migrants to other regions in Sweden, mainly of persons below 30 years old. International migration has helped mitigate the population decline but the region needs to accelerate the intake of foreign skilled people. Upper Norrland’s share of the foreign-born population is half the level in Sweden, highlighting the region’s difficulty in attracting and retaining newcomers.
However, the net migration trend in Västerbotten has improved in recent years, with a current positive balance, in comparison with Norrbotten and the trend of TL3 benchmark mining regions. However, the coronavirus crisis has particularly affected international immigration, which may imply a lower trend of migration inflows to Upper Norrland, like other regions, over the short and medium terms. In the aftermath of the crisis, this trend can change and a shift of society and policy preferences towards greater use of remote and virtual working can favour inflows of workers to remote rural regions, associated with longer stay for tourists combining work and leisure or an increase in nomadic workers.
Ageing is an increasing trend in Upper Norrland
The stagnation of population has led to a change in the age structure in Upper Norrland. Between 2001 and 2017, the elderly dependency ratio (the share of population above 65 years old over the working-age population) in Upper Norrland has increased from 27.4% to 36.6% (9.2 percentage points), above the increase in Sweden (from 26.7% to 31.6% - 5.2 percentage points). In 2019, the elderly dependency ratio of Upper Norrland, as for Sweden, is far above the ratio of the TL2 benchmark regions (20.5%) (Figure 2.9). In other words, while the average age of the population in Sweden has increased by 1 year (40 to 41 years old) over the last 20 years, in Upper Norrland, this ageing has occurred twice as fast, with an average age increase of 2 years (40-42 years old) during the same period.
Within Upper Norrland, the population of Norrbotten is ageing faster than in Västerbotten. The elderly dependency ratio in Norrbotten (39.5% in 2019) is 6 perceptual points over Västerbotten and 7.5 over the national ratio (Figure 2.9). Between 2001 and 2019, the young dependency ratio (the share of population below 15 years old over the working-age population) in Upper Norrland fell from 28.6% to 25.4%, at a much faster pace than the national average which remains constant at 28.5% (Figure 2.10). In 2001, Upper Norrland had about 92 762 young residents aged 0-14, whereas, in 2019, the youth population decreased to 84 131.
The fall of the share of young population has been particularly severe in the case of Norrbotten. The young dependency ratio in the region falls from 27.8% in 2001 to 25.5% in 2019. This figure represents a lower share of young people than in Västerbotten (25.8% on average since 2001) and relatively higher than the TL3 benchmark regions (22.1%).
Figure 2.9. Elderly dependency ratio in Swedish TL2 and TL3 regions, 2001‑19
Note: Calculated as a share of individuals over 65 years old over the working-age population (15-65 years old).
Source: OECD (n.d.[16]), “Regional Demography”, http://dx.doi.org/10.1787/a8f15243-en (accessed 27 January 2019).
Figure 2.10. Youth dependency ratio in Swedish TL2 and TL3 regions, 2001‑19
Note: Calculated as a share of individuals over 15 years old over the working-age population (15-65 years old).
Source: OECD (n.d.[16]), “Regional Demography”, http://dx.doi.org/10.1787/a8f15243-en (accessed 27 January 2019).
At the municipal level, mining municipalities are ageing faster than the core urban municipalities like Luleå and Umeå (Figure 2.11). For example, in 2019, Pajala’s elderly dependency ratio (35%) has reached almost twice the level in Umeå (17%) and Luleå (21%). Since, both cities have attracted young people and middle-aged immigrants, so its elderly dependency has been reduced and its young people are more likely to stay. As depicted in Figure 2.12, between 2002 and 2019, Upper Norrland’s mining municipalities have experienced a faster decline in the young and working-age population, in contrast with the trends in urban centres.
Figure 2.11. Youth and elderly dependency ratio, cities and mining municipalities, 2002‑19
Note: Calculated as a share of individuals over 65 and below 15 years old over the population 15-65 years old.
Source: OECD (n.d.[16]), “Regional Demography”, http://dx.doi.org/10.1787/a8f15243-en (accessed 27 January 2019).
Figure 2.12. Population change by age in mining municipalities and cities, 2002-19
Note: Net growth in the number of individuals. The graph on the left refers to the mining municipalities and the one on the right to the cities.
Source: Statistics Sweden (2019[11]), Statistical Database, http://www.statistikdatabasen.scb.se/pxweb/en/ssd/START__BE__BE0101__BE0101A/?rxid=3a012fe9-414f-47c2-8b84-25feb829e48d (accessed on 5 June 2019).
The ageing population and local demographic decline have led to a shrinking of the working-age population in Upper Norrland (Figure 2.13). Before the crisis, Upper Norrland’s share of the working population was very similar to the figure of Sweden, 64.2% and 65.5% respectively between 2001 and 2007. However, after the crisis, Upper Norrland’s working-age population experienced a rapid decline, much faster than in Sweden and the TL2 mining region average. By 2019, the working-age population in Upper Norrland represents a large share of the total population (61%), 0.9 perceptual points lower than in Sweden and 4.6 perceptual points than the average of TL2 benchmark regions.
At the TL3 level, Norrbotten has faced a more acute decline of the working-age population than Västerbotten. While both regions had a similar share of working-age population in 2000, the gap widened in favour of Västerbotten throughout the last two decades. In 2019, the share of the working-age population of Norrbotten (60.6%) is 1.5 perceptual points above the level of Västerbotten (62.1%). When comparing with other regions, the two TL3 regions of Upper Norrland have experienced a decrease in their working-age population as compared to the benchmark of TL3 mining regions. A small and decreasing workforce is not only a challenge for the sustainability of the current economic activity in the region but also hampers the growth of new businesses and the financial revenue of local municipalities (Chapter 3).
The sectoral distribution between the genders occurred unevenly. In 2018, the working-age population of Upper Norrland was 47.8% female; however, throughout the 20th century, a process of masculinisation of the mining industry reduced working opportunities for women (Abrahamsson et al., 2014[17]). Nonetheless, in the last years, old workplace cultures and worker identities have been changing, driven by emerging technologies and companies’ efforts to increase gender balance in their workforce (Eveline and Booth, 2003[18]). Due to the changing demand for skills and the possibilities offered by new technologies and automation, very different types of people and competencies will likely be hired in the future.
Figure 2.13. Working-age population in Swedish TL2 and TL3 regions, 2001‑19
Note: Share of the working-age population (15-64 years old) over the total population.
Source: OECD (n.d.[16]), “Regional Demography”, http://dx.doi.org/10.1787/a8f15243-en (accessed 27 January 2019).
In summary
Overall, Upper Norrland’s drop in population is explained by outmigration coupled with the structural ageing of its population, which has resulted in a decreasing workforce over time. The net amount of people leaving Upper Norrland is the highest across all Swedish regions and above the level experienced by the TL2 region benchmark region. It is driven by outmigration of the young population, particularly women. Further, its elderly dependency ratio has been increasing relatively rapidly, reaching levels above the national average and the TL2 benchmark regions. In particular, Norrbotten is experiencing higher outmigration and population ageing than in Västerbotten and the benchmark of TL3 mining regions. In mining communities, the situation is more severe: these are ageing faster and losing more population than core urban municipalities such as Luleå and Umeå. Therefore, since the financial crisis, the working-age population has declined in the region at a faster pace than in Sweden and TL2 benchmark mining regions. This phenomenon has occurred similarly in both TL3 regions, yet Västerbotten has experienced a less rapid workforce decline. The challenge for Upper Norrland during and after the COVID-19 crisis lies in retaining its young population and attracting a higher proportion of skilled migrants.
Regional economic trends
Upper Norrland – A high-income region in the Swedish context
The mining industry is a key contributor to the economy of Upper Norrland as well as an engine for regional development. In Upper Norrland, the mining industry has linkages to other industries such as construction, transportation, equipment manufacturing, education and research (Chapter 3). As discussed below (see next section), the volatility of international commodity prices has played an important role in the region’s economic performance.
Upper Norrland’s GDP per capita is high within the national and OECD regional context. Upper Norrland has the third-highest GDP per capita (USD 44 290) across the 8 TL2 regions in Sweden, right after Stockholm (USD 68 872) and West Sweden (USD 48 804) (Figure 2.14). Upper Norrland’s GDP per capita also ranks slightly above the average of OECD mining region (USD 42 087). In 2017, GDP per capita for Upper Norrland was 98% of the national average (USD 46 546) and 67% of Stockholm, which underlines the large income difference of the Swedish capital with the rest of the TL2 regions.
Figure 2.14. GDP per capita of regions of Sweden compared to OECD TL2 benchmark, 2018
Note: USD per head, constant prices, constant purchasing power parity (PPP), base year 2015.
Source: OECD (n.d.[16]), “Regional Demography”, http://dx.doi.org/10.1787/a8f15243-en (accessed 27 January 2019).
In the last 20 years, Upper Norrland has been closing the income gap with the national average (Figure 2.15). During 2000-17, the gap in the GDP per capita between Upper Norrland and Sweden has narrowed by 22% (from USD 5 097 in 2001 to USD 3 975 in 2017). In the period before the financial crisis (2000‑06), Upper Norrland’s economy experienced a constant acceleration with a much faster growth rate (5% annual average) than the national average (3%), mainly driven by high global demand of minerals and industrial products. During the crisis, Upper Norrland’s GDP per capita experienced a sharp drop, which ranked Upper Norrland as the TL2 region in Sweden with the largest decline during 2007-09 (-4% annual average vs -2% annual average across Sweden regions). However, in the post-financial crisis era, the Upper Norrland economy quickly recovered above the mining regions' TL2 benchmark, demonstrating its higher labor productivity following the surge in international commodity prices. On average during 2010-17, the region registered the largest GPD per capita growth (3.0% annual average) across Swedish regions (average growth of 1.8%) and exceeded the average growth of OECD TL2 mining regions (0.4%). It is worth noting that Upper Norrland has been expanding its GDP per capita gap with respect to the OECD TL2 mining regions, which underlines the high productivity level in the region (see next section).
At the TL3 regional level, the fall during the crisis and subsequent recovery did not occur equally. During the pre-crisis period, in 2000-06, the economy of Norrbotten and Västerbotten grew at similar rates. However, in 2009, Norrbotten experienced a record decrease (-18% annual rate), plunging its GDP per capita to 2003 levels. In contrast, the decrease of Västerbotten’s economy in 2009 (-7%) was less than half of Norrbotten, underlining the high vulnerability of the former region. In the post-crisis years, Norrbotten experienced a volatile recovery with a record growth immediately after the crisis (29% annual growth), followed by a deceleration trend in the subsequent years. Västerbotten’s recovery was instead less volatile, with steady economic growth (Figure 2.15).
The strong recovery of the mineral prices after the crisis has allowed Norrbotten’s economy to expand the gap with Västerbotten. By 2015, Norrbotten’s GDP per capita was 12% above that of Västerbotten, expanding the gap with respect to the beginning of 2000s (8%). However, Norrbotten has proven to be more vulnerable to external shocks, which makes its economic growth trend susceptible to facing larger shocks than its neighbouring TL3 region.
Figure 2.15. GDP per capita trend in Swedish TL2 and TL3 regions, 2001‑18
Source: OECD (n.d.[16]), “Regional Demography”, http://dx.doi.org/10.1787/a8f15243-en (accessed 27 January 2019).
Upper Norrland is vulnerable to external economic shocks
The relatively high dependence on the mining sector exposes these regions to external economic shocks. Regional economies that are heavily dependent on mining tend to be exposed to higher volatility related to changes in international commodity price (OECD, 2017[1]). The price of commodities has experienced high fluctuations during the crisis and post-crisis period, which has translated in volatilities in Upper Norrland’s GDP. Since 2001, its GDP has experienced higher volatility (USD 3 640 standard deviation) than for Sweden (USD 2 800) and the benchmark of TL2 mining regions (USD 2 185) (Figure 2.16). In the last decade, the proximity between the positive and negative peaks seems to indicate the great fluctuation of GDP and its dependence on the value of commodities.
The vulnerability to external shocks is not the same within the two TL3 regions, as Norrbotten’s economy has faced higher volatilities than Västerbotten’s. Between 2001 and 2016, Norrbotten’s GDP experienced higher volatility (USD 4 963 standard deviation) than Västerbotten (USD 2 600). This is mainly explained by the higher dependency of Norrbotten’s economy on the mining industry and related activities. Norrbotten’s GDP follows more closely the volatility of international prices of copper and iron ore. When the price of these metals reached a peak during 2006, 2008 and 2010, the GDP growth in Norrbotten experienced the highest values of the decade. Similarly, the negative peaks of prices in 2007, 2009 and 2012 coincided with the lowest values of GDP growth in Norrbotten since 2002.
A similar effect occurred in the TL2 benchmark, with sharp falls in 2007 and 2008. Reducing such volatility should be of interest to the entire Upper Norrland area in order to ensure sustainable and sustained growth (Chapter 3). This will be especially important in the context of the recent 2020 coronavirus crisis, which may once again highlight the vulnerability of the Upper Norrland economy to external shocks. As the chapter explains, the high dependence of its economy on mining and extractive activities may aggravate the effects of COVID-19 over time, as mining has been one of the first sectors most affected by the global slowdown. This is partly explained by the fact that the major importers of mineral materials have dramatically reduced their activity, consequently affecting suppliers. The spearhead has been China, where the reduction of the manufacturing and construction sector has implied the diminishing demand for mineral materials.
Figure 2.16. Standard deviation of GDP, Sweden and Upper Norrland regions, 2001‑16
Note: Standard deviation calculated with USD per capita, constant prices, constant PPP and base year 2015.
Source: GDP per capita: Calculations based on OECD (2016[19]), OECD Regional Statistics (database), http://dx.doi.org/10.1787/region-data-en (accessed 20 February 2020).
Figure 2.17. GDP growth rate in Västerbotten and Norrbotten vs. international commodity prices, 2002-16
Note: Copper and iron ore prices are calculated as their average prices. GDP growth rate uses per capita GDP, current PPP.
Source: (International Monetary Fund, 2020[20]) GDP per capita: OECD (2016[19]), OECD Regional Statistics (database), http://dx.doi.org/10.1787/region-data-en (accessed 20 February 2020).
In summary
Upper Norrland has the third-highest GDP per capita in Sweden as well as a low unemployment rate allowing the region to reduce its income gap with the rest of the country by 22% in the last 20 years. After the crisis (2010-17), the region registered the largest GPD per capita growth (3% annual average) across Swedish regions and widened its GDP per capita gap with the TL2 benchmark. Population decline and a fundamentally industrial economy along with high prices in the international commodity market have enabled Upper Norrland to experience an unstable but strong economic performance. However, this dependence on international commodity prices has generated a very volatile economy.
At the TL3 level, Norrbotten has proven to be a more volatile economy that experienced a drastic drop during the crisis, but recovery at a faster pace than Västerbotten and the TL3 benchmark. Norrbotten depicts a greater specialisation in mining activities than Västerbotten, which makes it more vulnerable to external shocks. Reducing such volatility should be of interest to the entire Upper Norrland area in order to ensure sustainable and sustained growth.
The unemployment rate is lower than Sweden but is increasing faster
During the post-crisis period, Upper Norrland’s unemployment rate has decreased at a much faster rate than in Sweden (Figure 2.18). Before the crisis, in 2007, the unemployment rate was at 6.9%, 0.6 points above the national average. However, the stronger recovery after the crisis helped Upper Norrland’s economy to reduce its unemployment rate from 9% in 2009 to 5.1% in 2018. This reduction is 2 perceptual points larger than at the national level (from 8.5% in 2009 to 6.9% in 2019). The relatively better performance on job creation in Upper Norrland has been associated with higher GDP growth after the crisis, the reduction of the workforce and its higher ageing rate. In 2018, the unemployment rate ranks at 5.1%, below the level in Sweden (6.6%) and TL2 mining regions (7.3%).
Figure 2.18. Unemployment rate over labour force in Sweden, Upper Norrland, Västerbotten, Norrbotten and TL2 & TL3 comparable regions
Note: Percentage of unemployed population over labour force 15-64 years old.
Source: OECD (n.d.[21]), “Regional Labour”, http://dx.doi.org/10.1787/a8f15243-en (accessed 27 January 2020).
At the TL3 level, Västerbotten exhibits a lower unemployment rate than Norrbotten (Figure 2.18). In 2019, the unemployment rate in Västerbotten (5.5%) was slightly below the level in Norrbotten (6%), with both remaining below the national average (6.9%). Västerbotten had a decline in unemployment that was relatively strong in 2014 but slowed down in 2016 and 2017.
In 2020, the changing working habits and the emergence of digital solutions in response to the COVID-19 crisis called for greater efforts to adapt to the elderly and the workforce to technological changes. Older workers and the elderly population were especially disrupted by new methods of work. Mining communities with an older workforce, a lower share of the service economy and a reliance on economic activities that depend on the physical presence of workers are being more vulnerable to the effects of the crisis.
At the municipal level, mining municipalities tend to benefit from a lower unemployment rate than the urban centres of the region. In Norrbotten, Luleå’s unemployment rate in 2019 was 3.3%, above the level in Pajala (3.1%) and much higher than in Jokkmok (1.9%) and Kiruna (1.8%). Likewise, in Västerbotten, in 2019, Umeå recorded an unemployment rate (3.0%) above the Västerbotten municipal average (2.8%) and the level in the mining municipality of Malå (2.3%).
Figure 2.19. Unemployment in cities and mining regions, 2019
Note: Unemployment rate as a percentage over labour-force population, 2019. The cities are Luleå and Umeå.
Source: RegionFakta (n.d.[22]), Statistics from Counties and Regions in Sweden, http://www.regionfakta.com/ (accessed on 15 February 2020).
In the regions of northern Sweden, the public sector is the top employer (Figure 2.20). Health, education and governments constitute important employers in Upper Norrland. A policy agenda to deliver quality public services to the most dispersed settlements has supported the expansion of labour demand in health and education activities across the region. In Upper Norrland, the top three employers by size in 2019 are in the public sector. The fourth-largest employer in Västerbotten is Umeå University while, in Norrbotten, it is the mining company, LKAB, which employs 3 475 people. In Västerbotten, the public sector is a relevant employer, representing 40% of total employees, which is mainly explained by the high cluster of healthcare in the region.
In summary
Like its economy, unemployment in Upper Norrland is highly volatile. Therefore, although its unemployment performance has been better than in the rest of the country over the last 20 years, the reasons are not necessarily positive. This effect is partly explained by the decline in its labour force, which is due to migration and the ageing of its population in the region in a context aggravated by the effects of the post-COVID-19 economic crisis. This unemployment rate decreased in Västerbotten than in Norrbotten. In particular, the rural and mining municipalities have a lower unemployment rate than the region’s urban centres.
Figure 2.20. Share of employment in the public sector in Upper Norrland’s regions compared to Sweden, 2015
Note: Share calculated as a percentage over total employment.
Source: OECD (2017[23]), OECD Territorial Reviews: Northern Sparsely Populated Areas, https://doi.org/10.1787/9789264268234-en.
Upper Norrland is highly specialised
At a national level, Upper Norrland’s economy is dominated by industrial activities (including energy and mining) linked to the natural resources (Table 2.5). The share of industrial activities on mining and energy (11.5%) are particularly much higher than the national level (3.3%) but slightly below the average of TL2 regions (13.4%). Together with manufacturing activities, also linked to the processing of natural resources like forestry, the industrial sector in Upper Norrland (26.3%) is much higher than the national level (18.8%) and similar to the benchmark of TL2 regions (26.3%). As much of these activities are export-oriented, the regional economy benefits from a higher share of tradeable activities than at the national level. This is positive, as productivity in tradeable activities tends to be larger than in non-tradeable activities across OECD countries and regions (OECD, 2019[24]; 2016[25]). However, services represent just a small share of the tradeable sector (9% vs. the national average of 15.7%), which can limit the gains from international trade as services tend to be linked with higher-value-added activities in GVCs (OECD, 2019[24]; 2016[25]).
Table 2.5. GVA share by sector in Sweden, Upper Norrland and OECD TL2 benchmark, 2015
Note: Tradeable sectors are defined by a selection of sectors defined in the System of National Accounts (SNA) 2008. They include agriculture, industry and manufacturing, information and communication, financial and insurance activities, agriculture and other services.
Source: OECD (n.d.[26]), “Regional Economy”, http://dx.doi.org/10.1787/a8f15243-en (accessed 27 January 2020).
Upper Norrland is creating SMEs but at a slower pace than the country
Inside Upper Norrland, Norrbotten depicts a greater specialisation in mining activities than Västerbotten (Table 2.6). In terms of both employment and GVA, the local quotient of specialisation in Norrbotten (4.0) doubles the level of Västerbotten (2.0). In contrast, Västerbotten is more specialised in manufacturing (1.2), while the Norrbotten quotient of specialisation (0.7) reveals the lower weight of this sector in the regional GVA. Other sectors of specialisation in terms of GVA for both regions are agriculture, forestry and fishing, construction and public sector (education, health).
Table 2.6. Specialisation Index by sector in Västerbotten and Norrbotten, 2015
Note: The location quotient for each sector is the ratio between the sector weight in regional GVA/employment, and the weight of the same sector in national GVA/employment. A value above 1 implies that the region is more specialised in that sector than the rest of the economy. GVA based on USD PPP constant values (2010). Upper Norrland is creating SMEs but at a slower pace than the country.
Source: OECD (n.d.[26]), “Regional Economy”, http://dx.doi.org/10.1787/a8f15243-en (accessed 27 January 2020).
In summary
Upper Norrland has the necessary characteristics to be described as a specialised region; a high GVA share and high level of employment dedicated to one specific sector. Mining occupies the highest level of employment, and likewise, the highest GVA share. It is not the same in both regions of Upper Norrland, because, while Västerbotten (2) has a more diversified economy, its GVA share in mining is half that of Norrbotten (4).
The number of companies in the region is relatively high but growth has stagnated
Upper Norrland has a high number of companies in relation to its population but the creation of new companies has been falling behind the country performance. Västerbotten and Norrbotten have a similar density of businesses with 39 companies per 1 000 inhabitants, similar level of other TL3 regions in Sweden (Figure 2.21). However, since the financial crisis, the creation of businesses has been decreasing in relation to the national dynamic (Figure 2.22). The share of companies in Västerbotten and Norrbotten within the total number of Swedish companies has experienced a constant decrease from levels of 3.1% and 2.9% in 2000 to 2.5% and 2.4% in 2019 respectively. The reason for this drop in the creation of establishments can be associated with a lower population, a low unemployment rate and the high reliance on mining activities that hamper entrepreneurship culture.
Figure 2.21. Density of business establishment growth, 2001-08
Note: Number of establishments per 1 000 citizens.
Source: RegionFakta (n.d.[22]), Statistics from Counties and Regions in Sweden, http://www.regionfakta.com/ (accessed on 15 February 2020).
Figure 2.22. Share of regional business establishments at the national level, 1998-2019
Note: The TL3 region’s share of workplaces in the state.
Source: RegionFakta (n.d.[22]), Statistics from Counties and Regions in Sweden, http://www.regionfakta.com/ (accessed on 15 February 2020).
The average size of business establishments in Upper Norrland has remained relatively constant. Norrbotten and Västerbotten have relatively similar sizes of business. On average, companies in both regions have around 12 employees. While the average size of business establishments in Upper Norrland TL3 regions has declined, this has occurred to a slower pace than other TL3 regions in Sweden (Figure 2.23). This result is coherent with the relevance of mining companies and the public sector as main employers in the regions. It is worth noting that in Upper Norrland mining municipalities, a significant number of small SMEs tend to be family-run or single-owner businesses (Regional Government of Norrbotten, 2019[27])).
The recent COVID-19 economic crisis has tested the endurance capacity of SMEs. Their financial capacity is small compared to large companies, generally with limited resources and no financial room for manoeuvre. SMEs showed less resilience and flexibility in dealing with the costs these shocks entail. Costs for prevention as well as requested changes in work processes, such as the shift to teleworking, were relatively higher for SMEs given their smaller size but, also, in many instances, the low level of digitalisation and difficulties in accessing and adopting technologies.
Given the limited resources of SMEs, and existing obstacles in accessing capital, the period over which SMEs can survive the shock is more restricted than for larger firms. Therefore, the government and institutional support are crucial in reducing the pressure on SMEs.
Figure 2.23. Average size of business establishments, 2001-18
Note: Average number of employees in business establishments.
Source: RegionFakta (n.d.[22]), Statistics from Counties and Regions in Sweden, http://www.regionfakta.com/ (accessed on 15 February 2020).
In summary
The absolute growth of businesses in Upper Norrland is positive; however, the rate of creation is lower than in the rest of the country. In addition, companies are getting smaller as the number of employees per company is decreasing.
The sectoral trends are changing
During the crisis, the economic sectors in Upper Norrland experienced fewer striking declines showing greater resilience to external effects than the rest of Sweden. However, many sectors in Upper Norrland recovered at a slower pace than in the rest of the country. The manufacturing activities were particularly vulnerable to the effects of the financial crisis in Sweden (-4.45%), relatively higher than in Upper Norrland (‑0.35%). A similar effect occurred in industry: the fall in Sweden (-4.74%) was much more significant than for Upper Norrland (-2.00%) (Figure 2.24). Nevertheless, when compared with other mining regions of the TL3 benchmark, the manufacturing sector in Upper Norrland showed a relatively higher vulnerability to the shocks of the financial crisis.
Other areas of specialisation in Upper Norrland in terms of GVA and employment, such as agriculture, forestry and fishing, and construction, responded better to the crisis than at the national level. However, public administration, which is a relevant sector for Upper Norrland, experienced a steeper drop.
Figure 2.24. Change in GVA share, by sector in Sweden, Upper Norrland and OECD TL2 benchmark, 2005‑15
Source: OECD (n.d.[26]), “Regional Economy”, http://dx.doi.org/10.1787/a8f15243-en (accessed 27 January 2020).
The arrival of an economic crisis – following the health crisis due to COVID-19 – affected the economic sectors of Upper Norrland unevenly. In practice, this crisis shared similarities with the financial crisis of 2008. While the Västerbotten region showed more resilience to external shocks thanks to its more diversified economy, the Norrbotten economy is concentrated in fewer sectors, resulting in a more vulnerable economy. The manufacturing and construction sectors were impacted in the early stages of the crisis; however, when the economic situation improved, these sectors rebounded, serving as a trigger for the region’s recovery.
At the TL3 level, situations are different for Västerbotten and Norrbotten. In Västerbotten, the economic sectors maintained a higher resilience compared to Norrbotten. In Västerbotten, sectors such as manufacturing (0.14%) and industry (-0.14%) were strongly resistant to the passage of the crisis, unlike Norrbotten (-0.84% and -3.72% respectively) (Figure 2.25). However, other sectors did suffer considerable falls. Public services in Norrbotten (-3.75%) and Västerbotten (-2.84%), as well as information and communication (-1.58% combined), suffered the worst part of the crisis, losing relevance in the GVA share of the region.
Figure 2.25. Change in GVA share, by sector, Västerbotten, Norrbotten and OECD TL3 benchmark, 2005‑15
Source: OECD (n.d.[26]), “Regional Economy”, http://dx.doi.org/10.1787/a8f15243-en (accessed 27 January 2020).
Between 2005 and 2015, industry in Upper Norrland experienced a lower decline than in the rest of the country (Table 2.7). During this period, the share of the industry in Upper Norrland’s GVA fell 2.0 percentage points, recording a lower decrease than the rest of the country (4.74). Both TL3 regions within Upper Norrland have responded differently to the crisis, where the share of the industry in Norrbotten’s GVA experienced a larger decease (3.72) than Västerbotten (0.14). Västerbotten’s industrial resilience responds to a more diversified economy that helped maintain the GVA share of the sector at a similar level than the pre-crisis period.
Table 2.7. GVA share change, 2005‑15
Source: OECD (n.d.[26]), “Regional Economy”, http://dx.doi.org/10.1787/a8f15243-en (accessed 27 January 2020).
During the post-2008 crisis period, tourism-related activities were growing following the trend at the national level. In recent year, both regions have maintained a very positive trend, doubling their values from 15 years ago. Norrbotten and Västerbotten have also developed linkages to strengthen the tourism-related activities within the region. Västerbotten is attracting tourism through its nature-based activities related to its lakes and river valleys. Norrbotten has great growth potential as well, benefiting from a wide range of nature-based tourism, especially during summer and winter, with Arctic-related activities (i.e. aurora borealis). Over the last decade, both regions have put greater priority on fostering its tourism offers with tourist attractions such as the aurora borealis, coastal recreation, hiking, camping and the Sami culture.
However, as in many countries, the impact of COVID-19 on international and domestic tourism has been overwhelming and immediate. It has especially affected international tourism throughout 2020, with some effects likely to continue in the medium term. The OECD estimates that the international tourism economy is expected to fall in 2020 between 45% and 70% (OECD, 2020[28]). Rural communities specialised in travel arrangements, leisure and hospitality were particularly vulnerable to the global slowdown. In the aftermath of the pandemic and while international tourism gradually recovers, domestic tourism has been playing an essential role in Upper Norrland. For this, it will be essential to ensure flight connections, take aggressive, and co‑ordinated policy action at the local, national and international levels to minimise job losses and business closures.
Upper Norrland’s industrial productivity is high in the national context
In the national context, Upper Norrland has been a strong productivity performer in terms of GDP per worker. The region had a higher level of labour productivity in industrial sectors than Sweden (Table 2.8). Norrbotten’s labour productivity in industry and in total is higher than in Västerbotten but both regions are below the TL3 benchmark average.
Upper Norrland’s labour productivity has experienced two peak periods in 2005 and 2006 and again in the post-crisis period, 2010 and 2011 (Figure 2.26). Since 2012, labour productivity has diminished. This change followed a constant trend and, in 2015, the labour productivity of Upper Norrland (USD 83 123) dropped to 8 percentage points below the national level (USD 90 330). Since 2000, the productivity gap between Upper Norrland and the national average has decreased slightly. This is partly due to a higher labour productivity growth rate at the national level.
Historically, Norrbotten has been a high-productivity region within Sweden and Upper Norrland. In 2000, Norrbotten (USD 73 126 per worker) was relatively more productive than Västerbotten (USD 65 475 per worker), reaching its lowest difference (6%) in the middle of the crisis in 2009, coinciding with the high volatility of the financial markets. In the post-crisis years (2012‑15), the gap has been on average 17%, widening again the difference between Norrbotten and Västerbotten (Figure 2.26).
Table 2.8. Productivity in Sweden, Upper Norrland and its TL3 regions, 2015
Note: Measured as USD per worker.
Source: OECD (n.d.[26]), “Regional Economy”, http://dx.doi.org/10.1787/a8f15243-en (accessed 27 January 2020).
Figure 2.26. Labour productivity trend in the TL3 regions of Upper Norrland, 2000‑15
Source: OECD (n.d.[26]), “Regional Economy”, http://dx.doi.org/10.1787/a8f15243-en (accessed 27 January 2020).
In summary
Upper Norrland has been more resilient to the effects of the crisis than the rest of Sweden. Sectors such as industry and manufacturing have shown relatively constant values over the period before and after both the 2008 and 2020 crises. The greater diversification of Västerbotten on the one hand and the high productivity ratios of Norrbotten on the other make Upper Norrland a resilient but volatile region in the short term.
Enabling factors for development
Snapshot of quality of life in Upper Norrland
Quality of life is important for a remote region like Upper Norrland for retaining and attracting people and business. The OECD’s analysis of well-being at the regional level provides a tool that allows policymakers to assess regional strengths and weaknesses, monitor trends and compare their outcomes to other regions, nationally and internationally (Box 2.3). To better understand the relationship between well-being and mining regions, the analysis presented in this section adopts the OECD regional well-being framework to compare outcomes of quality of life in Upper Norrland against the average of OECD TL2 regions, the OECD mining regions and Sweden’s average.
Box 2.3. OECD Regional Well-being Indicators
Building comparable well-being indicators at a regional scale
The OECD framework on measuring regional well-being builds on the OECD Better Life Initiative at the national level. It goes further to measure well-being in regions with the idea that well-being data are more meaningful if measured where people experience it. Besides place-based outcomes, the framework also focuses on individuals since both dimensions influence people’s well-being and future opportunities.
In line with national well-being indicators, regional well-being indicators concentrate on informing about people’s lives rather than on means (inputs) or ends (outputs). In this way, policies are directed to well‑being features that can be improved by policies. Regional well-being indicators also serve as a tool to evaluate how well-being differs across regions and groups of people.
Regional well-being indicators are multi-dimensional and include both material dimensions and quality of life aspects. They also recognise the role of citizenship, institutions and governance in shaping policies and outcomes.
Although well-being dimensions are measured separately, the regional well-being framework aims to allow for comparisons and interactions across multiple dimensions to account for complementarities and trade-offs faced by policymakers. At the same time, the comparison of regional well-being indicators over time allows comparing dynamics of well-being over time, as well as the sustainability and the resilience of regional development.
Regional well-being in Sweden is measured along 12 well-being dimensions: income, jobs, housing, health, access to services, education, civic engagement, environment and safety – for which there are comparable statistics at the regional level – and the three additional dimensions of work-life balance, community (social connections) and life satisfaction. The OECD database has available comparable data at the sub-national level only for the first two. The figure below shows the details the indicator used for each dimension.
Figure 2.27. Indicators by well-being dimension, Upper Norrland
Source: OECD (n.d.[29]), OECD Regional Well-Being (database), www.oecdregionalwellbeing.org (accessed on 27 May 2019).
Upper Norrland has relative high well-being outcomes in comparison with the average of OECD TL2 regions and the OECD mining regions (Figure 2.28), depicting that Upper Norrland (TL2) performs above the average OECD TL2 regions in all of the 11 dimensions of well-being. The region ranks particularly high in civic engagement, environmental quality and access to services. The lowest well-being outcomes in comparison with OECD TL2 regions is on housing, where the region ranks just slightly above the average. Likewise, Upper Norrland performs above in all well-being dimensions than the average of OECD mining regions in all well-being dimensions, with civic engagement, access to services and safety registering having the best outcomes.
The picture is mixed when Upper Norrland’s well-being is compared with the Swedish region average. Upper Norrland performs above Sweden’s regional average in six well-being dimensions. Environmental quality, accessibility to services and education are the dimension with the highest relative ranking. In contrast, the region ranks below in four dimensions, where health, income and community support experience the lowest performance with respect to Sweden’s regions average.
Figure 2.28. OECD Well-being, 2018
Note: Simple average of OECD TL2 regions = 100.
Source: OECD (n.d.[29]), OECD Regional Well-Being (database), www.oecdregionalwellbeing.org (accessed on 27 May 2019).
Overall, Upper Norrland stands out among all comparison groups in the following areas:
Environmental quality: The geographic location of the region in a large geographical extension close to the Arctic offers a great variety of natural ecosystems with fresh water sources, mountains and forests. This is important for the tourism industry and the attraction of people who allocate a high value to outdoors activities.
High level of civic engagement: Civic engagement matters for well-being as it allows for the expression of political voice and feedback to political leaders, essentially enhancing accountability and effectiveness of public policy (OECD, 2019[30]). A higher voter turnout in a country like Sweden – already above OECD average – offers a fertile ground for the region to involve citizens in policy design and the implementation of strategic programmes (Chapter 3). Such civic engagement is also related to its industrial history. The region has the largest proportion of employees affiliated to a trade union or employer organisation (85% vs. 75% across Sweden).
Accessibility to services: Despite its low-density and sparse settlement patterns, the region has made important efforts to ensure the delivery of quality public services. Part of its success comes from the large coverage of broadband in the region, which has enabled the delivery of education to remote municipalities. The share of households connected to broadband in Upper Norrland (99% in 2019) is above the average of European (98% on average in 2019) and OECD regions (70% on average in 2018) (Eurostat, 2020[31]; OECD, 2018[32]; n.d.[29]). The information and communication technology (ICT) usage in Upper Norrland is also high. In 2019, the region recorded the highest share of people taking online courses (27%), far above the average in Sweden regions (15%). The effort on deploying high-quality public services has leveraged a relatively higher education outcome than the average of OECD and Swedish regions.
In contrast, Upper Norrland has a relatively lower performance in housing availability and health outcomes:
In housing availability, the region seems to face challenges of land availability for construction. Norrbotten and Västerbotten rank among the three regions with a lower share of built-up land and associated land (Figure 2.2). Population decline has contributed to decreased housing demand pressures in certain areas of the region and lead to a slightly higher number of rooms available per person (1.8 in 2014) than the national average (1.7). However, in Norrbotten, many municipalities face challenges to develop new housing projects and increase the housing stock. Between 2000 and 2012, the dwelling stock in Norrbotten experienced a decrease (3%), in contrast with the increase of stock in Västerbotten (2.3%) and the Swedish regional average (3.6%). Such stagnation in dwellings is driven by years of restricted construction (Norrbotten's County Administrative Board, 2011[33]), partly related to the high share of land classified as of national interest (Chapter 4).
In health, indicators could improve within the national context. Upper Norrland, like Sweden, benefits from a lower rate of mortality (7.6 per 1 000 inhabitants) than the average of OECD regions (8.3). However, the region has the third-highest mortality rate among the eight TL2 Swedish regions (OECD, 2017[23]). In 2016, Upper Norrland ranked as the second region with the highest obesity and overweight rates (54% of the population between 16 and 84 years old), above the national average (50%). Related health issues do not seem to lead to undersupply of healthcare, as the region has been a frontrunner in telemedicine and has a high share of healthcare personal. For example, Västerbotten has the highest ratio of licensed healthcare personnel (2 866 per 100 000 inhabitants) among all TL2 regions in Sweden, while Norrbotten ranks just slightly below the national average (2 146) (National Board of Health and Welfare, 2018[34]). The sparsity of settlements and isolated population might explain part of the lower healthcare outcomes in Norrbotten (Norrbotten's County Administrative Board, 2011[33]).
Upper Norrland’s level of education stands out at the national level
The level of education in Upper Norrland is relatively high in Sweden and in the OECD context. In 2018, the majority of the population in Upper Norrland had at least upper secondary education and the share of the labour force with lower education is decreasing. Between 2000 and 2017, the share of the labour force with lower education dropped from 18.3% to 12.8%, reaching the levels of Stockholm. Correspondingly, the share of the labour force with tertiary educational attainment in Upper Norrland has risen in the past few years, from 30.1% in 2010 to 35.7% in 2017. This figure is above the level of TL2 OECD mining regions (34.5%) but below the national level (40.0%) (Figure 2.29)
In Norrbotten, the share of the population with higher education has increased at a faster pace than in Västerbotten (Figure 2.30). Outcomes for youth in Norrbotten is an area of concern. There has been a divergence in the level of higher education with the national level, which reflects the labour market structure of the region and the move of higher-skilled young people to cities. On the other hand, a significant share of young adults aged 20-24 in Västerbotten have higher education, a share above the national average. The same occurs for the population aged 15-64. This is a key difference between Västerbotten and its northern neighbour. The high level of education is due to the large universities mainly in the big cities. However, there are big differences within the region in terms of the level of higher education, as smaller rural municipalities have very low rates (Figure 2.31).
Figure 2.29. Share of level of education over labour force, Sweden, Upper Norrland and OECD TL2 benchmark, 2001‑17
Source: OECD (n.d.[35]), “Regional Innovation”, http://dx.doi.org/10.1787/a8f15243-en (accessed 27 January 2020).
Figure 2.30. Share of the level of education over labour force, Västerbotten and Norrbotten, 2000‑18
Source: OECD (n.d.[35]), “Regional Innovation”, http://dx.doi.org/10.1787/a8f15243-en (accessed 27 January 2020).
Figure 2.31. Share of the level of education over labour force, cities and mining municipalities, 2002‑17
Note: The cities are Luleå and Umeå.
Source: OECD (n.d.[35]), “Regional Innovation”, http://dx.doi.org/10.1787/a8f15243-en (accessed 27 January 2020).
Upper Norrland is a highly innovative region
The levels of innovation are high compared to Upper Norrland. Two major universities enable a centre of high academic performance in the Upper Norrland region, Luleå University of Technology and Umeå University.
The European criterion for measuring innovation through a wide range of indicators, classifies Upper Norrland region as “Strong + Innovative” within the Regional Innovation Scoreboard (European Commission, 2020[36])), positioning itself as an innovative environment. However, while patent applications and research and development (R&D) investments are reaching reasonable levels in 2018 (93.0 patent applications per million inhabitants), they remain below the national (247.4) and European (106.84) averages ( (European Commission, 2020[36])). The spearhead of innovation in Sweden is located in the capital, Stockholm, ranking as “Leader +” with a high rate of patents applications per million of inhabitants (569.5) (Figure 2.32).
In terms of expenditure, the annual average business expenditure on R&D as a percentage of GDP in Upper Norrland was 2.4% over the period 2003‑13, which is below the national average of 3.3% but above the EU average of 1.9% (European Commission, 2020[36]).
Table 2.9. Regional Innovation Scoreboard (RIS), 2019
Note: The RIS 2019 covers 238 regions across 23 EU countries.
Source: EC (2020[37]), RIS 2019 (database), https://ec.europa.eu/docsroom/documents/36081 (accessed on 23 February).
Figure 2.32. Innovation in Sweden, Stockholm and Upper Norrland’s TL3 regions, 2015
Source: OECD (n.d.[21]), “Regional Labour”, http://dx.doi.org/10.1787/a8f15243-en (accessed 27 January 2020).
In summary
The level of education in Upper Norrland outstands the rest of Sweden, the comparable benchmark and the OECD average. Education is precisely one of the best assets to face the challenges of the region. It helps to slow down migration by attracting young talent, mostly to cities home to the main universities. Robust public-private partnership structures have been made with industry, especially mining. This synergy, together with investment in R&D, has led Upper Norrland to be ranked as a high innovation region under the EU measures.
Annex 2.A. Selected OECD TL2 mining regions
Annex Table 2.A.1. Benchmark of OECD TL2 regions used for comparison with the TL2 region of Upper Norrland
Note: Selection of regions based on the region's specialization in the mining sector as well as its location quotient and a desk research to select the suitability.
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[8] UNEP (2019), Global Resources Outlook 2019, United Nations Environment Programme, http://www.resourcepanel.org/reports/global-resources-oultook (accessed on 24 May 2019).
[6] UNFCC (2015), Adoption of the Paris Agreement, United Nations.
Note
← 1. The geographic concentration index offers a picture of the spatial distribution of population within a country, as it compares the share of the population and the land area of each region. Differences in geographic concentration between two countries may be partially due to differences in the average size of regions in each country.