Economic perspectives on critical infrastructure in the nordic region
Economic perspectives on critical infrastructure in the nordic region
Introduction
Infrastructure refers to the general assets and systems that support daily life, from the electricity that powers homes to the transportation networks that enable mobility. Within these systems, critical infrastructure makes out the most essential assets and networks that provide vital societal services the disruption of which would significantly affect societal security, economic stability and public health (Forzieri et al., 2018; Pursiainen & Kytömaa, 2023; UNDRR, 2017). Growing geopolitical tensions and climate-related risks have increased concerns about the safety and reliability of these systems across the Nordic Region and Europe, promoting calls for a strengthened, all-hazards approach to critical infrastructure resilience (European Commission, 2025; Nordic Council, 2023).
Across the Nordic countries, as in much of Europe, the focus of critical infrastructure policy has shifted from protecting individual assets to ensuring the resilience of the services they provide (Larsson & Rhinard, 2020; Pursiainen, 2018). This transition is reflected in the EU Critical Entities Resilience (CER) Directive, which came into effect in 2023, and which emphasises not only the protection of infrastructure but also the continuity of the essential services it provides in sectors such as energy, water, transport and communications. The directive also highlights the role of critical entities (i.e., the organisations responsible for operating these systems) and their capacity to prevent, withstand and recover from disruptions caused by both natural risks and antagonistic threats, including natural hazards, terrorism, hybrid threats or pandemics (European Union, 2022).
What counts as 'critical' infrastructure is context-dependent, shaped by local needs, interdependencies, vulnerabilities and spatial conditions. One way to assess the value of critical infrastructure is through economic measures, which can indicate the value of either the physical infrastructure assets or the economic value generated through infrastructure use and services. It can be difficult to measure these aspects and compare them directly across regions, so analyses often rely on indicators or indices that combine multiple variables into a single measure, enabling comparisons across places and sectors.
It is worth noting that economic measures alone cannot fully capture the strategic significance of infrastructure in situations of disruption or crisis. Some assets may appear limited in economic value, yet remain essential for ensuring continuity of societal functions, emergency response or national preparedness. For example, electricity transmission lines or transport links in sparsely populated areas may have a modest economic value tied to them but are nonetheless important for maintaining system functionality under strained conditions. Nonetheless, insights into the economic value associated with infrastructure and its outputs contributes to a clearer picture of how different assets support societal functions and where disruptions may have particularly wide‑ranging effects.
This chapter uses two proxy measures to assess the economic value of infrastructure across sectors and Nordic countries and territories (see Table 9.1). The first examines the economic value of physical infrastructure assets, i.e., the economic value embedded in infrastructure (CDRI, 2023). This measure can be understood as the cost of replacing the infrastructure assets if they were to be destroyed.
The second measure examines the economic value of infrastructure use, i.e., the value of outcomes generated by its use (Batista e Silva et al., 2019). This includes four metrics: energy production, industrial turnover, freight transport and annual expenditure for social infrastructure. In this chapter, this measurement is analysed in relation to population size, to explore how infrastructure use and economic activity intersect with settlement patterns across the Nordic Region.
GIRI Index | HARCI-EU | |
|---|---|---|
What is measured? | Estimated replacement cost of physical infrastructure | Economic value generated by the use of specific services provided by infrastructure |
Interpretation | Exposed economic value if infrastructure is damaged or destroyed | The economic value generated from the infrastructure |
Sectors/variables included |
|
|
How data is used for analysis in this chapter | Cross-country and cross-sectoral comparison of infrastructure costs | Municipal level comparison of the value generated from infrastructure relative to population size |
Table 9.1: Data sources used in Chaper 9. |
Although these two economic measures do not capture all functional, operational, or economic dimensions of criticality, and should not be used as direct measures of criticality or for ranking countries, they enable comparative analysis across the Nordic Region. They help to identify the infrastructure sectors and locations that carry the greatest relative economic weight. An understanding of the relative value of infrastructure assets and their use also provides an important basis for discussing vulnerability and resilience across Nordic regions.
Economic value of infrastructure assets
The EU-level CER Directive identifies 11 critical sectors,
including energy, transport, water, and digital infrastructure (European Union, 2022). While all infrastructure within these sectors provides important services, the degree of economic value varies across sectors and individual assets in terms of their distribution, scale, and economic value.
Energy (electricity, district heating and cooling, oil, gas, hydrogen), transport (air, rail, water, road, public transportation), banking, financial market infrastructure, health, drinking water, wastewater, digital infrastructure, public administration, space and production, processing and distribution of food.
In the following analysis, data derived from the GIRI Index (CDRI, 2023) are used to estimate the economic value of infrastructure assets across Nordic countries and territories (see Box 9.1). This value reflects the economic investment embedded in infrastructure and serves as a proxy for potential economic losses if these assets were damaged or destroyed. The estimates are based on national capital stock, wealth data, and sector-specific indicators, which facilitate comparisons of the relative economic value of infrastructure across sectors and regions.
National comparison of infrastructure assets value
The variation across the Nordic countries and regions is reflected in the value of their infrastructure assets. Figure 9.1 illustrates the relationship between the total number of critical infrastructure assets (x-axis) and their estimated total economic value (y-axis) across the Nordic countries and autonomous territories. The data are based on estimates for six infrastructure sectors: land transport (roads and railways); air and water transport (ports and airports); energy; water and wastewater; oil and gas; and telecommunications. The bubble size represents infrastructure value per capita, which facilitates comparisons between countries of different population sizes.
Figure 9.1: Total estimated economic value of infrastructure assets in the Nordic countries. Source: Nordregio calculations based on data from GIRI-Index (CDRI, 2023), which estimates the exposed economic value of infrastructure. Bubble colours represent countries, and bubble size indicates infrastructure value per capita. Data covers land transport (roads, railways) sea and air transport (ports, airports), energy (generation, transmission, distribution), water and wastewater, oil and gas, and telecommunications. |
Overall, the figure shows that the estimated total value of infrastructure assets aligns more closely with population size than with geographical area. Sweden, the most populous country, has both the highest total infrastructure value and the largest number of assets. Norway follows, with a population around half that of Sweden, but records the highest per-capita value, largely due to capital-intensive sectors such as oil and gas. Denmark, with a population similar to Norway’s, also shows a comparable total infrastructure value, despite its land area being only about 11% of Norway’s.
However, different patterns are seen in Finland, which has a population and land area comparable to those of Norway, but a higher number of assets and a lower total infrastructure value. This results in the lowest per-capita value of the Nordic countries, which indicates a network composed of lower-value or less capital-intensive infrastructure. Iceland records a per capita value similar to that of Denmark, despite being about 2.5 times larger in land area and having a population roughly 15 times smaller.
The autonomous territories further illustrate the limited influence of territorial size. Greenland and the Faroe Islands each have around 55,000 inhabitants and display similar infrastructure counts and values, even though Greenland is more than 1,500 times larger in land area.
Sectoral composition
While there are clear differences in the estimated total value of infrastructure assets across the Nordic countries and territories, the way this value is distributed across sectors is similar across the region. To compare how the different infrastructure sectors relate to each other, Figure 9.2 depicts the relative share of each infrastructure sector’s economic value. Roads and railways account for the largest share of economic value in all countries and territories except Greenland, ranging from 42% in Denmark and the Faroe Islands to 50% in Iceland. The second-largest capital stock in all countries and territories, with the exception of Norway, is tied to energy infrastructure, ranging from 15% in Norway to 22% in Denmark. Notably, the economic value of Norway’s oil and gas infrastructure (18%) exceeds the value of its included energy infrastructure (15%). With its minimal road and rail networks, Greenland is an outlier: transport infrastructure accounts for less than 1% of its total infrastructure value, while energy accounts for 39%.
Figure 9.2: Relative economic value of infrastructure for critical sectors. Source: Nordregio calculations based on data from GIRI Index (CDRI, 2023), which estimates the total value of infrastructure on a country and territory level. The sectors include land transport (roads, railways); sea and air transport; (ports and airports); energy (power); water and waste infrastructure; oil and gas; and telecommunications. |
Interpreting the economic value of infrastructure assets
The estimates in Figures 9.1 and 9.2 indicate the economic value of infrastructure assets and, therefore, the scale of potential economic losses if those assets were damaged or destroyed. However, the data should not be interpreted as a direct measure of the criticality of different sectors or their infrastructure, as the strategic importance of an asset does not always correspond to its economic value. Criticality depends on many factors, such as societal impacts, availability of substitutes, interdependencies and the likelihood of cascading failures. Infrastructure that neither requires substantial investment nor generates high levels of economic output may still be crucial for enabling logistics, distributing essential services or maintaining operational continuity across larger systems.
For example, ports and airports account for a relatively small share of total economic value, yet play important roles in connectivity and trade, particularly in remote areas. Similarly, while telecommunications appear to have modest economic value, they are in fact deeply embedded in communication, emergency response, healthcare, public administration and financial systems. Recent hybrid attacks in the Baltics have highlighted redundancy challenges for communication infrastructure, as disruptions risk triggering cascading effects across society (Sari, 2025). The Arctic region faces unique challenges due to harsh weather conditions and reliance on foreign-controlled systems, which make it particularly vulnerable to high-impact failures and the lack of replacements (Lai & Flensburg, 2023; Thomson Ek & Wendt-Lucas, 2025).
As such, while the economic values presented in Figures 9.1 and 9.2 provide insight into the distribution and scale of infrastructure investments, they represent only one dimension of criticality. Sectors with limited redundancy, strong interdependencies or high cascade potential may, in practice, be more critical than their economic value suggests.
Box 9.1. Calculating the economic value of infrastructure assets
The economic value of the infrastructure assets in Figures 9.1 and 9.2 is derived from the Global Infrastructure Risk Model and Index (GIRI) provided by the Coalition for Disaster Resilient Infrastructure (CDRI, 2023). GIRI applies an Infrastructure Exposure Model (IEM) that combines top-down and bottom-up approaches to estimate infrastructure value. The top-down component uses macro-economic indicators toassess the total national value of infrastructure, including national capital stock and the share of infrastructure within overall wealth. This is complemented by a bottom-up approach that spatially allocates infrastructure value using GIS vector data and publicly available information on infrastructure assets and networks. Sector-specific indicators and indicative unit costs are used to estimate economic values, resulting in modelled replacement costs that represent the exposed economic value of infrastructure across six sectors. These estimates enable comparative analysis across countries and infrastructure sectors. For this analysis, GIRI data on infrastructure value and asset counts for each Nordic country and territory were converted from USD to euros and compared across sectors, asset counts, and per capita.
Economic value of infrastructure usage in relation to population
As policy on critical infrastructure increasingly shifts from protecting individual assets to ensuring the services they enable, it becomes relevant to examine economic measures of infrastructure use (see Box 9.2). This perspective allows comparison not only across countries, but also at the municipal level within them. Although governance and financing arrangements vary across the Nordic countries, municipalities and regions commonly play key roles in delivering infrastructure-related services (Slätmo & Bogason, 2024).
This analysis examines the economic value of infrastructure use based on four metrics: energy production, industrial turnover, freight transport, and annual expenditure on social infrastructure, all of which are derived from the HARCI-EU Index (Batista e Silva et al., 2019). These data are analysed in relation to permanent population size in Nordic municipalities and regions (see Map 9.1). Combined, these variables highlight the areas where infrastructure use value and population size align or diverge, and identify municipalities where people and high-value infrastructure are spatially co-located. The analysis reveals patterns of disproportionate vulnerability, i.e., areas in which infrastructure disruptions could have wide-ranging economic impacts, as well as areas with significant operational responsibilities for services that extend beyond local boundaries. However, this comparison does not imply that infrastructure use for the included measures primarily benefits the local population, nor that areas with lower infrastructure value are therefore less critical from a societal perspective. Rather, it reflects spatial exposure, and shows where disruptions or hazards may have both local and wider effects.
Map 9.1 applies a bivariate 3×3 classification, combining two variables: economic infrastructure use value and population size. This results in nine categories. For analytical clarity, the chapter focuses on the four corner categories, which represent the most contrasting combinations of these variables. Dark colours indicate high economic value of infrastructure use, while light colours indicate low value. Pink represents larger populations, and green represents smaller populations:
- Dark pink: high economic value + large population
- Dark green: high economic value + small population
- Light pink: low economic value + large population
- Light green: low economic value + small population
Together, these patterns illustrate how different regions face distinct resilience challenges and vulnerabilities, which underscores the need for differentiated, place-based resilience policies. The following sections examine each pattern in more detail.
Map 9.1: Infrastructure value in relation to population. Source: National Statistics Institutes (NSIs) and Nordregio elaboration on the HARCI-EU dataset (Batista e Silva et al., 2019) with national population figures of permanent populations as of 1 January 2019. The map illustrates the relationship between the total population and the mean economic value of infrastructure use across Nordic municipalities. The data for infrastructure value include energy production, industrial turnover, freight transport, and annual expenditure for social infrastructure. Nordic average economic value: 1.5 |
See and download map in |
High infrastructure value: Systemic hotspots and vulnerabilities
Nordic municipalities with a high economic value of infrastructure use (shown in dark colours in Map 9.1) are found both in urban regions with large populations and in rural regions with small ones. While high infrastructure value can be found in both contexts, population size has an influence on specific resilience challenges and governance needs.
High economic infrastructure value + large population (dark pink)
Most Nordic municipalities with high economic value in terms of infrastructure use and large populations are located in urban and peri-urban areas, such as Haugesund (Norway), Reykjavík (Iceland), Gladsaxe (Denmark), Solna (Sweden) and Helsinki (Finland). In these municipalities, infrastructure supports large populations and multiple interconnected services, which makes them potential systemic hotspots, in which disruptions in one system can quickly cascade into others and affect many people simultaneously. Resilience planning in these areas should therefore consider not only which infrastructure systems and actors are critical, but also how these systems interact. Although urban areas may benefit from closer proximity to backup options, their high degree of interdependence requires flexible and well-coordinated systems to prevent cascading failures.
High economic infrastructure value + small population (dark green)
Municipalities with a high economic value in terms of infrastructure use, but small populations often host infrastructure that serves much larger areas, such as major power plants, industrial sites, ports or transport hubs. Although these municipalities are relatively few in number, as shown on the map, they may bear a disproportionate share of the accountability for the operation and maintenance of infrastructure that supports regional or national systems.
While formal responsibility for infrastructure, such as industrial facilities or power generation, is typically tied to private or public entities, municipalities with small populations can still play a crucial role in hosting, operating, and maintaining these assets, thereby contributing to the resilience of infrastructure serving communities some distance away. Disruptions affecting infrastructure in these locations may therefore have disproportionate impacts and create vulnerabilities that extend well beyond the local area. Denmark stands out for consistently exhibiting high overall infrastructure values. In this context, some island municipalities with relatively small populations, such as Fanø, illustrate how disproportionate operational responsibilities and vulnerabilities can emerge in sparsely populated areas that host infrastructure of wider national importance.
Low infrastructure value: Local dependence and limited redundancy
Municipalities with a lower economic value in terms of infrastructure use, as shown in light colours in Map 9.1, often have small populations (light green). While fewer in number, this category also includes municipalities with large populations (light pink). Despite their lower estimated economic value, infrastructure in these areas can still be critical for local communities, particularly where alternative services or backup options are limited.
Low economic infrastructure value + small population (light green)
Municipalities in this category are typically in remote or sparsely populated regions, characterised by limited energy production, low industrial turnover, limited freight transport, and lower expenditure on social infrastructure. This pattern is especially pronounced in Iceland, but also appears in other Nordic countries, for example, in Røst (Norway), Árneshreppur (Iceland), Ydre (Sweden) and Enonkoski (Finland). These patterns may reflect lower infrastructure investment as a consequence of small population size, but they may also indicate areas where population levels remain low due to limited infrastructure and sparse service provision. In either case, infrastructure redundancy is likely to be low, leaving communities with few viable alternatives in the event of disruptions.
Low economic infrastructure value + large population (light pink)
The map shows a limited number of municipalities with low economic value, despite large populations. This reflects limited local contributions to the included services (e.g., energy production or freight transport), which indicates a high level of dependence on infrastructure located elsewhere. These municipalities may have fewer local obligations related to operating, maintaining and ensuring place-based infrastructure resilience. They remain vulnerable to disruptions in external systems. In such contexts, criticality arises from limited redundancy and a high degree of dependency on external supply, rather than the scale of local infrastructure assets.
Box 9.2. Calculating the economic value of infrastructure outputs
Map 9.1 combines two datasets: HARCI-EU economic infrastructure data and population data. The HARCI-EU dataset provides a spatial representation of the economic value of critical infrastructure across Europe (Batista e Silva et al., 2019). It harmonises multiple European geospatial and statistical data sources and aggregates them into 1 km grid cells, using sector-specific proxies to capture the distribution and concentration of infrastructure. Infrastructure value is expressed as an index, rather than a direct monetary value. Although published in 2019, the dataset remains suitable for regional comparison, as changes to the spatial distribution of major infrastructure systems are gradual.
The population data represent the resident population as of 1 January, based on official population registers, and reflect permanent rather than seasonal populations.
For this analysis, HARCI-EU raster data were aggregated to the municipal level by converting grid cells to points, removing zero values, merging sectoral layers, and calculating the mean infrastructure value within each municipality. These values were then combined with population data to create a bivariate map. Infrastructure value and population size were classified separately using a data-driven method in ArcGIS Pro, with class thresholds derived from the statistical distribution of each variable at the Nordic level. This approach assigns municipalities to relative categories of low or high infrastructure value, and small or large population, ensuring a balanced and comparable visual representation across the Nordic Region.
Conclusion
As critical infrastructure policy shifts from protecting individual assets towards ensuring the continuity of societal services, it is important to understand the economic significance of infrastructure assets and their use. Economic measures help to illustrate both the potential losses associated with disruptions and the broader societal importance of infrastructure.
Infrastructure criticality takes different forms across the Nordic Region. When comparing the economic value of infrastructure in different sectors, land transportation stands out as the sector with highest total value, accounting for up to half of total infrastructure value in most Nordic countries and territories. The analysis also reveals differences in how infrastructure use and settlements interact across the Nordic Region.
High-value infrastructure use is found in municipalities with both small and large populations, but the associated roles and challenges differ. Some small municipalities host infrastructure that serves much wider regions. They have significant operational and crisis-management responsibilities for nationally important systems. By contrast, some large population centres rely heavily on infrastructure located elsewhere, which increases their exposure to external disruptions.
Together, these findings highlight the need for differentiated, place-based resilience strategies that balance robustness and redundancy across the Nordic Region. For example, large urban centres with high infrastructure use value can function as systemic hotspots, where disruptions can potentially cascade across multiple sectors. Sparsely populated municipalities that host key infrastructure may be saddled with disproportionate operational responsibilities. Conversely, densely populated areas with limited local infrastructure value may be particularly vulnerable due to their dependence on external supply.
While these economic measures of infrastructure value highlight areas in which economic value is concentrated, they do not capture cascading effects that shape the impact of disruptions and the understanding of their criticality. Complementary assessments of strategic functionality and crisis‑related dependencies can further strengthen evaluations of critical infrastructures in the Nordic Region.
References
Batista e Silva, F., Forzieri, G., Marin Herrera, M. A., Bianchi, A., Lavalle, C. & Feyen, L. (2019). HARCI-EU, a harmonized gridded dataset of critical infrastructures in Europe for large-scale risk assessments. Scientific Data, 6(1), 126. https://doi.org/10.1038/s41597-019-0135-1
CDRI. (2023). Building & infrastructure | GIRI [Coalition of Disaster Resilient Infrastructure]. Global Infrastructure Resilience: Capturing the resilience dividend - A Biennial Report from the Coalition for Disaster Resilient Infrastructure. https://giri.unepgrid.ch/facts-figures/building-infrastructures
European Commission. (2025). EU Preparedness Union Strategy.: Vol. Secretariat General. Publications Office. https://data.europa.eu/doi/10.2792/1964849
European Union. (2022). DIRECTIVE (EU) 2022/2557 OF THE EUROPEAN PARLIAMENT AND OF THE COUNCIL of 14 December 2022 on the resilience of critical entities and repealing Council Directive 2008/114/EC (Official Journal of the European Union No. L 333/164). https://eur-lex.europa.eu/eli/dir/2022/2557/oj/eng
Forzieri, G., Bianchi, A., Silva, F. B. e, Marin Herrera, M. A., Leblois, A., Lavalle, C., Aerts, J. C. J. H. & Feyen, L. (2018). Escalating impacts of climate extremes on critical infrastructures in Europe. Global Environmental Change, 48, 97–107. https://doi.org/10.1016/j.gloenvcha.2017.11.007
Lai, S. S. & Flensburg, S. (2023). Gateways: Comparing Digital Communication Systems in Nordic Welfare States (p. 205) [Application/pdf, application/epub+zip]. Nordicom, University of Gothenburg. https://doi.org/10.48335/9789188855848
Larsson, S. & Rhinard, M. (Eds). (2020). Nordic Societal Security: Convergence and Divergence. Routledge. https://doi.org/10.4324/9781003045533
Nordic Council. (2023, March 15). International Strategy of the Nordic Council. https://doi.org/10.6027/politiknord2023-718
Pursiainen, C. (2018). Critical infrastructure resilience: A Nordic model in the making? International Journal of Disaster Risk Reduction, 27, 632–641. https://doi.org/10.1016/j.ijdrr.2017.08.006
Pursiainen, C. & Kytömaa, E. (2023). From European critical infrastructure protection to the resilience of European critical entities: What does it mean? Sustainable and Resilient Infrastructure, 8(sup1), 85–101. https://doi.org/10.1080/23789689.2022.2128562
Sari, A. (2025). Protecting maritime infrastructure from hybrid threats: Legal options. [Hybrid CoE Research Report 14.].
Slätmo, E. & Bogason, Á. (2024). Nordic rural policies for future service needs. Nordisk Administrativt Tidsskrift, 101(1). https://doi.org/10.7577/nat.5800
Thomson Ek, H. & Wendt-Lucas, N. (2025). Security threats to a digital world – Lessons on securing digital infrastructure in a changing environment. DigiHub. https://nordregioprojects.org/digihub/news/security-threats-to-a-digital-world-lessons-on-securing-digital-infrastructure-in-a-changing-environment/
UNDRR. (2017). Definition: Critical infrastructure | UNDRR. United Nations Office for Disaster Risk Reduction (UNDRR). https://www.undrr.org/terminology/critical-infrastructure