Part II is composed of individual country profiles aiming to provide insights on SME performance and entrepreneurial trends in each country, and to present business conditions in countries, along with recent policy initiatives to foster business dynamics and support SMEs in innovating and scaling up. The structure of the country profiles follows the conceptual framework of Part I, and information is presented in three sections: i) national SME sector structure and performance; ii) SME access to strategic resources; and iii) SME business environment.
OECD SME and Entrepreneurship Outlook 2019
Chapter 8. Methodology of the country profiles
Abstract
The statistical data for Israel are supplied by and under the responsibility of the relevant Israeli authorities. The use of such data by the OECD is without prejudice to the status of the Golan Heights, East Jerusalem and Israeli settlements in the West Bank under the terms of international law.
The SME and Entrepreneurship (SME&E) Outlook country profiles provide a concise overview of SME sector structure, performance and business conditions in each OECD country and they present recent national policy initiatives implemented to foster business dynamics and support SMEs in innovating and scaling-up.
For benchmarking SME access to strategic resources and SME business environment, a broad range of indicators are used and presented in the form of indices. Benchmarking indices rank from 0 to 200 (0 being the lowest OECD value, 200 the highest and 100 the median value, i.e. the middle position among OECD countries for which data are available). The charts highlight the position and dispersion of the top five (high performing countries) and bottom five (low performing countries) OECD values, as well as the country’s relative position vis-à-vis the median (dot). When data are not available, the dot, i.e. the country’s position in the ranking, does not figure on the graph.
In some cases, where indicators reflect potential barriers to SME performance (costs, administrative burden etc.), the benchmark was reversed (and marked with *), so that, in these cases, when a country ranks high, the country effectively performs well as compared to the OECD median.
The SME&E Outlook country profiles build on the most recent work and data available at the time of drafting. However due to differences in data collection calendars and methodologies, there may be time gaps across indicators and data interpretation should be done with caution.
Purpose and structure
Part II of the SME and Entrepreneurship (SME&E) Outlook is composed of individual country profiles aiming to provide insights on SME performance and entrepreneurial trends in each country and to present recent policy initiatives implemented to foster business dynamics and support SMEs in innovating and scaling-up.
The structure of the country profiles follows the conceptual framework of the publication as described in the reader’s guide at the forefront of the publication (Figure 8.1 and Figure 8.2). This conceptual framework is also applied in Part I that describes recent trends in SME business conditions and policy responses.
Information across the profiles is presented in three sections focusing respectively on: i ) national SME sector structure and performance, ii) SME access to strategic resources and iii) SME business environment. The content of the country profiles is standardised and harmonised in order to enable international comparison.
Part II covers 36 OECD countries. An abridged version of the profiles is available in the publication, a full version with more statistical and benchmarking tools is available online. The online version also proposes profiles for several emerging economies for which data and policy information is available.
SME structure and business dynamics
The first part of the country profiles presents, for a given country, the structure of and performance of the SME sector in terms of employment, value added, productivity and compensation of employees, and compares it with the OECD average (USA average in case of productivity). Recent trends in business dynamics, in particular enterprise creations and bankruptcies, are also commented, together with the evolution of job creation and destruction by enterprise births and deaths.
The analysis draws on the OECD Structural and Demographic Business Statistics (SDBS) database, which consists of official business statistics collected by the Statistics and Data Directorate in cooperation with national statistical offices and Eurostat; and the OECD Timely Indicators of Entrepreneurship (TIE) database, covering official business statistics and administrative data. The country profile of Canada makes also use of data from the OECD Trade by Enterprise Characteristics (TEC) database, which is a collection of official statistics compiled via the microdata linking of business and trade statistics.
Benchmarking SME business conditions: general approach and methodology
The country profiles are designed to provide a concise overview on SME business conditions in a particular country. Each dimension, e.g. access to finance, access to skills or market conditions etc., covers a range of SME policy relevant topics that are standardised in focus and contents for benchmarking purposes (Figure 8.2).
As to cover the many different aspects that are relevant to SME business conditions, the SME&E Outlook built on work carried out across the OECD and beyond, including on measurement and indicators.
The benchmarking indicators used to monitor SME business conditions are drawn from a broad range of primary OECD and non-OECD data sources. An inventory of indicators was conducted in the course of 2017-18 taking into account criteria of SME policy relevance, international comparability, regularity in data collection, country coverage and fair comparability over time. Indicators and primary data sources are presented in more details in Annex 8.A.
Policy information was drawn from recent OECD and non-OECD exercises of policy information collection and major international reports, in the same vein as for Part I. The sources used for each country are presented at the end of each profile. Some are general resources covering a number of countries, especially OECD countries; others are more country-specific.
A data infrastructure was built and integrated into the OECD corporate data management system in order to gather, store and harmonise information. After consolidation, the OECD SME ‘data lake’ is aimed to support future SME-related policy analysis and to evolve as needs evolve.
All indicators are presented in the form of indices for benchmarking purposes (OECD median=100).
The country’s values are compared to the median value observed in the OECD area, i.e. the middle position among OECD countries for which data are available. The use of the median avoids a statistical bias towards large players that skew the average, while still reflecting international rankings. The median has also the advantage over a simple ranking that it preserves the deviation between country values.
The distance of the country’s value from the OECD median value appears on the chart at a proportional distance from the median. This applies equally to all countries. In a simple ranking, the difference between two successive country values is 1 and the distance to the median is the rank.
Indices are reported on a common scale from 0 to 200 (0 being the lowest OECD value, 100 the median value, and 200 the highest) to make them comparable.
Given the value for country c at time t and the OECD minimum, the OECD median and the OECD maximum at time t, the country index of benchmark is calculated as followed:
If then
If then
The benchmark charts highlight the position and dispersion of the Top five (High) and Bottom five (Low) OECD values. The country’s relative position is marked with a dot. However, when data are not available, the dot, i.e. the country’s position in the ranking, does not figure on the graph.
In some cases:
Indicators were normalised to take account of the size of the economy (e.g. by GDP). This is for instance the case of electricity capacity.
The country benchmark was reversed (and marked with *) for the indicators that are considered as measures of potential barriers to SME performance. This is for instance the case of all indicators related to costs of accessing strategic resources, administrative, regulatory or trade barriers, the indebtedness of economic actors that may weigh on final demand and market prospects, fear of failure etc. In these cases, when a country ranks high on an indicator that usually monitors a barrier to entrepreneurship or a weakness in the SME business environment, the country effectively performs well as compared to the OECD median.
SME access to strategic resources
Three thematic sections explore the conditions under which SMEs can access and make use of strategic resources (Figure 8.2). Smaller firms are typically at disadvantage as compared to larger firms in accessing funding, appropriate skills and innovation assets (i.e. technology, data, business models and organisational practices, networks etc., either in their tangible or intangible forms). Yet financial capital, human capital and knowledge-based capital are key production factors and the determinants of firms’ competitiveness in knowledge-based economies.
Access to finance
Accessing appropriate sources of finance across all stages of their life cycle is critical for SMEs to start, innovate and grow. Yet, SMEs remain undercapitalised and heavily reliant on straight debt. Recent evidence suggests that financial institutions have become even more risk-averse, placing an extra burden on high-risk SMEs or on firms without collateral.
This section on SME access to finance focuses on:
SME self-funding capacity through profit;
The state of national banking system (i.e. financial soundness, the scope of bank credit to the private sector) and the existence of an interest rate spread for SMEs;
The effective access of SMEs to bank credit (including SME new lending, growth in SME outstanding loans, SME long-term loans, i.e. loans used to fund investment and growth needs rather than current operations) and potential barriers to SME bank credit in terms of cost (SME interest rate) and risk of rejection.
The availability of venture capital to support SME development at different stages (i.e. early stage including seed and start-up phases, and later stage).
This section builds on the work carried out for the Financing SMEs and Entrepreneurs: an OECD Scoreboard as well as the G20/OECD High-Level Principles on SME Financing (OECD, 2018[1]). It also makes use of OECD Structural Business Statistics and data compiled for the OECD Entrepreneurship Financing Database. Indicators on national banking systems also come from the International Monetary Fund Financial Soundness Indicators and the World Bank (WB) Data Bank on Development (Annex 8.A).
Access to skills
SMEs face greater difficulties in identifying, attracting and developing skills than larger firms. Recent survey results also show that people are not more confident in their ability to start a business than in the past. Yet skills are key assets for technology and innovation absorption and for managing the organisational changes needed during the transition.
This section on SME access to skills focuses on:
Adult literacy and training that reflect skills availability in the country and that is measured by adult educational attainment, adult skills for information and communication technologies (ICT), learning and creative thinking, and the access of workers’ to on-the-job training.
Student proficiency that reflects future skills potential in the country, and that is measured by the performance of 15-year-olds in collaborative problem-solving, mathematics and reading, as well as national graduation rate at tertiary level.
Entrepreneurial skills that are measured by perceived capabilities, entrepreneurial intentions and fear of failure among working-age population.
This section builds on the work carried out in the framework of the OECD Programme for International Student Assessment (PISA) and the OECD Programme for International Assessment of Adult Competences (PIAAC), as well as the OECD Job Quality database and official data on education collected by the OECD and the UNESCO. Results of the last Global Entrepreneurship Monitor (GEM) adult population survey are also included (Annex 8.A.).
Access to innovation assets
Innovation results from a process of accumulation through which firms increase their stock of knowledge-based capital. SME face particular barriers in adopting new technologies or new organisational and marketing practices, in participating in technology-intensive activities or integrating innovative networks.
This section on SME access to innovation assets focuses on:
Technology through SME acquisition of equipment and software, and SME adoption of high-speed broadband.
Organisation and processes with SME use of new IT-enabled tools (e.g. big data analysis, cloud computing services, supply chain management) and SME adoption of new commercial practices (e.g. e-sales).
SME collaboration networks, i.e. SME collaboration on innovation with the science base (universities and public research institutions), within supply chains (e.g. with suppliers) and within international networks (through cross-border participation in innovation collaborations).
SME R&D and innovation, and the relative percentage of domestic SMEs performing research and development (R&D) or engaged in innovation activities.
This sections builds on several international data collection including OECD-Eurostat R&D surveys, Eurostat Community Innovation Survey and the OECD ICT usage by Businesses database.
SME business environment
Three thematic sections explore the business environment and framework conditions under which SMEs can do business and grow. SMEs are typically more dependent on their business ecosystem than larger firms. Smaller firms are more vulnerable to deficient framework conditions, market failures and economic shocks, while inefficient infrastructure hampers their access to markets and the strategic resources they need to operate.
Institutional and regulatory framework
Although regulatory barriers to entrepreneurship have declined over time, the complexity of regulatory procedures is still a major obstacle for SMEs and entrepreneurs. Costs of complying with administrative requirements remain comparatively higher for smaller businesses. Inefficient insolvency regimes limit the restructuring of viable firms and the second chance offered to entrepreneurs.
This section on institutional and regulatory framework focuses on:
Regulation and looks into the level of administrative burdens on start-ups and the costs of starting a business or resolving insolvency, as well as efforts made to simplify procedures and strengthen the insolvency framework.
Justice, competition and taxation through a range of dimensions, including the quality of judicial process, the cost of enforcing contracts, distortions induced by State involvement, barriers in service and network sectors and the time to comply with tax obligations.
Public governance efficiency, proxied by the intensity of government debt, the adoption of regulatory impact assessment, the availability and relevance of participatory services on government websites and efforts to promote open government data.
This section builds on OECD work carried out for monitoring product market regulation, Measuring Regulatory Performance, the OECD Government at a Glance, as well as some WB indicators on Doing Business.
Market conditions
There is a large cross-country diversity in the opportunities and challenges for SMEs to access markets. Increased public attention has been given to levelling the playing field in recent years. Conditions for entering international and public markets, or accessing infrastructure, remain relatively difficult for smaller firms.
This section on market conditions focuses on:
Domestic market and considers the size of the domestically-supplied demand as well as consumption and investment prospects, proxied by the debt of non-financial corporations and households.
Public procurement, in particular, the size of domestic public procurement market, the provision of e-procurement functionalities that can ease access to tenders and contract management, and good practices in terms of payment of suppliers.
Trade and foreign direct investment, the country’s positioning in global value chains (i.e. the spread of its backward and forward linkages), trade restrictiveness on computer services, engineering and telecom services, trade facilitation practices and regulatory restrictiveness on foreign direct investment.
This section builds on OECD National Accounts, OECD Trade in Value Added (TiVA) database, the Services Trade Restrictiveness Indicators (STRI) database, OECD Trade Facilitation indicators and OECD FDI Regulatory Restrictiveness index, as well as work on public procurement carried out for the OECD Government at a Glance publication. In addition this section uses results of the latest WB Benchmarking Public Procurement report.
Infrastructure
Physical, digital and network infrastructure is the foundation of a dynamic business ecosystem. The quality of infrastructure is especially relevant for SME entry into distant markets and engagement in GVCs, or to secure their cost-efficient access to strategic resources.
This section on infrastructure focuses on:
Logistics and energy, especially the intensity of investment in transport infrastructure, the quality of infrastructure (e.g. in terms of logistical performance, electricity capacity or energy supply reliability) and their accessibility in terms of cost.
ICT and internet, the intensity of investments in ICT, the performance of digital infrastructure (measured by fixed and mobile broadband penetration rates and the level of digital security) and their accessibility in terms of cost.
R&D and innovation, the intensity of domestic R&D investment, the performance of R&D infrastructure (proxied by its output in number of international patents and the density of its connections, i.e. industry-science linkages, inter-regional linkages and international linkages).
This section builds on a broad range of international data resources, including: for transport and logistics, the OECD International Transport Forum database, the WB Logistics Performance index and the WB Doing Business indicators; for energy, the International Energy Agency (IEA)’s electricity information and IEA energy prices and taxes, as well as WB Doing Business indicators; for digital infrastructure, OECD National Accounts, OECD Broadband statistics and the OECD ICT usage by business database; for R&D and innovation infrastructure, OECD work on R&D, science, technology and industry (STI) and intellectual property data, more specifically the R&D Statistics (RDS) Database, Main Science and Technology Indicators (MSTI) database and the STI Micro-data Lab. Regional data are drawn from an earlier version of the OECD Regions at a Glance report.
Caveats and caution in interpretation
The SME&E Outlook country profiles build on the most recent work and data available at the time of drafting. However due to differences in data collection calendars and processes, benchmarking data may not refer to the same year across all indicators. Therefore there may be several years of time lag between SME performance data and SME business environment data. In some cases, data on business conditions are posterior to data on SME performance. This should be kept in mind when interpreting results. The cut-off date for the indicators on SME business conditions is mid-March 2019, except for the product market regulation indicators that were officially released later in Spring 2019.
Several analytical dimensions were not covered and may receive closer attention in the future when and where data allow. These include gender breakdown, industrial disaggregation or sub-national data for instance.
Some areas of interest may be unevenly covered by statistics as data in primary sources are not always available for all countries. This is the case of indicators on access to knowledge assets for non-EU countries.
Annex 8.A. Data sources and definitions
Annex Table 8.A.1. SME structure and performance
Employment |
Share of SMEs in total employment (%) |
Employment by enterprise size as a percentage of all persons employed in business economy. Micro firms include firms with 1-9 persons employed; small firms: 10-49 persons employed; medium-sized firms: 50-249 persons employed; and large firms: more than 250 persons employed. |
OECD Structural and Demographic Business Statistics database (SDBS) |
Value added |
Share of SMEs in total value added (%) |
Value added by enterprise size as a percentage of total business economy value added. Micro firms include firms with 1-9 persons employed; small firms: 10-49 persons employed; medium-sized firms: 50-249 persons employed; and large firms: more than 250 persons employed. |
|
SME employment by activity |
Share of SME employment in business employment by sector (%) |
Employment in SMEs as a share of the total business employment by sector. |
|
New firm creations |
Index, new enterprises creations in 2012=100 |
New enterprise creation, index 2012 =100. For the definition of enterprise creation see methodology in primary source. |
|
Bankruptcies |
Index, bankruptcies in 2012=100 |
Bankruptcies, index 2012='100.' For the definition of bankruptcies see methodology in primary source. |
|
Labour productivity |
Thousand USD, at constant exchange rate, 2010 base year |
Value added by enterprise size per person employed, as a percentage of large enterprises; business economy. |
|
Compensation per employee |
Thousand USD, at current exchange rate |
Compensation of employees per employee, by enterprise size class; manufacturing. |
|
Job creation / destruction |
Net job creation or destruction (% total employment) |
Net change in employment by enterprise births and enterprises deaths and in incumbent firms. It is expressed as a percentage of total business economy employment. |
|
Job creation by births of enterprises, by sector |
Sector share of job creation by enterprise births (%) |
Distribution of employment created by enterprise births across main sectors. |
|
Top ten sectors by the SME exports |
Share of SME exports in the sector (%) |
Share of SME exports as a percentage of exports by all firms in the activity sector. (graph shown only for Canada) |
|
SME exports in Canada and the United States |
Share of SME exports in the sector (%) |
Share of SME exports as a percentage of exports by all firms in the activity sector. (graph shown only for Canada) |
Annex Table 8.A.2. Access to finance
Self-funding |
|||
---|---|---|---|
SME profit margins |
Net operating surplus (% value added) |
Net operating surplus of firms with less than 250 employees as a percentage of their value added. Industry (excluding construction) only. Data refer to 2016. |
Structural Business Statistics - Business Demography Indicators |
Banking system |
|||
Financial soundness (capital/assets) |
Regulatory capital to risk-weighted assets |
This FSI is calculated using total regulatory capital as the numerator and risk-weighted assets as the denominator. Data are compiled in accordance with the guidelines of either Basel I or Basel II. It measures the capital adequacy of deposit takers. Capital adequacy and availability ultimately determine the degree of robustness of financial institutions to withstand shocks to their balance sheets. Data refer to 2017 or nearest year available. |
|
Domestic credit to private sector by banks |
Domestic credit to private sector by banks (% of GDP) |
Domestic credit to private sector by banks refers to financial resources provided to the private sector by other depository corporations (deposit taking corporations except central banks), 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. Data refer to 2017 or nearest year available. |
|
Interest rate spread for SMEs* |
Interest rate spread, small firms versus large firms (%) |
Measures the tightness of the market and the (positive or negative) correlation of interest rates with firm size. Increasing interest rate spread is likely to reduce SME access to finance. The indicator is treated as a potential barrier to SME performance and country benchmark has been reversed (and marked with *). Data refer to 2017. |
|
Bank credit |
|||
New SME lending |
New SME lending (% of total new firm lending) |
Measures the flow of bank loans and bank repayments over one year. As a percentage of total new lending, all firms. Data refer to 2016. |
|
Growth of SME outstanding loans |
Yearly growth rate of SME outstanding loans (%) |
Measures trends in SME demand for and access to bank credit. SME outstanding loans are a stock indicator reflecting both new lending and bank loans that have accumulated over time along with loan repayments. Growth is calculated as yearly rate. Data refer to 2016-17. |
|
SME long-term loans |
Share of long-term loans for SMEs |
Measures the debt structure of SMEs and whether loans are used to fund current operations rather than investment and growth needs. Long-term loans are loans for more than one year. Data refer to 2017. |
|
SME real interest rate* |
SME real interest rate, % |
Captures the real interest rate paid by SMEs considering the impact of the inflation rate. Increasing SME real interest rate is likely to signal more difficult SME access to finance. The indicator is treated as a potential barrier to SME performance and country benchmark has been reversed (and marked with *). Data refer to 2017. |
|
SMEs loan rejection rates |
SMEs loan rejection rates (%) |
Measures the relative number of SME credit applications who have not received the requested amount in full. Increasing SME loan rejection rates are likely to signal more difficult SME access to finance. The indicator is treated as a potential barrier to SME performance and country benchmark has been reversed (and marked with *). Data refer to 2017. |
|
Equity funding |
|||
Venture capital |
Venture capital (% of GDP) |
Venture capital investments (seed/start-up/other early stage and later stage venture) as a percentage of GDP. It excludes buyouts, turnaround and replacement capital, as these are directed at restructuring and generally concern larger enterprises. Data refer to 2016. |
OECD Entrepreneurship Financing Database |
Venture capital, early stage |
Venture capital, early stage (% of GDP) |
Venture capital investments at seed/start-up/other early stage as % of GDP. Data refer to 2016. |
OECD Entrepreneurship Financing Database |
Venture capital, later stage |
Venture capital, later stage (% of GDP) |
Venture capital investments at later stage as % of GDP. Data refer to 2016. |
OECD Entrepreneurship Financing Database |
Annex Table 8.A.3. Access to Skills
Adult literacy |
|||
---|---|---|---|
Adults at tertiary education level |
Adults at tertiary education level (%) |
Measures the percentage of adult population (25-64 years) having completed a tertiary level of education. Excludes vocational programmes. Data refer to 2017 or the nearest year available. |
|
Adults withcore ICT skills |
Adults without computer experience or core ICT skills (%) |
Percentage of 25-65-year-old adults with no computer experience or failing the ICT core in the PIIAC survey (%). The indicator is treated as a potential barrier to SME performance and country benchmark has been reversed (and marked with *). Data refer to 2015 or the nearest year available. |
OECD Survey of Adult Skills in OECD Skills report 2016 |
Readiness to learn and creative thinking |
Adult readiness to learn and creative thinking (%) |
Captures the readiness of working-age adults (16-65 years old) to learn and for creative thinking. It relies on six items related to openness to new experiences and creative thinking. See Grundke et al 2017 for detailed methodology. Data refer to 2015 or the nearest year available. |
OECD STI Scoreboard 2017 based on OECD Survey of Adult Skills data |
Workplace training and learning |
Job strain, training and learning, all workers (%) |
Refers to the number of workers that reported receiving training in their jobs. Job quality database focuses on three key dimensions: i) earnings quality, ii) labour market security and iii) quality of the working environment. Job strain is defined as jobs where workers face more job demands than the number of resources they have at their disposal (as described in Chapter 5 of How’s Life 2013). Two types of job demands are identified: i) time pressure which encompasses long working hours, high work intensity and working time inflexibility; and ii) physical health risk factors, such as dangerous work (i.e. being exposed to noise, vibrations, high and low temperature) and hard work (i.e. carrying and moving heavy loads, painful and tiring positions). Similarly, two types of job resources are considered, namely: i) work autonomy and learning opportunities which include workers’ freedom to choose and change their work tasks and methods, as well as formal (i.e. training) and informal learning opportunities at work; and ii) Social support at work which measures the extent of which workers receive social support from colleagues and supervisors. The composite Job Strain index, thus, refers to those jobs where the workers face one demand but have no resources, or face two demands but have one or no resource. Data refer to 2015 or the nearest year available. |
OECD Job Quality Database |
Student proficiency |
|||
Collaborative problem solving |
Top performing students in collaborative problem solving (%) |
Captures the capacity of students (15 years old) to engage in cognitive processing to understand and resolve problem situations where a method of solution is not immediately obvious. Scores from 0 (worst performance) to 600 (best performance). Share of top performers (i.e. students that achieved the highest level of proficiency - 5 and 6-) in total 15 year-old students. Data refer to 2017. |
|
Mathematics |
Top performing students in mathematics (%) |
Captures the capacity of students (15 years old) in mathematics. Scores from 0 (worst performance) to 600 (best performance). Share of top performers (i.e. students that achieved the highest level of proficiency - 5 and 6-) in total 15 year-old students. Data refer to 2015. |
|
Reading |
Top performing students in reading (%) |
Captures the capacity of students (15 years old) in reading. Scores from 0 (worst performance) to 600 (best performance). Share of top performers (i.e. students that achieved the highest level of proficiency - 5 and 6-) in total 15 year-old students. Data refer to 2015. |
|
Graduation at tertiary level |
Graduation rate at tertiary level (%) |
Graduation/entry rates represent an estimated percentage of an age group expected to graduate/enter a certain level of education at least once in their lifetime. Data are first-time graduation rates of less 30-year-olds and exclude internationally mobile students. Tertiary level includes both short- and long-cycle programmes at ISCED levels 5 to 8 (ISCED 2011). Data refer to 2016 or the nearest year available. |
|
Entrepreneurial skills |
|||
Perceived entrepreneurial capabilities |
Perceived capabilities among adult population (%) |
Percentage of 18-64 population (individuals involved in any stage of entrepreneurial activity excluded) who believe they have the required skills and knowledge to start a business. Scoring from 0 (low) to 100 (high). Data refer to 2017. |
Global Entrepreneurship Monitor (GEM) - Adult Population Survey |
Entrepreneurial intentions |
Entrepreneurial intentions among adult population (%) |
Percentage of 18-64 population (individuals involved in any stage of entrepreneurial activity excluded) who are latent entrepreneurs and who intend to start a business within three years. Scoring from 0 (low) to 100 (high). Data refer to 2017. |
Global Entrepreneurship Monitor (GEM) - Adult Population Survey |
Fear of failure* |
Fear of failure among adult population (%) |
Percentage of 18-64 population (individuals involved in any stage of entrepreneurial activity excluded) who indicate that fear of failure would prevent them from setting up a business. Scoring from 0 (low) to 100 (high). The indicator is treated as a potential barrier to SME performance and country benchmark has been reversed (and marked with *). Data refer to 2017. |
Global Entrepreneurship Monitor (GEM) - Adult Population Survey |
Annex Table 8.A.4. Access to Innovation
Technology |
|||
Equipment & software, small firms |
Acquisition of machinery, equipment and software, small firms (%) |
Share of innovative firms with [10-49] employees engaged in acquisition of machinery, equipment and software (%). Data refer to 2016. |
|
Equipment & software, medium firms |
Acquisition of machinery, equipment and software, medium-sized firms (%) |
Share of innovative firms with [50-249] employees engaged in acquisition of machinery, equipment and software (%). Data refer to 2016. |
|
High speed broadband, small firms |
Fixed broadband connection, high speed, small firms (%) |
Share of firms with [10-49] employees with a fixed broadband connection with at least a 100 Mbit/s download speed. All activities in manufacturing and non-financial market services. Data refer to 2018. |
|
High speed broadband, medium firms |
Fixed broadband connection, high speed, medium-sized firms (%) |
Share of firms with [50-249] employees with a fixed broadband connection with at least a 100 Mbit/s download speed. All activities in manufacturing and non-financial market services. Data refer to 2018. |
|
Organisation and processes |
|||
---|---|---|---|
Big data analysis, small firms |
Firms having performed big data analysis, small firms (%) |
Share of firms with [10-49] employees that have performed big data analysis. All activities in manufacturing and non-financial market services. Data refer to 2018. |
|
Big data analysis, medium firms |
Firms having performed big data analysis, medium-sized firms (%) |
Share of firms with [50-249] employees that have performed big data analysis. All activities in manufacturing and non-financial market services. Data refer to 2018. |
|
Cloud computing, small firms |
Cloud computing services, small firms (%) |
Share of firms with [10-49] employees that use cloud computing services. Cloud computing refers to ICT services over the Internet to access server, storage, network components and software applications. All activities in manufacturing and non-financial market services. Data refer to 2018. |
|
Cloud computing, medium firms |
Cloud computing services, medium-sized firms (%) |
Share of firms with [50-249] employees that use cloud computing services. Data refer to 2018. |
|
Supply chain management, small firms |
Supply chain management, small firms (%) |
Share of firms with [10-49] employees that share electronically supply-chain management (SCM) information with suppliers and customers. SCM information with suppliers and customers refer to the use of automated data exchange (ADE) applications. All activities in manufacturing and non-financial market services. Data refer to 2017. |
|
Supply chain mgt, medium firms |
Supply chain management, medium-sized firms (%) |
Share of firms with [50-249] employees that share electronically supply-chain management (SCM) information with suppliers and customers. Data refer to 2017. |
|
E-sales, small firms |
E-sales, small firms (%) |
Share of firms with [10-49] employees that sell goods or services over computer networks by methods especially designed for the purpose of receiving orders (i.e. webpages, extranet or electronic data interchange -EDI- but not orders by telephone, fax or manually types emails. Payments and delivery methods are not considered. All activities in manufacturing and non-financial market services. Data refer to 2018. |
|
E-sales, medium firms |
E-sales, medium-sized firms (%) |
Share of firms with [50-249] employees that sell goods or services over computer networks. Data refer to 2018. |
|
Innovation-collaboration networks |
|||
With the science base |
SMEs collaborating on innovation with higher education or public research institutions (% SMEs) |
Innovation collaboration involves active participation with other organisations in joint innovation projects (i.e. those aimed at introducing a new or significantly improved product or process), but excludes pure contracting out of innovation-related work. It can involve the joint implementation of innovations with customers and suppliers, as well as partnerships with other firms or organisations. Measured as a percentage of product and/or process innovative SMEs. Data refer to 2016 for EU countries and 2014 for non-EU countries. |
Eurostat CIS survey + national innovation surveys and OECD STI Scoreboard 2017 |
Within supply chains |
SMEs collaborating on innovation with suppliers (% SMEs) |
Innovation collaboration involves active participation with other organisations in joint innovation projects (i.e. those aimed at introducing a new or significantly improved product or process), but excludes pure contracting out of innovation-related work. It can involve the joint implementation of innovations with customers and suppliers, as well as partnerships with other firms or organisations. Measured as a percentage of product and/or process innovative SMEs. Data refer to 2016 for EU countries and 2014 for non-EU countries. |
Eurostat CIS survey + national innovation surveys and OECD STI Scoreboard 2017 |
Within international networks |
SMEs engaged in international collaboration for innovation (% SMEs) |
International collaboration on innovation refers to active cross-border participation in innovation collaborations. Measured as a percentage of product and/or process innovative SMEs. Data refer to 2014. |
|
R&D and innovation |
|||
R&D intensity, small firms |
SMEs performing R&D, small firms (% all firms) |
Business enterprise R&D expenditure (BERD) by size class, expressed as a % of total BERD. Small firms include firms with [10-49] employees. Data refer to 2017 or nearest year available. |
|
R&D intensity, medium firms |
SMEs performing R&D, medium-sized firms (% all firms) |
BERD by size class, expressed as a % of total BERD. Medium-sized firms include firms with [50-249] employees. Data refer to 2017 or nearest year available. |
|
Innovation, small firms |
Innovative firms, small firms (%) |
Share of innovative firms with [10-49] employees that have introduced any type of innovation (%). Data refer to 2016. |
|
Innovation, medium firms |
Innovative firms, medium-sized firms (%) |
Share of innovative firms with [50-249] employees that have introduced any type of innovation (%). Data refer to 2016. |
Annex Table 8.A.5. Institutional and regulatory framework
Regulations |
|||
---|---|---|---|
Administrative burdens on start-ups* |
Administrative burdens on start-ups (index) |
Component of the composite index "Barriers to domestic and foreign entry". Covers the administrative burden on joint-stock companies and personally-owned enterprises, as well as administrative burden related to licenses and permits procedures. Scores from 0 - least restrictive - to 6 - most restrictive. The indicator is treated as a potential barrier to SME performance and country benchmark has been reversed (and marked with *). Data refer to 2018. |
|
Simplification of regulatory procedures |
Complexity of regulatory procedures (index) |
Composite index "Complexity of regulatory procedures". Captures the government's communication strategy and efforts to reduce and simplify the administrative burden of interacting with the government. Scores from 0 - least restrictive - to 6 - most restrictive. Data refer to 2018. |
|
Cost of starting a business* |
Starting a business (cost in % of income per capita) |
Captures the cost (in % of income per capita) for starting a business, registering property and to prepare, file and pay taxes. The indicator is treated as a potential barrier to SME performance and country benchmark has been reversed (and marked with *). Data refer to 2018. |
|
Strength of insolvency framework |
Strength of insolvency framework (index) |
Measures the insolvency law de jure. Calculated as the sum of the scores on 4 other indices: i) commencement of proceedings index (with a range of 0–3), ii) management of debtor’s assets index (0–6), iii) reorganization proceedings index (0–3) and iv) creditor participation index (0–4). The strength of insolvency framework index ranges from 0 to 16, with higher values indicating insolvency legislation that is better designed for the rehabilitation of viable firms and the liquidation of nonviable ones. Data refer to 2018. |
|
Cost of resolving insolvency* |
Resolving insolvency (cost, % of estate) |
Indicator on the actual cost (in % of estate) to close a business. The indicator is treated as a potential barrier to SME performance and country benchmark has been reversed (and marked with *). Data refer to 2018. |
|
Justice, competition and taxation |
|||
Quality of judicial process |
Quality of judicial process (index) |
The quality of judicial processes index measures whether each economy has adopted a series of good practices in its court system in four areas: court structure and proceedings, case management, court automation and alternative dispute resolution. The index ranges from 0 to 5, with higher values indicating a more sophisticated and streamlined court structure. Data refer to 2018. |
|
Cost of enforcing contracts* |
Enforcing contracts (cost, in % claims) |
Resources required to enforce contracts, in terms of costs in % of claim. The indicator is treated as a potential barrier to SME performance and country benchmark has been reversed (and marked with *). Data refer to 2018 |
|
Distortions by state involvement* |
Distortions by state involvement (index) |
Composite index covering 1) public ownership, i.e. scope of state-owned enterprises (SOEs), government involvement in network sectors, direct control over business enterprises and governance of SOEs, 2) involvement in business operations, i.e. price controls and command and control regulation, and 3) design and assessment of regulations, i.e. assessment of regulations, stakeholder engagement and complexity of regulatory procedures. Scores from 0 - least restrictive - to 6 - most restrictive. The indicator is treated as a potential barrier to SME performance and country benchmark has been reversed (and marked with *). Data refer to 2018. |
|
Barriers in service/network sectors* |
Barriers in service/network sectors (index) |
Component of the composite index "Barriers to domestic and foreign entry", measuring the regulatory protection of incumbents, e.g. legal barriers to entry or antitrust exemptions. Scores from 0 - least restrictive - to 6 - most restrictive. The indicator is treated as a potential barrier to SME performance and country benchmark has been reversed (and marked with *). Data refer to 2018. |
|
Time to comply with tax obligations* |
Time to comply with tax obligations (hours per year required) |
Hours per year required to comply with corporate income tax, labour taxes and mandatory contributions and VAT or sales tax) for a standardised medium-sized domestic company. The indicator is treated as a potential barrier to SME performance and country benchmark has been reversed (and marked with *). Data refer to 2018. |
|
Public-governance efficiency |
|||
Government debt* |
Government debt (% of GDP) |
General government gross debt (i.e. across levels of government) as percentage of GDP. Debt is generally defined as all liabilities that require payment or payments of interest or principal by the debtor to the creditor at a date or dates in the future. All debt instruments are liabilities, but some liabilities such as shares, equity and financial derivatives are not debt. Debt is thus obtained as the sum of these liability categories, whenever available/applicable in the financial balance sheet of the general government sector: currency and deposits; debt securities; loans; and other liabilities (i.e. insurance, pension and standardised guarantee schemes, other accounts payable as well as, in some cases special drawing rights). The indicator is treated as a potential barrier to SME performance and country benchmark has been reversed (and marked with *). Data refer to 2016 or nearest year available. |
|
Regulatory impact assessment |
Regulatory Impact Assessment (index) |
Composite indicator covering primary laws along: 1) methodology of RIA, 2) systematic adoption of RIA, 3) transparency of RIA, and 4) oversight and quality control of RIA. Scores from -0 (low) to 4 (high). Data refer to 2014. |
|
E-participation |
E-participation (EPI index) |
Composite index that is derived as a supplementary index to the UN E-Government Survey. It extends the dimension of the Survey by focusing on the use of online services to facilitate provision of information by governments to citizens (“e-information sharing”), interaction with stakeholders (“e-consultation”), and engagement in decision-making processes (“e-decision making”). Qualitative assessment based on the availability and relevance of participatory services available on government websites. Score 0 (low) to 1 (high). Data refer to 2018. |
|
Open government data |
Open government data (index) |
Open useful and reusable government data index. Composite index that measures government efforts in promoting data availability and accessibility and in stimulating data re-use outside and inside government. Based on the International Open Data charter principles and on the methodology described in Ubaldi, 2013 (http://dx.doi.org/10.1787/5k46bj4f03s7-en). Data refer to 2017. |
Annex Table 8.A.6. Market conditions
Domestic market |
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---|---|---|---|
Domestically-supplied demand |
Domestic demand, share that is domestically supplied (%) |
Domestic value-added embodied in domestic demand. Estimates of final demand in country c for industry i final goods and services, broken down by the value added originating from source industry j in source country s (based on TiVA: Origin of value added in final demand). Data refer to 2011. |
OECD Trade in Value Added |
Debt of non-financial corporations* |
Debt of non-financial corporations (% of GDP) |
Liabilities of non-financial corporations, including special drawing rights, currency and deposits, debt securities, loans, insurance, pension, and standardized guarantees, and other accounts payable, expressed as a % of GDP. The indicator is treated as a potential barrier to SME performance and country benchmark has been reversed (and marked with *). Data refer to 2016 or the nearest year available. |
|
Debt of households* |
Debt of households and NPISHs (% of GDI) |
Liabilities of households and the non-profit institutions serving households (NPISHs) sector, including special drawing rights, currency and deposits, debt securities, loans, insurance, pension, and standardized guarantees, and other accounts payable as a percentage of its gross disposable income. The indicator is treated as a potential barrier to SME performance and country benchmark has been reversed (and marked with *). Data refer to 2016 or the nearest year available. |
|
Public procurement |
|||
Large public procurement market |
Size of public procurement (% of GDP) |
General government procurement spending as a percentage of GDP. Data refer to 2016 or the nearest year available. |
|
E-procurement functionalities |
E-procurement functionalities (index) |
Composite indicator covering the following areas: 1) Announcing tenders, 2) Electronic submission of bids (excluding by e-mails), 3) e-tendering, 4) Notification of award, 5) Electronic submission of invoices (excluding e-mails), 6) Ex post contract management. Scores from -0 (low) to 6 (high). Data refer to 2016 or the nearest year available. |
|
Payments of suppliers |
Payment of suppliers (index) |
Composite indicator that examines: 1) the procedure regarding suppliers’ request for payment, 2) the time frame for the purchasing entity to process payment, 3) the time frame for suppliers to actually receive payment, 4) the interests or penalties available to suppliers in case of payment delays. Score from 0 (regulatory framework that shows significant room for improvement) to 100 (regulatory framework that closely aligns with internationally recognized good practices). Data refer to 2016 or the nearest year available. |
|
Trade and foreign direct investment |
|||
Backward participation in GVCs |
Backward participation in GVCs |
Measured as foreign value-added embodied in a country's exports, as % of total gross exports of the exporting country. Data refer to 2009 or the nearest year available. |
|
Forward participation in GVCs |
Forward participation in GVCs |
Measured as domestic value-added embodied in partner countries exports, as % of domestic gross exports. Data refer to 2009 or the nearest year available. |
OECD STI Scoreboard 2017 |
Trade restrictiveness: computer services* |
Services Trade Restrictiveness (STRI), computer services (index) |
Composite index that quantifies restrictions on trade in services across five standard categories: 1) restrictions on foreign entry, 2) restrictions on the movement of people, 3) barriers to competition, 4) regulatory transparency, and 5) other discriminatory measures. Scores from 0 - completely open - to 1 - completely closed. The indicator is treated as a potential barrier to SME performance and country benchmark has been reversed (and marked with *). Data refer to 2018 or the nearest year available |
|
Trade restrictiveness: engineering* |
STRI, engineering services (index) |
id. |
STRI Database (OECD; 2014, 2015) |
Trade restrictiveness: telecom services* |
STRI, telecom services (index) |
id. |
STRI Database (OECD; 2014, 2015) |
Barriers to trade facilitation* |
Barriers to trade facilitation (index) |
Captures the recognition of foreign regulations, use of international standards and international transparency of domestic regulation. Scores from 0 - least restrictive - to 6 - most restrictive. The indicator is treated as a potential barrier to SME performance and country benchmark has been reversed (and marked with *). Data refer to 2013 or the nearest year available |
|
FDI regulatory restrictiveness* |
FDI regulatory restrictiveness (index) |
Measures statutory restrictions on foreign direct investment. The FDI Index focuses on four types of measures: i) equity restrictions, ii) screening and approval requirements, iii) restrictions on foreign key personnel, and iv) other operational restrictions (such as limits on purchase of land or on repatriation of profits and capital). Score from 0 (no regulatory impediments to FDI in the sector) to 1 (restricts foreign investment in the sector). The indicator is treated as a potential barrier to SME performance and country benchmark has been reversed (and marked with *). Data refer to 2017 or the nearest year available |
Annex 8.B. Policy sources and general references
EC (2017), SME Policy Database, European Commission, https://ec.europa.eu/growth/smes/business-friendly-environment/performance-review_en#interactive-sme-database
EC/OECD (2018), International Database on STI Policies – STIP Compass, https://stip.oecd.org/stip.html.
EC/OECD (2018), EC/OECD STIP Database 2018, https://stip.oecd.org/stip.html.
OECD (2019), Financing SMEs and Entrepreneurs 2019: An OECD Scoreboard, OECD Publishing, Paris, https://doi.org/10.1787/fin_sme_ent-2019-en.
OECD (2018), OECD Structural and Demographic Business Statistics Database. For figures A, B, C, E, F and G.
OECD (2018), OECD Timely Indicators of Entrepreneurship Database. For figure D.
OECD (2018), Financing SMEs and Entrepreneurs 2018: An OECD Scoreboard, OECD Publishing, Paris, http://dx.doi.org/10.1787/fin_sme_ent-2018-en.
OECD (2018), OECD Employment Outlook 2018, OECD Publishing, Paris, http://dx.doi.org/10.1787/empl_outlook-2018-en.
OECD (2018), Education Policy Outlook 2018: Putting Student Learning at the Centre, OECD Publishing, Paris, http://dx.doi.org/10.1787/9789264301528-en.
OECD (2017), Entrepreneurship at a Glance 2017, OECD Publishing, Paris, http://dx.doi.org/10.1787/entrepreneur_aag-2017-en.
OECD (2018), Final Summary Record of the 52nd Session of the OECD Working Party on SMEs and Entrepreneurship (WPSMEE), 23-24 April 2018, internal document (CFE/SME/M(2017)2/FINAL).
OECD (2017), Small, Medium, Strong. Trends in SME Performance and Business Conditions, OECD Publishing, Paris, http://dx.doi.org/10.1787/9789264275683-en.
OECD (2017), OECD Digital Economy Outlook 2017, OECD Publishing, Paris, http://dx.doi.org/10.1787/9789264276284-en.
OECD (2017), OECD Skills Outlook 2017: Skills and Global Value Chains, OECD Publishing, Paris, http://dx.doi.org/10.1787/9789264273351-en.
OECD (2017), Government at a Glance 2017, OECD Publishing, Paris, http://dx.doi.org/10.1787/gov_glance-2017-en.
OECD (2016), OECD Science, Technology and Innovation Outlook 2016, OECD Publishing, Paris, http://dx.doi.org/10.1787/sti_in_outlook-2016-en.
OECD (2015), OECD Regulatory Policy Outlook 2015, OECD Publishing, Paris, https://doi.org/10.1787/9789264238770-en.