This chapter examines how the regional attractiveness framework strengthens evidence-based territorial policymaking in Latvia. The chapter presents five practical use cases demonstrating how attractiveness indicators can support the full policy cycle. These cover: identifying territorial strengths and policy trade-offs; detecting untapped assets and structural mismatches; revealing opportunities for inter-municipal co-operation; grouping territories facing shared challenges to design common solutions; and monitoring regional progress over time. Applied across Latvia's municipalities, the framework surfaces persistent gaps in economic performance, connectivity and service accessibility alongside underutilised natural, cultural and human capital. The chapter concludes that realising the framework's potential requires its systematic integration into strategy design, investment programming and evaluation - moving beyond ad hoc diagnostics toward a genuine instrument for place-based policy.
Adopting the OECD Regional Attractiveness Approach to Enhance the Capacity of Local and Regional Governments in Latvia
Abstract
Latvia’s territorial development policy can be strengthened through a more systematic use of multidimensional, granular data. Conventional indicators such as GDP, productivity or employment remain of key importance, but they are often insufficient to fully capture the wider set of factors that influence a territory’s capacity to attract and retain investment, talent and visitors, shaping their competitiveness (OECD, 2025[1]). For instance, knowledge hubs – such as universities – and transport infrastructure can play an important role in attracting foreign direct investment (FDI), while talent attraction and retention are influenced by factors such as housing affordability and the quality of broadband connectivity (OECD, 2023[2]). In this context, the OECD regional attractiveness framework helps policymakers better understand the multidimensional strengths and constraints of Latvia’s territories. More details on the framework are presented in (Box 2.1).
Latvia is the first OECD country to adopt municipal-level attractiveness indicators to reinforce local development policy. While the OECD regional attractiveness framework was originally developed at the regional level, analysing development trajectories at a granular scale helps to uncover territorial disparities, local assets and place-specific constraints that can remain obfuscated by regional averages. It can also help policymakers design more precise interventions, tailor public goods and services to local needs, and support more balanced growth across localities (Seunga Ryu et al., 2024[3]).
This chapter examines how the OECD regional attractiveness framework can promote more effective local policymaking in Latvia. It is structured through five practical use cases on how attractiveness indicators support the policy cycle (see Figure 2.1): identifying territorial strengths and trade-offs; 2) detecting untapped potential and structural mismatches; 3) supporting territorial co-operation; 4) grouping territories facing similar challenges for more targeted interventions; and 5) strengthening capacity for monitoring attractiveness outcomes over time. In doing so, it shows how multidimensional indicators can serve not only as a diagnostic exercise, but also as a practical instrument for strategic planning, prioritisation and evidence-based territorial development.
The OECD regional attractiveness framework1 provides a comprehensive, systemic lens to help policymakers understand a territory’s competitive position and resilience. It was developed in response to a changing context in which regions face transitions linked to global value chain reconfiguration, demographic change, climate pressures, technological transformation and geopolitical uncertainty, while increasingly competing to strengthen their attractiveness to investment, talent and visitors to seize emerging opportunities. In this context, the framework offers a structured, internationally comparable and multidimensional tool to help policymakers identify development priorities, and design and monitor targeted interventions to enhance local resilience, rather than relying on one-size-fits-all solutions. The framework includes around 50 indicators at the TL3 level and more than 60 indicators at the TL2 level.
Indicators are grouped into fourteen dimensions across six multidimensional domains. The domains of attractiveness incorporate an array of indicators essential to territorial competitiveness and well-being: economic performance, cultural and visitor appeal, land resilience and housing, resident well-being, connectedness, and natural environment, each capturing a distinct dimension of what makes a territory attractive to investors, talent, and residents. Figure 2.2 illustrates the application of the framework through an attractiveness compass that situates territorial performance relative to national and EU peers.
Source: Own elaboration based on OECD (2023[2]), using the indicators presented in Annex A.
The OECD regional attractiveness framework can help policymakers identify territorial development needs while understanding the trade-offs that often arise across policy objectives. As development trajectories are shaped by localised assets and challenges, robust territorial data are essential to identify the drivers of underperformance, uncover underused local assets and design differentiated interventions that promote sustainable territorial growth while reinforcing national competitiveness (OECD, 2025[4]). In this context, the framework’s multidimensional perspective is valuable not only for diagnosing key strengths and constraints relevant to place-based policy, but also for assessing how interventions in one area may generate effects elsewhere. For example, investments in connectivity may strengthen accessibility and economic opportunities while increasing pressures on land use or ecosystems; tourism promotion may support local income and jobs while creating strains on housing affordability, public services or the environment; and growth strategies concentrated in dynamic urban areas may risk widening disparities with rural municipalities facing demographic and economic decline.
Several strengths emerge when analysing multidimensional indicators in Latvia, particularly in natural capital, renewable energy, and cultural amenities. Across regions, strong natural capital stands out as a shared asset, reflected in high and expanding forest cover, with all the municipalities performing better than the EU median in these indicators (Figure 2.3). Many territories in Latvia also perform favourably in renewable electricity generation and show comparatively low exposure to wildfire risk. In parallel, a number of municipalities demonstrate strong tourism potential, supported by a high density of museums and galleries, theatres, and strong business activity in the creative sector (Figure 2.3), although this has not been matched by tourism attraction. These characteristics provide an important foundation for sustainable development strategies centred on quality of life, green economies, and place-based tourism. This picture can be further complemented by embedding sustainable tourism indicators – an area in which the OECD is working to support member countries (OECD, Forthcoming, 2026[5]).
At the same time, many Latvian municipalities face constraints that limit their ability to translate local assets into stronger economic outcomes. Most of the municipalities exhibit underperforming economic performance relative to EU peers, reflected by lower GDP and productivity (Figure 2.3), particularly outside the main urban centres. Accessibility constraints also emerge frequently, including lower road quality, sparse transport networks, weaker active mobility infrastructure, and underperforming digital connectivity (Figure 2.3). In addition, tertiary educational attainment remains low in many territories, pointing to difficulties to tap in emerging high-value industries (Figure 2.3). Lastly, a number of indicators exhibit high dispersion, reflecting diverging local trajectories, such as measures of business dynamism, tourism performance, housing, and health. Together, these challenges reduce the capacity of municipalities to attract investors, talent and visitors to promote local economic growth and well-being.
In particular, regional-level evidence points to complex housing challenges. The European Commission (2026[6]) highlights that housing markets in Latvia remain underdeveloped outside major economic centres, alongside an outdated housing stock that reflects decades of underinvestment, ageing multi-apartment buildings, and limited renovation and energy-efficiency improvements. This is consistent with regional data showing that the share of dwellings built before 1980 exceeds the EU regional average (61.0%) in all five Latvian regions, particularly in Vidzeme (75.9%) and Kurzeme (75.0%). Moreover, Latvia’s position as the EU country with the second-highest overcrowding rate provides a supplementary narrative to the high vacancy levels: four of the five Latvian regions record shares of unoccupied dwellings well above the EU regional average (18.9%), particularly Latgale (30.2%), Kurzeme (28.7%) and Vidzeme (28.7%). In this context, the municipal-level indicator used in the attractiveness approach, the House Price Index that captures housing price dynamics, is information that should be considered alongside regional evidence on housing quality, overcrowding, deprivation, vacancy and dwelling age.
Each cell shows how many municipalities fall within each percentage-deviation range for a given indicator.
Note: For indicators marked with an asterisk, higher values are interpreted as having a negative impact, either due to the characteristics of the variable or, in the case of soil moisture only, because the EU median is negative. Colours are therefore reversed: blue indicates values below the EU median, while red indicates values above the EU median. Values below -100% correspond to indicators with negative values where the EU median is positive.
Source: Own elaboration based on OECD (2023[2]), using the indicators presented in Annex A.
Trade-offs between attractiveness dimensions should be considered when formulating development policies. As shown in Box 2.2, Saldus municipality overperforms EU peers in environmental and cultural dimensions. However, these strengths are accompanied by challenges in connectivity and economic performance, including relatively low digital infrastructure quality and limited transport accessibility. These constraints limit the municipality’s ability to fully leverage its assets for talent and tourism attraction. In this context, investments in physical connectivity could improve accessibility to public services, while digital infrastructure has been recognised as a driver of talent attraction (OECD, 2023[2]). These factors have also been robustly shown to support investment attraction, which is needed to revitalise the underperforming labour market (Khadaroo and Seetanah, 2008[7]; OECD, 2023[2]). At the same time, policies promoting sustainable tourism could help translate environmental and cultural strengths into local value creation and strengthen linkages with other economic sectors (Romão and Neuts, 2017[8]).
More broadly, effective territorial development requires balancing growth objectives with the preservation of the assets on which long-term attractiveness depends. In the case of Saldus, ensuring that infrastructure development is aligned with environmental protection and cultural heritage objectives remains critical to preserving the assets that underpin its attractiveness. More broadly, the case of Saldus illustrates how multidimensional territorial information can help policymakers move beyond single headline indicators to understand how domains are inter-linked. This type of evidence is essential to diagnose local development needs, identify policy trade-offs, and design interventions tailored to place-specific assets and bottlenecks (OECD, 2025[4]; JRC, 2022[9]) . In doing so, it can help municipalities better translate existing strengths into more inclusive and sustainable growth, while contributing to stronger national competitiveness.
Saldus municipality performs strongly in environmental and cultural dimensions, with a tree cover rate of 67% (EU median of 32%) and strong performance in cultural capital indicators when compared to EU peers (Figure 2.4). Together, these assets contribute to the municipality’s potential to attract visitors and residents seeking high environmental quality and cultural amenities. However, areas of underperformance are observed in its connectedness and economy. Digital download speeds (71 Mbps) and the share of paved roads (52%) are well below EU medians, while both GDP per capita and GVA per capita reach about 65% of EU levels. At the same time, unemployment is more than 1.5 times the EU figure. These aggregate challenges, however, vary across the municipal territory: for instance, while Saldus municipality benefits from good physical accessibility due to its location on the A9 national road connecting Riga and Liepāja, rural areas may face more limited local road quality, public transport frequency and access to services. Taken together, these gaps present a barrier to the municipality’s ability to fully leverage its assets for economic development, tourism and talent attraction.
Addressing these challenges requires balanced interventions that strengthen local economic opportunities while preserving the environmental and cultural assets that underpin the municipality’s attractiveness. Targeted investments in areas underperforming in digital and transport connectivity could help support tourism development and facilitate remote work opportunities. At the same time, policies promoting sustainable tourism and nature-based economic entrepreneurship could help translate the municipality’s natural capital and cultural heritage into new sources of economic dynamism. Infrastructure investments should therefore be designed in line with sustainable land-use planning and environmental protection objectives, for example by prioritising active mobility infrastructure, safeguarding key landscapes and aligning housing development with spatial planning strategies that protect forest ecosystems and cultural sites. Complementary measures, such as incentives to attract remote workers and creative industries, could further strengthen the local economy while preserving Saldus’ attractiveness drivers.
Source: Own elaboration based on OECD (2023[2]), using the indicators presented in Annex A.
Place-based policies can help unlock latent territorial assets by identifying, mobilising and leveraging local potential in ways that reflect each territory’s specific conditions, strengths and constraints (Rodriguez-Pose and Wilkie, 2016[10]; OECD, 2011[11]). Achieving this requires a robust understanding of local economic dynamics and territorial assets in place, including how different dimensions of attractiveness interact. In practice, a territory’s attractiveness is rarely uniform, as strong performance in one area often coexists with underperformance in another. Thus, the OECD framework helps policymakers not only to identify strengths and challenges, but also to detect mismatches that may reveal structural barriers preventing local assets from translating into stronger economic outcomes. For example, a region with high innovation capacity but low productivity, or with significant natural and cultural assets but limited tourism performance, may point to local barriers that better-targeted policies could help address, thereby enabling local assets to translate into greater economic value.
A common pattern in Latvia is the presence of strong natural and cultural assets that are not yet fully converted into tourism demand and wider local value. This is particularly important for regions with more limited economic performance, as OECD evidence indicates that tourism can be an important driver of economic development, contributing directly to GDP, services exports, employment and business activity (OECD, 2024[12])2. For example, Latgale Planning Region and its constituent municipalities combine extensive forests, lakes, protected areas and cultural infrastructure with relatively low appeal to visitors, measured by reduced overnight stays and low foreign visitor shares. A second example concerns housing advantages that are not fully converted into population attraction. Municipalities within Zemgale Planning Region, such as Bauska, offer relatively good environmental conditions and lower housing pressures than national and EU peers, yet face challenges to strengthen local labour markets and retain talent, with the region recording negative net inter-regional migration in each year of the last ten of available data, 2015–2024 (OECD, 2026[13]). A third recurring pattern is where proximity to metropolitan markets is not fully reflected in local economic dynamism. Several municipalities surrounding Riga benefit from access to the capital’s labour market and infrastructure but still record uneven economic outcomes. Finally, some territories possess strong renewable energy capacity and natural resources without a corresponding concentration of higher value-added green economic activity.
Jūrmala State City, located in the Riga planning region, shows contradictory results in regional education, innovation and productivity outcomes (Figure 2.5). The municipality performs strongly in indicators related to human capital, with 40% of its population holding tertiary education, well above the EU median (35%) and among the highest shares in Latvia. It also shows very strong performance in entrepreneurship, with an enterprise creation rate of 5%, ranking first nationally, suggesting a dynamic local business environment. In addition, Jūrmala benefits from strong tourism activity and relatively good connectivity, reflecting its proximity to Riga and its position as one of Latvia’s main tourism destinations. However, these favourable conditions coexist with relatively limited economic performance, as both GDP per capita and GVA per worker remain well below EU benchmarks. Two dynamics likely explain this gap: much of Jūrmala's educated and entrepreneurial population may be contributing their economic input in Riga rather than locally, reflecting the city's functional integration into the wider metropolitan area. The local economy itself is concentrated in tourism and hospitality – sectors that tend to generate lower productivity and value-added than the knowledge-intensive industries that Jūrmala's human capital profile could otherwise generate.
Identifying these mismatches helps policymakers to understand the structural barriers shaping local development outcomes. In the case of Jūrmala and other non-metropolitan areas, this implies strengthening metropolitan and peripheral linkages so that municipalities can better capture spillovers from nearby growth centres, including access to jobs, innovation ecosystems, consumer markets and specialised services (OECD, 2019[14]; Marshalian, Chan and Bournisien de Valmont, 2023[15]). Specific strategies include aligning fiscal incentives with partnership goals, ensuring that co-ordination incentives are embedded in spatial planning legislation, and creating legal partnership mechanisms such as shared service agreements (OECD, 2019[14]). Moreover, promoting innovation in peripheral areas is essential to tap into localised assets, particularly by facilitating talent mobility to these territories (Marshalian, Chan and Bournisien de Valmont, 2023[15]) and, in consequence, strengthening their attractiveness. Finally, as highlighted in the OECD Principles on Rural Policy, providing accessible data for non-metropolitan areas is essential to unlock their latent potential (OECD, 2019[14]).
Source: Own elaboration based on OECD (2023[2]), using the indicators presented in Annex A.
The OECD attractiveness framework supports policymakers in identifying opportunities for co-operation across territories (Jossec and Bandeira Morais, 2026[16]). By providing comparable indicators at a granular territorial scale, the framework helps make territorial disparities and complementarities visible, enabling policymakers to identify where co-ordinated responses across neighbouring jurisdictions may generate greater impact. As previously highlighted by the OECD, inter-municipal co-operation has proven to be an effective instrument across many OECD countries and EU Member States for addressing a range of local government challenges, including limited resources, administrative fragmentation, the investment burden faced by individual municipalities, and the more efficient organisation and delivery of public services (OECD, 2024[17]).
By leveraging multidimensional indicators, the framework enables the strategic use of complementary assets. For instance, municipalities with strong entrepreneurial activity may benefit from co-operating with neighbouring territories that host higher education institutions or research centres, enabling stronger innovation diffusion and knowledge spillovers across territories. Likewise, municipalities rich in natural or cultural assets may co-ordinate tourism strategies with nearby territories that offer stronger connectivity, accommodation capacity or tourism infrastructure, helping develop more integrated and sustainable tourism ecosystems. Such co-operative approaches can allow neighbouring territories to leverage their respective strengths, distribute economic opportunities more broadly and strengthen the collective attractiveness of territories.
The case of the neighbouring municipalities of Jelgava and Bauska in the Zemgale planning region illustrates how the framework can reveal complementarities between territories. Jelgava performs relatively well in labour market indicators compared with nearby municipalities (Box 2.3). However, the municipality faces constraints in housing conditions that may limit its ability to attract and retain workers. By contrast, neighbouring Bauska Municipality presents more favourable real estate conditions, which is accompanied by more limited labour market performance. Taken together, these patterns suggest potential complementarities between the two municipalities, where improved connectivity could help align labour market opportunities in Jelgava with more accessible housing in Bauska.
Co-operation is especially relevant when neighbouring municipalities face similar structural constraints. Processes such as population decline, labour market shortages, ageing, or climate-related risks often extend beyond administrative boundaries and require co-ordinated responses at the scale of functional areas. In such contexts, isolated policy actions may be insufficient or less effective, while joint strategies can help pool resources, achieve economies of scale and ensure policy coherence across territories. Moreover, co-operation can strengthen institutional capacity amid structural constraints, particularly in smaller municipalities with limited administrative and financial resources, by enabling the sharing of expertise and the joint delivery of services. For example, several neighbouring municipalities in Latgale Planning Region face a combination of population decline, more limited labour-market outcomes and longer travel times to key services. Co-ordinated approaches across these municipalities could help sustain access to healthcare and education through shared service provision, improve regional transport links, and jointly promote investment and skills attraction strategies that would be harder to deliver effectively through isolated local action.
Lastly, insights from the framework can facilitate the prioritisation of cross-border co-operation to leverage complementary territorial assets and address shared challenges. This is particularly important in the context of programmes such as Interreg in the EU, where identifying projects with the strongest cross-border relevance and impact remains a key policy priority (European Court of Auditors, 2021[18]). For example, the neighbouring territories of Latgale Planning Region and Utena County in Lithuania display complementary characteristics that could support deeper co-operation. While Latgale offers relatively stronger education assets, Utena performs better on innovation indicators, suggesting scope for joint initiatives linking skills development, applied research and business support in sectors such as wood industries (OECD, 2025[19]). The two areas also share rich cultural and natural resources, while Utena attracts higher tourism flows, creating opportunities for co-ordinated visitor routes, joint destination branding and cross-border tourism infrastructure (Ibid.).
The case of the neighbouring municipalities of Jelgava and Bauska in the Zemgale planning region illustrates how the attractiveness framework can reveal complementarities between territories. Jelgava performs relatively well on labour market indicators compared with neighbouring municipalities. Its unemployment rate is close to the EU median, and the municipality records strong entrepreneurial activity, with an enterprise creation rate of about 1.5 times the EU median, ranking highest in the region and suggesting a dynamic labour market. However, Jelgava faces constraints in housing affordability, with a House Price Index of 200 (base 100 = 2021) and annual increases nearly three times the EU median in recent years, limiting its ability to attract and retain workers. By contrast, neighbouring Bauska Municipality shows more favourable housing dynamics, with stable or even declining prices in the most recent period for which data are available (2024). Nevertheless, Bauska exhibits more limited labour market performance, with a lower employment rate and higher youth unemployment.
Differences in multidimensional measures help highlight potential complementarities between the two municipalities. Strengthening co-ordination between Jelgava and Bauska, particularly in areas such as transport connectivity, spatial planning and housing development, could help align labour market opportunities in Jelgava with housing availability in neighbouring Bauska. For instance, improved commuting links could allow workers to access employment opportunities in Jelgava while residing in Bauska. By identifying such complementarities, the attractiveness framework helps policymakers move beyond a purely competitive perspective between neighbouring territories and instead promote co-operative approaches to regional development that draw on the strengths and gaps of places in proximity.
Jelgava Municipality Bauska Municipality
Source: Own elaboration based on OECD (2023[2]), using the indicators presented in Annex A.
As highlighted by analysis of the Interreg programme in the EU, robust and comparable territorial data is essential to implement programmes of regional co-operation and their monitoring (European Court of Auditors, 2021[18]). In this respect, the attractiveness approach is particularly valuable, as it offers a consistent multidimensional evidence base to prioritise interventions with the greatest territorial relevance, define measurable objectives, and assess whether co-operation initiatives are delivering tangible outcomes over time, at both regional and municipal levels. At the same time, OECD evidence suggests that data alone is not sufficient to ensure successful territorial co-operation. Effective implementation also depends on enabling governance frameworks, adequate and predictable funding, incentives for municipalities to collaborate, and sufficient administrative and technical capacity (OECD, 2024[17]). Successful examples such as Finland illustrates these conditions in practice, combining a clear legal framework for joint authorities and contractual arrangements with flexible funding models, external oversight, and a mix of voluntary and mandatory co-operation in areas such as regional development and land-use planning (OECD, 2024[20]).
The OECD regional attractiveness framework can support policymakers in identifying families of territories that share similar structural characteristics or attractiveness challenges. By analysing multidimensional indicators across territories, it enables regions to be grouped according to comparable performance profiles in areas such as economic attractiveness, labour markets, housing, connectivity and the environment (Jossec and Bandeira Morais, 2026[16]). This, in turn, can help governments design common support packages and shared solutions tailored to the needs of territories facing similar challenges.
A range of shared development patterns across Latvian territories can also be identified through attractiveness indicators. One group includes the largest development centres, such as those represented in the Latvian Association of Large Cities, including Rīga and Jūrmala, which tend to combine stronger labour-market outcomes, higher incomes and good connectivity, while also facing housing affordability pressures and congestion risks. A second group comprises regional service centres and mid-sized municipalities with well-developed services, such as those grouped under the Latvian Association of Regional Development Centres, including Cēsis, and Sigulda, which often perform relatively well in employment, education and access to services, but face productivity constraints. A third group includes environmentally and culturally rich municipalities such as Ogre and Saulkrasti, where strong environmental quality, cultural amenities or tourism potential coexist with more limited business dynamism or accessibility challenges, as evidenced in Use Case #2.
A group of regions deserving special attention in recent years due to geopolitical uncertainty with neighbouring border countries and long-standing development challenges is Latvia’s eastern border municipalities. This group of municipalities holds unique cultural identities and rich natural landscapes; however, these assets have not insulated them from entrenched economic disparities. These include limited economic performance, limited innovation, higher unemployment, infrastructural gaps, and reduced access to essential services – disparities that hinder their potential to attract and retain people and investment, and which risk exacerbating territorial imbalances and social fragmentation, leaving these places more exposed to shocks, as evidenced by the ongoing security situation (Donoso Salas, Białogłowska and Flood, 2025[21]). The closure of Latvia’s eastern border with Russia and Belarus has resulted in both a direct economic impact and longer-term reputational risks in attracting investors, talent, and visitors (OECD, 2025[19]). In this context, by mapping performance consistently across these territories, the framework enables policymakers to move beyond crisis response and identify where existing assets, including relatively high rates of employer firm creation in the arts, entertainment, and recreation sector (Donoso Salas, Białogłowska and Flood, 2025[21]) can be leveraged as a foundation for place-based recovery strategies, and where cross-border and inter-regional co-operation with neighbouring EU regions along the eastern border could help build shared resilience (Box 2.4).
In this context, the use of multidimensional indicators could inform more targeted regional development programmes – for example, to strengthen the interventions under the Action Plan for the Security and Growth of the Eastern Border Region (Cabinet of Ministers, 2025[22])– aimed at improving connectivity, strengthening labour market opportunities, supporting local entrepreneurship and leveraging natural capital for sustainable economic diversification. Moreover, the identification of common assets in the cultural and creative industries, often overlooked drivers of development, also sheds light on priority sectors that could be further developed. As previously recognised (OECD, 2024[23]), cultural and creative sectors can contribute to local economies by generating employment and entrepreneurship opportunities, particularly for SMEs and young people, strengthening place identity and social cohesion, and supporting tourism through heritage, cultural events and creative experiences. They can also foster innovation spillovers to other sectors, such as digital services, education, manufacturing and hospitality.
For Latvian policymakers, the key priority is to embed this type of territorial segmentation more systematically across the policy cycle. In the policy design phase, it can help identify groups of municipalities facing common opportunities or constraints. During policy design, it can support more differentiated and better targeted interventions instead of uniform approaches. During implementation, it can improve co-ordination across ministries as they devise programmes specific to a subset of places facing unique challenges (e.g. Eastern municipalities, border regions, coastal areas, etc.). Finally, during monitoring and evaluation, it can help assess whether comparable territories are converging or diverging over time and whether policy measures are delivering results (Jossec and Bandeira Morais, 2026[16]).
Going more granular than the Eastern Border Region (EBR), analysis of Eastern Border Municipalities (EBM) in Latvia illustrates how the framework can identify common structural challenges. Across several economic indicators, this group of municipalities perform substantially below the national municipal average. GDP per capita reaches around USD 13,300 (PPP), compared with nearly USD 25,000 in other Latvian municipalities, while gross value added per capita is almost USD 10,000 lower (Figure 2.7). Labour market outcomes also lag, with unemployment exceeding 12% – nearly double that of non-EBM – and lower shares of the population holding tertiary education. Additionally, despite weaker economic performance, housing prices have increased more rapidly in recent years. Tourism activity also underperforms, with less than half the number of overnight stays recorded in non-EBM municipalities. Connectivity remains limited, as reflected in lower shares of paved roads and slower internet speeds. Access to public services is also more constrained, with longer travel times to hospitals and schools. At the same time, EBMs display shared strengths, including higher activity in the creative sector, better air quality, and lower exposure to extreme weather events.
Note: EBM are defined as municipalities bordering Russia and Belarus: Alūksne, Balvi, Ludza, Krāslava and Augšdaugava. Non-EBM correspond to the remaining municipalities, excluding State Cities to avoid comparisons with metropolitan areas. A * indicates indicators for which a lower value is preferred Differences shown in red indicate worse performance in EBM, while those shown in green indicate better performance.
Source: Own elaboration based on OECD (2023[2]), using the indicators presented in Annex A.
The OECD regional attractiveness framework enables a dynamic assessment of municipal and regional performance through attractiveness indicators, allowing policymakers to track how regions evolve over time considering needs and strengths (Use Case #1), structural mismatches (Use Case #2), complementarities (Use Case #3), and shared challenges across groups of regions (Use Case #4). This temporal dimension is essential to move from static diagnosis to evidence-based monitoring and policy iteration (Jossec and Bandeira Morais, 2026[16]).
To ensure successful regional governance reforms, strengthening policy monitoring and evaluation processes is fundamental, especially when reforms aim at enhancing regional competitiveness or implementing place-based policies (OECD, 2022[24]). This will be critical in the context of Latvia’s administrative territorial reform (ATR), where assessing its impact on service provision, accessibility and territorial performance remains a key policy imperative for VARAM in the years to come. In this context, Latvia could further strengthen its system of local performance indicators, RAIM, particularly with regard to the quality and accessibility of public services, while using the OECD framework to support the development of a consistent and scalable monitoring system that includes international comparability and adds strategic, long-term impact indicators – acting as a complement to – and not a duplication of – the national monitoring programme already in place. This takes place in a context where local authorities regard the provision of good-quality services as a significant challenge, especially for large, sparsely populated territories where getting people to services is a key bottleneck and those afflicted by demographic decline (OECD, 2026[25]; OECD, 2025[19]).
While this framework is not designed to replace local data collection, it complements Latvian sources by offering a comprehensive overview of development outcomes, benchmarked internationally. Across the OECD, many regional authorities rely on basic input metrics – such as euros spent, numbers of staff trained, or counts of service users – to monitor the progress of regional policies. In some cases, this is indeed characteristic of the Latvian context (OECD, 2025[19]), while some planning regions use a wider range of indicators along the policy cycle focussed more on outcomes (discussed in Chapter 3). Nevertheless, effective monitoring and evaluation is different from reporting for accountability or budgetary purposes (OECD, 2025[4]), as this kind of measures are often limited in their ability to capture the evolution of the underlying territorial assets that drive long-term economic growth and citizens’ well-being. By contrast, this multidimensional framework provides a more comprehensive evidence base to understand whether policy interventions are effectively strengthening the foundations of sustainable and inclusive territorial development, beyond short-term outputs.
Analysis of the education sector in Latvia exemplifies the use of the attractiveness framework to monitor development trajectories. In particular, education indicators within the framework reveal an absolute improvement in tertiary (higher-level) education attainment, coexisting with relative declines compared with the EU average (Box 2.5), highlighting the importance of combining temporal and comparative analysis. They also show decreased accessibility to primary educational establishments, with travel times higher than the EU median in all the Latvian municipalities as of 2023.
The analysis of education indicators highlights the importance of combining temporal and comparative perspectives when assessing territorial performance. As shown in Figure 2.7.A, the share of the population with tertiary education in state cities has increased steadily over the period 2019–2024, both before and after the 2021 ATR. While this trend is positive, the rate of increase has been slower than in EU peer regions, leading to a gradual decline in the relative position of Latvian state cities over time (Figure 2.7.B). This comparative perspective calls for further analysis of the drivers of this relative decline, including the comparative performance of local education systems, and the role of talent retention and attraction mechanisms.
Note: Data on pre-ATR state cities are used, as they have not experienced changes in their boundaries following the ATR.
Source: Own elaboration. See Annex A for definitions of the specific indicators.
Indicators on access to schools have deteriorated over time. As shown in Figure 2.8.A, all municipalities have experienced increases in their average travel time to the primary schools between 2020 and 2023, with particularly high increments in the easternmost and westernmost areas. This contrast with the declining trend observed at the EU level (Eurostat, 2026[26]). As seen in Figure 2.8.B, in the most recent period available, travel times adjusted to the nearest primary school – adjusted by population – in Latvian municipalities are up to five times the EU median. This trend points to growing spatial inequalities in access to educational services and underscore the need to strengthen provision, particularly in more remote areas.
Note: Data are provided at a 1 km × 1 km grid resolution and were aggregated by municipality using population weights. This provides the possibility of compare updated boundaries pre and post ATR.
Source: Own elaboration. See Annex A for definitions of the specific indicators.
The importance of embedding outcome and impact indicators across the full policy cycle is well illustrated by an assessment of the Vidzeme Planning Region Development Programme 2022-2027. The programme covers 12 priorities and over 100 indicators across four strategic targets, but a closer examination reveals an uneven distribution: while outcome and impact indicators are reasonably well represented in the economic and environmental priorities, social, mobility, community and housing priorities rely predominantly on activity counts and perception measures, leaving gaps in the programme's ability to assess whether interventions are generating meaningful territorial change (Vidzeme Planning Region, 2022[27]). Table 2.1 illustrates where these gaps arise and how the OECD Regional Attractiveness framework could help address them. In several cases – including travel time to the nearest school or healthcare facility, housing affordability dynamics, and transport connectivity benchmarks – the framework provides precisely the kind of comparable, place-based outcome data that the Vidzeme programme currently lacks, demonstrating how multidimensional attractiveness indicators can strengthen monitoring and evaluation throughout the policy cycle, not only at the diagnostic stage.
Source: Own elaboration based on Vidzeme Planning Region Development Programme 2022-2027.
By generating timely evidence on territorial trends and results, multidimensional attractiveness indicators enable policymakers to refine implementation processes and provide feedback to improve the design of subsequent interventions. Their importance is twofold. Tracking changes in indicators over time shows whether a territory is improving, while benchmarking against peers indicates whether it is improving fast enough to close gaps. This dual lens also helps policymakers distinguish between progress driven by local policy efforts and progress that simply reflects broader national or international trends – such as rising educational attainment across all territories – ensuring that policy conclusions are not drawn from trends that would have occurred regardless of intervention.
However, data availability alone is not sufficient to build effective monitoring and evaluation systems. Robust monitoring requires data to be included across the whole policy cycle, from design to implementation and review. In particular, embedding evaluation thinking into the initial stages of policy design can contribute to set clear policy objectives (OECD, 2025[4]). In addition, evidence must be translated into clear and actionable findings that policymakers and practitioners can use in decision making, rather than remaining as technical reporting (OECD, 2025[4]; Kusek and Rist, 2004[28]). Indeed, effective systems also depend on the skills and resources needed to interpret results and commission evaluations, particularly critical at the subnational level (OECD, 2025[4]; OECD/European Commission, 2025[29]).
Taken together, the five use cases presented in this chapter suggest that Latvia could benefit from a stronger use of multidimensional attractiveness indicators to support more coherent, evidence-based regional development policymaking:
1. Latvia could make greater use of the attractiveness framework as a strategic tool to diagnose territorial development challenges, identify local strengths, and manage trade-offs across policy objectives. Its comparative and multidimensional perspective is particularly valuable in a globally connected context in which territories increasingly compete to attract investment, talent and visitors, thereby shaping their resilience and contribution to the national economy. Thus, by revealing how municipalities perform relative to peers across a broad range of development drivers, the framework can help policymakers move beyond narrow economic metrics and design more targeted and coherent interventions.
2. Policymakers should place strong emphasis on converting underused local assets into higher value-added economic activity. As illustrated throughout this chapter, many Latvian municipalities combine strong environmental and cultural assets, well-educated populations and affordable housing. Nevertheless, translating these advantages into more attractive and competitive local economies depends on complementary drivers such as connectivity, labour market dynamism and access to quality public services.
3. Greater emphasis could be placed on territorial co-operation in Latvia. Many development challenges and opportunities extend beyond local boundaries, including labour markets, housing, transport systems, service provision and tourism ecosystems. The use of a multidimensional, evidence-based framework can support stronger co-ordination across neighbouring municipalities, planning regions and cross-border areas, thereby improving policy efficiency and enabling territories to benefit more from complementary assets.
4. Through the use of the attractiveness framework, Latvia could further differentiate policy instruments for groups of territories facing shared structural challenges. Border areas, shrinking territories, peri-urban growth zones often require distinct policy responses. A more segmented approach would allow interventions to better reflect local realities, facilitate the pooling of resources across territories facing common challenges, and support the monitoring of performance across areas with similar development profiles and trajectories.
5. Strengthening monitoring systems should remain a priority, particularly in the context of the Administrative Territorial Reform. Through the use of the attractiveness framework, Latvia could benefit from a systematic scheme to assess whether reforms and investments are fostering development goals such as competitiveness, connectivity, service quality and quality of life over time. The objective is not to replace existing monitoring systems, but rather to complement them with a set of common indicators that enables consistent benchmarking across Latvian territories.
Realising the potential of the attractiveness framework as a practical policy tool, however, requires that the attractiveness framework be embedded systematically into the policy processes through which regional development priorities are set, investments are allocated, and outcomes are evaluated – rather than used on an ad hoc basis for analytical exercises that remain disconnected from decision making. To this end, the Latvian government could embed the systematic use of multidimensional territorial indicators across the full cycle of regional development policy – from strategy design through to investment programming, monitoring, and evaluation Integrating the attractiveness framework in the RAIM platform is a start in this direction but cannot stop there. A deliberate selection exercise is needed to identify, from the attractiveness framework and complementary local and regional datasets, the indicators that draw a direct and explicit connection to the key strategic outcomes under the regional policy guidelines. This alignment between what is monitored and what is being pursued strategically is what transforms a data platform into a genuine policy tool. Equally important is who is involved in building and using it: developing the indicator set and the platform in consultation with planning regions, local authorities, and relevant line Ministries ensures that the tool reflects shared priorities, commands broad ownership, and supports accountability across levels of government. Ireland's Regional Development Monitor (Box 2.6) illustrates what this can look like in practice.
Planning regions can play a central role in this process, using multidimensional diagnostics to support their co-ordination function between national and local levels and to strengthen the evidence base for regional investment priorities. To ensure the approach delivers results rather than remaining an analytical exercise, VARAM should work with planning regions and municipalities to build interpretive capacity, develop complementary indicators on service accessibility and quality – particularly relevant in the context of the ATR – and establish a regular updating cycle that enables trend analysis over time and direct linkage to budgetary and programming decisions.
Ireland provides a useful example of how territorial data can be translated into a practical monitoring tool for regional development policy. The Regional Development Monitor (RDM), launched in 2022, is a publicly accessible online platform developed by Ireland’s three Regional Assemblies – in collaboration with strategic partners – that brings together a broad range of indicators organised explicitly around Key Regional Strategic Outcomes. These are grouped into four thematic pillars: Our People and Place (covering demographic change, housing, transport and health); Our Green and Sustainable Future (renewable energy, greenhouse gas emissions and water quality); Our Region's Economy (labour markets, foreign direct investment, lifelong learning and disadvantage); and An All-Island Perspective. This structure means the platform's data architecture directly mirrors the strategic architecture of Ireland's Regional Spatial and Economic Strategies (RSES), enabling regional authorities to assess whether priorities related to balanced growth, infrastructure provision and regional competitiveness are being achieved over time.
A key strength of the Irish model is that it was designed to serve multiple levels and actors simultaneously. Beyond regional assemblies – which are required to report on RSES progress, making regular use of the platform an operational necessity – the RDM supports national government departments in policymaking, local authorities in the preparation of city and county development plans, and researchers and the public in accessing real-time evidence on social, economic and environmental trends. This breadth of use, combined with quarterly updates and full public visibility, strengthens incentives for regular engagement and facilitates benchmarking and dialogue across territories and levels of government.
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