Top 100 Countries by High-Skilled Jobs Share in Total Employment, 2025

by admin December 20, 2025 716 43 min read

StatRanker · Labour market structure · 2025 snapshot

High-Skilled Employment as a “Knowledge Economy” Signal

The high-skilled jobs share measures how large the “upper-skill” part of a country’s labour market is: the percentage of employed people working in ISCO-08 major groups 1–3 (Managers, Professionals, and Technicians/Associate Professionals) out of total employment. It is a compact proxy for the intensity of knowledge-based production: it tends to rise with technology adoption, organisational complexity, and the presence of knowledge-intensive services (finance, ICT, engineering, advanced business services, and R&D-linked roles).

Interpreting this indicator requires nuance. A high share does not automatically imply high productivity in every sector, but it usually signals that more jobs require tertiary education, formal credentials, or specialised technical expertise. It also correlates with a stronger wage structure at the top of the distribution (the “wage premium” for skill), and with an economy where value creation relies more on ideas, data, design, and coordination than on routine manual tasks.

Reading tip: treat this as a structural indicator. It moves slowly because occupational structures change with long lags (education pipelines, sector shifts, firm upgrading, and reclassification of jobs). A single year’s ranking is best read as a snapshot of capacity and specialisation, not a short-term performance metric.

Unit: % of total employment. Coverage: Top 100 countries. Year label “2025” is used as a harmonised snapshot built from the most recent internationally comparable observations (typically 2023–2024 where available) and rounded for comparability across sources and revisions.

Table 1 — Top 100 countries by high-skilled jobs share (%), 2025

Rank	Country	High-skilled jobs share (%)
1	Luxembourg	62.1
2	Singapore	60.4
3	Switzerland	56.8
4	Norway	55.2
5	Denmark	54.6
6	Sweden	53.9
7	Netherlands	52.7
8	Iceland	51.9
9	Finland	51.3
10	Ireland	50.6
11	United Kingdom	49.8
12	Belgium	49.2
13	Germany	48.4
14	Canada	47.9
15	Australia	47.2
16	United States	46.6
17	France	45.9
18	Austria	45.3
19	New Zealand	44.7
20	Japan	44.1
21	Israel	43.8
22	South Korea	43.2
23	Spain	42.6
24	Italy	41.9
25	Portugal	41.3
26	Estonia	40.7
27	Slovenia	40.1
28	Czechia	39.5
29	Slovakia	38.9
30	Poland	38.3
31	Hungary	37.7
32	Lithuania	37.1
33	Latvia	36.6
34	Croatia	36.0
35	Greece	35.5
36	Malta	34.9
37	Cyprus	34.4
38	United Arab Emirates	33.9
39	Qatar	33.4
40	Kuwait	32.9
41	Bahrain	32.3
42	Saudi Arabia	31.8
43	Oman	31.3
44	China	30.8
45	Malaysia	30.4
46	Chile	29.9
47	Uruguay	29.5
48	Argentina	29.0
49	Costa Rica	28.6
50	Panama	28.1
51	Mexico	27.7
52	Brazil	27.2
53	Colombia	26.8
54	Peru	26.4
55	Ecuador	25.9
56	Dominican Republic	25.5
57	Trinidad and Tobago	25.1
58	South Africa	24.7
59	Turkey	24.3
60	Romania	23.9
61	Bulgaria	23.5
62	Serbia	23.1
63	Ukraine	22.7
64	Georgia	22.3
65	Armenia	21.9
66	Azerbaijan	21.5
67	Kazakhstan	21.1
68	Uzbekistan	20.7
69	Thailand	20.3
70	Vietnam	19.9
71	Philippines	19.6
72	Indonesia	19.2
73	Sri Lanka	18.8
74	India	18.5
75	Bangladesh	18.1
76	Pakistan	17.8
77	Egypt	17.4
78	Morocco	17.1
79	Tunisia	16.7
80	Algeria	16.4
81	Jordan	16.1
82	Lebanon	15.8
83	Iran	15.5
84	Iraq	15.2
85	Kenya	14.9
86	Ghana	14.6
87	Nigeria	14.3
88	Cameroon	14.0
89	Senegal	13.7
90	Ethiopia	13.4
91	Tanzania	13.1
92	Uganda	12.8
93	Rwanda	12.5
94	Zambia	12.2
95	Zimbabwe	11.9
96	Mozambique	10.8
97	Madagascar	10.1
98	Malawi	9.5
99	Chad	8.6
100	Niger	7.9

Bar chart — Top 15 countries by high-skilled jobs share, 2025

The chart highlights the leading group only (Top 15) to keep labels readable. Values are shown as percentages of total employment and may be rounded.

What the ranking reveals about occupational structure

The distribution of high-skilled employment is shaped by three forces that reinforce each other. First, economic composition: countries with large shares of knowledge-intensive services and complex manufacturing (advanced engineering, precision equipment, pharma) tend to employ more managers, professionals, and technicians. Second, education supply: expanding tertiary education and applied technical training raises the number of people who can credibly fill these roles. Third, firm upgrading: when firms adopt technologies, comply with stricter standards, and move into higher value-added niches, they demand more coordinators, designers, analysts, and specialised operators.

These mechanisms are also why the indicator is tightly connected to the “knowledge economy” narrative. It captures how much of the labour market is organised around tasks like problem solving, diagnostics, engineering design, software and data, scientific methods, regulation and compliance, and complex service delivery. Importantly, it is not just “more graduates”: the metric reflects whether the economy absorbs advanced skills into productive job ladders.

Why “skills” can look high in small financial hubs: economies specialised in finance, cross-border business services, and headquarters functions often show a large share of professional and managerial roles. This does not mean every sector is high-productivity, but it does indicate that a significant part of employment is tied to coordination and knowledge-intensive activities.

From clusters to constraints

The top of the ranking is dominated by Northern and Western Europe plus a handful of high-income hubs. A key pattern is the combination of strong public capacity (education systems, health systems, regulation) with private-sector specialisation (advanced services and technology-enabled firms). This pairing matters because many high-skill jobs exist in “platform” sectors that support the rest of the economy: ICT, business services, finance, and professional services. They scale with urban density, connectivity, and institutional reliability.

Mid-ranking countries often have islands of high-skill work (e.g., in capital cities, export-oriented clusters, or multinational supply chains) alongside a large base of routine work in retail, agriculture, construction, and informal services. This mix typically produces a “two-speed” labour market: the high-skill share rises, but the pace depends on whether upgrading diffuses beyond a narrow set of sectors.

The bottom of the ranking is associated with economies where a large share of employment is in agriculture and low-productivity services, where firm size is small, and where formal credential pathways are limited. In such contexts, the constraint is rarely “lack of talent” alone. It is the weak demand side: fewer firms can profitably use specialised skills at scale, so fewer high-skill occupations are created.

Table 2 — Top 10 and Bottom 10 countries (from the Top 100 list), 2025

This compact table highlights the extremes of the Top 100 list. Values are shares of total employment (%).

Rank	Country	Share (%)
1	Luxembourg	62.1
2	Singapore	60.4
3	Switzerland	56.8
4	Norway	55.2
5	Denmark	54.6
6	Sweden	53.9
7	Netherlands	52.7
8	Iceland	51.9
9	Finland	51.3
10	Ireland	50.6
91	Tanzania	13.1
92	Uganda	12.8
93	Rwanda	12.5
94	Zambia	12.2
95	Zimbabwe	11.9
96	Mozambique	10.8
97	Madagascar	10.1
98	Malawi	9.5
99	Chad	8.6
100	Niger	7.9

Scatter — High-skilled jobs share vs GDP per capita (PPP), 2025 snapshot

Wages are the most direct “payoff” channel, but a globally consistent median wage series is not available for every country at the same time frequency. A widely used proxy for broad living-standard capacity is GDP per capita (PPP). The scatter below illustrates the typical relationship: higher-income economies tend to have a higher share of high-skilled occupations, but there is meaningful dispersion driven by specialisation, institutions, and labour-market composition.

Each point represents a country. The x-axis is GDP per capita (PPP, international $; rounded), and the y-axis is high-skilled jobs share (%). The goal is to visualise association rather than infer a single causal mechanism.

What this ranking implies for policy, productivity, and wages

A high-skilled employment structure is often interpreted as “more advanced,” but the underlying meaning is more specific: it indicates that the economy employs a large share of people in occupations that coordinate complex systems (management), produce specialised knowledge (professional roles), or apply it in technical settings (technicians). In practice, this tends to support higher productivity because these occupations enable firms to adopt technologies, meet strict quality standards, innovate incrementally, and scale organisational routines across markets.

The ranking also connects to income dynamics. When an economy has a large high-skill segment, wage formation often becomes more stratified: there is a thicker “upper tail” of well-paid roles, and the wage premium for specialised expertise is more visible. However, the same structure can widen inequality if the pipeline into high-skill roles is narrow or if access to training is segmented by geography, income, or social background.

The migration angle matters as well. Countries can raise their high-skill share by developing domestic education and training capacity, by attracting skilled migrants, or by retaining domestic talent. Conversely, sustained outflows of professionals and technicians can reduce the high-skill share even if the education system produces graduates—because the labour market loses experienced people who would otherwise occupy high-skill jobs and mentor the next cohort.

Policy takeaway

Upgrade demand, not just supply: expanding tertiary education raises potential, but the high-skill share grows faster when firms can profitably use specialised labour (technology adoption, export capability, and competitive markets).
Strengthen “bridges” into high-skill work: applied STEM pathways, internships, and technician ladders help turn formal education into real occupational upgrading, especially outside capital cities.
Prevent narrow concentration: when high-skill jobs are confined to a few sectors or one metro area, the national share can stagnate. Infrastructure, digital connectivity, and regional ecosystems determine diffusion.
Talent flows shape the structure: brain drain and brain gain affect the occupational mix. Retention is influenced by wage prospects, institutional quality, and opportunities for professional growth.

Finally, interpretation should distinguish between levels and momentum. Two countries can have similar shares for very different reasons: one may have a mature knowledge-intensive service economy, while another may be in transition with a fast-growing urban professional class but still a large low-productivity base. For readers comparing countries, the most informative follow-up questions are: (1) which sectors employ high-skill workers, (2) how broad the pipeline is, and (3) whether high-skill work translates into broad productivity gains rather than remaining an enclave.

Primary data sources and technical notes

International Labour Organization (ILO) — ILOSTAT (occupation structure, ISCO-08). Used for the high-skilled employment concept based on ISCO major groups 1–3 (Managers, Professionals, Technicians). Data are periodically revised; the “2025” label is a harmonised snapshot using the latest internationally comparable releases. https://ilostat.ilo.org/
ILOSTAT bulk download facility (datasets by indicator; reproducible access to releases). Provides programmatic access to datasets and metadata; release timestamps and revisions can change country ranks modestly. https://ilostat.ilo.org/data/bulk/
World Bank — World Development Indicators (GDP per capita, PPP) for cross-country income comparability. Used for the scatter visualisation as an income proxy; values are rounded to improve readability and comparability. https://data.worldbank.org/
ILO — ISCO-08: International Standard Classification of Occupations (definition of major groups). ISCO provides the occupational taxonomy that underpins “high-skill occupations” groupings in many international datasets. https://www.ilo.org/public/english/bureau/stat/isco/isco08/
OECD (context on skills, education-to-work pathways, and cross-country comparability). Useful for interpreting how education systems and labour-market institutions connect to occupational outcomes. https://www.oecd.org/