Changes in Productivity and Industry dynamics in the Digital transition: The role of Intangibles
1. Changes in Productivity and
Industry dynamics in the Digital
transition:
The role of Intangibles
Chiara Criscuolo
Head, Productivity and Business Dynamics Division, Directorate for Science,
Technology and Innovation, OECD
based on joint work with D. Andrews, M. Bajgar, G. Berlingieri, S. Calligaris, F. Calvino,
C. Corrado, P.N. Gal, J.E. Haskel, A. Himbert, C. Josa Lasinio, L. Marcolin, J. Timmis, R. Verlhac
4th Annual Conference of the Global Forum on Productivity
20 June 2019
Sydney, Australia
2. • Productivity Slowdown and:
• Increase in profit dispersion (Bessen, 2017; Eggertsson et al., 2018)
• Increase in mark-ups (De Loecker and Eeckhout, 2017; Traina, 2018)
• Increase in industry concentration:
• evidence for the US (Furman and Orszag (2015); Autor et al., 2017; Bessen,
2017; Gutierrez and Philippon, 2016; Grullon et al., 2017; Crouzet and Eberly, 2018)
• for other world regions evidence limited and not clear-cut
(Valletti et al., 2017; Social Market Foundation, 2017; Gutiérrez and Philippon, 2018)
• Declining business dynamism (e.g. Haltiwanger et al., 2017)
• Decline in labour share (Autor et al., 2017) and investment
(Gutierrez and Philippon, 2016, 2017b; Crouzet and Eberly, 2018)
Evidence mostly from the United States
Motivation: Macro trends
3. Digital Technologies:
• lower costs of entry, operation, and experimentation;
• Ease sharing of ideas and innovation;
• network effects;
• Improve real-time measurement;
• Ease penetration of several markets and faster scaling up.
These characteristics can potentially:
o Increase efficiency and productivity growth;
o Be source of increased competition (Brynjolfsson et al., 2005).
But also:
o Lead to “Winner-takes-most” dynamics (Brynjolfsson et al., 2008; Bessen, 2017);
o Increase importance of complementary investments in intangibles
(Haskel and Westlake, 2017; Brynjolfsson and McElheran, 2016; Brynjolfsson et al., 2017).
Motivation: the role of the digital
transformation for competitive dynamics
4. • Decline in Knowledge diffusion Akcigit and Ates (2019)
• Implementation lags: Digitalisation, like other GPT needs
complementary innovations and investment in intangible capitals
(including organizational changes, and new skills)
• Brynjolfsson, Rock and Syverson, 2017
• Increase in Market Power driven by both changes in market
structure and changes in technology (importance of intangibles)
• De Loecker, Eeckhout, Mongey, 2019
• Heterogeneous and cyclical response of technology adoption to low
interest rates
• Liu, Mian and Sufi, 2019 (heterogeneity); Anzoategui, et al., 2016 (cyclicality)
Motivation: how can we explain these
trends? Competing explanations
5. What the presentation does
Bring together research by the Global Forum on
Productivity with work done in OECD Going Digital
Project and other ongoing research to contribute
to the debate:
• New evidence that goes beyond the US
• Link some of these trends to digital technologies
• New evidence on the role of intangibles in the
digital transformation
• VERY PRELIMINARY EVIDENCE
9. Productivity divergence within
countries too
Note: countries included are AUS, AUT, BEL, CHL, DNK, FIN, FRA, HUN, ITA, JPN, NLD, NOR, NZL,
SWE. The graphs shows the cumulated growth rates of dispersion within each country and sector
over the period. Source: Berlingieri et al., 2017 based on OECD MultiProd project
10. ..and the bottom seems to struggle to keep up…
Source: Berlingieri et al., 2019 based on OECD MultiProd project.
…With catch-up
being slower in
digital intensive
sectors and
services sectors
that are knowledge
intensive.
Labour
Productivity
Multifactor
Productivity
11. STYLIZED FACTS FROM CROSS-
COUNTRY MICRO DATA:
ENTRY RATES, MARK-UPS AND
CONCENTRATION
11
12. Declining Business Dynamism –
particularly in digital intensive sectors
Entry rates
Average trends within country-industry
13. 1. (Supply-Side) Markups
• Mark-up corresponds to the ratio between unit price (elasticity of output
with respect to intermediates) and marginal costs (the cost of
intermediates as a share of the firms revenue, observed in the data).
Intuition: in perfect competition input shares = output elasticities
• Captures changing input shares & production technologies across all
firms (importance of intangible assets and fixed costs)
• Few micro-assumptions (e.g. less sensitive to market definition)
2. Industry concentration
• Captures sales growth of big firms in both Europe and US
• Careful analysis taking into account cross-country ownership linkages and
MNEs activities across countries: apportioning to different industries
• Note: Industry vs market concentration
Mark-ups and Concentration
14. Rising mark-ups pushed by the top
Cobb-Douglas Translog
• Deciles of the mark-up distribution in the year 2-digit sector (A38) averaged
across sectors;
• Dynamics not due to a particular country.
15. Mark-ups higher in digital vs. less digital
intensive sectors and increasingly so
Average percentage differences in mark-ups (digital vs less digital sectors)
• Pooled OLS estimation;
• Robust to using Translog-mark-ups and TFP; clustering errors at industry-country;
excluding particular countries (e.g. US); Only surviving firms; Fixing digital at initial
period.
• Manufacturing<services & Non-Digital < digital
Source: Calligaris et al., (2018) “Mark-ups in the digital era”.
16. Concentration increased in both Europe and NA...
Increase in 3 out of 4 industries (2-digit) in each region
Source: Bajgar et al., (2019) “Industry Concentration in Europe and North America”
19 countries
considered as a
single market
18. Increase in concentration in digital vs low-
digital intensive sectors
Countries: SWE, JPN, FRA, FIN, USA, ITA, GBR, BEL, ESP
Highly digital-intensive industries reflect those with top quartile digital intensity in (2001-3) or (2013-15) as defined
according to the digital taxonomy of Calvino et al (2018).
Change in the share of sales due to 8 largest groups (rel. to 2002)
High Digital intensive
Low Digital intensive
19. Increase in concentration stronger in country-
industries with high investment in intangibles
Countries: SWE, JPN, FRA, FIN, USA, ITA, GBR, BEL, ESP. Industries: Manufacturing & Non-Financial Market Services
Intangible intensity of a country-industry defined as total intangible investment / value-added, mean values over
time. More (less) intangible-intensive country-industries reflects above (below) median.
Change in the share of sales due to 8 largest groups (rel. to 2002)
High Intangible intensive
Low Intangible intensive
Increase in 69% of country-
industries
Increase in 8 out of 9
countries
20. ARE THESE TRENDS LINK TO INTANGIBLE
ASSETS?
PRELIMINARY ECONOMETRIC EVIDENCE ON
CONCENTRATION, MARK-UPS AND
PRODUCTIVITY DISPERSION
23
21. Changes in concentration strongly correlated with
intangible (innovative property) investment
Countries: SWE, JPN, FRA, FIN, USA, ITA, GBR, BEL, ESP. Industries: Manufacturing & Non-Financial Market Services.
Investment as a share of value added, estimates shown for mean investment.
22. The effect of intangibles is stronger in globalised,
digital and concentrated sectors
Countries:
SWE, JPN,
FRA, FIN,
USA, ITA,
GBR, BEL, ESP.
Industries:
Manuf. &
Non-financial
Market
Services.
Estimates
shown for
average total
intangible
investment.
23. What can account for the digital mark-
up gap ?
0%
5%
10%
15%
20%
25%
30%
Investment in
tangibles
Investment in
intangibles
Market access Purchase of ICT
services input
Contribution to the mark-up-digital intensity relationship (using Gelbach
decomposition, 2016)
Investment in tangibles: ICT investment intensity + Intermediates ICT goods
Investment in intangibles: Software investment intensity+ % ICT specialists
Market access: E-sales intensity + Presence in the online market
Purchase of ICT services input: Intermediates ICT services
24. Evidence of the relationship between
intangibles and productivity divergence
Ongoing work Combining MultiProd data on productivity with
intangible investment data by Corrado et al. (2016)
Measures of intangible capital stocks and investment by country-industry
Including computer software and databases, R&D, design, brand equity, firms
specific human capital, organizational capital
Countries with both MultiProd and INTAN data:
Investment: AUT, BEL, DEU, DNK, FIN, FRA, IRL, ITA, NLD, PRT, SWE
• Preliminary analysis from econometric analysis suggests:
• Higher investment in Intangible capital is linked to higher
Productivity dispersion.
• This effect is stronger:
• At the top of the productivity distribution (90-50)
• In non-financial market services vs manufacturing
• After the financial crisis
25. • Productivity divergence (Andrews, et al., 2017, Berlingieri et al., 2017/19)
• Stronger in Digital intensive sectors; stronger pull from the top (winner
takes most) and lower catch-up at the bottom (diffusion). Clear role of
intangibles explaining for explaining differences (especially at the top)
• Increase in mark-ups, especially in the top half of the
distribution (Calligaris et al., 2018)
• And especially in digital intensive services mainly accounted for by
differences in intangible investment and use of digital services
• Declining business dynamism (Calvino and Criscuolo, 2019)
• Especially in digital intensive sectors
• Increase in concentration, in US; Europe and Japan (Bajgar,
Criscuolo and Timmis, 2019)
• stronger in intangible intensive sectors and more so in more open more
digital intensive sectors
Summary of the results
26. Implications for policies?
Implications depend on drivers
• Technological change, increased role of intangibles and
globalization allowing most efficient firms to be even more
efficient, expand and have higher mark-ups
• A competition problem?
• Reconsider Competition Policies (M&A thresholds; advocacy;
collaboration)
And challenges:
• Adoption and diffusion
• Complementarities
• Intangibles financing in start-ups and scale-ups
• Role of Intellectual Property rights 30