This appendix complements the economy profiles and the online data tables by providing the title, description, definition and source for each of the indicators included in the Global Innovation Index (GII) this year.
For all 139 economies in the GII in 2026, the most recent values, within the period 2016 to 2026, were used for each indicator.
The year provided next to the indicator description (directly below the indicator title) corresponds to the year when data were most frequently available for economies. When more than one year is considered, the period used is indicated at the end of the indicator’s source in parentheses.
Of the 79 indicators, 64 variables are hard data, 10 are composite indicators, marked with an asterisk (*), and five are survey questions: two from the Global Entrepreneurship Monitor, and three from the World Economic Forum, Executive Opinion Survey (EOS) – all marked with a dagger (†). In some cases, additional markings are provided at the end of the indicator description. Instances marked with a are indicators where higher scores indicate poorer outcomes, commonly known as “bads” and those marked with b signal indicators that were assigned half weights. Appendix I presents more details on the computation. Some indicators are scaled during computation to make them comparable across economies. Indicators are scaled either in relation to other comparable indicators or through division by gross domestic product (GDP) in current US dollars, purchasing power parity GDP in international dollars (PPP$ GDP), population, total trade, etc. In all cases, the scaling factor used was the value that corresponded to the same year as the unscaled indicator.
1. Institutions
1.1 Institutional environment
1.1.1 Operational stability for businesses*
Political, legal, operational or security risk index*a | 2025
Index that measures the likelihood and severity of political, legal, operational or security risks affecting business operations. Scores are annualized, standardized and aggregated for end Q1, Q2, Q3 and Q4.
Source: S&P Global, Market Intelligence, Country Risk Dataset (https://www.marketplace.spglobal.com/en/datasets/country-risk-(255)). Data year: 2025.
1.1.2 Government effectiveness*
Government effectiveness index* | 2024
Index that reflects perceptions of the quality of public services, the civil service, policy formulation and implementation, and the credibility of a government’s decisions.
Source: World Bank, Worldwide Governance Indicators (https://www.govindicators.org). Data year: 2024.
1.2 Regulatory environment
1.2.1 Regulatory quality*
Regulatory quality index*b | 2024
Index that reflects perceptions of the government’s ability to design and implement policies and regulations that promote private sector development.
Source: World Bank, Worldwide Governance Indicators (https://www.govindicators.org). Data year: 2024.
1.2.2 Rule of law*
Rule of law index*b | 2024
Index that reflects perceptions of the extent to which agents respect and follow the rules of society, including contract enforcement, property rights, the police, courts, and the likelihood of crime and violence. Scores are standardized.
Source: World Bank, Worldwide Governance Indicators (https://www.govindicators.org). Data year: 2024.
1.3 Business environment
1.3.1 Policy stability for doing business†
The extent to which governments ensure a stable policy environment for doing business† | 2025
Average answer to the survey question: In your country, to what extent does the government ensure a stable policy environment for doing business? [1 = not at all; 7 = to a great extent].
Source: World Economic Forum, Executive Opinion Survey 2025: “Government ensuring policy stability” indicator (EOSQ434) (https://www.weforum.org). Data years: 2017–2025.
1.3.2 Entrepreneurship policies and culture†
Entrepreneurship policies and culture index† | 2025
Average perception scores (five-year average) of experts on entrepreneurial policies and entrepreneurial culture (items B, C, I3, and I4 of the GEM National Expert Survey). Experts in different fields (purposive sampling, minimum 36 experts per year) assess conditions for entrepreneurship in their country via statements (0 = completely false; 10 = completely true). Country participation in GEM varies and therefore the number of experts and years on which this item is based differs according to the country.
Source: Global Entrepreneurship Monitor (GEM), National Expert Survey (NES) (https://www.gemconsortium.org/wiki/1142). Data years: 2016–2025.
2. Human capital and research
2.1 Education
2.1.1 Expenditure on education, % GDP
Government expenditure on education (% of GDP) | 2023
Total general (local, regional and central) government expenditure on education (current, capital and transfers), expressed as a percentage of GDP. It includes expenditure funded by transfers from international sources to government.
Source: UNESCO Institute for Statistics (UIS) online database (http://data.uis.unesco.org). Data years: 2016–2025.
2.1.2 Government funding/pupil, secondary, % GDP/cap
Government funding per secondary pupil (% of GDP per capita) | 2022
Average total (current, capital and transfers) general government expenditure per student, at secondary level, expressed as a percentage of GDP per capita.
Source: UNESCO Institute for Statistics (UIS) online database (http://data.uis.unesco.org). Data years: 2016–2024.
2.1.3 School life expectancy, years
School life expectancy, primary to tertiary education, both sexes (years) | 2024
Total number of years that a person of school entrance age can expect to spend within the primary to tertiary levels of education. For a child of a given age, the school life expectancy is calculated as the sum of the age-specific enrolment rates for primary to tertiary levels of education. The part of the enrolment that is not distributed by age is divided by the school-age population for the primary to tertiary level of education in which they are enrolled and multiplied by the duration of that level of education. The result is then added to the sum of the age-specific enrolment rates. A relatively high value indicates a greater probability of children spending more years in education and a higher overall retention rate within the education system. It must be noted that the expected number of years does not necessarily coincide with the expected number of grades of education completed due to grade repetition.
Source: UNESCO Institute for Statistics (UIS) online database (http://data.uis.unesco.org). Data years: 2016–2025.
2.1.4 PISA scales in reading, maths and science
PISA scales in reading, mathematics and science | 2022
PISA is the OECD’s (Organisation for Economic Co-operation and Development) Programme for International Student Assessment. PISA measures 15-year-olds’ ability to use their reading, mathematics and science knowledge and skills. Results from PISA indicate the quality and equity of learning outcomes attained around the world. The 2022 PISA survey is the eighth round of the triennial assessment. The indicator is built using the averages of the reading, mathematics and science scores for each country and economy. PISA scores are set in relation to the variation in results observed across all test participants in a country and economy. There is, theoretically, no minimum or maximum score in PISA; rather, the results are scaled to fit approximately normal distributions, with means around 500 score points and standard deviations around 100 score points for OECD countries. China did not participate in the 2022 PISA survey. China’s figure is based on the 2018 PISA cycle and represents the participating regions of Beijing, Shanghai, Jiangsu, and Zhejiang. Azerbaijan’s 2022 figure represents the participating jurisdiction of Baku.
Source: OECD Programme for International Student Assessment (PISA) (https://www.oecd.org/pisa). Data years: 2018–2022.
2.1.5 Pupil–teacher ratio, secondary
Pupil–teacher ratio, secondarya | 2024
The number of pupils enrolled in secondary school divided by the number of secondary school teachers (regardless of their teaching assignment). Where the data are missing for the secondary education level as a whole, the ratios for upper-secondary are reported; if these are also missing, the ratios for lower-secondary are reported instead. A high pupil–teacher ratio suggests that each teacher has to be responsible for a large number of pupils. In other words, the higher the pupil–teacher ratio, the lower the relative access of pupils to teachers
Source: UNESCO Institute for Statistics (UIS) online database (http://data.uis.unesco.org). Data years: 2017–2025.
2.2 Tertiary education
2.2.1 Tertiary enrolment, % gross
School enrolment, tertiary (% gross) | 2024
The ratio of total tertiary enrolment, regardless of age, expressed as a percentage of the population in the 5-year age group immediately following upper secondary education. Tertiary education, whether or not at an advanced research qualification level, normally requires, as a minimum condition of admission, the successful completion of education at the secondary level. The school enrolment ratio can exceed 100 percent due to grade repetition and the inclusion of under-aged and over-aged students, who are early or late entrants.
Source: UNESCO Institute for Statistics (UIS) online database (http://data.uis.unesco.org). Data years: 2017–2025.
2.2.2 Graduates in science and engineering, %
Graduates from science, technology, engineering and mathematics programs (% of total tertiary graduates) | 2024
The share of all tertiary-level graduates in natural sciences, mathematics, statistics, information and technology, manufacturing, engineering and construction as a percentage of all tertiary-level graduates.
Source: UNESCO Institute for Statistics (UIS) online database (http://data.uis.unesco.org); Eurostat database (https://ec.europa.eu/eurostat/data/database); and OECD, Education at a Glance (https://data-explorer.oecd.org). Data years: 2016–2025.
2.2.3 Tertiary inbound mobility, %
Tertiary inbound mobility rate (%) | 2024
The number of students from abroad studying in a given country as a percentage of the total tertiary-level enrolment in that country.
Source: UNESCO Institute for Statistics (UIS) online database (http://data.uis.unesco.org). Data years: 2017–2025.
2.3 Research and development (R&D)
2.3.1 Researchers, FTE/mn pop.
Researchers, full-time equivalent (FTE) (per million population) | 2024
Researchers in R&D are professionals engaged in the conception or creation of new knowledge. They conduct research and improve or develop concepts, theories, models, techniques, instrumentation, software or operational methods.
Source: UNESCO Institute for Statistics (UIS) online database (http://data.uis.unesco.org); Eurostat database (https://ec.europa.eu/eurostat/data/database); OECD, Main Science and Technology Indicators (MSTI) database (https://www.oecd.org/en/data/datasets/main-science-and-technology-indicators.html); and Ibero-American and Inter-American Network of Science and Technology Indicators (RICYT) (http://www.ricyt.org/en). Data years: 2016–2024.
2.3.2 Gross expenditure on R&D, % GDP
Gross expenditure on R&D (% of GDP) | 2024
Gross expenditure on R&D (GERD) is the total domestic intramural expenditure on R&D during a given period as a percentage of GDP. "Intramural R&D expenditure" is all expenditure for R&D performed within a statistical unit or sector of the economy during a specific period, regardless of the source of funding.
Source: UNESCO Institute for Statistics (UIS) online database (http://data.uis.unesco.org); Eurostat database (https://ec.europa.eu/eurostat/data/database); OECD, Main Science and Technology Indicators (MSTI) database (https://www.oecd.org/en/data/datasets/main-science-and-technology-indicators.html); and Ibero-American and Inter-American Network of Science and Technology Indicators (RICYT) (http://www.ricyt.org/en). Data years: 2016–2025.
2.3.3 Global corporate R&D investors, top 3, mn USD
Average expenditure of a country’s top three global companies on R&D, million USD | 2025
Average expenditure on R&D of the top three global companies. If a country has fewer than three global companies listed, the figure is either the average of the two companies or the total for a single company. Data are based on the 2025 EU Industrial R&D Investment Scoreboard. For countries not represented in the Scoreboard, companies from Orbis with R&D expenditure above USD 50 million were identified and used to complement the dataset. A score of 0 is given to countries with no listed companies in the Scoreboard and no companies in Orbis meeting the threshold. The data include economies outside the European Union (EU).
Source: The 2025 EU Industrial R&D Investment Scoreboard and Orbis database (https://iri.jrc.ec.europa.eu/scoreboard/2025-eu-industrial-rd-investment-scoreboard); and The 2025 EU Industrial R&D Investment Scoreboard and Orbis database (https://www.moodys.com/web/en/us/capabilities/company-reference-data/orbis.html). Data year: 2025.
2.3.4 QS university ranking, top 3*
Average score of the top three universities according to the QS World University Rankings* | 2025
Average score of the top three universities per country. If fewer than three universities are listed in the QS ranking of the global top 1,000 universities, the sum of the scores of the listed universities is divided by three, thus implying a score of zero for the non-listed universities. The 2026 ranking corresponds to data published in June 2025.
Source: QS Quacquarelli Symonds Ltd, QS World University Rankings, Top Universities (https://www.topuniversities.com/world-university-rankings). Data year: 2025.
3 Infrastructure
3.1 Information and communication technology (ICT)
3.1.1 ICT access*
ICT access index* | 2024
The ICT access index is a composite index that assigns weights to three ICT indicators (33 percent each): (1) Individuals who own a mobile cellular telephone; (2) Households with Internet access at home; and (3) Percentage of the population covered by mobile networks (at least 3G, at least LTE/WiMax, and at least 5G). The ICT indicator (3) Percentage of the population covered by mobile networks (at least 3G, at least LTE/WiMax, and at least 5G) is calculated by assigning a weight of 30 percent to Population covered by at least 3G, a weight of 50 percent to Population covered by at least LTE/WiMax, and a weight of 20 percent to Population covered by at least 5G.
Source: World Intellectual Property Organization (https://www.wipo.int); based on International Telecommunication Union (ITU) DataHub, accessed March 23, 2026 (https://datahub.itu.int). Data year: 2024.
3.1.2 ICT use*
ICT use index* | 2024
The ICT use index is a composite index that assigns weights to five ICT indicators (20 percent each): (1) Fixed-broadband Internet basket (% GNI per capita); (2) Fixed-broadband Internet traffic (GB per subscription); (3) Mobile data and voice high-consumption basket (% GNI per capita); (4) Mobile-broadband Internet traffic within the country (GB per subscription); (5) Active mobile-broadband subscriptions per 100 people.
Source: World Intellectual Property Organization (https://www.wipo.int); based on International Telecommunication Union (ITU) DataHub, accessed April 15, 2026 (https://datahub.itu.int). Data year: 2024.
3.1.3 Government online service*
Government online service index* | 2024
The Online Service Index (OSI) is a component of the E-Government Development Index. The OSI is a composite indicator that assesses how well governments use technology to deliver public services at the national level. It is based on a survey of national websites and e-government policies, with scores normalized to a range of 0 to 1. In the 2024 edition, the OSI is calculated based on five weighted subindices: services provision (45%), technology (5%), institutional framework (10%), content provision (5%), and e-participation (35%), with the overall score calculated from the normalized values of each subindex.
Source: Division for Public Institutions and Digital Government (DPIDG) of the United Nations Department of Economic and Social Affairs (UNDESA), E-Government Survey 2024 (https://publicadministration.un.org/egovkb/en-us/Reports/UN-E-Government-Survey-2024). Data year: 2024.
3.2 General infrastructure
3.2.1 Electricity output, GWh/mn pop.
Electricity output (GWh per million population) | 2024
Electricity production, measured at the terminals of all alternator sets in a station. In addition to hydropower, coal, oil, gas and nuclear power generation, this indicator covers generation by geothermal, solar, wind, tide and wave energy, as well as that from combustible renewables and waste. Production includes the output of plants that are designed to produce solely electricity as well as the output of combined heat and power plants. Electricity output in GWh is scaled by population.
Source: International Energy Agency (IEA) World Energy Balances, 2025 edition (https://www.iea.org/reports/world-energy-balances-overview). Data years: 2023–2024.
3.2.2 Aviation import dwell time
Logistic Performance Indicators (LPI) 2.0a | 2024
The time elapsed between the moment an air cargo shipment becomes ready to be picked up by the consignee or his agent until the moment the cargo is cleared by customs and leaves the destination airport. More details on the methodology can be found at: https://documents.worldbank.org/en/publication/documents-reports/documentdetail/099042226142027181.
Source: Logistic Performance Indicators (LPI) 2.0 World Bank Group (https://lpi.worldbank.org/en/indicator/AV_DT); and Cargo iQ (https://www.cargoiq.org). Data years: 2023–2024.
3.2.3 Logistics performance*
Logistics Performance Index* | 2023
A multidimensional assessment of logistics performance, the 2023 Logistics Performance Index (LPI) ranks 139 countries, combining data on six core performance components into a single aggregate measure that includes customs performance, infrastructure quality and timeliness of shipments. The data used in the ranking come from a survey of logistics professionals who are asked questions about the foreign countries in which they operate. The LPI’s six components are: (1) Customs: the efficiency of customs and border management clearance; (2) Infrastructure: the quality of trade and transport infrastructure; (3) International shipments: the ease of arranging competitively priced shipments; (4) Services quality: the competence and quality of logistics services; (5) Tracking and tracing: the ability to track and trace consignments; and (6) Timeliness: the frequency with which shipments reach consignees within scheduled or expected delivery times.
Source: World Bank, Logistics Performance Index 2023 (https://lpi.worldbank.org/en/indicators/survey-based-lpi-2007-2023); and World Bank (2023), Connecting to Compete 2023: Trade Logistics in the Global Economy – The Logistics Performance Index and its Indicators (https://documents.worldbank.org/en/publication/documents-reports/documentdetail/099042123145531599). Data year: 2023.
3.2.4 Gross capital formation, % GDP
Gross capital formation (% of GDP, three-year average) | 2025
Gross capital formation is expressed as the ratio of total investment in current local currency to GDP in current local currency. Investment or gross capital formation is measured by the total value of the gross fixed capital formation and changes in inventories and acquisitions less disposals of valuables for a unit or sector, on the basis of the System of National Accounts (SNA) 1993.
Source: International Monetary Fund, World Economic Outlook Database, October 2025 (https://data.imf.org/en/datasets/IMF.RES:WEO). Data years: 2017–2025.
3.3 Ecological sustainability
3.3.1 GDP/unit of energy use
GDP per total energy supply (per thousand 2020 PPP$ GDP) | 2023
Purchasing power parity gross domestic product (2020 PPP$ GDP) per total energy supply (TES). TES is made up of production + imports – exports – international marine bunkers – international aviation bunkers +/– stock changes. GDP/TES is an indicator of energy productivity.
Source: International Energy Agency (IEA) World Energy Balances, 2025 edition (https://www.iea.org/reports/world-energy-balances-overview). Data years: 2023–2024.
3.3.2 Low-carbon energy use, %
The share of a country’s total energy supply (TES) that is from low-carbon intensive sources | 2024
The low-carbon intensive energy share is calculated based on its share of a country’s Total Energy Supply (TES), expressed in petajoules. TES is a measure of the total amount of energy that a country needs to supply to meet its final end-use demand. It reflects the energy that is either produced domestically or imported, minus what is exported or stored. The full energy mix is considered, comprising high-carbon intensive fossil fuel sources (oil, coal, and natural gas) as well as low-carbon intensive sources (hydro, nuclear, wind, biomass, solar, and geothermal). To allow low-carbon intensive energy sources to be compared on a consistent basis with fossil fuels, the Physical Energy Content method is used. For non-combustible renewables such as wind and solar, the primary energy equivalent is measured as the gross amount of electricity generated, with an efficiency assumption of 100%. For non-fossil fuel sources involving a heat input (nuclear, solar, and geothermal), fixed thermal efficiency factors are applied: 33% for nuclear and solar, and 10% for geothermal. For biomass combustion, an efficiency factor of 33% is used.
Source: The Energy Institute Statistical Review of World Energy (https://www.energyinst.org/statistical-review). Data year: 2024.
3.3.3 ISO 14001 environment/bn PPP$ GDP
ISO 14001 Environmental management systems, number of certificates issued (per billion PPP$ GDP) | 2024
ISO 14001 specifies the requirements for an environmental management system that an organization can use to enhance its environmental performance. ISO 14001 is intended for use by an organization that is seeking to manage its environmental responsibilities in a systematic manner that contributes to the environmental pillar of sustainability. ISO 14001 helps an organization to achieve the intended outcomes of its environmental management system, providing value for the environment, the organization itself and interested parties. Consistent with the organization's environmental policy, the intended outcomes of an environmental management system include enhancement of environmental performance, fulfillment of compliance obligations and achievement of environmental objectives. ISO 14001 is applicable to any organization, regardless of size, type or nature, and applies to the environmental aspects of its activities, products and services that the organization determines it can either control or influence from a life cycle perspective. ISO 14001 does not state specific environmental performance criteria. It can be used in whole or in part to systematically improve environmental management. Claims of conformity to ISO 14001, however, are not acceptable unless all its requirements are incorporated into an organization's environmental management system and fulfilled without exclusion. The data are reported per billion PPP$ GDP.
Source: International Organization for Standardization (ISO) and International Accreditation Forum (IAF) CertSearch (https://www.iafcertsearch.org); and International Monetary Fund, World Economic Outlook Database, October 2025 (https://data.imf.org/en/datasets/IMF.RES:WEO). Data year: 2024.
4. Market sophistication
4.1 Credit
4.1.1 Finance for startups and scaleups†
Finance for startups and scaleups† | 2025
Average perception scores (five-year average) of experts on finance for starting and growing firms (item A1 of the GEM National Expert Survey). Experts in different fields (purposive sampling, minimum 36 experts per year) assess conditions for entrepreneurship in their country via statements (0 = completely false; 10 = completely true). Country participation in GEM varies and therefore the number of experts and years on which this item is based differs according to the country.
Source: Global Entrepreneurship Monitor (GEM), National Expert Survey (NES) (https://www.gemconsortium.org/wiki/1142). Data years: 2016–2025.
4.1.2 Domestic credit to private sector, % GDP
Domestic credit to private sector (% of GDP) | 2024
Domestic credit to private sector refers to financial resources provided to the private sector by financial corporations, such as through loans, purchases of non-equity securities, and trade credits and other accounts receivable, that establish a claim for repayment. For some countries, these claims include credit to public enterprises. The financial corporations include monetary authorities and deposit money banks, as well as other financial corporations where data are available (including corporations that do not allow transferable deposits but do accept such liabilities as time and savings deposits). Examples of other financial corporations are finance and leasing companies, money lenders, insurance corporations, pension funds and foreign exchange companies.
Source: International Monetary Fund, International Financial Statistics database (https://data.imf.org); and Organisation for Economic Co-operation and Development, National Accounts data files; data extracted from the World Bank's World Development Indicators database (https://databank.worldbank.org/source/world-development-indicators). Data years: 2016–2024.
4.1.3 Loans from microfinance institutions, % GDP
Loans from all microfinance institutions (% of GDP) | 2024
Outstanding loans from all microfinance institutions in a country as a percentage of its GDP.
Source: International Monetary Fund, Financial Access Survey (FAS) (https://data.imf.org/en/datasets/IMF.STA:FAS). Data years: 2020–2024.
4.2. Investment
4.2.1 Market capitalization, % GDP
Market capitalization of listed domestic companies (% of GDP, three-year average) | 2024
Market capitalization (also known as "market value") is the share price times the number of shares outstanding (including their several classes) for listed domestic companies. Investment funds, unit trusts and companies whose only business goal is to hold shares of other listed companies are excluded. Data are the average of the end of year values for the last three years.
Source: World Federation of Exchanges database (https://www.world-exchanges.org/our-work/statistics); extracted from the World Bank’s World Development Indicators database (https://databank.worldbank.org/source/world-development-indicators). Data years: 2017–2024.
4.2.2 Venture capital (VC) received, deal count/bn PPP$ GDP
Venture capital deals received by enterprises headquartered in a given economy (per billion PPP$ GDP, three-year average) | 2025
Indicator that reflects the total number of VC deals received in a given economy. These are transactions going to a venture or company which has its headquarters in the underlying economy. Investors may originate from any global region. Included investors range from individual angels, angel groups, seed and venture funds, corporate venture capital (CVC) arms, and other corporate entities. Deals associated with accelerator programs are excluded unless the accelerator participates in follow-on rounds, in which case only those subsequent financings are included. All equity transactions and mixed debt-and-equity deals are counted. Pure debt deals are excluded, as they fall under venture debt datasets rather than VC activity datasets. The data corresponds to VC deal counts between January 1, 2023, and December 31, 2025. The data represent the three-year average of 2023–2025 deals and are reported per billion PPP$ GDP.
Source: PitchBook Data, Inc (https://www.pitchbook.com); and International Monetary Fund, World Economic Outlook Database, October 2025 (https://data.imf.org/en/datasets/IMF.RES:WEO). Data years: 2024–2025.
4.2.3 Late-stage VC deal count, % global VC
Late-stage VC deal counts received by enterprises headquartered in a given economy (% of all VC deal counts worldwide, three-year average) | 2025
Indicator that reflects the total number of VC late-stage deal counts going to a venture or company which has its headquarters in the underlying economy. The transactions encompass both Late Stage and Venture Growth rounds, according to the firm’s internal stage classification system. Late-Stage VC is defined as either (1) financings for companies that are five or more years old, regardless of round label, or (2) rounds labelled Series C or later, regardless of company age. Venture Growth typically includes Series E and beyond. In cases where a round label is not available, classification is determined by factors such as company age, number of prior VC rounds, investor type, and company status. Only equity and mixed equity-debt financings are included. Full-debt financings are excluded. The data corresponds to VC deals between January 1, 2023, and December 31, 2025. The data represent the three-year average of 2023–2025 deals and are reported as a percentage of all VC deals worldwide at all investment stages.
Source: PitchBook Data, Inc (https://www.pitchbook.com). Data years: 2024–2025.
4.2.4 VC investors, deal count/bn PPP$ GDP
Venture capital deals completed by investors (per billion PPP$ GDP, three-year average) | 2025
Indicator that captures the number of unique VC deals involving at least one investor headquartered in the underlying economy. To avoid duplication, if multiple investors from the same country participate in a single deal, the deal is counted only once for that country. Deals associated with accelerator programs are excluded unless the accelerator participates in follow-on rounds, in which case only those subsequent financings are included. All equity transactions and mixed debt-and-equity deals are counted. Pure debt deals are excluded, as they fall under venture debt datasets rather than VC activity datasets. The data correspond to VC deals between January 1, 2023, and December 31, 2025. The data represent the three-year average of 2023–2025 deals and are reported per billion PPP$ GDP.
Source: PitchBook Data, Inc. (https://www.pitchbook.com); and International Monetary Fund, World Economic Outlook Database, October 2025 (https://data.imf.org/en/datasets/IMF.RES:WEO). Data years: 2024–2025.
4.3. Trade, diversification and market scale
4.3.1 Applied tariff rate, weighted avg., %
Tariff rate, applied, weighted average, all products (%)a | 2024
The effectively applied tariff is the minimum tariff imposed by one country to another representing the most advantageous tariff, encompassing all preferential trade agreements and most-favored-nation (MFN) tariffs, and weighted by the import values of the product and country of origin pairings. All calculations have been conducted based on imported products at the Harmonized System (HS) subheading level. Tariffs include both ad valorem duties and ad valorem equivalents in the calculations. Any missing tariffs or Ad Valorem equivalents not calculated at the subheading level have been omitted. The European Union (27) is treated as a unified entity, thus intra-EU trade has been disregarded.
Source: WTO Analytical Database (https://www.wto.org/english/tratop_e/tariffs_e/tariffs_e.htm). Data years: 2016–2024.
4.3.2 Domestic industry diversification
Domestic industry diversification (based on manufacturing output)a | 2023
The Herfindahl-Hirschman Index (HHI) for the domestic industry is defined as the sum of the squared shares of industries in total manufacturing output.
Source: United Nations Industrial Development Organization (UNIDO), Industrial Statistics Database (INDSTAT), two-digit level of the International Standard Industrial Classification (ISIC) Revision 3 and Revision 4 (https://stat.unido.org). Data years: 2016–2024.
4.3.3 Domestic market scale, bn PPP$
Domestic market scale as measured by GDP, bn PPP$ | 2025
The domestic market size is measured by GDP based on the PPP valuation of country GDP, in current international dollars (billions).
Source: International Monetary Fund, World Economic Outlook Database, October 2025 (https://data.imf.org/en/datasets/IMF.RES:WEO). Data years: 2024–2025.
5. Business sophistication
5.1. Knowledge workers
5.1.1 Knowledge-intensive employment, %
Employment in knowledge-intensive services, % of workforce (15+ years old) | 2025
Sum of people in categories 1 to 3 as a percentage of total people employed, according to the International Standard Classification of Occupations (ISCO). Categories included in ISCO 08 are: 1 Managers; 2 Professionals; 3 Technicians and Associate Professionals. Where ISCO 08 data were not available, ISCO 88 data were used. Categories included in ISCO 88 are: 1 Legislators, senior officials and managers; 2 Professionals; 3 Technicians and associate professionals.
Source: International Labour Organization (ILO), ILOSTAT Database of Labour Statistics (https://ilostat.ilo.org). Data years: 2016–2025.
5.1.2 Females employed w/advanced degrees, %
Females employed with advanced degrees, % total employed (25+ years old) | 2025
The percentage of females employed with advanced degrees out of total employed. The employed comprise all persons of working age who, during a specified brief period, were in one of the following categories: (1) paid employment; or (2) self-employment. Data are disaggregated by level of education, which refers to the highest level of education completed, classified according to the International Standard Classification of Education (ISCE). Data for Canada are based on Table 14-10-0020-01 of the country's Labour Force Survey estimates.
Source: International Labour Organization, ILOSTAT Database of Labour Statistics (https://ilostat.ilo.org); and Statistics Canada, Table 14-10-0020-01 Unemployment rate, participation rate and employment rate by educational attainment, annual (https://www150.statcan.gc.ca/t1/tbl1/en/tv.action?pid=1410002001). Data years: 2016–2025.
5.1.3 Youth demographic dividend, %
Youth demographic dividend (% of total population) | 2026
The Youth demographic dividend refers to the share of the population aged 0–24 years as a percentage of the total population. It reflects the potential economic and innovation-related advantage that a country may derive in the future from a large youth cohort. This demographic structure is referred to as a “dividend” because, if effectively educated and integrated into the labor force, young people can enhance future innovation capacity, sustain long-term economic growth, and mitigate the effects of population aging.
Source: United Nations Department of Economic and Social Affairs, Population Division, World Population Prospects 2024 (https://population.un.org/wpp). Data year: 2026.
5.1.4 GERD performed by business, % GDP
GERD performed by business enterprises (% of GDP) | 2024
Gross expenditure on R&D performed by business enterprise as a percentage of GDP. For the definition of GERD, see indicator 2.3.2.
Source: UNESCO Institute for Statistics (UIS) online database (http://data.uis.unesco.org); Eurostat database (https://ec.europa.eu/eurostat/data/database); OECD, Main Science and Technology Indicators (MSTI) database (https://www.oecd.org/en/data/datasets/main-science-and-technology-indicators.html); and Ibero-American and Inter-American Network of Science and Technology Indicators (RICYT) (http://www.ricyt.org/en). Data years: 2017–2025.
5.1.5 GERD financed by business, %
GERD financed by business enterprises (% of GERD) | 2023
Gross expenditure on R&D financed by business enterprise as a percentage of total gross expenditure on R&D. For the definition of GERD, see indicator 2.3.2.
Source: UNESCO Institute for Statistics (UIS) online database (http://data.uis.unesco.org); Eurostat database (https://ec.europa.eu/eurostat/data/database); OECD, Main Science and Technology Indicators (MSTI) database (https://www.oecd.org/en/data/datasets/main-science-and-technology-indicators.html); and Ibero-American and Inter-American Network of Science and Technology Indicators (RICYT) (http://www.ricyt.org/en). Data years: 2017–2025.
5.2. Innovation linkages
5.2.1 Public research–industry co-publications, %
Public–private co-authored research publications (% of total research publications, five-year average) | 2025
Public–private co-authored research publications as a percentage of all research publications. Research publications are limited to the following four main fields of science: Biomedical and health sciences, Life and earth sciences, Mathematics and computer science, and Physical sciences and engineering. The definition of the “private sector” includes all for-profit business enterprises, covering all manufacturing and services sectors. This includes research institutes and other corporate R&D laboratories that are fully funded or owned by for-profit business enterprises. Organizations in the private education sector and private health care sector organizations (including hospitals and clinics) are not classified as private sector.
Source: Centre for Science and Technology Studies (CWTS), Leiden University, based on Clarivate Web of Science (https://www.cwts.nl). Data year: 2025.
5.2.2 University–industry R&D collaboration†
The extent to which businesses and universities collaborate on R&D† | 2025
Average answer to the survey question: In your country, to what extent do businesses and universities collaborate on research and development (R&D)? [1 = not at all; 7 = to a great extent].
Source: World Economic Forum, Executive Opinion Survey 2025: “University–industry collaboration in R&D” indicator (EOSQ072) (https://www.weforum.org). Data years: 2017–2025.
5.2.3 University industry and international engagement, top 5*
Times Higher Education (THE) ranking, combined Industry and International pillar score, two-year average of up to five universities* | 2023
Average score of up to five universities per country, based on the Times Higher Education World University Rankings (WUR). For each university, the score is calculated as the average of the International and Industry pillar scores. Universities are ranked within each country based on this combined score, and the top five selected (or all universities if fewer than five are available). The country score is calculated as the average of the selected universities’ scores. The final score is the average of the country scores for the 2025 and 2026 editions of the WUR, reflecting data from the corresponding academic years. The 2026 ranking corresponds to data from the academic year ended in 2022 and 2023.
Source: Times Higher Education, World University Rankings 2026 (https://www.timeshighereducation.com/world-university-rankings/2026/world-ranking). Data year: 2023.
5.2.4 State of cluster development†
How widespread clusters are† | 2025
Average answer to the survey question: In your country, how widespread are well-developed and deep clusters (geographic concentrations of firms, suppliers, producers of related products and services, and specialized institutions in a particular field)? [1 = nonexistent; 7 = widespread in many fields].
Source: World Economic Forum, Executive Opinion Survey 2025: “State of cluster development” indicator (EOSQ109) (https://www.weforum.org). Data years: 2017–2025.
5.2.5 Patent families/bn PPP$ GDP
Number of patent families filed in at least two offices (per billion PPP$ GDP) | 2022
A patent family is a set of interrelated patent applications filed in one or more countries or jurisdictions to protect the same invention. Patent families containing applications filed in at least two different offices is a subset of patent families where protection of the same invention is sought in at least two different countries. In this report, “patent families data” refers to patent families containing applications filed in at least two intellectual property (IP) offices; the data are scaled by PPP$ GDP (billions). A patent is a set of exclusive rights granted by law to applicants for inventions that are new, non-obvious and industrially applicable. A patent is valid for a limited period of time (generally 20 years) and within a defined territory. The patent system is designed to encourage innovation by providing innovators with time-limited exclusive legal rights, thus enabling them to reap the rewards of their innovative activity.
Source: World Intellectual Property Organization, Intellectual Property Statistics (https://www.wipo.int/ipstats); and International Monetary Fund, World Economic Outlook Database, October 2025 (https://data.imf.org/en/datasets/IMF.RES:WEO). Data year: 2022.
5.3 Knowledge absorption
5.3.1 Intellectual property payments, % total trade
Charges for use of intellectual property, i.e., payments (% of total trade, three-year average) | 2024
Charges for the use of intellectual property not included elsewhere, i.e., payments (% of total trade), average of three most recent years or most recent year. Value is calculated according to the Extended Balance of Payments Services Classification EBOPS 2010, that is, code SH: Charges for the use of intellectual property not included elsewhere, as a percentage of total trade. Total trade is defined as the sum of total imports of code G goods and code SOX commercial services (excluding government goods and services not included elsewhere) plus total exports of code G goods and code SOX commercial services (excluding government goods and services not included elsewhere), divided by 2. According to the sixth edition of the International Monetary Fund’s Balance of Payments Manual, the item “Goods” covers general merchandise, net exports of goods under merchanting and non-monetary gold. The “commercial services” category is defined as being equal to “services” minus “government goods and services not included elsewhere.” Receipts are between residents and non-residents for the use of proprietary rights (such as patents, trademarks, copyrights, industrial processes and designs, including trade secrets and franchises), and for licenses to reproduce or distribute (or both) intellectual property embodied in produced originals or prototypes (such as copyrights on books and manuscripts, computer software, cinematographic works and sound recordings) and related rights (such as for live performances and television, cable or satellite broadcast).
Source: Trade in Commercial Services database (https://stats.wto.org); and WTO–OECD Balanced Trade in Services (BaTiS) dataset ( https://www.wto.org/english/res_e/statis_e/gstdh_batis_e.htm). Data years: 2020–2024.
5.3.2 High-tech imports, % total trade
High-tech imports (% of total trade) | 2024
High-technology imports as a percentage of total trade. High-technology exports and imports contain technical products with a high intensity of R&D, defined by the Eurostat classification, which is based on Standard International Trade Classification (SITC) Revision 4 and the OECD definition. Commodities belong to the following sectors: aerospace; computers and office machines; electronics telecommunications; pharmacy; scientific instruments; electrical machinery; chemistry; non-electrical machinery; and armament. Trade Data Monitor (TDM) data are used to complement Comtrade data and improve data timeliness where necessary.
Source: United Nations Comtrade Database (http://comtrade.un.org); Trade Data Monitor (https://www.tradedatamonitor.com); and World Trade Organization and United Nations Conference on Trade and Development (https://stats.wto.org). Data years: 2018–2024.
5.3.3 ICT services imports, % total trade
Telecommunications, computer and information services imports (% of total trade) | 2024
Telecommunications, computer and information services imports as a percentage of total trade according to the OECD’s Extended Balance of Payments Services Classification EBOPS 2010, coded SI: Telecommunications, computer, and information services. Values are based on the classification of the sixth (2009) edition of the International Monetary Fund’s Balance of Payments and International Investment Position Manual and Balance of Payments database. For the definition of total trade, see indicator 5.3.1.
Source: Trade in Commercial Services database (https://stats.wto.org); and WTO–OECD Balanced Trade in Services (BaTiS) dataset (https://www.wto.org/english/res_e/statis_e/gstdh_batis_e.htm). Data years: 2020–2024.
5.3.4 FDI net inflows, % GDP
Foreign direct investment (FDI) net inflows (% of GDP, three-year average) | 2024
FDI net inflow is the average of the most recent three years of net inflows of investment to acquire a lasting management interest (10 percent or more of voting stock) in an enterprise operating in an economy other than that of the investor. It is the sum of equity capital, reinvestment of earnings, other long-term capital, and short-term capital as shown in the balance of payments. This data series shows net inflows (new investment inflows less disinvestment) in the reporting economy from foreign investors, and is divided by GDP. Data extracted from the World Bank's World Development Indicators database.
Source: International Monetary Fund, International Financial Statistics and Balance of Payments databases (https://data.imf.org); World Bank, International Debt Statistics (www.worldbank.org/en/programs/debt-statistics); and OECD GDP estimates (https://data.oecd.org); data extracted from the World Bank's World Development Indicators database (https://databank.worldbank.org/source/world-development-indicators). Data years: 2023–2024.
5.3.5 Green-field R&D & high-tech FDI
RCA in green-field FDI announcements, R&D and high-tech projects (counts) | 2025
Revealed Competitive Advantage (RCA) in green-field foreign R&D and high-tech investment (inflows and outflows), project announcements, in counts, 3-year average. fDi Markets classifies green-field FDI as cross-border investment in a new physical project or expansion that creates new jobs and capital investment. It excludes mergers, acquisitions or other equity investments. Green-field investment brings new productive capacity, technology and capability rather than simply a change of ownership, which maps onto innovation better than does total FDI flows. The sector and activity tagging isolates innovation-relevant FDI (R&D, design, ICT, etc.). The RCA is calculated as a given economy’s share of world high-tech and R&D FDI projects announcements divided by its share of world Gross Fixed Capital Formation (GFCF).
Source: FT Locations fDi Markets and International Monetary Fund, World Economic Outlook Database, April 2026 (https://www.ftlocations.com/products-and-services/fdi-markets); and International Monetary Fund, World Economic Outlook Database, April 2026 (https://data.imf.org/en/datasets/IMF.RES:WEO). Data years: 2021–2025.
5.3.6 Research talent, % in businesses
Researchers in business enterprise (%) | 2024
Researchers in the business enterprise sector, measured in full-time equivalence (FTE), refers to researchers as professionals engaged in the conception or creation of new knowledge, products, processes, methods and systems, as well as in the management of these projects, broken down by the sectors in which they are employed (business enterprise, government, higher education and private non-profit organizations). In the context of R&D statistics, the business enterprise sector includes all firms, organizations and institutions whose primary activity is the market production of goods or services (other than higher education) for sale to the general public at an economically significant price, and the mainly private non-profit institutions serving them; the core of this sector is made up of private enterprises.
Source: UNESCO Institute for Statistics (UIS) online database (http://data.uis.unesco.org); Eurostat database (https://ec.europa.eu/eurostat/data/database); OECD, Main Science and Technology Indicators (MSTI) database (https://data-explorer.oecd.org); and Ibero-American and Inter-American Network of Science and Technology Indicators (RICYT) (http://www.ricyt.org/en). Data years: 2016–2024.
6. Knowledge and technology outputs
6.1 Knowledge creation
6.1.1 Patents by origin/bn PPP$ GDP
Number of resident patent applications filed at a given national or regional patent office (per billion PPP$ GDP) | 2024
The definition of a patent can be found in the description of indicator 5.2.5. A resident patent application refers to an application filed with the intellectual property office for or on behalf of the first-named applicant’s country of residence. For example, an application filed with the Japan Patent Office by a resident of Japan is to be considered a resident application for Japan. Similarly, an application filed with the European Patent Office (EPO) by an applicant who resides in any of the EPO member states (for example Germany) is considered to be a resident application for that member state (Germany). Data are scaled by PPP$ GDP (billions).
Source: World Intellectual Property Organization, Intellectual Property Statistics (https://www.wipo.int/ipstats); and International Monetary Fund, World Economic Outlook Database, October 2025 (https://data.imf.org/en/datasets/IMF.RES:WEO). Data years: 2016–2024.
6.1.2 PCT patents by inventor origin/bn PPP$ GDP
Number of Patent Cooperation Treaty (PCT) applications by inventor origin (fractional counts, per billion PPP$ GDP) | 2025
Indicator that measures the inventive output of economies based on the origin of inventors listed in published international patent applications filed through the WIPO-administered Patent Cooperation Treaty (PCT). Using a fractional counting method, each application is proportionally attributed to the countries of residence of all listed inventors, thereby offering a more accurate view of inventive activity. The data cover only published PCT applications and are limited to PCT Contracting States (158 to date). Data are scaled by PPP$ GDP (billions).
Source: World Intellectual Property Organization, Intellectual Property Statistics (https://www.wipo.int/ipstats); and International Monetary Fund, World Economic Outlook Database, October 2025 (https://data.imf.org/en/datasets/IMF.RES:WEO). Data year: 2025.
6.1.3 Utility models by origin/bn PPP$ GDP
Number of resident utility model applications filed at the national patent office (per billion PPP$ GDP) | 2024
A utility model (UM) is a special form of patent right. The terms and conditions for granting a UM are slightly different from those for patents and include a shorter term of protection and less stringent patentability requirements. A resident UM application refers to an application filed with an intellectual property (IP) office for or on behalf of the first-named applicant's country of residence. For example, an application filed with the IP office of Germany by a resident of Germany is considered a resident application for Germany. Data are scaled by PPP$ GDP (billions).
Source: World Intellectual Property Organization, Intellectual Property Statistics (https://www.wipo.int/ipstats); and International Monetary Fund, World Economic Outlook Database, October 2025 (https://data.imf.org/en/datasets/IMF.RES:WEO). Data years: 2019–2024.
6.1.4 Scientific and technical articles/bn PPP$ GDP
Number of scientific and technical journal articles (per billion PPP$ GDP) | 2025
The number of articles published in the fields of science and technology. This encompasses 182 different research categories belonging to research areas including agriculture, biochemistry, cell biology, chemistry, computer science, engineering, environmental sciences, mathematics, molecular biology, oncology, physics and many more. Article counts are taken from a set of journals covered by the Science Citation Index Expanded (SCIE) and the Social Sciences Citation Index (SSCI). Articles are classified by year of publication and assigned to each economy on the basis of the institutional address(es) listed in the article.
Articles are counted on a count basis (rather than a fractional basis) – that is, for articles with collaborating institutions from multiple economies, each economy receives credit on the basis of its participating institutions. Data are reported per billion PPP$ GDP.
Source: Clarivate, Web of Science, May 2026 (https://clarivate.com/webofsciencegroup/solutions/web-of-science); and International Monetary Fund, World Economic Outlook Database, October 2025 (https://data.imf.org/en/datasets/IMF.RES:WEO). Data year: 2025.
6.1.5 Citable documents H-index
The H-index is an economy’s number of published articles (H) that have received at least H citations | 2025
The H-index expresses the journal's number of articles (H) that have received at least H citations. It quantifies both journal scientific productivity and scientific impact, and is also applicable to scientists, journals, and so on. The H-index is tabulated from the number of citations received in subsequent years by articles published in a given year, divided by the number of articles published that year.
Source: SCImago, SJR SCImago Journal & Country Rank, retrieved April 2026 (https://www.scimagojr.com). Data year: 2025.
6.2 Knowledge impact
6.2.1 Labor productivity growth, %
Growth rate of GDP per person employed (%, five-year average) | 2025
Growth rate of real GDP per person employed, average of five most recent available years (2021–2025). Growth of GDP per person engaged provides a measure of labor productivity (defined as output per unit of labor input). GDP per person employed is GDP divided by total employment in the economy.
Source: The Conference Board Total Economy Database, April 2026 (https://www.conference-board.org/data/economydatabase). Data year: 2025.
6.2.2 Unicorn valuation, % GDP
Combined valuation of a country’s unicorns (% of GDP) | 2026
Total valuation of all unicorns in a country as a percentage of GDP. A unicorn company is a private company with a valuation over USD 1 billion. The indicator is based on unicorns as of January 2026, covering nearly 2,000 companies worldwide. For African countries, the dataset is supplemented with data from Africa: The Big Deal. PitchBook data is used as a complementary source to enrich data coverage, with duplicates removed.
Source: CBInsights, Tracker – The Complete list of Unicorn Companies (https://www.cbinsights.com/research-unicorn-companies); Africa: The Big Deal (https://thebigdeal.substack.com/p/unicorns); Pitchbook Unicorns Company Tracker (https://www.pitchbook.com); and International Monetary Fund, World Economic Outlook Database, October 2025 (https://data.imf.org/en/datasets/IMF.RES:WEO). Data year: 2026.
6.2.3 Software spending, % GDP
Total computer software spending (% of GDP) | 2025
Computer software spending includes the total value of purchased or leased packaged software, such as operating systems, database systems, programming tools, utilities and applications. It excludes expenditures for internal software development. The data are estimated based on software and services industry sales data. For countries where industry sales data are unavailable, the data are estimated using macro level variable and trade data. Data are reported as a percentage of GDP.
Source: S&P Global, Market Intelligence (https://www.marketplace.spglobal.com/en/datasets). Data year: 2025.
6.2.4 High-tech manufacturing, %
High-tech and medium-high-tech manufacturing (% of total manufacturing output) | 2023
High technology and medium-high technology (MHT) output as a percentage of total manufacturing output, on the basis of the OECD classification of Technology Intensity Definition, itself based on International Standard Industrial Classification (ISIC) Rev.3 and Rev.4.
Source: United Nations Industrial Development Organization (UNIDO), Industrial Statistics Database (INDSTAT), two-digit level of the International Standard Industrial Classification (ISIC) Revision 3 and Revision 4 (https://stat.unido.org). Data years: 2016–2024.
6.3. Knowledge diffusion
6.3.1 Intellectual property receipts, % total trade
Charges for use of intellectual property, i.e., receipts (% total trade, three-year average) | 2024
Charges for the use of intellectual property not included elsewhere, i.e., receipts (% of total trade), average of three most recent years or most recent year. Value is calculated according to the Extended Balance of Payments Services Classification EBOPS 2010, that is, code SH: Charges for the use of intellectual property not included elsewhere, as a percentage of total trade. Receipts are between residents and non-residents for the use of proprietary rights (such as patents, trademarks, copyrights, industrial processes and designs, including trade secrets and franchises), and for licenses to reproduce or distribute (or both) intellectual property embodied in produced originals or prototypes (such as copyright on books and manuscripts, computer software, cinematographic works and sound recordings) and related rights (such as for live performances and television, cable, or satellite broadcast). Values are based on the classification of the sixth (2009) edition of the International Monetary Fund’s Balance of Payments and International Investment Position Manual and Balance of Payments database. For the definition of total trade, see indicator 5.3.1.
Source: Trade in Commercial Services database (https://stats.wto.org); and WTO–OECD Balanced Trade in Services (BaTiS) dataset (https://www.wto.org/english/res_e/statis_e/gstdh_batis_e.htm). Data years: 2016–2024.
6.3.2 Production and export complexity
The Economic Complexity Index | 2024
The Economic Complexity Index is a ranking of countries based on the diversity and complexity of their export basket. High-complexity countries are home to a range of sophisticated, specialized capabilities and are therefore able to produce a highly diversified set of complex products. Determining the economic complexity of a country is not solely dependent on a country’s productive knowledge. Information about how many capabilities a country has is contained not only in the absolute number of products that it makes, but also in the ubiquity of those products (the number of countries that import those products) and in the sophistication and diversity of the products that those other countries make. Economic complexity expresses the diversity and sophistication of the productive capabilities embedded in the exports of each country.
Source: The Atlas of Economic Complexity, Growth Lab at Harvard University (https://atlas.hks.harvard.edu). Data year: 2024.
6.3.3 High-tech exports, % total trade
High-tech exports (% of total trade) | 2024
High-technology exports as a percentage of total trade. See indicator 5.3.2 for details. Data for Hong Kong, China are corrected for re-exports using data from the Trade Data Monitor (TDM). TDM data are used to complement Comtrade data and improve data timeliness where necessary.
Source: United Nations Comtrade Database (http://comtrade.un.org); Trade Data Monitor (https://www.tradedatamonitor.com); and World Trade Organization and United Nations Conference on Trade and Development (https://stats.wto.org). Data years: 2018–2024.
6.3.4 ICT services exports, % total trade
Telecommunications, computer and information services exports (% of total trade) | 2024
Telecommunications, computer and information services exports as a percentage of total trade according to the Extended Balance of Payments Services Classification EBOPS 2010, coded SI: Telecommunications, computer, and information services. Values are based on the classification of the sixth (2009) edition of the International Monetary Fund’s Balance of Payments and International Investment Position Manual and Balance of Payments database. For the definition of total trade, see indicator 5.3.1.
Source: Trade in Commercial Services database (https://stats.wto.org); and WTO–OECD Balanced Trade in Services (BaTiS) dataset (https://www.wto.org/english/res_e/statis_e/gstdh_batis_e.htm). Data years: 2020–2024.
6.3.5 ISO 9001 quality/bn PPP$ GDP
ISO 9001 Quality management systems, number of certificates issued (per billion PPP$ GDP) | 2024
ISO 9001 specifies requirements for a quality management system when an organization needs to demonstrate its ability to provide products and services that meet both customer and applicable statutory and regulatory requirements. It aims to enhance customer satisfaction through the effective application of the system, including processes for improving the system and ensuring conformity to customer and applicable statutory and regulatory requirements. All the requirements of ISO 9001 are generic and intended to be applicable to any organization, regardless of its type or size, or the products and services it provides. The data are reported per billion PPP$ GDP.
Source: International Organization for Standardization (ISO) and International Accreditation Forum (IAF) CertSearch (https://www.iafcertsearch.org); and International Monetary Fund, World Economic Outlook Database, October 2025 (https://data.imf.org/en/datasets/IMF.RES:WEO). Data year: 2024.
7. Creative outputs
7.1 Intangible assets
7.1.1 Intangible asset intensity, top 15, %
Intangible asset value as a percentage of a firm’s total value, average of the top 15 firms | 2025
The data cover a global list of firms for which intangible asset value and total firm value are observed. Only the top 15 firms of each economy are considered, ranked by intangible assets in absolute terms (in USD). Countries with fewer than 15 firms are not considered. For each firm, the intangible asset value is divided by the firm’s total value before the arithmetic mean across the top 15 firms for each economy is computed.
Source: Brand Finance Global Intangible Finance Tracker (https://brandirectory.com/reports/global-intangible-finance-tracker-gift/2025). Data years: 2022–2025.
7.1.2 Trademarks by origin/bn PPP$ GDP
Number of classes in resident trademark applications issued at a given national or regional office (per billion PPP$ GDP) | 2024
A trademark is a sign used by the owner of certain products or the provider of certain services to distinguish them from the products or services of other companies. A trademark can consist of words or a combination of words and other elements, such as slogans, names, logos, figures and images, letters, numbers, sounds and moving images. The procedures for registering trademarks are governed by the legislation and procedures of national and regional intellectual property (IP) offices. Trademark rights are limited to the jurisdiction of the IP office that registers the trademark. Trademarks can be registered by filing an application at the relevant national or regional office(s) or by filing an international application through the Madrid System. A resident trademark application refers to an application filed with an IP office for or on behalf of the first-named applicant’s country of residence. For example, an application filed with the Japan Patent Office by a resident of Japan is considered to be a resident application for Japan. Similarly, an application filed with the European Intellectual Property Office by an applicant who resides in any of the EU member states, such as France, is considered to be a resident application for that member state (France). This indicator is based on class count – the total number of goods and services classes specified in resident trademark applications. Data are scaled by PPP$ GDP (billions).
Source: World Intellectual Property Organization, Intellectual Property Statistics (https://www.wipo.int/ipstats); and International Monetary Fund, World Economic Outlook Database, October 2025 (https://data.imf.org/en/datasets/IMF.RES:WEO). Data years: 2017–2024.
7.1.3 Global brand value, top 5,000, % GDP
Global brand value of the top 5,000 brands (% of GDP) | 2026
Sum of global brand values, top 5,000 as a percentage of GDP. Brand Finance calculates brand value using the royalty relief methodology, which determines the value that a company would be willing to pay to license its brand if it did not own it. The methodology is compliant with industry standards set in ISO 10668. This approach involves estimating the future revenue attributable to a brand and calculating a royalty rate that would be charged for the use of that brand. Brand Finance’s study is based on publicly available information on the largest brands in the world. This indicator assesses the economy’s brands in the top 5,000 global brand database and produces the sum of the brand values corresponding to that economy. This sum is then scaled by GDP. A score of 0 is assigned where there are no brands in the country that make the top 5,000 ranking. A score of "n/a" is assigned where Brand Finance has been unable to determine if there are brands from the country that would rank within the top 5,000 due to data availability limitations.
Source: Brand Finance database (https://brandirectory.com); and International Monetary Fund, World Economic Outlook Database, October 2025 (https://data.imf.org/en/datasets/IMF.RES:WEO). Data year: 2026.
7.1.4 Industrial designs by origin/bn PPP$ GDP
Number of designs contained in resident industrial design applications filed at a given national or regional office (per billion PPP$ GDP) | 2024
An industrial design is a set of exclusive rights granted by law to applicants to protect the ornamental or aesthetic aspect of their products. An industrial design is valid for a limited period of time and within a defined territory. A resident industrial design application refers to an application filed with an intellectual property office for or on behalf of the applicant’s country of residence. For example, an application filed with the Japan Patent Office by a resident of Japan is considered to be a resident application for Japan. Similarly, an application filed with the European Intellectual Property Office (EUIPO) by an applicant who resides in any of the EUIPO member states, such as Italy, is considered to be a resident application for that member state (Italy). This indicator is based on design count – the total number of designs contained in resident industrial design applications. Data are scaled by PPP$ GDP (billions).
Source: World Intellectual Property Organization, Intellectual Property Statistics (https://www.wipo.int/ipstats); and International Monetary Fund, World Economic Outlook Database, October 2025 (https://data.imf.org/en/datasets/IMF.RES:WEO). Data years: 2017–2024.
7.2 Creative goods and services
7.2.1 Cultural and creative services exports, % total trade
Cultural and creative services exports (% of total trade) | 2024
Creative services exports as a percentage of total exports according to the Extended Balance of Payments Services Classification EBOPS 2010 – that is, EBOPS code SI3: Information services; code SJ22: Advertising, market research, and public opinion polling services; code SK1: Audio-visual and related services; and code SK23: Heritage and recreational services as a percentage of total trade. Values are based on the classification of the sixth (2009) edition of the International Monetary Fund’s Balance of Payments and International Investment Position Manual and Balance of Payments database. See indicator 5.3.1 for the full definition of total trade.
Source: Trade in Commercial Services database (https://stats.wto.org); and WTO–OECD Balanced Trade in Services (BaTiS) dataset (https://www.wto.org/english/res_e/statis_e/gstdh_batis_e.htm). Data years: 2023–2024.
7.2.2 National feature films/mn pop. 15–69
Number of national feature films produced (per million population, 15–69 years old) | 2024
A feature film is defined as a film with a running time of 60 minutes or longer. It includes works of fiction, animation and documentaries. It is intended for commercial exhibition in cinemas. Feature films produced exclusively for television broadcasting, as well as newsreels and advertising films, are excluded. Data are reported per million population aged 15–69 years old.
Source: OMDIA (https://omdia.tech.informa.com/products/cinema-and-movies-intelligence-service); and United Nations, Department of Economic and Social Affairs, Population Division, World Population Prospects 2024 (https://population.un.org/wpp). Data years: 2019–2024.
7.2.3 Entertainment and media market/th pop. 15–69
Global telecom and entertainment & media outlook (per thousand population, 15–69 years old) | 2025
The Global Telecom and Entertainment & Media Outlook is a comprehensive source of global analyses and five-year forecasts of consumer and advertising spending across different territories and entertainment and media segments. The figures for Algeria, Bahrain, the Islamic Republic of Iran, Jordan, Kuwait, Lebanon, Malta, Morocco, Oman, Qatar, Tunisia and Yemen were estimated from a total corresponding to Middle East and North Africa (MENA) countries, while the figures for Australia and New Zealand were estimated from a total corresponding to Oceania countries. In both cases, a breakdown of total GDP (current USD) for the above-mentioned countries was used to define referential percentages.
Source: PwC, Global Telecom and Entertainment & Media Outlook, 2025–2029 (https://www.pwc.com/gx/en/industries/tmt/media/outlook.html); United Nations Department of Economic and Social Affairs, Population Division, World Population Prospects 2024 (https://population.un.org/wpp); and International Monetary Fund, World Economic Outlook Database, October 2025 (https://data.imf.org/en/datasets/IMF.RES:WEO). Data years: 2024–2025.
7.2.4 Creative goods exports, % total trade
Creative goods exports (% of total trade) | 2024
Total value of creative goods exports (current USD) over total trade. Creative goods exports based on the 2009 UNESCO Framework for Cultural Statistics, Table 3, International trade of cultural goods and services defined with the Harmonized System (HS) 2007 codes; World Trade Organization and United Nations Conference on Trade and Development, Trade in Commercial Services database, itself based on the sixth (2009) edition of the International Monetary Fund’s Balance of Payments and International Investment Position Manual and Balance of Payments database. For the definition of total trade, see indicator 5.3.1. Trade Data Monitor (TDM) data are used to complement Comtrade data and improve data timeliness where necessary.
Source: United Nations Comtrade Database (http://comtrade.un.org); Trade Data Monitor (https://www.tradedatamonitor.com); and World Trade Organization and United Nations Conference on Trade and Development (https://stats.wto.org). Data years: 2018–2024.
7.3 Online creativity
7.3.1 Top-level domains (TLDs)/th pop. 15–69
Generic top-level domains (TLDs) and country-code TLDs (per thousand population, 15–69 years old) | 2025
The sum of Generic top-level domains (TLDs) and country-code TLDs as a proportion of thousand population, 15–69 years old. A top-level domain (TLD) encompasses various categories maintained by the Internet Assigned Numbers Authority (IANA) for internet use. Generic TLDs cover five generic domains (.biz, .info, .org, .net, and .com), excluding sponsored domains such as .name or .pro, and all new generic TLDs. Country-code TLDs are assigned to specific economies, countries, or territories and represent total domain registrations within each country-code TLD, with exceptions for ccTLDs licensed for global commercial use. For confidentiality reasons, only normalized values are reported; while relative positions are preserved, magnitudes are not.
Source: ZookNIC Inc (https://www.zooknic.com); and United Nations, Department of Economic and Social Affairs, Population Division, World Population Prospects 2024 (https://population.un.org/wpp). Data year: 2025.
7.3.2 GitHub commits/mn pop. 15–69
GitHub commits pushes received and sent (per million population, 15–69 years old) | 2025
GitHub is the world’s largest host of source code, and a commit is the term used for a change on this platform. One or more commits can be saved (or pushed) to projects (or repositories). Thus, “GitHub commit pushes received and sent” refers to the sum of the number of batched changes received and sent by publicly-available projects on GitHub within a specific economy. Automated activity resulting in non-productive commits is excluded.
Source: GitHub (https://github.com); and United Nations, Department of Economic and Social Affairs, Population Division, World Population Prospects 2024 (https://population.un.org/wpp). Data year: 2025.
7.3.3 Mobile app creation/bn PPP$ GDP
Global downloads of mobile apps (per billion PPP$ GDP, two-year average) | 2025
Global downloads of mobile apps, by origin of the headquarters of the developer/firm, scaled by PPP$ GDP (billions). Global downloads are compiled by Sensor Tower, public data sources and the company’s proprietary forecast model based on data from Google Play Store and iOS App Store in each country. Since data for China are not available for Google Play Store and only for iOS App Store, data from China are treated as missing.
Source: Sensor Tower App Performance Insights (https://sensortower.com); and International Monetary Fund, World Economic Outlook Database, October 2025 (https://data.imf.org/en/datasets/IMF.RES:WEO). Data year: 2025.