At the core of SME competitiveness is the knowledge and skills of the workforce. This cluster examines how these are developed across the lifecycle, starting with how education systems foster entrepreneurial skills and align practical training with SME needs. It then considers how SMEs access relevant skills, leveraging skills intelligence, upskilling and reskilling, and empowering women entrepreneurs. It also explores the role of the social economy and support for social enterprise development.
SME Policy Index for Western Balkans and Türkiye 2026
Regional Profile
Abstract
The world of work is undergoing profound transformation. The green and digital transitions, alongside demographic change, are reshaping how economies function and the skills required across industries. In the Western Balkans and Türkiye (WBT), where small and medium-sized enterprises (SMEs) form the backbone of economic activity, these shifts create opportunities and pressure. To remain competitive and productive in an increasingly complex economic landscape, SMEs must continuously adapt, drawing on their workforce’s skills, knowledge and capabilities to innovate, respond to technological change and navigate new market demands.
Education systems are at the centre of this transformation. They shape the human capital that underpins SME competitiveness, not only by equipping learners with foundational and technical skills, but by fostering entrepreneurial mindsets that enable future generations to create and grow their own businesses.
Yet across the region, evidence suggests that education and training are not fully keeping pace with these evolving demands. Foundational learning outcomes remain significantly below OECD averages: in the latest Programme for International Student Assessment (PISA) assessment, the regional average score1 stands at 402 in mathematics (compared with 472 for the OECD) and 393 in reading (versus an OECD average of 476). Moreover, performance has declined since the previous PISA cycle, with average scores falling by around 20 points in mathematics and reading – sharper drops than those observed across the OECD as a whole (OECD, 2023[1]).2 While these declines partly reflect global disruptions to education systems, they also underscore the persistent learning gap between WBT and OECD economies, highlighting significant scope for convergence. Businesses themselves echo these concerns: across the region,3 more than 30% of firms reported that the skills developed through formal education do not meet the needs of their company (RCC, 2023[2]).
Against this backdrop, strengthening the connection between education systems and SME ecosystems has become a key policy priority. This section examines how education and training systems can better support SME development, by both fostering entrepreneurial capabilities among learners and strengthening the alignment between education pathways and the evolving skills needs of SMEs.
4.1.1. Fostering entrepreneurial skills and mindsets through education
Nurturing entrepreneurial skills and mindsets among students is becoming increasingly important as global demand for these competencies continues to grow, with projections suggesting a 32% increase in Europe alone by 2030 compared to 2016 (European Commission, 2024[3]). Building these foundations begins within the education system and relies on progressive approaches to teaching and assessment that embed entrepreneurship across the learning process.
Entrepreneurship is formally recognised as a cross-curricular competence across most of the region
Across the WBT region, entrepreneurship education is increasingly aligned with the European Union’s (EU) Reference Framework for Key Competences for Lifelong Learning, where “entrepreneurship” has been positioned as a transversal competence rather than a standalone subject area (European Commission, 2018[4]).4 Five of the seven WBT economies formally designate it as a cross-curricular key competence within pre-university education frameworks (Table 4.1). Such integration is significant, as it positions entrepreneurship as a transferable capability, linked to problem-solving, creativity and initiative, rather than as narrowly business-oriented knowledge. Embedding it across subjects enables repeated exposure in varied learning contexts, reinforcing competence development through application rather than isolated instruction.
Two notable deviations illustrate alternative models. In Kosovo, entrepreneurship is not formally recognised as a distinct key competence but is instead embedded indirectly within broader competences such as “Thinking”, “Learning”, and “Life, work and environment”, which may reduce its policy visibility and coherence. Albania, on the other hand, formally recognises entrepreneurship but primarily delivers it through mandatory standalone subjects rather than a cross-curricular approach. While this ensures dedicated instructional time, it risks confining entrepreneurship to specific courses rather than embedding it systematically across the curriculum. Taken together, regional trends suggest convergence toward EU‑aligned cross-curricular integration, though differences in implementation models may shape the intensity and consistency of student exposure.
Source: Adapted from information provided by WBT governments during the assessment period.
Insufficient teacher training hinders the effective implementation of entrepreneurship as a key competence
Formal recognition of entrepreneurship as a key competence has expanded across the region, but translation into classroom practice remains uneven. A central constraint lies in limited pedagogical support to help teachers operationalise curriculum objectives through concrete, experiential learning approaches. Across most WBT economies,5 professional development offerings rarely include dedicated training on entrepreneurship as a cross-curricular competence. Provision is often either absent (e.g. in Kosovo and North Macedonia) or uneven. Where it exists, this unevenness may reflect geographic disparities – as in Bosnia and Herzegovina, where provision varies across entities and cantons – or differences across education levels, as in Albania, where annual modules on entrepreneurial skills are limited to vocational education and training (VET) teachers.
Such gaps have direct implications for instructional quality. Evidence consistently shows that, without structured pedagogical models and hands-on training, teachers struggle to translate entrepreneurial competences into meaningful classroom activities (Gracia-Zomeño et al., 2025[5]). Even in economies with comparatively more developed tools and formal frameworks, like Montenegro and Türkiye, surveys indicate that teachers frequently report low confidence in delivering entrepreneurship education effectively (Taşyürek and Metin Göksu, 2023[6]; Montenegro Ministry of Economic Development, 2025[7]). Together, these patterns suggest that curriculum reform alone is insufficient: without systematic investment in teacher capacity, including targeted training and sustained support, the formal recognition of entrepreneurship as a key competence risks remaining largely declarative, limiting its potential to equip students with the necessary skills and knowledge.
4.1.2. Bridging the divide between education and training systems and SMEs
Equipping students with relevant skills is critical to facilitating a smooth transition from education to employment and ensuring alignment with labour market needs. Across the WBT region, trends in rates of youth not in employment, education or training (NEET) reveal uneven progress: while several economies (Albania, Bosnia and Herzegovina, Montenegro, North Macedonia and Serbia) have recorded substantial declines over the past decade, the others (Kosovo and Türkiye6) continue to face persistently high levels. Even the region’s strongest performers, Serbia and Montenegro, remain well above the EU average of 9.1% in 2024, underscoring ongoing structural challenges in school-to-work transitions (Figure 4.1).
Notes: NEET: youth not in employment, education or training. Given that data were drawn from different sources, full comparability cannot be ensured due to potential methodological differences. Although all data points refer to the 15-24 year-old age group, other variations may exist, including differences in reference periods or the treatment of vocational education students. As a result, the regional average should be interpreted as indicative only.
Sources: OECD (2025[8]); Eurostat (2024[9]); INSTAT (2025[10]); MONSTAT (2025[11]); World Bank (2026[12]).
Dual VET is gaining momentum, supported by recent legal and regulatory reforms that clarify its implementation
Against this backdrop, strengthening the integration of work-based learning within formal education systems has become a central policy priority, with dual VET emerging as a key instrument to narrow the gap between education provision and labour market demand. Indeed, in recent years, all WBT economies have revised their VET legislation to better regulate the core elements of dual provision. In most cases, reforms have involved amendments to existing VET laws; however, some systems, notably Serbia and Sarajevo Canton in Bosnia and Herzegovina, have introduced dedicated dual VET legislation. These stand‑alone laws can offer advantages by consolidating provisions on contracts, remuneration, insurance and mentor qualifications, thereby enhancing legal clarity and predictability for employers. They may also signal increasing policy maturity, reflecting a shift from pilot-based experimentation toward more institutionalised work-based learning systems. Nonetheless, regardless of legislative format, the effectiveness of reform ultimately hinges on parallel improvements in implementation capacity, financing mechanisms and quality assurance.
Despite this legislative momentum, scope remains to further align with international benchmarks7 regarding the intensity of workplace learning. Progress is visible in some systems: Kosovo, for example, has increased the share of programme time spent in placements from 28% to 50% following recent reforms (European Training Foundation (ETF), 2025[13]). In economies at the upper end of the regional range – such as Serbia8 and Türkiye, where placement shares approach 60% – programme design is broadly aligned with these good practice thresholds. However, emerging evidence suggests that actual exposure to workplace learning may remain below intended levels. Initial monitoring from Serbia indicates that the placement duration reported by students may fall short of the levels prescribed in legislation (Renold et al., 2025[14]). Although comparable data are not systematically available across all economies, structural constraints, including limited employer participation and uneven regional access to placements, suggest that similar implementation gaps may arise elsewhere. These limitations are likely reflected (at least partially) in employer perceptions, with firms across the region frequently reporting that graduates lack sufficient hands-on experience (RCC, 2023[2]).
Employer incentive schemes to offset the costs of dual VET placements are expanding across the region, though their scale and accessibility continue to evolve
Ensuring sustained employer participation in dual VET remains a persistent challenge across much of the region.9 This reflects, in part, structural characteristics of the WBT economies, where SMEs dominate and often operate under significant human and financial resource constraints, making the provision of student placements difficult to sustain. In parallel, relatively high levels of business informality10 further limit firms’ ability to engage in formal training arrangements (see Cluster 1). These constraints are compounded by mandatory student remuneration requirements in most economies (Table 4.2), which increase the direct costs associated with hosting trainees. Taken together, these factors constrain both the capacity of and incentives for firms to participate, leaving some unable to offer placements and others discouraged where the perceived costs outweigh the expected benefits. This limited participation contributes to a self‑reinforcing cycle, whereby restricted access to placements reduces students’ opportunities to develop practical competencies, reinforcing concerns about workforce readiness and further discouraging firms from engaging given the associated costs.
Note: n.a.: not applicable.
Sources: GOPA Worldwide Consultants (2024[15]); Serbia Ministry of Education, Science and Technological Development/Centre for Educational Policies (2021[16]); ETF (2025[17]); information provided by WBT governments during the assessment period.
In response, WBT economies have begun introducing financial incentives to encourage employer engagement, using a diverse mix of instruments (Table 4.3), ranging from tax exemptions and wage reimbursement schemes to grant programmes and emerging dedicated dual VET funds. Montenegro stands out for its efforts to establish a more structured funding mechanism through its dedicated Fund for the Support for Dual Education. While such incentives represent an important step in addressing cost barriers, particularly given relatively low employer participation levels across most of the region with the notable exception of Türkiye, their effectiveness may be limited if implemented in isolation. Financial subsidies inherently carry risks of deadweight effects, whereby public funding supports training that employers might have undertaken regardless (OECD, 2023[18]). Moreover, smaller firms often face difficulties accessing available support due to limited awareness of funding opportunities, eligibility requirements and administrative application processes. As a result, existing incentive schemes may not fully reach the segment of firms most cost-constrained, limiting their capacity to independently expand participation in dual VET arrangements.
Source: Adapted from information provided by the WBT governments during the assessment period.
The way forward for building foundational human capital for SME competitiveness
Strengthen the implementation of entrepreneurship as a cross-curricular competence through systematic teacher capacity-building and structured pedagogical support. To translate curriculum reform into meaningful learning outcomes, governments should institutionalise dedicated, mandatory professional development on entrepreneurship as a cross-curricular competence across all pre‑university levels. This should include practical training on experiential and project-based learning methods, structured teaching toolkits aligned with national curricula, and continuous peer learning mechanisms to support application in diverse classroom contexts. Moreover, entrepreneurship pedagogy should be embedded in initial teacher education programmes as well as the provision of regular, rather than ad hoc, in-service modules to ensure a comprehensive foundation.
Strengthen employer engagement in dual VET systems through more targeted support to SMEs, enabling them to participate in and deliver high-quality workplace training. In particular, efforts should focus on adapting dual VET arrangements to the operational realities of SMEs, thereby enhancing the accessibility and attractiveness of participation.
For economies with more advanced implementation of their dual VET systems (e.g. Serbia, Türkiye and parts of Bosnia and Herzegovina): The priority should be ensuring that students meet the legally required duration and learning outcomes of in-company training. Achieving this will require sustaining strong engagement of firms and ensuring a sufficient supply of placement opportunities. One effective approach could be to expand pooled training models or training alliances that allow multiple SMEs to jointly host or “rotate” trainees, helping smaller firms overcome limited in-house training capacity (Box 4.1). In parallel, governments could more systematically promote and replicate successful company-led training models (e.g. through structured roadshows, peer learning platforms or case study dissemination) to encourage wider uptake among SMEs.
For economies where dual VET systems remain at the pilot or early expansion stages (e.g. Albania, Kosovo, Montenegro, North Macedonia, and parts of Bosnia and Herzegovina): Policy efforts should focus on scaling participation gradually while building employer confidence in the system. In several cases, including North Macedonia and some jurisdictions in Bosnia and Herzegovina, incentives for employer participation remain limited or absent. Introducing targeted measures, such as tax incentives, wage subsidies for trainees or preferential access to public support programmes, could help encourage SME engagement and facilitate broader roll-out. Alongside financial incentives, awareness-raising campaigns should highlight the long-term productivity, recruitment and retention benefits of dual VET, helping reposition apprenticeship participation as a strategic investment in workforce development rather than as a short-term cost for employers.
Germany’s dual vocational education and training (VET) system incorporates several collaborative training arrangements designed to enable small and medium-sized enterprises (SMEs) to offer work‑based learning placements for students. One such approach is the use of training alliances (“Ausbildungsverbünde”), in which multiple firms jointly organise and deliver apprenticeship training. These alliances allow companies to pool resources and share training responsibilities, enabling apprentices to acquire the full set of competencies required by a given occupation even when individual firms cannot provide all the elements of the training programme internally.
In practice, training alliances typically involve a lead training company that co-ordinates the programme, while partner firms provide training modules covering specific skills or production stages. In some cases, external training centres (“überbetriebliche Ausbildungsstätten”) or chambers of commerce and crafts support the delivery of specialised training components. This model is particularly valuable for SMEs, which may lack the equipment or specialised staff needed to deliver the full training curriculum independently. By participating in a training alliance, SMEs can host apprentices for specific phases of training while relying on partner organisations to provide complementary skills development.
For Western Balkan and Türkiye economies seeking to further expand employer engagement, Germany’s pooled training models offer a useful example of how SMEs can overcome capacity constraints while maintaining high-quality training. Such arrangements help create a mutually beneficial framework in which SMEs gain access to a reliable workforce pipeline while students benefit from exposure to a broader range of practical skills across multiple firms.
Sources: Federal Institute for Vocational Education and Training (2024[19]); ibw Austria (2016[20]).
Ensuring that SMEs have access to a skilled workforce begins in the education system, but in today’s rapidly evolving economy this starting point alone is no longer sufficient. Technological change, shifting production processes and new business models are continuously reshaping the types of skills that employers need and the nature of many occupations. As a result, workers increasingly need to adapt over the course of their careers, whether by moving into new roles or by updating their skills to keep pace with changes within their current jobs. Global estimates suggest that by 2027 around 60% of employees will require some form of additional training to remain effective in a technology-driven labour market (World Economic Forum, 2025[21]). In the WBT economies, this makes continuous upskilling and reskilling11 particularly important to ensure that workers remain employable while businesses maintain their productivity and competitiveness.
Yet, businesses across the region continue to report substantial difficulties in finding workers with the skills required for their operations. Surveys consistently show that a large share of businesses across the region report difficulties recruiting skilled labour, ranging from around 40% of firms in Bosnia and Herzegovina to nearly 75% in Montenegro, with four of the seven economies recording rates above 60%.12 These shortages reflect not only limited participation in adult learning, but also deeper structural challenges. Training provision does not always keep pace with emerging market demands linked to the green and digital transitions, the growing role of artificial intelligence (AI) and broader structural shifts in sectoral composition. At the same time, weak systems for anticipating future skills needs limit policymakers’ and education providers’ abilities to prepare the workforce for upcoming changes.
Recognising the importance of addressing these challenges, and reflecting the priorities set in the European Union’s Union of Skills (European Commission, 2025[22]), the human capital pillars of the reform agendas across the WBT economies emphasise the need to strengthen the responsiveness of skills systems and improve the alignment between labour market demand and the supply of skills. Building on this objective, this section examines how the SME skills ecosystem can become more responsive and inclusive, focusing on four inter-related dimensions: 1) strengthening skills intelligence systems; 2) expanding adult learning opportunities; 3) developing targeted upskilling initiatives to address the impacts of AI; and 4) supporting the entrepreneurial potential of women.
4.2.1. Understanding and anticipating skills needs
Meeting the evolving demands of the labour market requires more than reacting to change as it occurs; it requires anticipating future shifts by assessing current needs and imbalances and projecting how they are likely to evolve over time. In this context, skills intelligence13 (which includes assessment and anticipation tools) plays a central role, providing the evidence base needed to align education and training systems with real-world labour market demand. However, despite widespread recognition of its importance, skills intelligence systems across the WBT region are still in relatively early stages.
Despite progress in expanding skills assessment tools, weak institutional ownership and limited integration into policy frameworks constrain their overall utility
Across the WBT region, efforts to institutionalise skills intelligence have primarily focused on strengthening short-term assessment mechanisms. Most notably, employer surveys and training needs analyses (TNAs) are now widespread and increasingly regularised, reflecting growing recognition of the need for structured labour market feedback. While their predominance provides a useful foundation for collecting key market data, reliance on these tools alone does not yield a comprehensive picture. Such surveys risk overlooking supply-side dynamics, including education outputs and migration trends, and may lack the sector-specific and occupation-level granularity when not complemented by tools such as sector skills councils and industry round tables. In addition, their periodic nature limits continuous engagement with the private sector, reducing the ability to capture rapidly evolving skills needs in real time.
A more structural concern is the sustainability and institutional ownership of skills assessment mechanisms. Several tools developed during previous reform cycles, often with donor support, have not been updated or formally integrated into national governance frameworks, reducing what were intended to be foundational instruments into one-off exercises. For instance, Kosovo’s Barometers (Labour Market Barometer, VET Barometer and Skills Barometer), once considered a regional good practice, have not been updated since 2022. In North Macedonia, sectoral analyses undertaken by donors have yet to be institutionalised within domestic structures. This pattern reflects a broader regional trend: where tools are not embedded within national institutions, backed by stable funding and incorporated into regular policy cycles, their relevance diminishes rapidly in the face of evolving labour market dynamics. At the same time, even when assessments are conducted, their results are not consistently used to inform the design or updating of education and training programmes, limiting their contribution to evidence-based policymaking.
Skills anticipation systems are underdeveloped, limiting their ability to effectively forecast future labour market and demographic needs
Although the development and use of skills assessment tools are gradually advancing, skills anticipation and forecasting mechanisms remain comparatively underdeveloped. Although several economies have expressed policy commitments to strengthen anticipation frameworks, operationalisation has been modest. Recent initiatives point to incremental progress, such as Albania’s development of a forecasting tool with support from the employment services of Lithuania and Sweden, and Serbia’s inclusion of projections of knowledge and skills needs through 2027 in its 2025 Employer Survey; however, these efforts remain largely short-term in scope. Institutional fragmentation further constrains system development, as responsibility for labour market data collection is often dispersed across multiple ministries and agencies, and in the absence of a clearly mandated co-ordinating body, data compilation, harmonisation and strategic analysis remain weak. Persistent technical limitations compound these challenges, as data are not consistently aligned with Eurostat standards; are insufficiently disaggregated, including by sector and gender; and are not always collected on a regular or longitudinal basis.
These weaknesses are particularly consequential because effective skills anticipation must extend beyond labour demand analysis to incorporate structural shifts in labour supply. Demographic trends across the region, including population decline, rapid ageing, and sustained emigration of youth and skilled labour,14 are fundamentally reshaping the size of the workforce and its composition. Population projections suggest substantial contraction across most WBT economies by 2050 (Table 4.4), with the working-age population expected to decline even more sharply, by around 20%15 (World Bank, 2025[23]). Emigration plays a significant role in this trend, as an estimated 70-80% of emigrants from the region are of working age (Ayerst et al., 2025[24]).
As a result, labour shortages have emerged as one of the most significant constraints on business activity, with firms reporting workforce shortages as the primary obstacle to doing business in the region in 2024 (RCC, 2024[25]). Without systematically integrating demographic projections into forecasting models, planning risks overestimating future labour availability and underestimating emerging shortages. The absence of integrated, cross-sectoral data frameworks therefore limits the capacity of anticipation systems to capture the combined effects of technological change, sectoral transformation and demographic contraction. Strengthening skills forecasting in the region will thus require not only more sophisticated modelling tools, but also improved institutional co-ordination and broader data integration that encompasses labour market, education and demographic indicators.
4.2.2. Addressing skills needs of SMEs through adult education
Equally important to gathering skills intelligence is ensuring that the insights it generates translate into accessible and responsive adult learning opportunities. Although lifelong learning is widely recognised as a policy priority across the region, participation remains structurally weak. In 2024, adult learning rates ranged from 1.6% of adults aged 25-64 in Albania and Bosnia and Herzegovina to 8.0% in Türkiye, placing the regional average at 3.8 – just 29% of the EU average (13.3%) (Figure 4.2). Such low uptake indicates that adult learning systems are not yet operating at the scale required to support continuous upskilling and reskilling. Persistent informality across the region further compounds this challenge, as workers operating outside the formal economy are less likely to benefit from government-led skills development initiatives or employer-supported training (see Cluster 1).16 As a result, workers face limited opportunities to update their competences, and firms struggle to adapt their workforce to technological change, shifting sectoral demand and the green and digital transitions.
Notes: 2015 data were not available for Bosnia and Herzegovina; 2016 data were used. For Kosovo and North Macedonia, 2024 data were not available at the time of writing, so 2023 figures were used for comparison.
Sources: Eurostat (2025[27]); OECD (2025[8]); additional data provided by national statistical offices.
Provision of training for skills for twin transition has continued to expand, although large‑scale delivery of green transition skills has yet to be fully operationalised
Training provision across the WBT region increasingly reflects the growing importance of skills linked to the green and digital transitions. However, progress across these two domains has been uneven: while programmes aimed at strengthening digital skills have expanded considerably and are now relatively well developed in most economies (see Cluster 3), initiatives focused on building skills for the green transition remain far less advanced – a pattern also observed in broader OECD trends (Pissareva et al., 2025[28]). This gap is particularly notable given the scale of labour market adjustment expected in the coming years. Around 20% of total employment in the region is estimated to be affected by the green transition, either because workers are currently employed in carbon-intensive “brown” sectors threatened by decarbonisation (see Cluster 2) or because their roles will require significant reskilling as production processes evolve (World Bank, 2025[23]). Despite this, existing green skills training provision remains fragmented and largely ad hoc. Many initiatives are delivered through chambers of commerce or development agencies and operate at a relatively small scale, meaning that the number of beneficiaries remains far below the workforce potentially affected by structural change. Policy frameworks such as national Reform Agendas and Just Transition Plans increasingly recognise the importance of reskilling, but their focus has tended to concentrate on supporting workers displaced from carbon-intensive industries, particularly coal, rather than systematically developing training pipelines for emerging green sectors such as renewable energy, sustainable agriculture, energy-efficient construction or circular economy activities. While some promising initiatives are emerging, including Türkiye’s Green Industry Academy and the RisiAlbania programme in Albania, these remain isolated examples rather than components of a broader, co-ordinated regional approach.
Policy incentives further reinforce this imbalance between digital and green skills development. Whereas schemes supporting digital upskilling are relatively widespread, policy instruments linked to the green transition tend to prioritise financial support for technological upgrades and equipment investments, with comparatively limited attention to workforce reskilling. This gap is particularly problematic given that the labour market impacts of the green transition are expected to fall disproportionately on lower-skilled workers. In several economies – including Kosovo, Bosnia and Herzegovina, North Macedonia and Serbia – between 25% and 30% of workers with low levels of education are estimated to be employed in occupations at risk of disruption as decarbonisation progresses (World Bank, 2025[23]). At the same time, international evidence consistently shows that adults with lower levels of education and those employed in lower-skilled occupations are less likely to participate in adult learning (OECD, 2025[29]). As a result, a structural mismatch emerges: those most exposed to labour market disruption are also those least likely to access training opportunities that could help them adapt. Without more targeted, accessible and large-scale reskilling initiatives, current training systems risk falling short of equipping vulnerable workers with the competencies required to navigate the green transition while maintaining competitiveness and inclusive labour market participation.
Uptake of micro-credentials remains extremely low across the region
Micro-credentials are increasingly promoted at the EU level as a flexible instrument to support modular, demand-driven upskilling and reskilling, including under the European Commission’s Union of Skills (European Commission, 2025[22]). In the WBT region, however, regulatory and institutional frameworks have yet to evolve in a way that would allow microcredentials to perform this function at scale. Only three of the seven economies (Montenegro, Serbia and Türkiye) formally recognise micro-credentials in their legal frameworks, and even in these cases, operationalisation remains partial. Namely, in Montenegro and Serbia, guidance does not sufficiently define core elements, including clear linkages to the respective National Qualifications Frameworks (NQFs). Without such alignment, micro-credentials risk lacking credibility, comparability and stackability, limiting their recognition by employers and reducing their value as a tool for addressing skills gaps within firms.
In the remaining four economies, micro-credentials are neither legally defined nor formally recognised, and initiatives are largely confined to donor-supported pilot projects. The absence of a coherent regulatory anchor and government-led strategic direction suggests that micro-credentials have yet to be positioned as a central instrument for workforce development. This limits the availability of short, flexible training pathways that could help SMEs, particularly those seeking rapid, targeted skill upgrades, adapt more quickly to technological change and evolving market demands.
4.2.3. Upskilling to support AI adoption and use
Globally, businesses are anticipating significant shifts in jobs and skills, with around 60% expecting expanded digital access to transform business operations (World Economic Forum, 2025[21]). The rapid emergence and diffusion of artificial intelligence (AI) is a key driver of this transition, increasing demand for technology-related skills, including AI, big data and broader digital literacy. WBT SMEs are no exception. Firms across the region report evolving job profiles, with routine tasks increasingly exposed to automation, while new roles and opportunities are emerging. Realising these gains, however, will depend on the extent to which SMEs and their workforce possess the knowledge and skills required to adapt.
Low levels of foundational digital skills constrain the potential impact of AI upskilling and limit the ability of SME workforces to adapt to a labour market increasingly shaped by AI
Foundational digital competencies constitute the essential precondition for training in AI-related applications in the workplace. However, across the WBT region, the share of the population with at least basic digital skills remains substantially below the EU average. In several economies, including Albania and Kosovo, this share stands at around one quarter of the population, while even the strongest performers in the region– Montenegro and Serbia – reach only slightly more than 40%. The regional average of 33% represents roughly 55% of the EU average (60.4% in 2025), underscoring a pronounced structural gap (Figure 4.3). In this context, efforts to promote AI upskilling, whether focused on basic operational uses or more advanced data-driven applications, risk being constrained by insufficient absorptive capacity among the general workforce. Without a broader digital literacy base, SMEs may struggle to identify complementarities between human capital and AI technologies, limiting productivity gains and potentially widening competitiveness gaps as AI adoption accelerates across the European Union.
Notes: Data are unavailable for Albania (2025) and North Macedonia (2023). Data are not collected for Kosovo, but the OECD imputed a value to give a starting, albeit imperfect, comparison point.
Sources: Eurostat (2026[30]); OECD (2025[8]).
AI training programmes are expanding but remain too generic, failing to target the workers and sectors most vulnerable to automation
In response to growing recognition of AI’s transformative potential, economies across the region have introduced AI training programmes aimed at supporting the practical application of AI in business contexts. Public provision has expanded relatively quickly, and, in most cases, courses are offered free of charge—– or, as in Montenegro, fully subsidised for SMEs – to ensure broad accessibility. However, while the availability of these programmes is increasing, they remain largely generic in design and have paid limited attention to differences in workforce composition or to which groups of workers are likely to be the most affected by AI-driven change. While AI exposure is often concentrated in higher skilled sectors such as ICT and finance, where complementarities between advanced skills and AI technologies are stronger (World Bank, 2025[23]), the structure of employment in the Western Balkans differs markedly from that of more advanced EU economies. A significant share of employment in the region remains concentrated in lower- and mid-skilled occupations, particularly in manufacturing, agriculture, construction and trade, where routine tasks are prevalent and automation risks are higher (World Bank, 2025[23]). This makes the region structurally more vulnerable to displacement effects, even as the capacity to leverage AI for productivity gains remains uneven. Some early efforts to address this gap are emerging, including sector-specific upskilling initiatives targeting SMEs in manufacturing in Türkiye and Bosnia and Herzegovina (Republika Srpska), which aim to support the practical integration of AI tools in production processes and industrial operations.
These challenges are compounded by unequal access to training opportunities. In the WBT economies, like elsewhere, lower educated workers are less likely to engage in training, reflecting limited access and weaker incentives for employer-sponsored upskilling. International evidence points to a negative relationship between automation exposure and participation in training (Lassébie, Marcolin and Quintini, 2022[31]), a problematic dynamic in economies where large shares of the workforce are employed in routine-intensive sectors. As AI adoption gradually extends beyond ICT and finance into more traditional industries, many of which are central to economic output in the region, the absence of targeted, sector‑specific upskilling risks widening productivity gaps and deepening labour market polarisation. Without deliberate efforts to tailor AI training to vulnerable occupational groups and key sectors, current initiatives may reinforce existing inequalities rather than supporting inclusive technological adaptation.
4.2.4. Improving talent availability by empowering women entrepreneurs
In the context of persistent skills gaps and labour shortages, the underutilised entrepreneurial potential of women represents an important opportunity to help mitigate these challenges and ensure that SMEs have access to the right skills in sufficient quantity. However, women remain significantly underrepresented among entrepreneurs and business owners across the WBT economies, ranging from 18% of entrepreneurs in Türkiye to 34% in Serbia. Even at the upper end, this only represents around one-third of total entrepreneurs, highlighting substantial untapped potential for further progress.
Sectoral segregation and persistent data gaps limit women’s entrepreneurship as a driver of innovation and higher value growth
Across the region, women’s entrepreneurship is primarily embedded as a cross-cutting policy priority, reflected in its integration across employment, SME, innovation and, in some cases, specific sectoral strategies. In certain contexts, such as Montenegro and Bosnia and Herzegovina (Republika Srpska), the adoption of dedicated strategies for women entrepreneurship signal even stronger institutional recognition. Yet, Smart Specialisation Strategies, key documents guiding national economic policy, show little evidence that women or women entrepreneurs are explicitly considered, neither during the preparatory stages nor in the final strategy documents. The prevailing policy framing at the economy level tends to emphasise entrepreneurship primarily as a labour market activation tool for inactive or unemployed women. While this serves an important inclusion objective, it risks under-positioning women entrepreneurs as drivers of innovation, productivity and structural transformation.
As a result, policy support tends to concentrate on entry-level or micro-business creation, with a comparatively limited focus on high-growth sectors or innovation-intensive activities, specifically those in ICT or STEM fields. Although explicit references to increasing women entrepreneurs’ representation in these sectors are evident in certain strategies in select economies,17 promotion remains uneven and often insufficiently linked to broader competitiveness agendas. Structural barriers to finance reinforce this pattern: expansion into capital-intensive sectors requires greater upfront investment, yet women entrepreneurs (particularly those in rural areas) are often less likely to possess collateral,18 established credit histories or access to investor networks. Lower levels of financial literacy and familiarity with complex financing instruments can further constrain the uptake of available credit.
Monitoring these shifts is further constrained by significant data gaps. Only around half of the economies (Albania, Kosovo, Montenegro and Serbia19) systematically collect and publish data on the sectoral distribution of women entrepreneurs or women-led firms. In the absence of consistent, gender-disaggregated sectoral data, governments lack a reliable baseline against which to assess whether policy efforts are diversifying women’s participation into higher value-added sectors. Reliance on ad hoc donor-funded surveys, often based on limited samples and varying methodologies, further weakens comparability and continuity. The result is not only an evaluation challenge but a structural weakness in data architecture that limits the ability to design, target and refine policy interventions toward growth-oriented women’s entrepreneurship.
Weak care infrastructure and limited family support policies reduce women’s ability to start and sustain entrepreneurial ventures
Across all sectors, women entrepreneurs in the WBT region face constraints linked to the disproportionate burden of care responsibilities. While most economies provide relatively robust maternity leave protections, the extent to which these rights apply to self-employed women varies. In five of the seven economies, self‑employed women are entitled to the same maternity leave benefits as salaried employees. In contrast, gaps remain in Kosovo and Serbia, where protections are less comprehensive, either lacking a guaranteed entitlement or a minimum allowance, respectively (Table 4.5). Furthermore, even where equal rights are formally in place, uptake can be limited. Evidence points to barriers such as low awareness of entitlements (particularly among women in rural areas, as observed in Albania (Cinque et al., 2022[32])) as well as fragmented or unclear procedures for claiming benefits, as reported in the Bosnia and Herzegovina (Federation of Bosnia and Herzegovina).
Note: This table refers only to paid maternity leave.
Source: Adapted from information provided by WBT governments during the assessment period.
Beyond maternity protections, structural gaps in childcare provision are a significant constraint on women’s entrepreneurship. Namely, limited availability, uneven geographic coverage and affordability challenges directly restrict women’s capacity to enter and sustain business activity. In many rural municipalities, childcare provision is insufficient: in Kosovo and North Macedonia, some municipalities lack public facilities altogether. In urban areas, by contrast, offerings tend to be in place, but demand still vastly outstrips supply, resulting in waiting lists and limited access. This leaves mothers with few alternatives: either absorb the high cost of private childcare – which can be prohibitive, particularly for early-stage entrepreneurs – or rely on informal care networks of family and friends, which may limit flexibility and working hours. Although targeted support measures exist, such as Belgrade’s monthly subsidy of approximately RSD 33 000 (around EUR 280) for families whose children were not admitted to public kindergartens (Jovanovic, 2025[33]), these initiatives remain localised rather than systemic.
The way forward for developing SME workforce knowledge and skills
Institutionalise and strengthen forward-looking skills anticipation systems. This requires embedding forecasting tools within national governance structures, assigning clear institutional responsibility for skills intelligence co-ordination, and ensuring stable funding and regular update cycles. Existing instruments such as employer surveys or TNAs should be integrated into broader anticipation systems that generate medium- and long-term projections of labour market needs. Embedding these tools within regular policy processes would help ensure that skills intelligence informs education, training and employment policy in a systematic and sustained manner rather than remaining a series of ad hoc or donor-driven exercises.
Ensure that skills anticipation tools systematically identify emerging skills needs related to the twin transitions. Forecasting tools should explicitly assess the implications of digitalisation and the green transition for labour demand across sectors, including the emergence of new occupations and the transformation of existing ones. Integrating these insights into policy planning would support the timely adaptation of curricula, training programmes and reskilling initiatives, ensuring that education and training systems are better aligned with the evolving skills requirements of the digital and green transitions. France’s National Observatory for Jobs and Occupations of the Green Economy provides a useful example of such an approach (Box 4.2).
Expand and better target training systems to support workers and SMEs most vulnerable to disruption from the green and digital transitions, including artificial intelligence. Upskilling and reskilling efforts should be tailored to sectors facing higher risks of displacement or transition, such as manufacturing in the context of AI and “brown” sectors such as mining in the green transition. Training should be delivered through accessible formats, including modular and workplace-based learning, and supported by co-financing mechanisms to reduce participation costs for SMEs. Clear outcome and impact indicators should be embedded to assess effectiveness and inclusiveness, while systematic monitoring and evaluation can support the refinement and scaling of programmes to ensure they deliver meaningful labour market outcomes and strengthen SMEs’ adaptive capacity.
Scale up the use of micro-credentials as flexible, modular upskilling pathways for SMEs and their workforce. To support broader uptake of micro-credentials, efforts should focus on strengthening their integration into national systems. In some economies (Montenegro, Serbia and Türkiye), this will require further formalisation through the introduction of clear standards, quality assurance mechanisms and alignment with NQFs. In others (Albania, Bosnia and Herzegovina, Kosovo, and North Macedonia), the priority will be to establish a clear legal basis recognising micro-credentials within the NQF. Strengthening this regulatory anchoring would enable micro‑credentials to function as recognised and portable qualifications, offering SMEs accessible, short form training options better aligned with evolving skills needs.
France’s National Observatory for Jobs and Occupations of the Green Economy provides a structured example of how skills anticipation tools can be used to identify labour market implications of the green transition and inform policy planning. Established in 2010 under the Ministry for Ecological Transition, the Observatory operates through a distinctive governance model that brings together a wide range of public institutions across policy domains and levels of government. Members include the French Agency for the Environmental Transition, the Centre for Studies and Research on Employment and Skills, the National Institute of Statistics and Economic Studies, the Directorate General for Employment and Vocational Training, and regional employment and training observatories. This multi-institutional structure facilitates co-ordination between environmental, labour market, statistical and training authorities, strengthening the capacity to monitor how environmental policies and the shift toward a low‑carbon economy affect employment and skills needs.
The Observatory analyses labour market trends associated with the green transition by identifying “green jobs” (occupations directly linked to environmental protection) and “greening jobs” (occupations undergoing transformation as environmental requirements reshape production processes). Through the use of labour market statistics, sectoral studies and occupational analysis, the Observatory tracks how the demand for skills evolves across sectors and regularly publishes indicators and analytical reports to inform policy discussions.
For the WBT economies, similar arrangements could help strengthen skills anticipation systems by integrating analysis of digital and green transitions into labour market forecasting exercises. Establishing dedicated analytical functions, whether through observatories (as planned in Albania and North Macedonia), specialised units within ministries or co-ordinated inter‑institutional platforms, could help systematically identify emerging skills needs and inform adjustments to education, training and reskilling policies.
Sources: OECD (2025[34]; 2024[35]); France Ministry of Ecological Transition and Territorial Cohesion (2025[36]).
Strengthen policy support for SMEs that actively invest in employee upskilling, professional development and retention. Given the low levels of adult learning across the region, policy frameworks could recognise and incentivise SMEs that play a direct role in building workforce skills, particularly where firms compensate for gaps in formal education through in‑company training. Targeted instruments could include co-financing schemes for workforce development, support for firm-level training initiatives (including internal training programmes) or more favourable tax treatment of employee benefits aimed at improving retention and attraction.
Continue to expand support for fostering women entrepreneurs’ participation in high‑growth, innovation-intensive fields. Strengthening such support requires a stronger evidence base to understand the current sectoral distribution of women-led businesses and to track whether policy measures effectively expand women’s participation in higher value-added and innovation-driven activities.
In economies where sectoral data for women entrepreneurs is not yet collected (Bosnia and Herzegovina [Federation of Bosnia and Herzegovina], North Macedonia, Türkiye): priority should be given to establishing mechanisms to collect, harmonise and regularly publish data on the sectoral distribution of women-led businesses. Integrating these indicators into national business registers, statistical surveys and SME monitoring frameworks would provide policymakers with a stronger evidence base to assess whether support measures are effectively expanding women’s participation in higher value-added and growth-oriented sectors.
In economies with sectoral data (Albania, Bosnia and Herzegovina [Republika Srpska], Kosovo, Montenegro, and Serbia): policy efforts should focus on targeted measures to reduce sectoral segregation and support women entrepreneurs in technology-intensive fields. These may include dedicated financial instruments, such as grants or seed funding for women-led start-ups in ICT and STEM sectors, alongside specialised incubation or acceleration programmes that combine technical mentoring with business development support. Strengthening linkages between universities, research institutions and women entrepreneurs can further facilitate the commercialisation of STEM-based innovations.
Address care-related constraints affecting women’s entrepreneurship by taking steps to reduce structural barriers to business creation and growth. One key action would be to strengthen maternity leave protections for self-employed women where these remain less favourable than those available to salaried workers (Kosovo and Serbia), thereby reducing financial disincentives that may discourage women from pursuing entrepreneurship. In parallel, all economies should expand the availability of affordable childcare infrastructure, particularly in rural municipalities where provision remains limited, through a combination of public investment, targeted subsidies and reduced regulatory thresholds for employer-provided childcare services.
A small business rarely succeeds in isolation. For many SMEs, competitiveness depends not only on the skills of their workforce, but also on their ability to rely on trust-based relationships, local networks and collaborative norms (i.e. “social capital”). Yet, SMEs across the WBT region often operate under structural constraints linked to limited scale, financing and internal capacities, which can restrict access to talent, learning opportunities and knowledge exchange. In this context, the social economy20 constitutes an important institutional channel through which SMEs in the region can build and mobilise social capital, supporting human capital development and strengthening their capacity to adapt, innovate and grow.
While the social economy is expanding globally, encompassing over 4.3 million organisations and 6.3% of the European workforce (European Commission, 2025[37]), it remains at a very early stage of development in the WBT region. Indeed, in the six Western Balkan economies, it is estimated that there are only around 1 080 social enterprises operating,21 in addition to another 9 000 operating in Türkiye alone, showcasing significant scope for further development of the sector. Namely, strengthening the social economy could contribute to sustainable competitiveness by fostering innovation in economic and social spheres and supporting the creation of quality jobs (OECD/European Union, 2025[38]), which can help reduce inequalities and support economic convergence between WBT economies and the European Union.
Against this backdrop, this section examines the key building blocks for strengthening the social enterprise ecosystem, focusing on improved mapping alongside the development of a more supportive legal and institutional environment.
4.3.1. Mapping the social enterprise landscape
Understanding the structure and scope of the social enterprise landscape is a necessary first step toward fostering the broader development of the social economy. Yet, across the WBT economies, systematic identification and mapping of social enterprises remain uneven, resulting in incomplete registration coverage and limited availability of reliable information on the sector.
Registers of social enterprises are either underdeveloped or not yet established, leaving efforts to map the social economy ecosystem at an early stage
Registers of social enterprises are beginning to emerge as an administrative mechanism to formalise social enterprises, with systems established in Albania, Bosnia and Herzegovina (Republika Srpska), Kosovo and Serbia (Table 4.6). However, the absence of comparable mechanisms across the remaining economies limits the consistency and completeness of registration practices across the region. Even where registers exist, their institutional design often constrains their scope. Registers are typically maintained as internal administrative lists within individual ministries rather than as centralised or interoperable systems, and are rarely publicly accessible. In addition, registration frameworks frequently lack standardised data requirements, with limited and uneven collection of basic information such as legal form, sector of activity or employment size (with the exception of Bosnia and Herzegovina [Republika Srpska]).
Notes: n.a.: not applicable. NPO: non-profit organisations. Years shown in parentheses indicate the target year for completion of the benchmark.
Sources: Adapted from information provided by WBT governments during the assessment period.
Moreover, registration uptake remains low and often diverges from estimates of social enterprises operating in practice. While the relative novelty of social enterprise legislation partly explains limited registration, additional structural factors contribute to weak participation. For example, many organisations remain cautious about formal registration due to additional obligations, such as profit reinvestment rules or enhanced reporting requirements, particularly where registration does not confer clear operational advantages. In the absence of explicit incentives or differentiated treatment, registration frameworks risk remaining underutilised and incomplete as a basis for sector identification (OECD/European Union, 2025[39]).
Incomplete registration systems translate into structural data gaps that reinforce the statistical and policy invisibility of social enterprises
The absence of comprehensive registration data prevents social enterprises from being systematically captured in official statistical systems, limiting the ability of national statistical offices and competent line ministries to produce reliable evidence on the sector’s size, structure and economic contribution. In policy environments where the allocation of resources and institutional support is increasingly evidence-driven, this lack of visibility weakens the sector’s standing relative to more established economic actors. As a result, social enterprises are often treated as a residual subset of the non-profit or SME landscape rather than as a distinct category with specific development needs and policy potential.
These data gaps have direct consequences for policy effectiveness and accountability. Ex ante, limited information constrains government’s capacity to diagnose structural challenges, including financing constraints, skills needs or regional concentration. Ex post, it restricts the ability to monitor and evaluate whether public interventions lead to increased formalisation, improved sustainability, or growth in employment and economic activity. Moreover, registers function as a key entry point for integrating social enterprises into broader policy systems, including skills intelligence, SME support instruments and labour market programmes. In their absence, social enterprises remain structurally excluded from mainstream policy frameworks, perpetuating a cycle in which limited data constrains policy action, and limited policy action reinforces sector invisibility.
4.3.2. Creating an enabling environment for social enterprises
Advancing the social economy ecosystem requires a comprehensive enabling environment that combines clear and functional legal frameworks with access to financing, skills development and capacity-building support. These elements are critical to enabling social enterprises and social entrepreneurs not only to establish viable operations, but also to scale, innovate and remain competitive within evolving market conditions.
Governments have made progress in advancing legal frameworks for social enterprises
WBT economies increasingly have a dedicated legal framework for social enterprises, although coverage remains uneven. Legislation is currently in force in Albania, Bosnia and Herzegovina (Republika Srpska), Kosovo and Serbia, while draft frameworks are under development in Bosnia and Herzegovina (Federation of Bosnia and Herzegovina), Montenegro and North Macedonia. These frameworks establish the formal parameters of social enterprise activity, but their practical impact depends less on their existence than on how definitions are operationalised.
Table 4.7 points to two distinct definitional design choices that shape the inclusiveness of social enterprise frameworks: the scope of the social mission and eligibility by legal form. In several cases, namely in Albania and Kosovo, legislative definitions remain closely anchored in work integration models that prioritise employment of disadvantaged groups, often through specific workforce thresholds. Although such models play a critical role in advancing labour market inclusion, narrow mission definitions risk overlooking those organisations that pursue broader social or environmental objectives through alternative business models. A second design element concerns eligibility across legal forms. Inclusive frameworks, which prevail across most WBT economies with dedicated legislation (with the notable exception of Albania), allow a broad range of organisational structures to obtain social enterprise status and support the formal recognition of de facto social enterprises. Variations across these two dimensions influence not only regulatory clarity, but also the extent to which legal frameworks capture the full diversity of social enterprise activity and support sector growth.
Notes: n.a.: not applicable. WISE: work integration and social enterprise. NPO: non-profit organisation. There are two types of social enterprises in Kosovo: Category A (must provide social and care services for vulnerable groups) and Category B (broader production and service activities but must employ at least 30% of workers from vulnerable groups).
Sources: Government of Albania (2016[40]); Government of Serbia (2022[41]); Government of RS (2021[42]); Government of Kosovo (2018[43]).
Public support for social enterprises is expanding, but existing instruments remain largely generic and insufficiently adapted to the sector’s dual economic and social mission
Social enterprises’ hybrid business models create structural financing and capacity-building needs that conventional SME support systems are not designed to address. For instance, traditional lending instruments are generally designed for businesses with predictable revenue generation and profit‑maximising models, making them poorly suited to social enterprises, which often reinvest earnings, operate under mission-driven governance and face less stable income streams. As a result, social enterprises tend to rely heavily on public funding, primarily through mainstream SME support programmes. While these programmes can provide valuable support, they are not specifically tailored to the needs of social enterprises and often face high demand, placing social enterprises in direct competition with conventional SMEs that may be better positioned to meet eligibility criteria. Dedicated and institutionalised financing mechanisms for social enterprises remain rare, with financial support frequently delivered through short-term, project-based initiatives. Although some economies have begun exploring more structured approaches, including commitments in Albania to establish a dedicated support fund and legislative provisions in Bosnia and Herzegovina (Republika Srpska) allowing for the creation of Social Entrepreneurship Fund(s), implementation remains limited, hindering the development of stable and predictable financing ecosystems for social enterprises (Government of Albania, 2023[44]; Government of RS, 2021[42]).
Capacity-building support reflects many of the same structural shortcomings observed in financing support. Although social enterprises are generally eligible to participate in mainstream entrepreneurship and SME training programmes, these initiatives are rarely designed to reflect the distinct operational and governance models characterising social enterprises. Tailored training initiatives remain limited in scale and continuity, leaving persistent gaps in specialised capacity-building support. Such limitations are particularly evident in social impact measurement and reporting. Across economies like Albania, Kosovo and Serbia, regulatory frameworks increasingly require social enterprises to demonstrate social outcomes as part of registration or ongoing reporting obligations, yet these expectations have not been accompanied by systematic technical assistance or training provision. As reporting requirements expand, registered social enterprises will face growing compliance challenges that can restrict access to financial support, limit participation in public procurement or place formal social enterprise status at risk. More broadly, increasing compliance obligations without corresponding capacity-building support may discourage potential social enterprises from pursuing formal registration, ultimately weakening sector formalisation and reducing the effectiveness of policy frameworks intended to support social enterprise development.
The way forward for strengthening social capital by advancing social entrepreneurship
Strengthen data infrastructure through interoperable and comprehensive social enterprise registers. WBT governments should accelerate the establishment and upgrading of social enterprise registers so they function as strategic policy tools rather than administrative lists.
For economies with existing registers (Albania, Bosnia and Herzegovina [Republika Srpska], Kosovo, and Serbia): Efforts should focus on strengthening the operational and analytical value of existing systems. Registers should be made publicly accessible in searchable formats to enhance transparency and visibility, while technical interoperability with national statistical offices and broader business registers should be established to enable systematic data exchange and integration into official statistics. Clear procedures for regular updating and verification of entries should also be introduced to ensure data accuracy and policy relevance.
For economies without operational registers (Bosnia and Herzegovina [Federation of Bosnia and Herzegovina], North Macedonia, and Türkiye): Priority should be given to establishing a formal legal and institutional framework for social enterprise registration. From the outset, registers should include clearly defined eligibility criteria and mandatory core data fields (e.g. legal form, sector of activity, employment, turnover and social objectives) and, in line with the recommendations above, be designed to ensure interoperability and integration with national statistical and administrative systems to support future policy monitoring and analysis.
Develop tailored financing and capacity-building instruments aligned with the hybrid nature of social enterprises. Governments across the region should establish permanent and institutionalised financing mechanisms, such as social enterprise funds, blended finance schemes or impact investment facilities, to reduce reliance on short-term and donor-driven project funding (Box 4.3). Financing instruments should reflect social enterprises’ reinvestment obligations, governance structures and variable revenue patterns. In parallel, governments should expand specialised capacity-building programmes focused on governance, business sustainability, scaling and impact management. Particular attention should be paid to strengthening training and technical support on social impact measurement and reporting, especially in economies where regulatory frameworks require evidence of social outcomes.
Launched in 2015, the Portugal Social Innovation initiative aims to strengthen the social economy by supporting social innovation and social entrepreneurship projects that generate new solutions to pressing societal challenges. Within this overarching objective, a core aim is to develop financing instruments tailored to the specific needs and hybrid models of social economy entities.
Specifically, the initiative combines four complementary instruments:
1. Capacity building for social investment: lump-sum grants (up to EUR 50 000, 18 months) to strengthen the organisational and management capacities of early-stage social innovation and entrepreneurship initiatives.
2. Partnerships for impact: matching grants (70% public, 30% private co-financing) exceeding EUR 50 000 for projects lasting 1-3 years, supporting early growth and scaling.
3. Social impact bonds: outcome-based financing in priority public policy areas (e.g. employment, health, education), with full reimbursement of eligible costs upon verified achievement of the agreed-upon outcomes.
4. Social Innovation Fund: financial instruments, including guarantee mechanisms and co‑investment facilities, designed to address market failures in access to finance for more mature social enterprises.
During its first cycle (2015-2022), the programme launched 8 open calls, receiving 1 244 applications, of which 693 were approved, mobilising approximately EUR 148 million. It is estimated that the supported projects reached around 1.4 million beneficiaries.
Portugal Social Innovation provides a strong example of how governments can institutionalise dedicated financing mechanisms while embedding structured capacity building. Its life cycle approach, combining grants, matching funds, outcome-based instruments and blended finance, ensures that support evolves with the maturity of social enterprises, reducing reliance on short-term donor funding and strengthening long-term ecosystem sustainability.
Sources: European Commission (2022[45]); Pedro and Bomba (n.d.[46]); OECD (2025[47]).
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[6] Taşyürek, Z. and M. Metin Göksu (2023), “A view on entrepreneurship from the perspective of teachers”, International Journal of Eurasian Education and Culture, Vol. 8/22, pp. 1862-1897, https://doi.org/10.35826/ijoecc.703.
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[12] World Bank (2026), “Share of youth not in education, employment or training, total (% of youth population) – North Macedonia [dataset]”, https://data.worldbank.org/indicator/SL.UEM.NEET.ZS?locations=MK (accessed on 26 February 2026).
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← 1. This average excludes Bosnia and Herzegovina, which did not participate in the PISA 2022 cycle.
← 2. It is important to note that the regional averages and regional trends in performance are impacted by the decline observed in Albania, which is among the largest recorded across participating systems. OECD analysis suggests that factors such as student test engagement may have influenced the results, which should consequently be considered when interpreting changes over time. For more information, see: https://www.oecd.org/en/publications/2023/12/pisa-2022-results-volume-i_76772a36/full-report/how-much-effort-do-students-put-into-the-pisa-test_4a45c973.html.
← 3. This figure excludes any estimate of Türkiye.
← 4. The entrepreneurship key competence is underpinned by the EU Entrepreneurship Competence Framework (EntreComp) to guide competence development.
← 5. One clear exception is Montenegro, where dedicated trainings are available through the national Digital Education Platform.
← 6. It is worth noting that there is a substantial gender gap in Türkiye that is not observed in the other WBT economies: indeed, the NEET rate among young women was nearly double that of young men in 2024 (30.0% versus 16.3%, respectively).
← 7. The European Framework for Quality and Effective Apprenticeships stipulates that work-based learning should constitute 50% of programme duration.
← 8. These efforts are ongoing in Serbia. Namely, starting from the 2026/2027 school year, the proportion of time spent in work-based learning will gradually increase to amount to at least 60% of total instruction time in three-year VET programmes (and 40% for four-year programmes). For more information, see: https://www.etf.europa.eu/sites/default/files/2025-09/WBL-Serbia-edited_clean.pdf.
← 9. The exception is Türkiye, where employers with more than 10 employees are obligated to host student trainees.
← 10. For more details on the informal economy and its impact on SME development in the region, see Section 1.2.1, “Reducing informal competition for SMEs,” in Cluster 1 of the regional profile.
← 11. Upskilling involves short, focused training aimed at enhancing or updating existing knowledge, skills, or competences developed through prior learning. Reskilling, often referred to as retraining, involves acquiring an entirely new set of skills to enable individuals to transition into a different occupation or field of work. For more information, see: https://unevoc.unesco.org/home/sandbox-tvetipedia/lang=en/filt=all/id=462; https://unevoc.unesco.org/home/TVETipedia+Glossary/lang=en/show=term/term=Retraining#start.
← 12. These economies include Serbia (60%), North Macedonia (70%), Türkiye (72%) and Montenegro (75%). It should be noted that these figures are not fully comparable, as they are derived from nationally developed methodologies and data sources. Nonetheless, they provide a useful indicative baseline for illustrating the scale of the challenge across the region. Further details on the underlying data and calculation methods for each economy are provided in the respective economy profiles.
← 13. “Skills intelligence” can be defined as the “process of identifying, collecting, analysing, synthesising and presenting quantitative or qualitative information on skills and the labour market to: (i) identify key trends and demands in the labour market, (ii) assess, anticipate and forecast skills needs, (iii) address skills gaps and mismatches and (iv) adapt provision of education and training accordingly.” For more, see: https://www.cedefop.europa.eu/en/tools/vet-glossary/glossary/kompetenzanalytik.
← 14. The sustained outflow of skilled migrants from the WBT region poses a major obstacle to SMEs, given its direct impact on talent availability. For more information on the dynamics of labour migration in the Western Balkan economies, see: https://www.oecd.org/content/dam/oecd/en/publications/reports/2022/05/labour-migration-in-the-western-balkans_c885a35f/af3db4f9-en.pdf.
← 15. This regional projection excludes Türkiye.
← 16. For more details on the informal economy in the region, see Section 1.2.1, “Reducing informal competition for SMEs”, in Cluster 1 of the regional profile.
← 17. These include Montenegro’s Strategy for the Development of Women’s Entrepreneurship 2025-28, Türkiye’s 2030 Industry and Technology Strategy, and RS’s Strategy for the Development of Entrepreneurship of Women 2025-31.
← 18. Data, when available, confirm this trend. For instance, in Montenegro, women hold only about 25% of registered assets; in North Macedonia, women own only 26% of property; in Serbia, 25.6% of women hold sole ownership of immovable property, and 12.8% co-own. More details on these figures and their implications for women entrepreneurs can be found in the individual economy profiles.
← 19. It is worth noting that Republika Srpska does collect gender-disaggregated data; however, Bosnia and Herzegovina is excluded from this list due to the absence of comparable data in the Federation of Bosnia and Herzegovina and the lack of consolidated statistics at the state level.
← 20. The OECD defines the social economy as “made up of a set of organisations such as associations, cooperatives, mutual organisations, foundations, and, more recently, social enterprises. In some cases, community-based, grassroots and spontaneous initiatives are part of the social economy in addition to non-profit organisations, the latter group often being referred to as the solidarity economy. The activity of these entities is typically driven by societal objectives, values of solidarity, the primacy of people over capital and, in most cases, by democratic and participative governance.” For more, see: https://legalinstruments.oecd.org/en/instruments/OECD-LEGAL-0472.
← 21. This estimate is based on figures presented in each economy profile: 379 in Albania; 50 in Bosnia and Herzegovina (derived from an estimate of 25 in the FBiH and doubled to approximate national coverage due to the absence of estimates for RS); 50 in Kosovo (midpoint of the estimated 30-70 range); 50 in Montenegro; 57 in North Macedonia; and 500 in Serbia. Data for each economy were provided by governments and/or other relevant institutions to the OECD during the assessment cycle. It is important to note that these estimates are not based on a fully comparable methodology and should therefore be interpreted with caution. Differences in legal definitions, where such definitions exist, as well as variations in registration systems may affect comparability across cases.