5.4. Market entry
Digitalisation and the diffusion of information and communication technologies (ICTs) have revolutionised the way in which firms and markets operate, with important differences in business dynamism between digital-intensive and other sectors of the economy. Higher levels of business dynamism are associated with higher productivity. Analysis based on the OECD DynEmp3 database shows that digital-intensive sectors are, on average, characterised by higher business dynamism, as indicated by higher job reallocation rates and a larger share of young firms (see Calvino and Criscuolo, 2019 for further discussion).
In order to assess the role of market entry and business dynamism in top digital-intensive sectors, three key indicators have been analysed: average firm entry rates, exit rates and post-entry employment growth of entrants after five years. Digital-intensive sectors have higher entry rates than average in all countries analysed. They also have higher exit rates in most countries considered, though the magnitude of these differences is smaller than for entry rates. Cross-country differences in the sample are significant. Austria, the Netherlands and Turkey show the highest differences between the highly digital-intensive and all sectors of the economy.
Examination of the average post-entry employment growth of new firms five years after entry shows that surviving entrants in highly digital-intensive sectors grow faster, on average, than those in other sectors of the economy. Although this is true for most countries, the magnitude of the difference varies. The largest differences occur in Costa Rica, Portugal and Finland, whereas differences are smaller in Hungary, Turkey, the Netherlands and Japan.
Higher business dynamism in sectors characterised by stronger digital intensities is likely related to the diffusion of digital technologies, with the associated emergence of a wide range of new applications and business models. This is also consistent with the fact that these technologies have lower entry barriers and tend to facilitate interaction, information flows and access to markets, thus creating more opportunities for experimentation. ICTs are highly pervasive general-purpose technologies that stimulate entry and innovation not only in sectors producing them, but also in other digital-intensive sectors.
Access to finance for new and innovative firms involves both debt and equity finance. Venture capital (VC) is an important source of equity funding, especially for young technology-based firms. Available industry level data show that VC investments in 2017 were concentrated in the ICT sector in many countries, especially Lithuania, Luxembourg, Spain, the United Kingdom and the United States. The latter represents the biggest market for VC, where four in every ten dollars of VC went to the ICT sector, amounting to 0.17% of GDP.
The most digital-intensive sectors are often more dynamic and scale-up faster than other sectors of the economy.
Definitions
Entry rates are the number of entering units divided by the number of entering and incumbent units.
Exit rates are the number of exiting units over the number of exiting and incumbent units.
Post-entry employment growth is the ratio between total employment at time t + 5 over total employment at time t of surviving entrants.
Highly digital-intensive sectors are those in the upper (“high”) quartile of the distribution by digital intensity. They consist of Computer and electronics; Machinery and equipment; Transport equipment; Telecommunications; IT; Legal and accounting; Scientific R&D; Marketing and other business services; and Administrative and support services. See Calvino et al. (2018), Table 3.
Venture capital is private capital provided by specialised firms acting as intermediaries between primary sources of finance (insurance, pension funds, banks, etc.), private start-up and high-growth companies, with shares that are not freely traded on any stock market.
Measurability
The figures report unweighted averages across sectors and available years for the period 1998-2015 in the “Highly digital-intensive” and “All sectors” groups using “transition matrices” or yearly flow data from the OECD DynEmp3 database. The “transition matrices” summarise growth trajectories of cohorts of units from year t to year t + j. The analysis focuses on cohorts of entrants followed for five years (with t = 1998, 2001, 2004, 2007, 2010 and j = 5). Figures are based on manufacturing and non-financial market services, with the exception of Japan where only manufacturing data are available. Self-employment and the Coke and Real estate sectors are excluded from the analysis. A detailed coverage table is available in Calvino and Criscuolo (2019).
Data on venture capital are drawn from national or regional venture capital associations and commercial data providers. There is no standard international definition of venture capital or breakdown by stage of development. The OECD Entrepreneurship Financing Database aggregates original data to fit the OECD classification of venture capital by stages. Venture capital investment is influenced by differences in tax and innovation incentive regimes across countries.
Source: OECD calculations based on DynEmp3 Database, http://oe.cd/dynemp, January 2019. See 1.
← 1. Figures for each country report unweighted averages of entry and exit rates across STAN a38 industries and available years for the time period 1998-2015, focusing separately on sectors in the “Highly digital-intensive” and “All sectors” groups. A coverage table is available in Calvino and Criscuolo (2019).
Figures are based on data covering manufacturing and non-financial market services, and exclude self-employment and the Coke and Real estate sectors. Data for Japan are for manufacturing only. The classification of sectors according to digital intensity is based on Calvino et al. (2018) (top quartiles in either of the two periods considered in the study). Owing to methodological differences, figures may deviate from officially published national statistics. Data for some countries are still preliminary.
Source: OECD calculations based on DynEmp3 Database, http://oe.cd/dynemp, January 2019. See 1.
← 1. For Hungary and Turkey, the gap, though very small, is inverted such that the other sectors have slightly higher post-entry employment growth than the highly digital-intensive sectors.
The figure reports the ratio between total employment at t + 5 over total employment at time t of surviving entrants. Figures for each country report unweighted averages across STAN a38 sectors and available years (cohorts) for the period 1998-2015, focusing on the gap between the highly digital-intensive and other sectors groups. Cohorts can start in 1998, 2001, 2004, 2007 and 2010. A coverage table is available in Calvino and Criscuolo (2019).
Figures are based on data covering manufacturing and non-financial market services, and exclude self-employment and the Coke and Real estate sectors. Data for Japan are for manufacturing only. The classification of sectors according to digital intensity is based on Calvino et al. (2018) (top quartiles in either of the two periods considered in the study). Owing to methodological differences, figures may deviate from officially published national statistics. Data for some countries are still preliminary.
Source: OECD, Entrepreneurship Financing Database, November 2018. See 1.
← 1. For Israel, data refer to 2014.
For Japan and South Africa, data refer to 2016.
For the United States, data include venture capital investments done by other investors alongside venture capital firms, but exclude investment deals that are 100% financed by corporations and/or business angels.
Data providers are: Invest Europe (European countries), ABS (Australia), CVCA (Canada), KVCA (Korea), NVCA/Pitchbook (United States), NZVCA (New Zealand), PwCMoneyTree (Israel), RVCA (the Russian Federation), SAVCA (South Africa) and VEC (Japan).