The SME&E Outlook country profiles 2021 benchmark the 38 OECD member countries along: i) the COVID-19 impact on business dynamics, national policy frameworks in place and the short-term and structural policy responses provided by governments; ii) Factors of SME&E structural vulnerability, including the size of the SME and self-employed population, and exposure to lockdowns and disruptions in global value chains; and iii) Sources of SME&E resilience, including digital uptake, access to liquidity support, availability of skills on the labour market, and the entrepreneurship regulatory framework. This chapter presents the methodology, definitions and sources used in the country profiles. It builds on the most recent work and comparable data available at the time of drafting, however, because of cross-country differences in data collection and gaps, interpretation should be done with caution.
OECD SME and Entrepreneurship Outlook 2021
5. Methodology of the country profile
Abstract
Part II of the SME and Entrepreneurship (SME&E) Outlook 2021 is made of standardised country profiles that explore the factors of vulnerability and sources of resilience of the SME sector and entrepreneurship in the country, and give a spotlight on the government’s responses to “build back better”. Part II covers the 38 OECD member countries. The profiles are available in the print publication and online.
The SMEEO country profiles build on work carried out across the OECD and beyond. Measurement and indicators have been selected on the basis of their SME&E policy relevance, international comparability, and the most extensive country coverage. Primary data sources are presented in more details in the Annex Table 1. Policy information was drawn from recent OECD and non-OECD work on monitoring the impact of COVID-19 more broadly. In some cases, information was complemented with national documentation.
A data infrastructure was built and integrated into the OECD corporate data management system to gather, store and harmonise information. After consolidation, the OECD SME&E ‘Data Lake’ is aimed to support future SME- and entrepreneurship-related policy analysis and to evolve as needs evolve.
COVID-19 impact on the SME&E sector
The first section presents a comparative overview of the stringency of government measures since the beginning of the pandemic and the impact on business dynamics, i.e. firm entries and firm exits over the year.
Stringency of government measures
The stringency of government measures is gauged by the Oxford Government Stringency Index (Hale et al., 2021[1]), a composite measure based on nine indicators including school closures, workplace closures, closure of public transport or travel bans. This composite measure is a simple additive score of the nine indicators measured on an ordinal scale, rescaled to vary from 0 to 100 (100 = strictest). The index is shown as the response level of the strictest sub-region where policies vary at the subnational level. Country values are provided from January 2020 to April 2021.
Firm creation and firm exits/bankruptcies
Business dynamics are measured by two indicators: i) firm entries as the number of new enterprises created between January 2020 and March 2021, expressed in year-on-year difference (%) and cumulative year-on-year difference (%); and ii) firm exits as the number of enterprises exiting between January 2020 and March 2021, expressed in year-on-year difference (%) and cumulative year-on-year difference (%). In case data on firm exits are not available at the country level, variations in the number of bankruptcies are used instead. All data are drawn from the OECD Timely Indicators of Entrepreneurship database (OECD, 2021[2]).
Policy framework and policy spotlight
A brief description of the national SME&E policy framework is provided for each country. Information is drawn from the stocktake of existing SME policy frameworks in OECD countries conducted as part of the OECD Strategy for SMEs. Three types of SME&E policy frameworks are proposed: i) countries with specific SME&E strategies; ii) countries with (multi)annual action plans or other dedicated documents on SME&E policies; and iii) countries where SME&E policies are part of wider strategies and policy frameworks.
A snapshot on the major liquidity support measures and structural policy initiatives implemented in each country to build back better is also discussed. Aligned with the points under discussion in Chapter 2, 3, and 4, this policy spotlight relies on the monitoring of SME policy responses to COVID-19 that was conducted between February 2020 and February 2021 by the OECD Centre for Entrepreneurship, SMEs, Regions and Cities (OECD, 2021[3]). The monitoring of structural policies and recovery plans draws on publicly available information and feedback from the OECD Committee on SMEs and Entrepreneurship.
Factors of SME&E structural vulnerability
The second section benchmarks each country vis-à-vis OECD along four dimensions that are identified as factors of vulnerability during the pandemic: i) the relative size of the micro- and SME (MSME) sector and the population of self-employed; ii) the country’s economic exposure to lockdowns and business disruptions; iii) the country’s and domestic SMEs’ exposure to international trade and global value chain (GVC); and iv) the prevalence of informality, although this factor will be considered on a case-by-case basis since it is less prominent in more advanced economies.
Size of the MSME sector
Micro-firms, SMEs and self-employed have been severely hit during the crisis (Chapter 1). They were more likely to close business or experience severe drops in sales due to lockdowns or disruptions in supply chains. The size of the MSME sector is expressed as a percentage of total employment and total value added, and compare to the OECD total. The year of reference is 2018 (or latest year available). Data come from the OECD Structural and Demographic Business Statistics database (OECD, 2021[4]). The share of the self-employed in total employment is presented from 2005 to 2019 and is drawn from the OECD Annual Labour Force Statistics (OECD, 2020[5]).
Economic exposure to lockdowns and business disruptions
Economic sectors where social distancing is more difficult to implement or where activities are highly related to international mobility and trade have been the most affected by COVID-19 containment measures (OECD, 2020[6]). The “Statistical Insights: Small, Medium and Vulnerable” note identifies these sectors. Their contribution to total economy is expressed as a share of total employment in 2018 (or latest year available), which signals the degree of a country’s exposure to the business shock.
In addition, two indicators complement this perspective on economic exposure, by shedding light on some regional and sectoral aspects. The country profile looks at the region (TL2 level) with the highest share of jobs at risk due to COVID-19, drawing on the “OECD Regional Outlook 2021” (OECD, 2021[7]) and the “Job Creation and Local Economic Development 2020: Rebuilding Better” reports (OECD, 2020[8]). The year of reference is 2017 (or latest year available). This section also looks at the direct contribution of tourism as a share of total employment in 2019 (or latest year available) based on the OECD Tourism Statistics database (OECD, 2021[9]).
Exposure to international trade and GVCs
Firms, places and people that were more engaged in international trade and long GVCs were also more vulnerable (Chapter 3).
A country’s exposure to trade and GVCs is estimated by the share of SMEs in export and import trade value, and the share of SMEs in export and import trade value of long GVCs. Long GVCs are defined as the top 10 longest value chains based on the OECD Inter-Country Input-Output (ICIO) model (OECD, 2018[10]) (De Backer and Miroudot, 2013[11]), and using the International Standard Industrial Classification of All Economic Activities Revision 4 (ISIC Rev.4) at two digits: i.e. manufacturing of textiles (13), manufacturing of wearing appeal (14), manufacturing of leather and related products (15), manufacturing of rubber and plastics products (22), manufacturing of basic metals (24), manufacturing of computers, electronics, and optical equipment (26), manufacturing of electrical equipment (27), manufacturing of other machinery and equipment (28), manufacturing of motor vehicles, trailers and semi-trailers (29), and manufacturing of other transport equipment (30). Data are for 2015 (or latest year available), and drawn from the OECD Trade by Enterprise Characteristics database (OECD, 2021[12]).
In addition, the country profile looks at the economic impact of foreign affiliates (FAs) through their local sourcing or supplying activities. The share of FAs sourcing domestically and the share of FA output used domestically are for 2016 and calculations are based on the OECD Analytical AMNE Database on the Activity of Multinational Enterprises (OECD, 2017[13]).
For countries where data on FA activities (AMNE data) and the share of SMEs in export and import trade value (TEC data) are not available, structural vulnerabilities are benchmarked using Trade in Value Added (TiVA) database. More specifically, countries are compared based on i) the intensity of their backward linkages in GVCs (proxied by the import content of exports, i.e. foreign value added embodied in gross exports as a percentage of total gross exports), ii) the intensity of their forward linkages in GVCs (proxied by domestic value added embodied in foreign exports as a percentage of total gross exports), iii) their reliance on foreign final demand (proxied by the share of domestic value added embodied in foreign final demand), and iv) the importance of intermediate imports for international competitiveness (proxied by the share of re-exported intermediate imports in total intermediate imports). The year of reference is 2016.
Sources of SME&E resilience
The third section looks at the sources of resilience of SMEs, namely i) their digital readiness, ii) their cash reserves, and/or access possibly given to government liquidity support; iii) the existence of supportive entrepreneurship framework conditions in the country; and iv) the availability and optimal use of innovation skills in the labour market.
Digital readiness
The COVID-19 crisis gave a big push to SME digitalisation and those that were already operating online or have been able to adapt products and processes to the digital world on short notice have been more likely to sustain activities and revenues amidst the turmoil (OECD, 2021[14]) (Chapter 1). Digital readiness is proxied by the uptake of some digital technologies by small enterprises (1-9 employees) prior to COVID-19. Digital uptake is indeed consistently lower in smaller firms across countries, and diffusion gaps are relatively constant across firm size classes (OECD, 2021[14]). The benchmark is made on the population the most likely to be lagging in the digital transition.
The digital technologies considered are i) high-speed broadband, i.e. percentage of small businesses with a broadband download speed at least 100 Mbit/s; ii) social media, i.e. percentage of small businesses that are using social media; iii) e-commerce, i.e. percentage of small businesses receiving orders over computer networks; and iv) cloud computing, i.e. percentage of small businesses purchasing cloud computing services. These four technologies have been selected for their particular role in the digital transformation of SMEs (OECD, 2021[14]). High-speed broadband connection is a prerequisite for (large) data transfer, just-in-time communication, and the use of other digital technologies. Uneven access to high-speed broadband is also one main factor associated with digital gaps across firms and sectors, and sectoral value added. Social media and e-sales are the primary forms of digitalisation for SMEs, as firms tend to digitalise marketing functions first. Cloud computing serves as a platform technology and helps SMEs enhance IT capacity and access digital solutions at low costs.
Indicators on digital adoption are retrieved from the OECD ICT Access and Usage by Businesses database (OECD, 2021[15]). They are presented on a stylised adoption curve that features increasing potential benefits in adoption for earlier adopters (16% of the total population) and an early majority of adopters (34%), and decreasing gains for the late majority (34%) and laggards in adoption (16%). This adoption curve illustrates Rogers’ innovation diffusion theory that suggests a threshold beyond which there are decreasing returns on innovation adoption (in terms of market shares) (Rogers, 1962[16]). Depending on the indicators, the years of reference are 2019 or 2020 (or latest year available).
Cash reserves and government’s liquidity support
Liquidity shortages have been a major issue for SMEs during the COVID-19 crisis, most of them having only a couple of months of income in cash reserves to pay charges and salaries as revenues collapsed. SME cash reserves are proxied by profit margin, i.e. gross operating surplus of firms with 1-249 employees in industry (except construction) as a percentage of their production. Data refer to 2018 (or latest year available) and are drawn from the OECD Structural and Demographic Business Statistics database (OECD, 2021[4]).
SMEs that have been able to access government support during the year have been more likely to maintain operations and not close business (Chapter 1). SME access to liquidity support in the country is proxied by the share of SMEs that received i) government support (broad category); ii) government support in the form of grants or subsidies; iii) government support in the form of credit or deferral of payments; iv) non-financial government support (e.g. information, technical assistance or advisory services). Data are drawn from business responses to the “Future of Business Survey” December 2020, which collects feedback from 18 million SMEs with a Facebook page operating in OECD countries and beyond (Facebook, OECD and World Bank, 2020[17]).
Entrepreneurship regulatory framework
Administrative and regulatory framework conditions are critical for entrepreneurship, especially in the phase of recovery when business dynamics will support an optimal reallocation of resources towards the most efficient firms (OECD, 2019[18]). Framework conditions for entrepreneurship are proxied by a number of indicators that measure i) the simplification and evaluation of regulations (composite index from 1 -the most complex- to 6 -the simplest-), ii) administrative burdens on start-ups (composite index from 1-the less burdensome- to 6 -the most burdensome), the cost of starting a business (% of income per capita), the strength of insolvency framework (composite index from 1 – the weakest- to 16 - the strongest-) and the cost of resolving insolvency (% of estate). The two first indicators are drawn from the OECD Product Market Regulation database (OECD, 2021[19])); the last four are drawn from the World Bank Doing Business 2020 report (World Bank, 2020[20])). The years of reference are respectively 2018 and 2019.
All indicators are presented in the form of benchmarking indices and 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. The same methodology was used in the SME&E Outlook 2019 (OECD, 2019[18]).
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
Therefore, 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, the country benchmark was reversed for the indicators that are considered as measures of potential barriers to SME performance. This is the case for administrative burdens, the cost of starting a business, and the cost of resolving insolvency.
Innovation skills
The availability and use of innovation skills have been critical for the resilience of SMEs as they intend to adapt to new business conditions. They will be as critical for the recovery going forward. Innovation skills in a country are gauged through two set of indicators.
First, the perceived capabilities of the adult population to start a business, i.e. percentage of 18-64 population who believe they have the required skills and knowledge to start a business. Data refer to 2019 and are drawn from the Global Entrepreneurship Monitor (GEM) Adult Population Survey (Global Entrepreneurship Monitor, 2021[21]).
Second, the existence of shortage or surplus of some innovation skills in the country based on the composite indices of the OECD Skills for Jobs database (OECD, 2018[22]). Positive values indicate skill shortage while negative values point to skill surplus. The larger the absolute value, the larger the imbalance. Results are presented on a scale that ranges between -1 and +1. The maximum value reflects the strongest shortage observed across OECD (31) countries and skills dimensions. Skills imbalances reflect diverging growth in demand and supply of a skill. A shortage emerges if the labour supply for that skill does not increase or does not increase as fast as the demand for it, since typically it takes time for the education and training system to adjust to demand and produce the ditto skills. A country with sluggish demand for certain skills could therefore experience less imbalances for such skills because the pace of demand increase is more similar to that of supply increase. Data refer to 2015.
Innovation skills that are considered in the benchmarking include: i) computer and electronics skills, i.e. knowledge of circuit boards, processors, chips, electronic equipment, and computer hardware and software, including applications and programming; ii) adaptability/flexibility skills; iii) complex problem solving skills, i.e. developed capacities used to solve novel, ill-defined problems in complex, real-world settings, and iv) practical intelligence for innovation that is considered as personal characteristics that can affect how well someone performs a job (i.e. workstyle).
All indicators are presented as benchmarking indices as for the entrepreneurship framework conditions (see above), along the same methodology used in the SME&E Outlook 2019 (OECD, 2019[18]). Skills shortages and surplus are treated the same way (turned into absolute values), in order to highlight imbalances in the labour market. The country benchmark was reversed to reflect potential barriers to SME performance.
Caveats and caution in interpretation
The SME&E Outlook 2021 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. The cutting-off date for the indicators on SME&E and business conditions is 16 April 2021.
Some areas of interest may be unevenly covered by statistics as data in primary sources are not always available for all countries. Some alternative indicators could be proposed. Please refer to sources and methods.
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