Women’s participation
in inventive activity
Evidence from EPO data
November 2022

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WOMEN’S PARTICIPATION IN INVENTIVE ACTIVITY:
EVIDENCE FROM EPO DATA

Hungarian biochemist Katalin Karikó has spent 30 years
researching messenger ribonucleic acid (mRNA). Her
method to modify mRNA for safe use in the human bodyhas paved the way for vaccines against coronavirus andother diseases, as well as prospective therapies for cancer
and heart disease. Karikó won the 2022 European Inventor
Award in the “Lifetime achievement” category.
< Table of contents | Executive summary | Key findings | Content | Annex

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WOMEN’S PARTICIPATION IN INVENTIVE ACTIVITY:
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Foreword
Currently, Europe is facing multiple challenges to publichealth, energy supply, its environment and geopoliticalstability. The ability to meet many of these issues
successfully depends more than ever on creativity andinnovation. Our ability to shore up our economies also
depends on a vibrant innovation sector supported byeffective intellectual property protection. Industries thatmake intensive use of intellectual property rights (IPR),
for example, already contribute 45% of the GDP of the EU.
They are also more resilient in times of economic crisis.
This is a time when we must therefore do everything
we can to nurture and empower diverse talent in
the innovation sector. However, we know that theseaspirations are not always met. The history of scienceand invention is indeed full of remarkable women,
whose inventions have changed our lives – from Marie
Curie and her pioneering research into radioactivity,
to the key role played by Katalin Karikó’s in developing
mRNA vaccine technology used most recently to fightthe COVID-19 pandemic. Yet women scientists havehistorically been denied equal opportunity, and theyremain under-represented among inventors named on
patent applications.
Drawing on the EPO’s cutting-edge patent data, thisstudy seeks to present an up to date and accurate pictureof gender and patenting, as it stands today. It aims toprovide key insights into the state-of-play of innovation
by women in Europe, which can be used by policymakers
and businesses.

< Table of contents | Executive summary | Key findings | Content | Annex

It shows that real progress has been made in recent
decades, with some European countries and industries
leading the way towards more inclusiveness. However,there is still clear evidence of a persistently anddisproportionately low number of women inventors.
This gap is wider in Europe than in other parts of theworld, especially in some Asian countries where highshares of women inventors constitute a major force forinnovation. It has deep-rooted causes spanning theculture, educational systems and job markets indifferent countries.
Increasing women’s participation in science thus remains
a major challenge for Europe to address, as well as a key
factor in its future sustainability and competitiveness.
To help support a progressive agenda, this study also
identifies some positive trends and measures that canbe taken, such as supporting the mobility of womenscientists and accelerating the career of star inventors
among them. Continuing to raise awareness of this issue
and its consequences is also of the utmost importance.
The EPO intends to fully play its role by highlighting
the successes of women inventors, and informing the
public debate with evidence on the inventor gender gap.
By providing this insight, we can help ensure that theinnovation and IP sectors lead the field in diversity andinclusion.

António Campinos
President, European Patent Office

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WOMEN’S PARTICIPATION IN INVENTIVE ACTIVITY:
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Table of contents
Foreword

03

List of tables and figures....................................................................................................................................................................................................................................................................................................05
List of abbreviations............................................................................................................................................................................................................................................................................................................... 06
List of countries..............................................................................................................................................................................................................................................................................................................................07
Executive summary08

Key findings

09

1.

Introduction

13

2.

Methodology

15

3.

Women’s inventorship worldwide and in EPO countries

18

4.

Composition effects: technology and applicant type25

5.

Productivity, impact and role of women in teams

31

5.1

Productivity and impact .................................................................................................................................................................................................................................................................................31

5.2

Teamwork ...........................................................................................................................................................................................................................................................................................................................35

5.3

Internationalisation ..............................................................................................................................................................................................................................................................................................37

6.

Conclusion

40

Annex 1 Methodology

41

A.1.1		

Conceptual issues .....................................................................................................................................................................................................................................................................................41

A.1.2		

Patent and inventor data ..............................................................................................................................................................................................................................................................42A.1.3		

Methods ................................................................................................................................................................................................................................................................................................................43

Annex 2 List of regions, number of inventors and WIR

45

References

47<< Table of contents | Executive summary | Key findings | Content | Annex

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WOMEN’S PARTICIPATION IN INVENTIVE ACTIVITY:
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List of tables and figures
TablesTable 1

Gender attribution rate by inventor country of residence (for disambiguated inventors).........................................................15

Table 2

WIR by applicant type and technology field, 2010–2019...........................................................................................................................................................28

Table A.1

Gender attribution rate by inventor country of residence (disambiguated inventors and PATSTAT’s
person_id).................................................................................................................................................................................................................................................................................................... 44

Table A.2

List of regions, number of inventors and WIR............................................................................................................................................................................................45

FiguresFigure E.1

WIR, 1978–2019................................................................................................................................................................................................................................................................................... 09

Figure E.2

WIR by EPO country, 2010–2019...................................................................................................................................................................................................................................10

Figure E.3

WIR in EPO countries by technological sector and applicant type, 2010–2019......................................................................................... 11

Figure E.4

Comparison of WIR with women’s shares in total employment, PhD enrolment, PhD graduates in STEM,
R&D personnel, researchers and managers, 2010–2019........................................................................................................................................................... 12

Figure 1

Women’s participation in patenting in EPO countries, various measures, 1978–2021................................................................... 18

Figure 2

WIR in EPO countries compared with top countries, 1978–2019....................................................................................................................................19

Figure 3

WIR by EPC country, 2010–2019 (priority year)........................................................................................................................................................................................20

Figure 4

Ranked gender balance in the 25 largest patenting EPO countries by WIR, 1990–2019...............................................................21

Figure 5Comparison of WIR with women’s shares in total employment, PhD enrolment, PhD graduates in STEM,
R&D personnel, researchers and managers, 2010–2019........................................................................................................................................................... 22

Figure 6

Ratios of WIR across NUTS2 regions of EPO countries, 2010–2019.............................................................................................................................23

Figure 7

WIR across technological sectors, 1990–2019...........................................................................................................................................................................................25

Figure 8

WIR across technological fields in Chemistry, 1990–2019.......................................................................................................................................................26

Figure 9

WIR by applicant type, 1990–2019............................................................................................................................................................................................................................27

Figure 10

Cross-country analysis of the correlation of the WIR with specialisation in Chemistry and with university
and PRO patenting, 2010–2019......................................................................................................................................................................................................................................29

Figure 11

WIR across groups of inventors by their productivity in EPO countries, 1990–2019..........................................................................31

Figure 12

WIR among star inventors, 1990–2019...............................................................................................................................................................................................................32

Figure 13

WIR among star inventors, excluding experienced inventors, 1990–2019.......................................................................................................33

Figure 14

Share of patent applications including at least one woman across different patent indicators....................................... 34

Figure 15

Distribution of patent applications across team sizes with and without women, 1978–2019............................................35

Figure 16

WIR among the most central and leading inventors in a network, 1980–2019........................................................................................ 36

Figure 17

Share of international co-inventors among inventors by EPO country, 2010–2019............................................................................37

Figure 18

WIR among immigrants and nationals, 2010–2019..........................................................................................................................................................................38<< Table of contents | Executive summary | Key findings | Content | Annex

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WOMEN’S PARTICIPATION IN INVENTIVE ACTIVITY:
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List of abbreviations
EPC

European Patent Convention

EPO

European Patent Office

IBM-GNR

Global Name Recognition produced by IBM

IPIntellectual property

IPC

International Patent Classification

mRNA

Messenger ribonucleic acid

PATSTATEPO worldwide patent statistics database

PCT

Patent Cooperation Treaty

PRO

Public research organisation

R&D

Research and development

SSA

Social Security Administration

STEM

Science, technology, engineering and mathematics

UKIPO

United Kingdom Intellectual Property Office

USPTO

United States Patent and Trademark Office

WGND

Worldwide Gender Name Dictionary

WHO

World Health Organization

WIPO

World Intellectual Property Organization

WIR

Women inventor rate<
< Table of contents | Executive summary | Key findings | Content | Annex

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WOMEN’S PARTICIPATION IN INVENTIVE ACTIVITY:
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List of countries
AT

AustriaBE

Belgium

BG

Bulgaria

CH

Switzerland

CY

CyprusCZ

Czech Republic

DE

Germany

DK

Denmark

EE

Estonia

ES

Spain

FI

Finland

FR

FranceGR

GreeceHR

Croatia

HU

Hungary

IE

IrelandIS

Iceland

IT

Italy

LI

LiechtensteinLT

Lithuania

LU

Luxembourg

LV

LatviaMC

MonacoNL

Netherlands

NO

NorwayPL

PolandP.R. China

People’s Republic of China

PT

PortugalR. Korea

Republic of Korea

RO

Romania

RS

SerbiaSE

SwedenSI

SloveniaSK

Slovakia

TR

TurkeyUK

United Kingdom

US

United States<< Table of contents | Executive summary | Key findings | Content | Annex

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WOMEN’S PARTICIPATION IN INVENTIVE ACTIVITY:
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Executive summary
While women’s contributions to science and technology
have been increasing in recent decades, parity with men
has still not been reached. This study examines women’s
participation in patenting activity at the EPO in the 38
contracting states to the European Patent Convention(EPC). 1 The analysis focuses on all European patentapplications submitted between 1978 and 2019, withoccasional extensions until 2021, where possible. Using
disambiguated inventor data and attributing gender toindividual inventors based on their names, the analysis
provides evidence on the presence of women inventors
across different countries, time periods, technology fields
and patent applicant profiles.

1

The data exclude Montenegro, which acceded the EPC on 1 October 2022, after this study was prepared.

< Table of contents | Executive summary | Key findings | Content | Annex

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WOMEN’S PARTICIPATION IN INVENTIVE ACTIVITY:
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Key findings
1.

The share of women inventors has increased steadily
over time but is still below parity with that ofinventors who are men. In EPO countries, the women
inventor rate (WIR), which measures the percentageof women inventors among all inventors in patentapplications in a given year, increased from around
2% in the late 1970s to more than 13% in 2019.

Figure E.1

WIR, 1978–2019
WIR

30%

25%

20%

15%

10%

5%

0%
1978

1980

1982

1984

1986

1988

1990

1992

1994

1996

1998

2000

2002

2004

2006

2008

2010

2012

2014

2016

2018

Appplication incoming year
EPO states

US

Japan

R. Korea

P.R. China
Source: author’s calculations< Table of contents | Executive summary | Key findings | Content | Annex

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WOMEN’S PARTICIPATION IN INVENTIVE ACTIVITY:
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2. In 2019, the WIR in EPO countries (13.2%) is well
above that in Japan (9.5%) but below the US WIR 		(15.0%). P.R. China and R. Korea show much higher
shares of women inventors (26.8% and 28.3% in 2019,respectively), although the estimates are less robust
than for other countries. Among EPC contracting 		states, Latvia (30.6% in 2010-2019), Portugal (26.8%),
Croatia (25.8%), Spain (23.2%) and Lithuania (21.4%)
have the highest WIR values, while Germany (10.0%),
Luxembourg (10.0%), Liechtenstein (9.6%) andAustria (8.0%) have the lowest.

Figure E.2

WIR by EPO country, 2010–2019
Latvia

30.6%
26.8%

Portugal
Croatia

25.8%
23.2%

Spain
21.4%

Lithuania
Estonia

20.7%

Greece20.7%

Poland18.2%

Romania

17.8%

Turkey17.7%

Serbia

17.7%
17.4%

Slovenia

16.6%

France15.8%

Belgium

15.1%

Cyprus
Italy

14.3%

Ireland

14.0%

Bulgaria

13.9%

Iceland13.5%

Finland

12.6%

United Kingdom

12.4%

Hungary

12.4%

Denmark

12.4%

Sweden12.2%

Slovakia

12.0%

Switzerland

11.9%

Netherlands

11.9%
11.7%

Czech Republic

11.2%

NorwayMonaco10.3%

Luxembourg

10.0%

Germany

10.0%

Liechtenstein

9.6%
8.0%

Austria
5%

10%

15%

20%

25%

30%

35%

Source: author’s calculations< Table of contents | Executive summary | Key findings | Content | Annex

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WOMEN’S PARTICIPATION IN INVENTIVE ACTIVITY:
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3. Differences across EPO countries can largely be
explained by those countries’ technology
specialisations and the contributions of universities
and public research organisations (PROs) to patenting
activity.
a.
		
		
		
		
		
		
		

b.
		
		
		
		
		
		

Chemistry stands out as the technology sector
with the highest share of women inventors. The
WIR in the 2010–2019 period reached over 22%,
while the values in other technology sectors 		
ranged from 10.1% in Instruments to 5.2% in 		
Mechanical engineering. Within the Chemistry
sector, Biotechnology and Pharmaceuticals have
WIR values over 30%.

Patent applications from universities and PROs 		
have a significantly larger share of women 		inventors than their counterparts from 		
companies. The WIR of 19.4% for this segment
in 2010–2019 significantly exceeds that of 		
individual inventors (9.3%) and privatecompanies (10.0%).

Figure E.3

WIR in EPO countries by technological sector and applicant type, 2010–2019
1. Technological sector

2. Applicant type

25%

25%

22.4%
20%

20%

18.2%

15%
10%

15%

11.9%

5%

10.1%
7.9%
5.4%

1990-1999

Instruments

2000-2009

13.3%

10%

7.3%
5.8%
4.0%

5.2%
3.5%

7.0%

0%
Chemistry

19.4%
18.1%

Electricalengineering

Other fields

5.2%
3.8%
2.4%
Mechanicalengineering

5%

10.0%
8.8%
6.1%

9.3%
7.8%
6.0%

Businesscompany

Individual
inventor0%
University
and PRO2010-2019
Source: author’s calculations< Table of contents | Executive summary | Key findings | Content | Annex

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WOMEN’S PARTICIPATION IN INVENTIVE ACTIVITY:
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4. There is a consistent pattern of a decreasing shareof women in segments ranging from total
employment to PhD enrolment, to PhD graduates
in STEM, to R&D personnel and researchers, topatenting. This confirms the diagnostic of a “leaking
pipeline” issue, whereby women in EPO countries
face increasing obstacles when progressing in STEM
careers. Further analysis shows that women
inventors, on average, produce fewer inventions thaninventors who are men, which is partly due to theirlower seniority.

6. Women are also over-represented among inventors
whose names and surnames are infrequent in theircountry of activity and more frequent abroad,which indicates a higher WIR for migrant women
inventors than for native ones. This suggests that
support for international mobility may give women
more opportunities to engage in inventive careers.

5. Women are more likely to be found in inventor
teams than among individual inventors, but theytend to have less senior positions in such teams
than men. This reflects the increasing division of
intellectual labour that accompanies theaccumulation of knowledge, especially in technology
fields in which women inventors tend to specialise,
and bodes well for the future of women in patenting.

Figure E.4

Comparison of WIR with women’s shares in total employment, PhD enrolment, PhD graduates in STEM, R&D personnel,
researchers and managers, 2010–2019
FranceGermany

United Kingdom

50%

50%

50%

40%

40%

40%

30%

30%

30%

20%

20%

20%

10%

10%

10%

0%

0%

0%

Employment

Enrolled in PhD

PhD graduated in STEM

R&D personnel

Researchers

Managers

WIR
Source: author’s calculations< Table of contents | Executive summary | Key findings | Content | Annex

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WOMEN’S PARTICIPATION IN INVENTIVE ACTIVITY:
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1. Introduction
While women’s contributions to science and technology
have been increasing in recent decades, parity with men
has still not been reached. As a result, society is missingout on many goods, drugs and services due to the low
participation of women in inventive activities. According
to recent research, for instance, patenting in the UnitedStates could quadruple if women, minorities and children
from low-income families became inventors at the samerate as men (Bell et al., 2019). It also shows that a lack ofwomen inventors translates into reduced breadth andinclusivity of technology (Nielsen et al., 2017; Koning
et al., 2021; Jaravel and Einiö, 2021).2 For example, ananalysis of US biomedical patents by Koning et al. (2021)
showed that women’s patents are more likely to focus on
women-specific health problems and men’s patents on
men-specific ones.
This study specifically focuses on women’s participationin patenting activity at the EPO in the 38 contracting
states to the European Patent Convention (EPC). Drawing
on patent data encompassing all European patentapplications between 1978 and 2019, with occasional
extensions until 2021, the study aims to provide
policymakers and the general public with relevant
insights and evidence on the contribution of women totechnological innovation and its development over time,
and the gaps that remain to be bridged to exploit the fullpotential of women inventors in Europe.
Assessing women’s participation in patenting is useful
not only to account for this gender gap, but also tounderstand its causes and consequences. Unlike mostindicators of women’s participation in STEM activities,
patents provide a precise measure of the output of
inventive activities at the individual level. The wealthof information available in patent data therefore
enables fine-grained analysis of the activities of women
inventors, including their distribution across industries
and geographies, the science and technology fields inwhich they specialise, as well as their position in scientificteams and collaboration networks.

About the gender gap in patenting
The low participation of women in patenting has
been attributed to a variety of factors. First andforemost, women who choose any type of career,and especially those in the STEM professions, face
tougher selection than men.3 This explains the “leaking
pipeline” phenomenon, by which invisible barriers filter
out women STEM graduates first from research jobs
and subsequently from the upper echelons of theirorganisations. Typically, women academics or senior R&D
staff are rare compared with women STEM students,
and their under-representation increases in proportion
to the seniority of the position (Alper, 1993; Delgado andMurray, 2021).
Women at universities have fewer links to industry
and are confined to more traditional academic careermodels than men. Available evidence shows that womenacademics submit about 40% fewer patent applications
than men, despite a similar scientific productivity (Dinget al., 2006). In addition, when it comes to inventions
that are both described in scientific publications andpatented, women credited as authors in the publications
are less likely than their co-authors who are men to
be credited as inventors in the corresponding patents(Lissoni et al., 2013; 2020).
Low recognition extends to business R&D, where womenearn less than men although they contribute as muchto the development of high-quality inventions (Hoisl
and Mariani, 2017). Evidence from US patents suggeststhat women inventors are less likely than men who
invent to obtain and maintain patent rights (Jensen etal., 2018; Reshef et al., 2021) and that their patents arecharacterised by a smaller average number of claims andcitations (Jensen et al., 2018).

2	An extensive summary of this research avenue is presented in a post by Matt Clancy on the innovation blog “What’s new under the sun”,
https://mattsclancy.substack.com/p/gender-and-what-gets-researched?r=3iwbj&utm_campaign=post&utm_medium=email
3	STEM stands for science, technology, engineering and mathematics.

< Table of contents | Executive summary | Key findings | Content | Annex

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WOMEN’S PARTICIPATION IN INVENTIVE ACTIVITY:
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Outline of the report
This report uses data from patent applications at theEuropean Patent Office (EPO) to examine the contributionof European women to inventorship. In particular, genderis attributed to EPO inventors based on their names,
allowing the computation of a “women inventor rate”(WIR) and other statistics across countries, sub-national
regions, technologies and applicants, as well as over time.
Section 2 presents an overview of recent research on
women’s inventorship and describes the methodology forgender attribution. Section 3 presents results per country
and over time, while section 4 looks at the composition
effects of women’s contributions by technology andtype of applicant. Section 5 analyses women inventors’
individual productivity and participation in inventor
teams. Section 6 presents a conclusion.

< Table of contents | Executive summary | Key findings | Content | Annex

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WOMEN’S PARTICIPATION IN INVENTIVE ACTIVITY:
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2. Methodology
For this study, all patent applications included in PATSTAT(the EPO worldwide patent statistics database) and filed
at the EPO between 1976 and 2019 are considered, which
is a total of 3 945 992 applications. For some statistics,
data from 2020 and 2021 have been included (thusadding 159 294 applications, all of which with at least
one inventor residing in an EPC country).

Table 1The study methodology follows Toole et al. (2019, 2021)
and consists in attributing gender to roughly 93% ofdisambiguated inventors (4 158 000 individuals) based on
the inventors’ names (see Box 1).4 Patents and inventors
are in turn assigned to countries according to theinventor address, based on the address data in PATSTAT.
As reported in Table 1, the attribution rate is highest for
EPO countries (98%), followed by the US (95%) and Japan(93%). Other Asian countries have lower attribution rates:
83% for India, 69% for R. Korea and 59% for P.R. China.

Selected EPO countries:

See Annex 1 for further information about the patentand inventor data preparation, gender attribution andinventor disambiguation processes and other conceptualissues.

Gender attribution rate by inventor country of residence(for disambiguated inventors)
Attribution (%)

Number (x 1 000)

All countries

92.6

4 158

All EPO countries

97.8

1 653

Germany

98.2

543

France98.0

257

Sweden

97.5

66

Italy

98.0

116

Switzerland

97.7

79

Netherlands

95.9

91

UK

97.7

214

US

95.2

1 095

P.R. China

58.8

111

Japan

92.5

883

R. Korea

68.6

149

India

83.1

38

Selected non-EPO countries:

Note: EPC contracting states are: Albania, Austria, Belgium, Bulgaria, Croatia, Cyprus,
Czech Republic, Denmark, Estonia, Germany, Finland, France, Greece, Hungary,
Iceland, Ireland, Italy, Latvia, Liechtenstein, Lithuania, Luxembourg, Malta, Monaco,
Netherlands, North Macedonia, Norway, Poland, Portugal, Romania, San Marino,
Serbia, Slovenia, Slovakia, Spain, Sweden, Switzerland, Turkey and United Kingdom.
The study data exclude Montenegro, which was not yet an EPC contracting state
when this report was prepared.

4	Attributing gender on the sole basis of the inventors’ names has its limitations, especially when it comes to Asian inventors both in Asian countries
and elsewhere. With the rise of patenting in such countries, and the increasing migration flows of Asian inventors to North America, Europe andAustralia, this will soon become a critical issue. One possible way forward is to merge this dataset with the inventors’ public profiles (from social
media or institutional websites) and/or administrative data, in line with what academic researchers have been doing with historical data or for
relatively limited samples over the past few years. This would require solving not only the technical problems associated with such a demanding data
linkage effort, but also the legal and ethical issues associated with the handling of sensitive data.

< Table of contents | Executive summary | Key findings | Content | Annex

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WOMEN’S PARTICIPATION IN INVENTIVE ACTIVITY:
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Box 1: Overview of recent studies on women’s inventorship
Whatever its origins, the gender gap in patenting has been
extensively documented in recent years. In the absence of
inventors’ gender information on patents, patent attribution
requires name analysis.
Naldi et al. (2004a, 2004b) made one of the first attempts inthis direction. The authors collected 8 291 different names (withassociated gender) from different sources such as dictionaries,
calendars, books, internet sites, record offices and telephone
directories, for six European countries. Based on those names,
they successfully attributed a gender to around 97% of 100 000
inventors with addresses in the selected countries, as per EPO
patents filed in 1998. Frietsch et al. (2009) extended the analysis
to all EPO patents until 2005 for 14 countries. Sugimoto et al.
(2015) considered all USPTO granted patents (1976-2013) anddetermined the inventors’ gender by comparing their names toseveral worldwide name information lists (such as Wikipedia and
WikiName) and some country-specific gender information lists(such as the US census) plus additional semantics for hard-togenderise Asian names. Their success rate in assigning gender
was around 90% for US-resident inventors (higher for European
countries, lower for Asian ones). Also for the US, Delgado et al.
(2019), Delgado and Murray (2021, 2018) and Reshef et al. (2021)
counted the gender occurrences of each name in the US Social
Security Administration (SSA), starting from the beginning of
the 20th century, and computed the frequency of its attribution
to men and to women. They then attributed inventors a gender
if their name was unambiguously attributable to a man or awoman.

< Table of contents | Executive summary | Key findings | Content | Annex

Quite recently, a number of intellectual property (IP) offices havealso engaged in gender attribution efforts. To date, the mostcomprehensive one is that of the UK Intellectual Property Office,which, in 2016, examined all patents included in PATSTAT (UKIPO,
2016). The authors of this study used two different externalsources of genderised names: first, census data (US SSA and the
UK Office for National Statistics); second, all Facebook public
profile pages with both name and gender information (Tang et al.,2011). Attribution rates were around 80-90% for the US, Japan, theUK, Germany, France and Italy, but were much lower for P.R. China(27.90%), Republic of Korea (29.09%) and Chinese Taipei (11.62%).
The World Intellectual Property Organization (WIPO) produces
gender information for inventors listed on Patent Cooperation
Treaty (PCT) patents, based on a dictionary of 6.2 million
names for 182 different countries (recently updated to include
approximately 25 million names; Lax-Martinez et al., 2021). As
explained by Lax-Martinez et al. (2016, 2021), the information
sources include social security registers and national statistical
offices of various countries, Wikipedia lists and even manual
checks by WIPO officials. Attribution rates are mostly over or close
to 90%, not only for Western countries (97% for the US, 99.2%
for Germany, 98.9% for the UK) but also for Asian ones (94% forJapan, 92.1% for R. Korea, 88.3% for P.R. China and 88.9% for India).
More recently, the USPTO published both a report and its sequelfor inventors from the PatentsView database (Toole et al., 2019,2021). The methodology of the study made it possible to attribute
gender to roughly 93% of inventors (3 244 813 individuals), a figurethat rises to 96% for US residents and falls to 90% for Japan,
72% for India, and 51% for P.R. China.

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WOMEN’S PARTICIPATION IN INVENTIVE ACTIVITY:
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Spanish scientist Elena García Armada has developed
a battery-powered exoskeleton for children withdisabilities. The adaptable device features a networkof small motors with sensors, software and machinery
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rehabilitation sessions, reducing muscle degradation andmedical complications. García Armada won the 2022 European
Inventor Award in the “Popular Prize” category.

< Table of contents | Executive summary | Key findings | Content | Annex

epo.org | 17

WOMEN’S PARTICIPATION IN INVENTIVE ACTIVITY:
EVIDENCE FROM EPO DATA

3. Women’s inventorship worldwide and in EPO countries
Various metrics can be used to evaluate the patenting
activity of women across regions and over time. The
principal metric is the women inventor rate (WIR), whichmeasures the percentage of women inventors andrequires disambiguated inventor data. In addition, twoother metrics can be considered (following Delgado etal., 2019; Delgado and Murray, 2021; Martinez et al., 2016;
Toole et al., 2019): women’s share of patents, which does
not require disambiguated inventor data but attributes
each patent fractionally to each inventor appearing on it
and aggregates all women’s shares across patents; andthe share of patent applications that include at least
one woman inventor, which does not require inventor
disambiguation either. Yearly computations for all three
metrics are presented by year of application for European
patents at the EPO, so as to avoid truncation in the mostrecent years.
As shown in Figure 1, the WIR for EPO countries has
increased consistently in recent decades, from around
2% in the late 1970s to over 13% in 2019. Women’s shareof patents follows a similar but slightly lower path. Thisdifference in levels can be explained in two ways. First, it

could simply be the case that women are less productive
inventors than men, meaning they produce fewer patents
per head (further explored in Section 5). Second, thedifference may be due to women’s over-representationin large teams, which translates into a lower shareof patents due to fractional counting of inventors’
contributions. In turn, this over-representation may be
explained by the women inventors’ specialisations intechnology fields in which teamwork is the norm (further
explored in Section 4).
Women’s share of patent applications and share of
inventor teams including at least one woman are metrics
that can be extended until 2021 due to availability of data.
Overall, both metrics have been increasing further in themost recent years. However, the share of inventor teams
including at least one woman, which is systematicallyhigher, is increasing faster than the WIR. This clearly
implies that the increase of women’s patenting activity
must be attributed to an increase in their participation
in inventor teams, rather than to the production of “solo”
patent applications.

Figure 1

Women’s participation in patenting in EPO countries, various measures, 1978–2021

25%

20%

15%

10%

5%

0%
1978 1980 1982 1984 1986 1988 1990 1992 1994 1996 1998 2000 2002 2004 2006 2008 2010 2012 2014 2016 2018 2020

Woman in patenting

Woman inventor rate (WIR)At least one woman in teamSource: author’s calculations< Table of contents | Executive summary | Key findings | Content | Annex

epo.org | 18

WOMEN’S PARTICIPATION IN INVENTIVE ACTIVITY:
EVIDENCE FROM EPO DATA

Figure 2 compares the ensemble of EPO countries witha number of other major contributors to patenting
worldwide. The WIR in EPO countries (13.2%) is slightly
lower than in the United States (15% in 2019), in line withthe findings of Toole et al. (2019), but higher than in Japan
(9.5%). Note however that it is significantly lower than in
P.R. China (26.8%) and R. Korea (28.3%), which exhibit thehighest WIR levels among the top innovation centres.5

Figure 2

WIR in EPO countries compared with top countries, 1978–2019
WIR

30%

25%

20%

15%

10%

5%

0%
1978

1980

1982

1984

1986

1988

1990

1992

1994

1996

1998

2000

2002

2004

2006

2008

2010

2012

2014

2016

2018

Appplication incoming year
EPO states

US

Japan

R. Korea

P.R. China
Source: author’s calculations

5	This result should be interpreted with caution, because gender attribution for these two Asian countries is relatively poor and is based on less strict
criteria for identifying women, which may translate into low precision (high number of false positives).

< Table of contents | Executive summary | Key findings | Content | Annex

epo.org | 19

WOMEN’S PARTICIPATION IN INVENTIVE ACTIVITY:
EVIDENCE FROM EPO DATA

Figure 3 provides details on the WIR across EPO countries,
for the 2010–2019 period by priority year.6 The highest
WIR levels are recorded in Latvia (30.6%), Portugal(26.8%), Croatia (25.8%), Spain (23.2%) and Lithuania(21.4%). Interestingly, Austria (8.0%), Germany (10.0%)
and the Netherlands (11.9%), which are among the top
10 patenting countries at the EPO (see EPO Patent Index
2021), are at the bottom of the ranking. Yet, differences
are also considerable among larger patenting countries,
with France (16.6%), Belgium (15.8%) and Italy (14.3%)
scoring much better on this metric.

Once again, cross-country differences may depend oncomposition effects, which are further investigated in
the next section. The countries with a higher WIR may
be patenting more in technological fields with higher
women’s participation, or depend more, for patenting,on universities and public research organisations (PROs)
rather than companies, the former being possibly more
open to women’s participation, due to historical reasonsor public regulation.

Figure 3

WIR by EPO country, 2010–2019 (priority year)

30% 30.6

26.8

25%

25.8
23.2

20%

21.4 20.7 20.7
18.2 17.8 17.7 17.7

17.4

15%

16.6

15.8

15.1

14.3 14.0 13.9

13.5

10%

12.6 12.4 12.4 12.4 12.2 12.0 11.9 11.9

11.7 11.2

10.3 10.0 10.0

9.6

8.0

5%
0%
LV

PT HR ESLTEE GR PL RO TR RSSI

FR BE CY

IT

IE

BG

IS

FI

UK HU DK SE SK CH NL CZ NO MC LU DE

LI

AT

Note: 34 out of 38 countries are featured in this Figure. Albania, Malta, North Macedonia and San Marino are excluded, having too few patent applications with inventors’
addresses in the country during the period analysed. The study data also exclude Montenegro, which was not yet an EPO contracting state when this report was prepared.
Source: author’s calculations

6	The priority date is the first date of filing of a patent application for a given invention. It is essential for determining whether any subsequent
application for the same invention can still be assessed as novel. It also makes it possible to determine whether the subject-matter of a patentapplication is prior art on a particular date.

< Table of contents | Executive summary | Key findings | Content | Annex

epo.org | 20

WOMEN’S PARTICIPATION IN INVENTIVE ACTIVITY:
EVIDENCE FROM EPO DATA

Figure 4 shows the evolution of country rankings forthree 10-year periods (1990–1999, 2000–2009 and2010–2019), with various positions appearing to be rather
stable over time. In the most recent period, Portugal,
Spain and Greece presented the highest WIR values.
Hungary, Slovakia and Bulgaria show the largest drop
in rankings over time from their top positions in the
1990s. The country that shows the most significant
improvement is Turkey, climbing from 16th positionin the 1990s to 6th in the 2010s.

Figure 4

Ranked gender balance in the 25 largest patenting EPO countries by WIR, 1990–2019
Ranking
1

Portugal

2

Spain

3

Greece4

Poland5

Romania6

Turkey7

Slovenia

8

France9Belgium

10

Italy

11

Ireland12

Bulgaria

13

Finland

14

United Kingdom

15

Hungary16

Denmark

17

Sweden18

Slovakia

19

Switzerland

20

Netherlands

21

Czech Republic

22

Norway23

Luxembourg

24

Germany

25

Austria

1990-99

2000-092010-19
Source: author’s calculations< Table of contents | Executive summary | Key findings | Content | Annex

epo.org | 21

WOMEN’S PARTICIPATION IN INVENTIVE ACTIVITY:
EVIDENCE FROM EPO DATA

Besides comparing the WIR across countries and overtime, it can also be compared to indicators of women’s
participation in other types of related economic andscientific activities, such as women’s share of total
employment, among PhD enrolment, among PhD
graduates in STEM, among R&D personnel, among
researchers and among managers. Figure 5 reports theresults of this exercise for nine EPO countries (which are
the largest in terms of patenting at the EPO).

share of women falls to around 30%, while elsewhere
it remains high and above 40% (as in Italy, Spain andespecially the Netherlands). The share of women further
decreases when looking at data on R&D personnel andresearchers, with a few exceptions (Spain and the UK).
This suggests that the “leaking pipeline” mechanism
is at work: women are less represented among PhD
graduates in STEM and then further hampered in theircareers as researchers. At the same time, though, theleaking pipeline alone cannot explain the low WIR values
observed in all countries. Even the lowest shares ofresearchers and R&D personnel are still multiples of the
WIR in the countries concerned. For example, in Germany
women account for 27% of all R&D staff, almost threetimes its WIR, while the proportion between the two
metrics is still 2 to 1 for France. Even among managers,
usually an occupation highly dominated by men,
women’s shares are around 2–3 times bigger than among
inventors.

Several stylised facts emerge. The main, and very striking,result is that in all nine countries the share of womenamong inventors in European patent applications is
significantly lower than in any of the other activities. In all
nine countries the share of women in total employment
is above 40% and sometimes even above 50%, but always
a multiple of their share among inventors (WIR). Data for
PhD enrolment show a similar picture. PhD graduates
in STEM present a slightly different picture: in somecountries, notably Germany, Belgium and Sweden, theFigure 5Comparison of WIR with women’s shares in total employment, PhD enrolment, PhD graduates in STEM, R&D personnel,
researchers and managers, 2010–2019
Germany

Spain

50%

50%

50%

40%

40%

40%

30%

30%

30%

20%

20%

20%

10%

10%

10%

0%

0%

0%

Italy

Netherlands

Sweden

50%

50%

50%

40%

40%

40%

30%

30%

30%

20%

20%

20%

10%

10%

10%

0%

0%

0%

United Kingdom

Belgium

Denmark

50%

50%

50%

40%

40%

40%

30%

30%

30%

20%

20%

20%

10%

10%

10%

0%

0%

0%

Employment

Enrolled in PhD

PhD graduated in STEM

FranceR&D personnel

Researchers

Managers

WIR

Notes: Employment: Share of women in the labour force (% of total labour force) – source: World Bank. PhD enrolment: Share of women enrolled in tertiary education, ISCED 8
programmes (PhD) – source: Eurostat. PhD graduated in STEM: Share of women graduated at doctoral level, in STEM (science, maths, computing, engineering), among population
aged 25-34 – source: Eurostat. R&D personnel: Total R&D personnel (head counts), % women – source: UNESCO. Researchers: Researchers (head counts), % women.
Managers: Women’s share of employment in senior and middle management (%) – source: World Bank (ILOSTAT database). WIR: Women inventor rate.
Source: author’s calculations< Table of contents | Executive summary | Key findings | Content | Annex

epo.org | 22

WOMEN’S PARTICIPATION IN INVENTIVE ACTIVITY:
EVIDENCE FROM EPO DATA

Finally, Figure 6 provides geographical information on
the WIR across all regions (NUTS2) of EPO countries.7
In particular, it maps the ratio between the WIR as
calculated for each region and the WIR calculated at
the national level for the country to which the region
belongs. Darker zones indicate regions with higher WIR
values compared with the national average and lighterzones regions with lower values. The first observation isthat the degree of regional heterogeneity is remarkable.
Most regions’ WIR ratio is below 80% of the national
average and a few regions have a WIR value that is twice
as high as the national average. The latter is the case forsome peripheral regions with relatively low patenting
activity, such as southern Italy or eastern Poland, butalso for some of the largest innovation hubs in Europe,such as London, the Capital Region of Denmark (which
includes Copenhagen) or Lazio (the region of Rome in
Italy). Indeed, with a few exceptions, such as Lombardy(the region of Milan in Italy), most of the large nationalinnovation hubs have a WIR which is above the national
average or at least very close to it.

Very high WIR values in peripheral regions may bestatistical artifacts, due to paucity of observations (sothat a handful of observations can make a big difference).
High WIR values in large national innovation hubs may
be due to a mix of different factors: a specialisationin technological fields where women inventors are
relatively well represented; the weight carried by patentsfrom universities, which reserve more opportunities for
women scientists than the private sector; and possibly
some genuine sociological factors, such as a higher
acceptance of women in professions dominated bymen. However, it may also be the case that locational
advantages, such as the necessity of physical proximity
to other inventors and researchers in order to access theirknowledge, are more important for women than for men.
Women, relative to men, are less likely to move acrosslocations and participate in conferences and seminars
away from their residence (Delgado et al., 2019).

Figure 6

Ratios of WIR across NUTS2 regions of EPO countries, 2010–2019

Source: author’s calculations

7	Annex 2 lists all NUTS2 regions, together with the number of inventors identified, the regional WIR and the WIR gap.

< Table of contents | Executive summary | Key findings | Content | Annex

epo.org | 23

WOMEN’S PARTICIPATION IN INVENTIVE ACTIVITY:
EVIDENCE FROM EPO DATA

Serbian-American bioengineer Gordana Vunjak-Novakovic
has opened new horizons in regenerative medicine withher method for growing new tissue outside the bodyusing a patient’s own cells. The approach is safer, more
precise and less intrusive in facial reconstruction, andholds promise for replacing damaged lung and hearttissue. Vunjak-Novakovic won the 2021 European Inventor
Award in the “Popular Prize” category.
Serbian-American bioengineer Gordana Vunjak-Novakovic has
opened new horizons in regenerative medicine with her method
for growing new tissue outside the body using a patient‘s own
cells. The approach is safer, more precise and less intrusive infacial reconstruction, and holds promise for replacing damaged
lung and heart tissue. Vunjak-Novakovic won the 2021 European
Inventor Award in the “Popular Prize” category.

< Table of contents | Executive summary | Key findings | Content | Annex

epo.org | 24

WOMEN’S PARTICIPATION IN INVENTIVE ACTIVITY:
EVIDENCE FROM EPO DATA

4. Composition effects: technology and applicant typeThis section looks at the variations of the WIR bytechnological sector and by applicant type to explore
whether these factors can explain the differences in WIRvalues across countries.

engineering (5.2%). Chemistry also shows the mostremarkable growth over time, especially around the turnof the century, jumping from 11.9% to 18.2%. This might
be explained by various factors, ranging from women’s
educational preferences, which in turn may be affectedby role models in the family (Hoisl et al., 2022), to theworking conditions in different economic sectors andtheir impact on the work-family balance. Instruments(10.1%), Electrical engineering (7.3%) and Other fields(7.0%) show WIR values closer to Mechanical engineeringthan to Chemistry.

Figure 7 presents WIR values across five broad
technological sectors (see Schmoch, 2008) for three
10-year time intervals. Across all five sectors, women’sshares increase over time. Chemistry stands out as thesector with by far the highest WIR (around 22% in the
2010–2019 period), which is four times higher than thevalue in the sector with the lowest WIR, MechanicalFigure 7

WIR across technological sectors, 1990–2019

25%

22.4%
20%

18.2%
15%
10%

11.9%

10.1%
7.9%
5.4%

5%

7.3%
5.8%
4.0%

7.0%
5.2%
3.5%

5.2%
3.8%
2.4%

0%
Chemistry

1990-1999

2000-2009

Instruments

Electrical engineering

Other fields

Mechanical engineering

2010-2019

Notes: Data used in the Figure correspond to patent applications whose inventors reside in one (or more) of the 38 EPO countries.
Source: author’s calculations< Table of contents | Executive summary | Key findings | Content | Annex

epo.org | 25

WOMEN’S PARTICIPATION IN INVENTIVE ACTIVITY:
EVIDENCE FROM EPO DATA

Figure 8 breaks Chemistry down into a number of smaller
technology fields (see Schmoch, 2008). It shows that the
WIR is highest in Biotechnology and Pharmaceuticals,
which both have more than 30% women inventors in
the most recent period, and, to a lesser extent, in Foodchemistry (28.1%) and Organic fine chemistry (25.8%),
Basic materials chemistry (22.6%) and Macromolecularchemistry (20.5%). Chemical engineering (10.8%) and
Environmental technology (9.2%) show the lowest rates
of women inventors within the Chemistry sector.

Figure 8

WIR across technological fields in Chemistry, 1990–2019
20.4%

Biotechnology
17.3%

Pharmaceuticals

Basic materials chemistry

15.7%

8.9%

Macromolecular chemistry

12.1%

5.8%

Materials, metallurgy

10.2%

6.0%

Surface technology

5.4%

Chemical engineering

4.6%

Environmental technology0%2000-2009

5%

8.5%
7.9%

6.8%

25.8%

22.6%

15.3%

7.7%

Micro-structure and nano-tech

28.1%

21.2%

11.3%

30.2%

22.1%

13.1%

Organic fine chemistry

30.7%

24.0%

15.8%

Food chemistry

1990-1999

26.1%

20.5%

14.7%
14.5%

11.9%
10.8%

9.2%
10%

15%

20%

25%

30%

35%

2010-2019

Note: Data used in the Figure correspond to patent applications whose inventors reside in one (or more) of the 38 EPO countries.
Source: author’s calculations< Table of contents | Executive summary | Key findings | Content | Annex

epo.org | 26

WOMEN’S PARTICIPATION IN INVENTIVE ACTIVITY:
EVIDENCE FROM EPO DATA

Various sources suggest that women are overrepresented on university patents relative to those filed
by companies (Delgado and Murray, 2018; Martinez etal., 2016; Toole et al., 2019). Figure 9 reports the WIR
for different types of patent applicants, distinguishing
between individual inventors, companies, anduniversities and PROs (including hospitals, non-profit
organisations and governmental agencies). The latter
host the largest proportion of women inventors, close to
20% in the 2010–2019 period and two times larger thanthe WIR for companies (10.0%) and individual inventors(9.3%). This may once again reflect women’s educational

preferences for chemistry and the life sciences as well as
the importance of universities and PROs among patentapplicants in these fields. However, it may also have to dowith women’s preference for working at universities andPROs, which offer less gender-biased working and social
conditions compared with those of companies employeesor, possibly, individual inventors (who are likely associatedwith small firms and start-ups). Indeed, as Table 2 shows,the WIR among university inventors is systematicallyhigher than among companies or individual inventors,
irrespective of the technological field chosen.

Figure 9

WIR by applicant type, 1990–2019

20%
15%

19.4%

18.1%
13.3%

10%

8.8%

10.0%

6.1%

5%

6.0%

9.3%

7.8%

0%
University and PRO

1990-1999

2000-2009

Business company

Individual inventor

2010-2019

Note: Data used in the Figure correspond to patent applications whose inventors reside in one (or more) of the 38 EPO countries.
Source: author’s calculations< Table of contents | Executive summary | Key findings | Content | Annex

epo.org | 27

WOMEN’S PARTICIPATION IN INVENTIVE ACTIVITY:
EVIDENCE FROM EPO DATA

Table 2

WIR by applicant type and technology field, 2010–2019
WIR
Individual
Inventor (1)Difference

Company(2)

University and
PRO (3)(3) - (1)(3) - (2)Electrical machinery, apparatus, energy

4.1

4.4

11.7

7.6***

7.2***

Audio-visual technology

5.6

5.0

7.2

1.6***

2.2***

Telecommunications

5.8

5.2

6.8

1.0

1.6***

Digital communication

4.6

7.0

6.8

2.2**

-0.2

Basic communication processes

4.2

3.8

6.2

2.0

2.3***

Computer technology

6.3

6.7

9.1

2.8***

2.4***IT methods for management

6.5

8.6

10.6

4.1***

2.0**

Semiconductors

6.0

7.8

13.7

7.7***

5.9***

Optics

6.9

6.8

9.7

2.8***

2.9***

Measurement

5.7

4.6

10.7

5.0***

6.1***

Analysis of biological materials

17.5

20.2

27.9

10.4***

7.7***

Control

6.4

4.3

8.6

2.2**

4.4***

Medical technology

9.1

9.3

14.5

5.4***

5.2***

Organic fine chemistry

20.3

19.9

25.6

5.3***

5.7***

Biotechnology

21.3

25.1

30.8

9.5***

5.7***

Pharmaceuticals

20.0

23.3

30.9

10.9***

7.5***

Macromolecular chemistry

10.9

14.8

23.9

13.0***

9.1***

Food chemistry

16.0

22.9

29.2

13.2***

6.2***

Basic materials chemistry

11.6

16.7

23.1

11.5***

6.4***

Materials, metallurgy

7.5

9.8

18.6

11.1***

8.8***

Surface technology

5.6

8.8

14.4

8.8***

5.6***

Micro-structure and nano-tech

12.9

9.3

18.4

5.5***

9.1***

Chemical engineering

5.4

7.2

17.2

11.8***

10.0***

Environmental technology

5.5

6.5

13.8

8.3***

7.3***

Handling

6.5

3.8

7.3

0.8

3.5***
5.0***

Machine tools

3.0

2.7

7.7

4.7***Engines, pumps, turbines

3.4

3.3

7.0

3.6***

3.7***

Textile and paper machines

7.3

6.4

18.9

11.6***

12.5***

Other special machines

5.6

4.9

13.0

7.4***

8.1***

Thermal processes and apparatus

3.6

4.6

8.6

5.0***

4.0***

Mechanical elements

3.4

2.7

6.1

2.7***

3.4***

Transport

4.9

3.6

6.0

1.1**

2.4***

Furniture, games

9.2

5.8

9.8

0.6

4.0***

Other consumer goods

14.0

8.2

11.9

-2.1**

3.7***

Civil engineering

4.5

2.9

6.7

2.2***

3.8***< Table of contents | Executive summary | Key findings | Content | Annex

epo.org | 28

WOMEN’S PARTICIPATION IN INVENTIVE ACTIVITY:
EVIDENCE FROM EPO DATA

Econometric analysis confirms that both the technology
specialisation of a country and the contribution ofuniversities and PROs to its patenting activity determinethat country’s WIR. Figure 10 relates the WIR valuesof a country to its patent specialisation in Chemistry(Figure 10 a)) and to its share of patent applications thatstem from universities and PROs (Figure 10 b)), for the

2010–2019 period. Both relationships are clearly positive,
and a quadratic OLS regression estimates that a country’s
technological specialisation can explain over 35% of
the cross-country variation in WIR (R2≥0.36), and that
universities and PROs make a similar or even stronger
contribution, explaining 59% of the variation (R2≥0.59).
The two pieces of evidence are also clearly correlated.

Figure 10

Cross-country analysis of the correlation of the WIR with specialisation in Chemistry and with university and
PRO patenting, 2010–2019a) WIR vs specialisation in Chemistry, 2010–2019
Share of patent applications in Chemistry
50%
LV

40%
CY

LT

HR

BE
GR

30%

MC
LU

20%

AT

NO

LI

NL
CZ

DE

CH
DK
UK
SK
HU

PT

ES
IS
BG
IT
IE

FR

SI

PL

EE

RS
TR

FI
SE

SM

10%
0

10

20

30

WIR
R-squared=.362b) WIR vs patenting by universities and PROs, 2010–2019
Share of patent applications from universities and PROs
50%
LV

40%

30%

LT
PT

FR

PL

20%
CZ

10%
DE
AT

0%

SM

0

LI

LU
MC

SK

UK
DK
NO CH FI
SE
NL

IS

BE
IE
BG

CY

RS

EE
GR

TR
SI
RO

ES
HR

IT

10

20

30

WIR
R-squared=.593
Source: author’s calculations< Table of contents | Executive summary | Key findings | Content | Annex

epo.org | 29

WOMEN’S PARTICIPATION IN INVENTIVE ACTIVITY:
EVIDENCE FROM EPO DATA

Scientists Madiha Derouazi (Switzerland) and Elodie Belnoue(France) have developed a platform to produce therapeuticanti-cancer vaccines. Derouazi established AMAL Therapeutics tocommercialise the platform in 2012. Seven years later Boehringer
Ingelheim acquired the company, with patents contributing
significantly to AMAL’s value as a biotech start-up. The teamwon the 2022 European Inventor Award in the “Small andmedium-sized enterprises” category.

therapeutic anti-cancer vaccines. Derouazi established
AMAL Therapeutics to commercialise the platform in2012. Seven years later Boehringer Ingelheim acquired
the company, with patents contributing significantly
to AMAL’s value as a biotech start-up. The team won
the 2022 European Inventor Award in the “Small andmedium-sized enterprises” category.

Scientists Madiha Derouazi (Switzerland) and Elodie
Belnoue (France) have developed a platform to produce< Table of contents | Executive summary | Key findings | Content | Annex

epo.org | 30

WOMEN’S PARTICIPATION IN INVENTIVE ACTIVITY:
EVIDENCE FROM EPO DATA

5. Productivity, impact and role of women in teams
Metrics such as the WIR are informative about women’s
participation in patenting, but say little about women
inventors in terms of productivity (e.g. number of patentapplications filed throughout their careers), the type of
patent applications they contribute to (e.g. technicaland economic impact of patent applications), and theirroles within and across inventor teams or networks (e.g.
the extent to which they hold leadership positions or
are visible within the inventor community). This section
provides insights into these aspects.

5.1 Productivity and impact

Covering the same three decades as the previous
sections, Figure 11 reports the WIR for different groups
of inventors based on their productivity, i.e. the numberof patent applications in which the person is mentioned
as an inventor within the respective observation period.
For all periods, WIR values decrease with the numberof patent applications per inventor. The WIR reaches its
maximum for inventors with just one patent applicationand its minimum for those with eight or more patentapplications. This clearly indicates that women are
over-represented among the less prolific inventors, andunder-represented among the most productive ones.

Assuming that talent is equally distributed acrossmen and women (Bell et al., 2019), women inventors’
productivity, leadership and visibility could differ, on
average, from that of inventors who are men for anumber of reasons. These include barriers to promotion
within corporate labs or to tenured positions in academiaor, for independent inventors or academic ones, fewer
business connections, with less opportunity for women toaccess intellectual property protection (Ding et al., 2009).

Figure 11

WIR across groups of inventors by their productivity in EPO countries, 1990–2019
1990-1999

2000-20092010-2019

1

1

1

2

2

2

3

3

3

4

4

4

5

5

5

6

6

6

7

7

7

8+

8+

8+

0%

5%

10%

15%

0%

5%

10%

15%

0%

5%

10%

15%

Note: Data used in the Figure correspond to patent applications whose inventors reside in one (or more) of the 38 EPO countries.
Source: author’s calculations< Table of contents | Executive summary | Key findings | Content | Annex

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WOMEN’S PARTICIPATION IN INVENTIVE ACTIVITY:
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However, the analysis presented in Figure 11 does not take
into account productivity variations across technologies.
Inventors with the same number of patents in a given
period could appear in different deciles had they filed
these patents in one or another technology (for example,
the average number of patents per person in Mechanicalengineering is generally lower than in Chemistry).
To the extent that women are over-represented insome technologies and under-represented in others,

composition effects need to be taken into account. For
this reason, Figure 12 focuses only on the top inventorsof the productivity distribution, the “star inventors”, who
are in the top 5% and top 1% of the patent-per-person
distribution of each technological field. The Figure showsthat as with productivity ranking, there are also fewer
women inventors and that this relationship does notdepend on composition effects.

Figure 12

WIR among star inventors, 1990–2019
WIR, in %WIR, in %

14%

14%

12%

12%

10%

10%

8%

8%

6%

6%

4%

4%

2%

2%

0%

0%
1990-1999

Star inventors (top 5%)

2000-20092010-2019Non-star inventors (bottom 95%)

1990-1999

Star inventors (top 1%)

2000-20092010-2019Non-star inventors (bottom 99%)

Note: Data used correspond to patent applications whose inventors reside in one (or more) of the 38 EPO countries.
Source: author’s calculations< Table of contents | Executive summary | Key findings | Content | Annex

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WOMEN’S PARTICIPATION IN INVENTIVE ACTIVITY:
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The above analysis has established that women tend to
produce fewer patents than men, even when controllingfor different technology fields. However, since thecalculations were restricted to specific time windows,
the results do not necessarily show seniority effects.
Even so, participation by women in patenting is relatively
new, so some of the most productive inventors in a given
time window may have accumulated knowledge andexperience that allow them to be more productive withinthat window. This issue is dealt with in Figure 13, which
reproduces the statistics of Figure 12 after excluding all
inventors whose first patent had a priority year before
the initial year of each 10-year time window. In thisway, only inventors who entered the profession in thatsame time window are considered. After eliminating theseniority effect, the differences in WIR between star andnon-star inventors become smaller. This suggests that,at least in part, the productivity gap between men andwomen declines over time, with more women reaching
more senior positions. However, the speed of theconvergence will depend on how easy or difficult it will be
for women to advance in their careers.
Patent applications may also differ in terms of breadthof protection and economic or technological impact.
Therefore, the following analysis aims to establish
whether women, on average, produce “different” patentsfrom men.

Figure 13

WIR among star inventors, excluding experienced inventors, 1990–2019
WIR, in %WIR, in %

14%

14%

12%

12%

10%

10%

8%

8%

6%

6%

4%

4%

2%

2%

0%

0%
1990-1999

Star inventors (top 5%)

2000-20092010-2019Non-star inventors (bottom 95%)

1990-1999

Star inventors (top 1%)

2000-20092010-2019Non-star inventors (bottom 99%)

Note: Data used in the Figure correspond to patent applications whose inventors reside in one (or more) of the 38 EPO countries.
Source: author’s calculations< Table of contents | Executive summary | Key findings | Content | Annex

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WOMEN’S PARTICIPATION IN INVENTIVE ACTIVITY:
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Figure 14 uses different qualitative indicators based on
Squicciarini et al. (2013), namely:— the patent’s radicalness, which – broadly speaking –captures the extent to which it is based on knowledge
from outside the technology to the advance of
which it contributes (as measured, technically, by
the number of technological sectors appearing in its
citations of the prior art, but not among the sectors
to which the patent itself belongs)— the number of claims per patent— the number of citations received by the patent(forward citations) in the five years following thepriority date

For each indicator, patents in the top 5% and thebottom 95% of the indicator’s distribution within eachtechnological field are presented separately (for example,
the 5% most original patents versus the remaining95%). The share of patent applications that include atleast one woman is then calculated for each group ofpatent applications. For a majority of indicators andtime periods, no clear pattern emerges. This suggests
that, in contrast to productivity, women do not appear
to be over- or under-represented in groups of patentapplications that differ in terms of breadth of protection
or economic or technological impact. To put it differently,
while women tend to produce fewer patents than men,
their inventions are as good as and sometimes better
than those of men. This suggests that gender differences
are not due to some ex ante distribution of talent andeffort, but to a different distribution of opportunities.

— the patent’s family size (number of patents filed
worldwide with the same priority, i.e. protecting thesame invention)— the patent’s generality, which – broadly speaking –captures the patent’s impact across the technological
spectrum as measured by the distribution of its
forward citations across all the technological fields(the more concentrated in a technological field thecitations, the lower the generality, and vice versa)— the patent’s originality, which – broadly speaking –captures the extent to which a patent recombines
previously unrelated pieces of knowledge, as
measured by the distribution of its citations of theprior art across all the technological sectors (the moreconcentrated in a technological sector the citations,the lower the originality, and vice versa)

Figure 14

Share of patent applications including at least one woman across different patent indicators
1990-1999

2000-20092010-2015

Claims

14.6%
11.5%

Claims

21.3%
17.1%

ClaimsFamily size

15.3%
11.4%

Family size

19.9%
17.1%

Family size

Fwd citations 5y

14.0%
11.5%

Fwd citations 5y

20.1%
17.1%

Fwd citations 5y

21.3%
20.1%

Generality

10.9%
12.8%

Generality

16.2%
19.3%

Generality

19.6%
21.2%

Originality

22.5%
16.9%

Originality

25.6%
19.9%

Radicalness

18.8%
17.2%

Radicalness

23.2%
20.0%

Originality

11.2%

16.9%

11.1%
11.6%

Radicalness
0%

10%

20%

% at least 1 woman

Bottom 95%

0%

10%

20%

% at least 1 woman

24.3%
19.1%
22.0%
20.1%

0%

10%

20%

% at least 1 woman

Top 5%

Note: Data used in the Figure correspond to patent applications whose inventors reside in one (or more) of the 38 EPO countries. The last time window is reduced to the
2010–2015 period (instead of 2010–2019) so as to avoid truncation when using forward citations (5y).
Source: author’s calculations< Table of contents | Executive summary | Key findings | Content | Annex

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WOMEN’S PARTICIPATION IN INVENTIVE ACTIVITY:
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5.2 Teamwork
The importance and size of inventor teams varyacross technologies. Patents in pharmaceuticals andbiotechnology are more likely than those in other fields
to result from teamwork and especially from large
teams of inventors. In general, the more science-baseda technology is, the more important and the larger aninventor team is. This also explains why inventor teams
on university patents are larger than those on
companies’ patents.
From this it can be inferred that over-representationof women on university and pharma/biotech patents
translates into their over-representation on patents
listing more than one inventor. This is clearly illustrated
by Figure 15. Patent applications listing at least one
woman among their inventors are more likely to be
produced by teams, rather than by individual inventors.
Teams that include women inventors also tend to belarger than those that include only men. Even morestrikingly, the share of patent applications with larger
teams, comprising four or more inventors, grew fasterover time if a woman was involved.

The preponderance of women in teams and particularly
in large ones begs the question of their role in suchteams: how often do they lead the teams or, conversely,
how often do they play a more operational, possibly
marginal role? Unfortunately, the sample provides nodirect information on the position of women in patentapplications, which would require access to their CVs or
to their social security data. However, at least two typesof information entirely contained in patent data can still
provide some indication as to their role within the team.
First, inventor networks are calculated and inspected toestablish whether women occupy more or less central
positions. An inventor network is a graph in which
nodes are inventors and ties are collaboration instances(Breschi and Lissoni, 2004). In the simplest form ofsuch a network, two inventors are tied when they haveco-invented at least once. Several inventor networks arecalculated, one for each five-year interval between 1980
and 2019, by considering all patent applications filed ineach time interval, in all EPO countries. Based on different
measures derived from social network theories (Borgatti
and Everett, 2006), it is then possible to examine thecentrality of each inventor to the network.8

Figure 15

Distribution of patent applications across team sizes with and without women, 1978–2019
Teams with at least one woman

Teams without women

90

90

80

80

70

70

60

60

50

50

40

40

30

30

20

20

10

10

0

0
1978 1 981 1984 1987 1990 1993 1996 1999 2002 2005 2008 2011 2014 2017

1 inventor

2-3 inventors

4-6 inventors

1978 1 981 1984 1987 1990 1993 1996 1999 2002 2005 2008 2011 2014 2017

6+ inventors

Note: Data used in the Figure correspond to patent applications whose inventors reside in one (or more) of the 38 EPO countries.
Source: author’s calculations

8	Centrality is simply calculated as the number of each inventor’s ties (degree centrality). This may run from zero to N-1, where N is the number ofnodes (inventors) in the network. In practice, the most central inventor never reaches more than a small fraction of N-1.

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WOMEN’S PARTICIPATION IN INVENTIVE ACTIVITY:
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Second, for each patent produced by a team in a given
year the most senior inventor in the team is identified,based on the number of patent applications each
inventor has produced in the previous years. This will be
zero for all inventors at their first patent application, andgreater than zero for all those with at least one former
patent application (Akcigit et al., 2018).
Figure 16 presents WIR values calculated for all inventors,
for five-year time windows, and compares them with
the WIR of: (1) the top 5% most central inventors in the
network, (2) the top 5% most central inventors (with the
top 5% computed also per technology field) and (3) the
subset of inventors comprising only the most senior onesin each team.

The Figure shows that women are over-represented
among highly central inventors in the network, since theWIR values are higher for this inventor sample (red line)
than for all inventors (blue line). However, this difference
can be fully explained by the over-representation of
women in teamwork-intensive technology fields. If thiscomposition effect is taken into account and the WIR for
highly central inventors in technology-specific networks
is considered, the WIR values among the most central
inventors (dashed red line) actually fall slightly below
the general WIR (red line) for many time periods. Thissuggests that women are no more or less central thanmen.
However, the analysis also confirms that women are lesssenior than men. WIR values calculated for the sampleof the most senior inventors (green line) are lower thanthe overall WIR. This suggests that team leaders are more
often men than women.

Figure 16

WIR among the most central and leading inventors in a network, 1980–2019

18%
16%
14%
12%
10%
8%
6%
4%
2%
0%
1980-1984

WIR overall

1985-1989

WIR top-5 degree centrality

1990-1994

1995-1999

2000-2004

WIR top-5 degree centrality, by technology field

2005-20092010-20142015-2019

WIR senior inventors
Source: author’s calculations< Table of contents | Executive summary | Key findings | Content | Annex

epo.org | 36

WOMEN’S PARTICIPATION IN INVENTIVE ACTIVITY:
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5.3 Internationalisation
The analysis is extended to the capacity of women
inventors to reach out to inventors in other countries,that is, their degree of internationalisation.
Figure 17 explores this aspect by looking at the average
share of unique co-inventors residing in a foreign country,
separately for men and women, across a selection of EPO
countries for the 2010–2019 period. In many countries theaverage level of internationalisation is higher among men
than women. There are notable exceptions, however,including Austria, Finland, Denmark and Switzerland, andeven some very large countries such as Germany andFrance.

Figure 17

Share of international co-inventors among inventors by EPO country, 2010–2019
90%
80%
70%
60%
50%
40%
30%
20%
10%
0%
LI MC LU SK RS CY HR BG RO CH BE GR CZ

Among womenIE HU EE AT

IS

LT NO UK PT DK

SI

PL

SE

ES NL FR

LV

IT

DE

FI

TR

Among men

Note: 34 out of 38 countries are featured in this figure. Albania, Malta, North Macedonia and San Marino are excluded, having too few patent applications with inventors’
addresses in the country during the period analysed.
Source: author’s calculations< Table of contents | Executive summary | Key findings | Content | Annex

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WOMEN’S PARTICIPATION IN INVENTIVE ACTIVITY:
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Another way to measure the internationalisationof inventors is through their mobility (temporary or
permanent). This is relevant for two reasons. First,
international mobility of STEM workers, and in particularinventors, is on the rise and contributes distinctively
to knowledge circulation worldwide (Breschi et al.,2017; Useche et al., 2020). It is fuelled both by generalmigratory movements and by multinational companies’
international recruitment and assignment policies(Kerr et al., 2016). At the same time, Delgado et al.
(2019) find, for the US, that women inventors are moregeographically constrained in their ability to accessknowledge than men. The proposed explanation isthat women take a disproportionate share of family
responsibilities, limiting their ability to move abroad
and team up with foreign colleagues (within and acrossorganisations). Once again, technological progress could
stand to gain from the removal of a gender gap, this timein terms of international mobility.

Figure 18 shows WIR values for immigrants and nationals
for a selection of EPO countries in the 2010–2019 period,
and the ratio between the two. The migration status of
inventors is estimated using name and surname analysis.9
The Figure clearly shows that, in many countries, WIR
values are higher among immigrants. It can be concluded,
therefore, that for many EPO countries the international
mobility of inventors is a clear contributor to closing thegender gap in patenting.

Figure 18

WIR among immigrants and nationals, 2010–2019
WIR in %

Ratio

60%

2.5

50%

2.0

40%
1.5
30%
1.0

20%

0.5

10%
0%

0.0
MC AT NLSI

LV CH DE LU NO DK RO UK SE BE FR

WIR among nationals

WIR among immigrants

LT HR GR IS HU FI

IT

TR

IE

CZ EE RS CY BG PT ES SK PL

LI

WIR ratio
Source: author’s calculations

9

Performed using IBM-GNR, as described in step 2 of the gender attribution methodology in Annex 1. However, here both the name and surname ofinventors are used. If neither is considered frequent in the country where the inventor resides (within-country frequency lower than 90), they arelabelled as an immigrant (for details, see Coda-Zabetta et al., 2021 and Lissoni and Miguelez, 2021).

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WOMEN’S PARTICIPATION IN INVENTIVE ACTIVITY:
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Portuguese engineers Nuno Correia and Carla Gomes
from INEGI have led the development of a mooring
platform for floating solar farms. The system tracks thesun, engineers
rotating eachsolar
panelandto optimise
efficiency.
Portuguese
Nuno
Correia
Carla Gomes
from INEGICorreia
and
Gomes
have
developed
thesystemunder
have led the development of a mooring platform for floating
contract
technology
SolarisFloat,
which
solar farms.
The from
systemtracks thecompany
sun, rotatingeach solar
panel
will
commercialiseit.
The
Portuguese
team
were
finalists
to optimise efficiency. Correia and Gomes have developed thethe 2022
EuropeanInventor Awardin theSolarisFloat,“Small andsystem atundercontractfrom technology
company
medium-sizedenterprises”
category.
which will commercialise it. The Portuguese team were finalists
at the 2022 European Inventor Award in the “Small andmedium-sized enterprises” category.

< Table of contents | Executive summary | Key findings | Content | Annex

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WOMEN’S PARTICIPATION IN INVENTIVE ACTIVITY:
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6. Conclusion
The report presents an in-depth study of women’s
participation in patenting at the EPO in the 38 EPC
contracting states10 to better understand the presence of
women inventors across different countries, time periods,
technology fields and applicant types.
The contribution of women to patenting has been
growing consistently over time. Even so, it is far not only
from being fully balanced with that of men, but also
from catching up with the share of women among STEM
researchers and graduates. Since researchers’ incomes arestrongly related to their contributions to patenting (Bellet al., 2019), this clearly puts women in a disadvantaged
position. This gap also harms society’s technologicalprogress, as new technologies may be missing due towomen’s lower access to patenting. This translates into
many human needs that remain unfulfilled.

Second, the presence of women in patenting increases
with the importance of teamwork, although womenremain under-represented among team leaders.
Despite persistent differences across technologies, theimportance of teamwork and collaboration is growing
in all fields, due to the increasing division of intellectual
labour that accompanies the accumulation of knowledge.
This trend bodes well for the future of women inpatenting and should be supported by appropriate
policies and human resource management practices.
Efforts to stimulate the international mobility of womenscientists could be a promising lever in this context,
in light of the higher women inventor rates observed
among migrant inventors.

Two main stylised facts stand out from the analysis. First,
the gender gap varies appreciably across technologies
and types of applicants: the more science-based a field (inparticular, the closer to the life sciences) and the higher
the weight of universities and public laboratories inpatenting, the larger the share of women. This suggeststhat the fields where the gender gap is more acute could
usefully borrow from those where it is weaker, in terms ofwork practices and cultural acceptance. The same applies
to companies relative to universities.

10 The data exclude Montenegro, which acceded the EPC on 1 October 2022, after this study was prepared.

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WOMEN’S PARTICIPATION IN INVENTIVE ACTIVITY:
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Annex 1 – Methodology
A.1.1

Conceptual issues

The methodology aims to match EPO inventors’ names
to various lists of worldwide names for which gender isalready known (usually with an indication of probability).
When carrying out this task, a number of obstacles had tobe overcome.
First, the gender of some names varies with language.
“Andrea” provides a typical example, being an Italianman’s name, but a woman’s one in most other languages.
In principle, the relevant language should be safely
inferred from the individual’s country or region ofresidence. However, for inventors this is less and less asafe guess, due to the extent and continuous increaseof migration in highly skilled and in particular STEM
professions, mainly towards patent-intensive countries(Fink and Miguelez, 2017; Lissoni and Miguelez, 2021).
Unfortunately, as the nationality or country of birth ofinventors is not available, it is necessary to infer theirpotential migratory background by name analysis.

Finally, great importance is attached to the disambiguationof inventors. In a nutshell, disambiguation consists in
identifying as the same person two or more inventors
with the same or similar names, but different addresses
while at the same time taking care not to introduce false
positives, that is, wrongly identify as the same person
two distinct inventors (Pezzoni et al., 2014).11 Only very
few of the surveyed studies use disambiguated data, themain exception being Toole et al. (2021, 2019). This comesat a cost. First, absent disambiguation, it is impossible tocalculate individual productivity (number of patents perinventor) and compare men with women in this respect.
Second, it is impossible to know whether the numberof women inventors is under- or over-estimated relative
to that of inventors who are men, as this depends onwhether women are, respectively, more or less productive
than men (or are under- or over-represented in highpatenting fields). Last but not least, it is impossible totrace inventors over time or in space and then produce a
gender analysis of careers, mobility and collaborations.
Disambiguated data helps to overcome these limitations.

Second, certain names are gender-neutral (such as“Yannick” in French, or “Tracy” in English), for which
unfortunately there is no remedy unless the inventor’s
personal information can be recovered, which is notpossible for a large-scale study like ours.
A third difficulty arises from the English transliterationof names originally written in non-Latin alphabets,
especially East-Asian ones. With transliteration, theoriginal name’s gender may be lost. For patents within
the same simple family (patents covering the same
invention in different offices) it would be possible, in
principle, to recover and genderise the name as written
in the original alphabet. But this is not the case forpatents that are not also filed in the inventor’s homecountry or country of origin (if migrant). The rise of Asian
inventorship makes this methodological issue well worth
investigating in the future.

11 In short, two key parameters for assessing the quality of disambiguation exercises are precision (share of false positives over total cases, where a false
positive originates from treating as one two different individuals) and recall (share of false negatives, which originate from treating a single individualas two different ones). The more restrictive the disambiguation criteria used, the higher the precision, often at the cost of low recall. The criteria used
by PATSTAT to assign inventors their person_id are extremely restrictive (exact match of name-surname combination and address), which implies
high precision and very low recall. This requires further disambiguation, aimed at increasing the recall rate without compromising precision.

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WOMEN’S PARTICIPATION IN INVENTIVE ACTIVITY:
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A.1.2

Patent and inventor data

This study considers all patent applications included in
PATSTAT and filed at the EPO between 1976 and 2019:a total of 3 945 992 patent applications. In particular,
all documents with “EP” as application authority are
selected from PATSTAT, excluding those with application
kind code “D2”, which are “artificial applications”
according to PATSTAT documentation. While only
the inventors with addresses in a European Patent
Convention (EPC) country are ultimately selected forour gender analysis, the gender attribution exercise isapplied to all inventors listed on all patent applications,irrespective of their address.12 This is done in order bothto create a database for further research and to produce
some internal diagnostics on the effectiveness of ourattribution exercise.
For some statistics, the period covered also includes 2020
and 2021 (adding 159 294 applications, all of which with atleast one inventor with residence in an EPC country).
Time-wise, the patents are classified according to their
EPO priority date, with some exceptions in which theincoming year of the application at the EPO is used.13 The
IPC classification, which we re-elaborate where necessary
by reclassifying patents in a broad technological field,
as per Schmoch (2008), is used to categorise patentapplications by technology.
Inventors are initially identified based on their PATSTAT
identifier (person_id), which is unique for all inventors
with exactly the same name and address. After gender
attribution, however, they are further disambiguatedin order to increase recall (reduce the false negatives)(Pezzoni et al., 2014).

Inventors’ information contained in patent data is
precious, but it may come with errors that could affectboth gender attribution and inventor disambiguation.
Despite applications to the EPO being among the mostcomplete and detailed (in terms of the quality andquantity of the information publicly provided), errors
remain. Some of the main problems and the ways they
are addressed in this report are presented below.
1.

The first and foremost issue when using inventor
data for economic analysis is that inventors’ names
are not disambiguated, as pointed out in the previous
subsection. This is why we used an improved (andadapted) version of the Massacrator algorithm(Pezzoni et al., 2014), as described in section 3.3.

2.

Visual inspection also enabled us to identify certain
cases where name and surname had flipped position
in PATSTAT. This affects disambiguation only to alimited extent, but it may be problematic for gender
attribution. While “FROOME, Christian” is clearly 		a man, “CHRISTIAN, Froome” cannot be attributed,
since “Froome” does not exist in any available gender
dictionary. Some of these cases can be identified andthe name and surname flipped (e.g. “FROOME,
Christian” and “CHRISTIAN, Froome” receive the same
inventor identifier after disambiguation), but a broader
correction is beyond the scope of the present work.

3. It is not uncommon for the name-surname field toinclude other information and stop words, such as
the name/address of the inventor’s employer(e.g. “c/o Philips Corp. Int. Prop. GmbH”) or theirtitle (e.g. “Dipl. Wirt. Ing.”). In this case we apply
several cleaning heuristics that significantly reducethe influence of these words. Yet, the problem
persists in a number of cases.
4. Finally, precision of the address field (which helps us
with the disambiguation of inventors’ names) may
differ, too. The address field is empty in only 0.015%
of cases. Yet, addresses with street level precision
constitute “only” 62% of all records. Despite this,address information in EPO patents is the mostdetailed among the largest patent offices (forexample, the USPTO only collects information on
the city of residence of the inventor).

12 For the list of EPC countries, go to https://www.epo.org/about-us/foundation/member-states.html (last accessed on 30 May 2022).
13 The priority date is the filing date of the very first patent application for a specific invention, irrespective of the patent office where the application
was filed. Application incoming year instead refers to either the filing year of the European patent application (for applications filed direct with the
EPO (Article 75 EPC)) or the year of entry into the European phase (for international (PCT) patent applications (Article 158(2) and Rule 107 EPC)).

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WOMEN’S PARTICIPATION IN INVENTIVE ACTIVITY:
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A.1.3

Methods

Gender attribution
The main sources of information on the gender of names
are:
1.

2.

the Global Name Recognition system, a name searchtechnology produced by IBM (“IBM-GNR” below). Thissystem uses a database produced by the US
immigration authorities in the first half of the
1990s, when they registered all names and surnamesof all foreign citizens entering the US, along with 		their nationality and gender. The database contains
around 750 000 full names, plus country-sensitive
orthographic and abbreviation rules (Breschi et al, 		2017). Each first name and surname is assigned to oneor (more often) several countries of likely origin(ci, with i=1…n), along with information on its
cross-country and within-country frequency. First 		
names are also assigned to gender, again inprobabilistic terms (probability p of being a woman’sname and 1-p of being a man’s name), irrespectiveof ci. IBM-GNR also provides some information on theworldwide frequency of names, 5% of which are toorare for any statistics to be reliable (“rare names”).
the Worldwide Gender-Name Dictionary (“WGND”
below), produced by WIPO. It currently includes
25 million names from 182 different countries. For
each name and country contained in the dataset, agender is provided for that country, based on
previous gender studies found in the literature aswell as information from national public statistical
offices – see Lax-Martínez et al. (2016) and
Lax-Martinez et al. (2021) for details.

The gender attribution is performed in two rounds andfour steps (more details in Toole et al., 2019, which uses
the same methodology):
Step 1: Based on the IBM-GNR and excluding rare names,
all inventors are classified as women (men) whose name’sp (1-p for men) is 97% or more. This threshold is reduced
to 95% if the name is highly frequent in the IBM-GNR
library, and to 90% if, on top of this, it is associated, forthe specific inventor, with a genderised middle name. In
this way, it is possible to attribute gender to 80.62% of
the initial number of 3 674 314 unique name+surname
combinations.
Step 2: For the remaining inventors, the WGND is used,which allows conditioning gender on the inventor’scountry of origin. To infer this the inventor’s residence(which could be misleading in the presence of large
migration flows) is ignored and instead the IBM-GNR’s
ci list (list of countries in which the inventor’s name has
non-zero frequency) is used. Then, the inventor’s surname
is examined and the country in the ci list associatedto the highest cross-country frequency is selected.
Afterwards, a gender is assigned to each inventor,
conditional on the gender information provided by the
WGND for the associated country. This completes thefirst round of gender attribution.14
Step 3: A second attribution round is performed for
those inventors who, at the end of the first round, still
have non-genderised names and whose surnames areassociated with countries of origin with poor gender
attribution levels (typically Asian countries, chiefly
P.R. China, Chinese Taipei, Singapore, Macao, Hong Kong,
R. Korea and India). For these inventors, step 1 is rerun but
with lower thresholds for gender attribution (60% for
P.R. China, Chinese Taipei, Singapore, Macao and Hong
Kong, 70% for R. Korea and 80% for India).
The steps above result in a gender attribution of
3 432 646 unique name+surname combinations (93.42%of the total unique name+surname combinations). Thistranslates into 93.9% gender attribution of PATSTAT’s
person_id – see Table 1.

14 In the infrequent case in which an inventor is not associable to any country of likely origin, the country of residence of his/her first patent ever at EPO
is used – for which, again, disambiguation is crucial.

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WOMEN’S PARTICIPATION IN INVENTIVE ACTIVITY:
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Disambiguation
Disambiguation is performed next, following Pezzoni etal. (2014). In a nutshell, the inventors’ names, surnames
and addresses are cleaned and parsed first. Next, allinventors are fuzzy-matched based on the similarity ofstrings containing their cleaned names and surnames.
Finally, the matches thus obtained are further filtered on
the basis of 20 criteria, grouped into six families: networkties (based on co-invention instances; see Breschi and
Lissoni, 2009), geographical proximity, patent applicant’s
person_id, patent’s field of technology, citations andothers. If, as a result of disambiguation, a given inventor
is assigned more than one gender (as when two inventors
with similar names, but different gender are identified
as the same person), the observation is split so as toincrease precision and avoid bias in our calculations ofgender statistics.15

As a result of disambiguation, the count of inventors in
the dataset decreases from the original 7 215 925 (numberof person_ids in the PATSTAT sample) to 4 489 587 uniqueinventors (number of unique identifiers created by thealgorithm), 92.57% of whom are attributed a gender. 16
Gender attribution coverage
Table A.1 shows the result of our gender attribution steps.
The share of genderised inventors is high (more than 90%,
regardless of whether measured at the level of person_id
or after disambiguation). Attribution is noticeably higher
if we restrict the analysis to EPO countries (which are
the focus of this report). In fact, non-attribution rates
concentrate in Asian countries, particularly in P.R. China,
R. Korea, India and, to a lesser extent, Japan.

Table A.1

Gender attribution rate by inventor country of residence (disambiguated inventors and PATSTAT’s person_id)
1

2

3

4
By person_id

By disambiguated inventor
Attribution %# (x 1 000)

Attribution %# (x 1 000)

All countries

92.6

4 158

94.0

6 784

All EPO countries

97.8

1 653

98.2

2 685

Germany

98.2

543

98.7

907

France

98.0

257

98.2

426

Sweden

97.5

66

97.8

105

Italy

98.0

116

98.5

195

Switzerland

97.7

79

98.2

127

Netherlands

95.9

91

96.5

151

UK

97.7

214

98.2

337

US

95.2

1 095

95.7

1 990

P.R. China

58.8

111

59.8

137

Japan

92.5

883

93.3

1 348

R. Korea

68.6

149

74.6

217

India

83.1

38

84.6

52

Selected EPO countries:

Selected non-EPO countries:

Notes: EPC contracting states are: Albania, Austria, Belgium, Bulgaria, Croatia, Cyprus, Czech Republic, Denmark, Estonia, Germany, Finland, France, Greece, Hungary,
Iceland, Ireland, Italy, Latvia, Liechtenstein, Lithuania, Luxembourg, Malta, Monaco, Netherlands, North Macedonia, Norway, Poland, Portugal, Romania, San Marino, Serbia,
Slovenia, Slovakia, Spain, Sweden, Switzerland, Turkey and United Kingdom. The study data exclude Montenegro, which was not yet an EPC contracting state when thisreport was prepared.

15 The alternative solution would be to assign the gender of the most productive inventor. This is problematic, as men tend to be more productive,
on average, in patent data, so this could slightly bias downwards women’s contribution to inventorship.
16 Note that, compared with Pezzoni et al.’s (2014) original application of the algorithm, some improvements in data preparation have been introduced,
such as considering the whole list of patents produced by inventors from all patent offices, in order to build their network of co-inventors (instead ofrelegating this to the EPO co-inventors) or introducing geocoding to match potential pairs of names to be disambiguated.

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WOMEN’S PARTICIPATION IN INVENTIVE ACTIVITY:
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Annex 2 – List of regions, number of inventors and WIR
Table A.2

List of regions, number of inventors and WIR
NUTS2# Inventors 2010-2019

WIR 2010-2019

WIR ratio 2010-2019

AT11

270

8.1

1.0

AT12

2 773

6.3

0.8

AT13

3 540

14.8

1.9

AT21

943

5.4

0.7

AT22

3 951

8.2

1.0

AT31

4 895

6.3

0.8

AT32

996

3.6

0.5

AT33

1 651

8.8

1.1

AT34

1 712

4.4

0.5

BE10

1 660

18.6

1.2

BE21

3 578

13.9

0.9

BE22

855

11.3

0.7

BE23

2 932

18.7

1.2

BE24

4 007

17.5

1.1

BE25

1 444

8.0

0.5

BE31

1 195

17.9

1.1

BE32

902

17.2

1.1

BE33

1 453

13.5

0.9

BE34

247

8.1

0.5

BE35

386

16.6

1.1

BG31

21

BG32

34

11.8

0.9

BG33

22

BG34

22

BG41

323

11.8

0.9

BG42

41

7.3

0.5

CH01

6 751

15.2

1.3

CH02

5 762

9.4

0.8

CH03

7 629

15.0

1.3

CH04

8 138

12.4

1.1

CH05

4 397

6.0

0.5

CH06

2 948

6.3

0.5

CH07

947

11.1

0.9

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WOMEN’S PARTICIPATION IN INVENTIVE ACTIVITY:
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NUTS2# Inventors 2010-2019

WIR 2010-2019

WIR ratio 2010-2019

CY00

137

15.3

1.0

CZ01

931

14.1

1.2

CZ02

494

8.7

0.7

CZ03

388

11.3

1.0

CZ04

172

10.5

0.9

CZ05

800

14.8

1.3

CZ06

820

9.6

0.8

CZ07

469

11.7

1.0

CZ08

255

9.8

0.8

DE11

22 016

6.9

0.7

DE12

14 433

10.1

1.0

DE13

9 230

7.5

0.8

DE14

8 387

8.4

0.8

DE21

27 450

10.1

1.0

DE22

2 484

4.8

0.5

DE23

4 225

6.9

0.7

DE24

3 842

8.0

0.8

DE25

10 252

8.0

0.8

DE26

4 698

9,2

0.9

DE27

6 117

6.0

0.6

DE30

8 925

13.2

1.3

DE40

2 933

9.9

1.0

DE50

1 057

10.5

1.1

DE60

4 718

16.4

1.7

DE71

13 255

14.7

1.5

DE72

2 616

9.1

0.9

DE73

1 923

5.6

0.6

DE80

1 035

16.5

1.7

DE91

5 351

10.3

1.0

DE92

5 572

10.8

1.1

DE93

2 294

7.9

0.8

DE94

3 279

5.5

0.6

DEA1

12 871

13.4

1.4

DEA2

12 168

11.2

1.1

DEA3

4 901

10.0

1.0

DEA4

5 582

6.7

0.7

DEA5

7 409

6.8

0.7

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WOMEN’S PARTICIPATION IN INVENTIVE ACTIVITY:
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NUTS2# Inventors 2010-2019

WIR 2010-2019

WIR ratio 2010-2019

DEB1

2 194

7.8

0.8

DEB2

529

6.2

0.6

DEB3

8 375

14.8

1.5

DEC0

1 653

11.5

1.2

DED2

3 903

10.6

1.1

DED4

1 756

7.9

0.8

DED5

1 127

14.4

1.4

DEE0

1 723

13.1

1.3

DEF0

4 462

11.2

1.1

DEG0

3 170

10.2

1.0

DK01

7 737

17.1

1.4

DK02

977

8.4

0.7

DK03

2 217

7.4

0.6

DK04

3 651

8.4

0.7

DK05

993

6.4

0.5

EE00

647

21.0

1.0

EL30

970

23.6

1.1

EL41

2

EL42

12

EL43

74

13.5

0.7

EL51

38

21.1

1.0

EL52

247

17.4

0.8

EL53

9

EL54

13

EL61

23

4.3

0.2

EL62

4

EL63

87

18.4

0.9

EL64

23

13.0

0.6

EL65

8

ES11

976

2.5

1.1

ES12

401

19.0

0.8

ES13

208

18.3

0.8

ES21

3 043

23.7

1.0

ES22

985

23.5

1.0

ES23

118

14.4

0.6

ES24

1 224

24.7

1.1

ES30

6 154

24.7

1.1

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WOMEN’S PARTICIPATION IN INVENTIVE ACTIVITY:
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NUTS2# Inventors 2010-2019

WIR 2010-2019

WIR ratio 2010-2019

ES41

680

21.0

0.9

ES42

272

16.5

0.7

ES43

63

17.5

0.8

ES51

8 602

22.8

1.0

ES52

2 317

21.1

0.9

ES53

191

29.8

1.3

ES61

2 326

23.9

1.0

ES62

453

17.9

0.8

ES64

2

ES70

178

16.3

0.7

FI19

3 649

8.2

0.7

FI1B

8 416

14.5

1.2

FI1C

2 250

13.0

1.1

FI1D

2 046

10.0

0.8

FI20

14

FR10

36 362

18.3

1.1

FR21

885

12.0

0.7

FR22

1 785

15.9

1.0

FR23

2 259

12.4

0.8

FR24

2 976

14.7

0.9

FR25

940

12.2

0.7

FR26

1 385

14.2

0.9

FR30

2 889

17.7

1.1

FR41

1 764

14.7

0.9

FR42

3 379

15.5

0.9

FR43

1 908

8.0

0.5

FR51

3 814

13.8

0.8

FR52

5 295

13.8

0.8

FR53

1 175

9.5

0.6

FR61

3 541

15.4

0.9

FR62

5 805

15.3

0.9

FR63

571

14.9

0.9

FR71

19 330

16.4

1.0

FR72

2 682

16.0

1.0

FR81

2 523

23.0

1.4

FR82

7 212

17.2

1.0

FR83

50

16.0

1.0

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WOMEN’S PARTICIPATION IN INVENTIVE ACTIVITY:
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NUTS2# Inventors 2010-2019

FRY1

14

FRY2

18

FRY3

6

FRY4

66

FRY5

2

HR03

WIR 2010-2019

WIR ratio 2010-2019

13.6

0.8

57

14.0

0.6

HR04

374

26.2

1.1

HU10

2 060

11.8

1.0

HU21

208

11.5

0.9

HU22

159

5.0

0.4

HU23

147

15.6

1.3

HU31

181

14.4

1.2

HU32

236

17.8

1.4

HU33

336

13.4

1.1

IE01

1 600

11.0

0.8

IE02

4 664

15.4

1.1

IS00

1

IS01

268

14.2

1.0

IS02

67

16.4

1.1

ITC1

5 535

14.1

1.0

ITC2

86

15.1

1.1

ITC3

1 485

15.4

1.1

ITC4

14 881

12.8

0.9

ITF1

659

17.9

1.3

ITF2

87

24.1

1.7

ITF3

1 376

23.4

1.7

ITF4

1 031

20.0

1.4

ITF5

80

17.5

1.2

ITF6

301

22.9

1.6

ITG1

818

19.7

1.4

ITG2

305

27.9

2.0

ITH1

539

4.3

0.3

ITH2

668

11.5

0.8

ITH3

5 389

10.0

0.7

ITH4

1 866

10.6

0.7

ITH5

7 527

13.1

0.9

ITI1

3 973

15.4

1.1

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WOMEN’S PARTICIPATION IN INVENTIVE ACTIVITY:
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NUTS2# Inventors 2010-2019

WIR 2010-2019

WIR ratio 2010-2019

ITI2

496

10.9

0.8

ITI3

1 176

11.8

0.8

ITI4

3 569

22.6

1.6

LI00

4

LT00

411

22.6

1.0

LU00

1 023

9.8

1.0

LV00

558

30.5

1.0

MC00

3

NL11

601

14.0

1.2

NL12

426

8.2

0.7

NL13

289

3.8

0.3

NL21

1 618

7.0

0.6

NL22

2 869

10.2

0.9

NL23

272

6.3

0.5

NL31

1 920

15.3

1.3

NL32

3 946

12.0

1.0

NL33

5 837

11.7

1.0

NL34

347

13.0

1.1

NL41

17 502

11.7

1.0

NL42

3 563

14.3

1.2

NO01

2 250

15.9

1.4

NO02

120

9.2

0.8

NO03

1 086

9.7

0.9

NO04

1 035

5.4

0.5

NO05

1 031

6.6

0.6

NO06

938

12.0

1.1

NO07

178

18.5

1.7

PL11

793

24.0

1.3

PL12

2 336

22.4

1.2

PL21

1 771

11.7

0.7

PL22

830

14.0

0.8

PL31

254

24.4

1.4

PL32

315

14.0

0.8

PL33

108

26.9

1.5

PL34

116

17.2

1.0

PL41

653

16.1

0.9

PL42

189

23.3

1.3

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WOMEN’S PARTICIPATION IN INVENTIVE ACTIVITY:
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NUTS2# Inventors 2010-2019

WIR 2010-2019

WIR ratio 2010-2019

PL43

199

2.5

0.1

PL51

944

16.9

0.9

PL52

134

9.0

0.5

PL61

259

18.1

1.0

PL62

114

22.8

1.3

PL63

649

23.3

1.3

PT11

1 764

28.9

1.1

PT15

59

23.7

0.9

PT16

762

22.2

0.8

PT17

932

24.9

0.9

PT18

172

34.9

1.3

PT20

31

12.9

0.5

PT30

9

RO11

154

17.5

1.0

RO12

149

13.4

0.8

RO21

159

22.6

1.3

RO22

24

12.5

0.7

RO31

78

15.4

0.9

RO32

411

25.1

1.4

RO41

57

12.3

0.7

RO42

358

11.5

0.6

SE11

7 959

12.3

1.0

SE12

4 112

11.7

1.0

SE21

1 297

5.6

0.5

SE22

5 313

12.6

1.0

SE23

6 133

14.3

1.2

SE31

1 280

9.5

0.8

SE32

394

11.9

1.0

SE33

717

10.5

0.9

SI03

775

17.2

1.0

SI04

1 222

17.5

1.0

SK01

269

13.4

1.1

SK02

338

12.1

1.0

SK03

132

9.8

0.8

SK04

167

9.6

0.8

TR10

3 423

19.6

1.1

TR21

220

7.7

0.4

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WOMEN’S PARTICIPATION IN INVENTIVE ACTIVITY:
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NUTS2# Inventors 2010-2019

WIR 2010-2019

WIR ratio 2010-2019

TR22

45

20.0

1.2

TR31

300

22.7

1.3

TR32

21

TR33

779

6.5

0.4

TR41

650

16.6

1.0

TR42

725

20.6

1.2

TR51

542

16.6

1.0

TR52

35

2.9

0.2

TR61

63

20.6

1.2

TR62

47

19.1

1.1

TR63

19

TR71

22

TR72

34

14.7

0.9

TR81

4

TR82

6

TR83

32

6.3

0.4

TR90

14

TRA1

33

6.1

0.4

TRA2

4

TRB1

35

34.3

2.0

TRB2

8

TRC1

23

0.0

0.0

TRC2

5

TRC3

2

UKC1

990

9.9

0.8

UKC2

1 054

14.1

1.2

UKD1

243

6.6

0.5

UKD3

1 335

10.7

0.9

UKD4

813

6.6

0.5

UKD6

1 217

12.1

1.0

UKD7

1 013

24.9

2.0

UKE1

716

20.0

1.6

UKE2

731

13.3

1.1

UKE3

671

7.7

0.6

UKE4

1 291

8.9

0.7

UKF1

3 070

9.1

0.7

UKF2

1 354

9.5

0.8

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NUTS2# Inventors 2010-2019

WIR 2010-2019

WIR ratio 2010-2019

UKF3

440

5.9

0.5

UKG1

1 522

6.3

0.5

UKG2

1 150

6.0

0.5

UKG3

1 839

8.6

0.7

UKH1

7 702

13.9

1.1

UKH2

3 120

15.6

1.3

UKH3

1 472

10.7

0.9

UKI3

6 223

14.2

1.2

UKI4

1 876

14.4

1.2

UKI5

402

8.7

0.7

UKI6

579

12.1

1.0

UKI7

1 396

13.8

1.1

UKJ1

13 232

17.4

1.4

UKJ2

5 531

7.8

0.6

UKJ3

2 775

7.4

0.6

UKJ4

975

8.4

0.7

UKK1

4 829

6.8

0.6

UKK2

695

4.5

0.4

UKK3

262

17.9

1.5

UKK4

506

7.9

0.6

UKL1

815

8.7

0.7

UKL2

1 230

14.7

1.2

UKM2

1 992

9.5

0.8

UKM3

766

13.3

1.1

UKM5

1 089

14.6

1.2

UKM6

237

10.5

0.9

UKN0

1 005

14.1

1.2

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Published and edited by
European Patent Office
MunichGermany© EPO 2022
Authors
Valentina Di Iasio (University of Southampton)
Francesco Lissoni (BSE, UMR CNRS 6060 – Université deBordeaux and ICRIOS – Bocconi University, Milan)
Ernest Miguelez (BSE, UMR CNRS 6060 – Université deBordeaux)
Gianluca Tarasconi (ipQuants AG)
Yann Ménière, Muzio Grilli, Ilja Rudyk (EPO)
DesignPD Communication (EPO)
The report can be downloaded from: epo.org/women-inventors

978-3-89605-309-1< Table of contents | Executive summary | Key findings | Content | Annex

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