Expert workshop on the creation and uses of combined environmental and economic performance datasets at the micro-level - 10-11 July 2018 - OECD, Paris

1. FIRM-LEVEL PATENT DATA ON
GREEN INNOVATION
Antoine Dechezleprêtre
Environment Directorate and Economic Department
Environment/economic microdata workshop
11 July 2018

2. • 94m patents
• 200 patent offices
• Applicant name and address; same for inventors
(physical person)
• Patent families
• Quality measures: citations, renewals, grant
status, international families (eg triadic) etc
Patstat

3. 3
The Y02 patent classification

4. 4
Energy

5. 5
CCS

6. 6
Buildings

7. 7
Transportation

8. 8
Waste

9. 9
Manufacturing

10. 10
Adaptation

11. 11
ICT

12. • AIR POLLUTION ABATEMENT
– Emissions abatement from stationary sources (e.g. SOx, NOx, PM emissions
from combustion plants)
– Emissions abatement from mobile sources (e.g. NOx, CO, HC, PM emissions
from motor vehicles)
• WATER POLLUTION ABATEMENT
– Water and wastewater treatment
– Oil spill cleanup
• WASTE MANAGEMENT
– Solid waste collection
– Material recovery, recycling and re-use
– Fertilizers from waste
– Incineration and energy recovery
• WATER CONSERVATION AND RECOVERY
– Indoor water conservation; Irrigation water conservation; Water distribution
– Water collection (rain, surface and ground-water); Water storage
OECD additional Green patents

13. • 41m+ patents linked with 760,000 firms
• Matching: name cleaning and harmonization
followed by lots of manual checks (eg Panasonic
1229 different applicant names)
• 190k US firms, 72k CN, 67k DE
• Mean 55 patents/firm
• Median 3 patents
• Min 1; Max 652351 (Panasonic/Matsushita)
• #2 Toshiba (546k), #3 Hitachi (460k), etc
The Patstat-Orbis link

14. • 91k firms with at least 1 Y02 (CCMT) patent
• Mean 21 patents/firm
• Median 2 patents
• Max 30k (Toyota)
• #2 GE; #3 Toshiba, Siemens, etc
Green patents at firm level

15. 15
Drivers of embodied technological
change
Lots on A and B

16. Clean Dirty
Fuel Price 0.992** -0.539***
ln(FP) (0.411) (0.177)
Clean Spillover 0.399*** -0.160***
SPILLC (0.085) (0.049)
Dirty Spillover -0.331*** 0.231***
SPILLD (0.076) (0.054)
Own Stock Clean 0.505*** 0.212**
KC (0.111) (0.107)
Own Stock Dirty 0.246*** 0.638***
KD (0.054) (0.080)
#Observations 68,240 68,240
#Units (Firms and individuals) 3,412 3,412
Impact of fuel prices on clean/dirty
innovation in the car industry
Notes: Estimation by Conditional fixed effects (CFX), all regressions
include GDP, GDP per capita & time dummies. SEs clustered by firm.

17. The impact of the EU ETS on low-
carbon innovation

18. 18
Drivers of embodied technological
change
Nothing on C

19. • How to best incentivize green innovation? (e.g.
combination of policies)
• Does policy-induced green innovation give firms
a first-mover advantage when other countries
catch up?
• Do green inventor firms perform better?
• Do resources (capital, more productive
employees) flow to greener firms?
Other unanswered questions

20. • Use of patented technologies within the
firm
• Technology supply chains
– Eg licenses, or (domestic) sales of products
with embodied green tech
20
Missing data

21. Limitations
• Patents = the tip of the iceberg. 4% of UK
innovating firms patent (Hall 2013).
• Patents more common for large firms
• Other common measures
– R&D exp: limited availability; not
disaggregated at technology level
– Carbon intensity etc: might capture
operational innovation (eg fuel switching)
New measures necessary

22. Thanks