An Analysis of the Innovative Activity of
Entrepreneurial and Young Firms in the UK∗
Mark Rogers
Harris Manchester College, University of Oxford and Aston University
Christian Helmers
Wolfson College, University of Oxford
PRELIMINARY - DO NOT CITE
This Version: June 2009

ABSTRACTThis paper provides an overview of a new database that uses intellectual property data to track
the innovative activity of firms in the UK. The paper looks at the extent and nature of patenting
activity, focusing on micro firms and SMEs. Over the period 2000 to 2007, SME patenting
has increased whereas large firm patenting has fallen and micro firm patenting has been roughly
constant. Most micro and SMEs patent while relatively young (aged ten or less) and this tendency is becoming more pronounced over time. The paper provides some preliminary analysis
on micro firms and SMEs that become high growth firms (defined as having greater than 20%
growth per annum). Overall, 28.0% of young micro and SMEs achieve high growth (over 2002
to 2007). In comparison, 29.4% of young micro or SMEs that patent achieve high growth. Thisdifference is much greater for firms in the high-tech industries.

KEYWORDS: Firm growth, intellectual property.
JEL Classification: L25, O12∗

We acknowledge financial support from the UK’s Business, Innovation and Skills Department.
Authors’ email addresses: christian.helmers@wolfson.ox.ac.uk and mark.rogers@hmc.ox.ac.uk

1Introduction

One of the most important aspects of modern economies is the generation of new, entrepreneurial firms, especially those that are pursing innovative activities. The ability
to generate and grow such firms is thought to be a major factor in raising productivity
levels and ensuring a sustainable future. While the importance of such firms is widely
accepted the evidence base on such firms is sparse. If measurement and quantification
are the prerequisites to analysis and understanding, the lack of data on such firms
suggests weak analysis and poor understanding. In particular, while survey and small
sample data do exist there is a paucity of large sample data. This paper reports on a
database containing the population of UK firms, as well as their intellectual property
in form of patents and trade marks, for the 2000 to 2007 period. This paper provides
some preliminary analysis of the data. The construction of such databases is part ofan OECD project entitled Analysis of the Innovative Activity of Entrepreneurial andYoung Firms that intends to foster database development across OECD member countries.
The basic components necessary for the construction of such an integrated database
are twofold. First, data on the creation of new firms must be available. In the UK,
Companies House contains details of all new (registered) companies, as well as all existing and active companies. For example, in 2001 around 162,000 new firms wereincorporated and there were around 2 million existing firms. Second, there needs to be
an indicator(s) of which firms are innovative and entrepreneurial.1 There is an argument that all new firms are innovative and/or entrepreneurial: the fact that they are
new suggests they are offering a new product or service, or offering an existing product or service to a new market. However, new firms contain a large number of firmsthat offer standard, existing products and services in different markets (e.g. ‘cafes andrestaurants’ and ‘business services’ such as web designers and consultants). Analysis
might want to distinguish these firms from those that offer more innovative products
and services. How should one define ‘more innovative’ ? A useful categorisation of
innovation is: new-to-firm, new-to-economy, and new-to-world. There is an interestin using intellectual property registrations as indicators of these categories. This paper focuses on patenting activity of firms. A new or young firm that makes a patentapplication considers it has a new to the world innovation.2 Another possibility is to
use trade mark data. A firm with a trade mark might be considered to have created a
new-to-the-economy innovation. These issues, along with a consideration of the benefits and drawbacks of intellectual property (IP) data, are discussed in more detail below.
1
Schumpter (1942, p.13) stated ‘The function of entrepreneurs is to reform or revolutionize thepattern of production by exploiting an invention, or more generally, an untried technological possibility
for producing a new commodity or producing an old one in a new way.’ This quote is taken from
Audretsch et al (2006, p.4) who discuss in more detail the issues of entrepreneurial and innovative firms.
Greenhalgh and Rogers (2009) also discuss the distinction between entrepreneurship and innovation.
2
To be specific: The firm files the patent application since it believes the invention to be new-toworld. The patent application relates to an invention, which may then be developed into an innovation.
The firm hopes that obtaining a patent will assist appropriability of the innovation. This new-to-theworld belief is confirmed if the patent is subsequently granted.

2

The end point of such database construction is to allow further insight into thecharacteristics and efficiency of the entire innovation process in modern economies. Although much is known about innovation in large and medium sized firms, there aremany gaps in our knowledge about smaller and newer firms. In the UK and elsewhere
there is strong interest in understanding why innovative firms are formed and how
such firms prosper. A closely linked issue is the creation of so-called high growth firms(sometimes classified into ‘gazelles’ or ‘gorillas’, see BERR (2008)). Quantification ofsuch innovative and high growth firms, including the analysis of trends at the economy level, is an important step in understanding the economy. This paper provides an
overview of new and young UK firms and their patent activity.
Section 2 describes the database creation and the nature of the IP data. Section
3 contains an overview of patenting in the UK with a specific focus on the differences
between micro, SME and large firms. Section 4 provides a preliminary discussion of
performance and patenting, with a focus on growth rates.

2

The Oxford Firm-level Intellectual Property Database

The data used for the analysis come from the Oxford Firm Level IP (OFLIP) database.
The database draws on the Financial Analysis Made Easy (FAME) data that cover theentire population of registered UK firms (FAME downloads data from Companies House
records).3 In this paper we use ‘firms’ to mean registered firms. Hence a firm refers to
the legal entity that organizes production, in contrast to census-type data that often
uses the plant or production unit. In addition, OFLIP contains data on the IP activity of firms in the form of patents and trade marks. OFLIP has been constructed bymatching the FAME database and a number of IP datasets.
The FAME database is a commercial database provided by Bureau van Dijk.4 To
construct the data base, two versions of the FAME database have been used: FAME
October 2005 and March 2009. The main motivation for using two different versionsof FAME is that FAME keeps details of ‘inactive’ firms (see below) for a period of four
years. If we used only the 2009 version of FAME, we would be unable to allocate IP toany firm that has exited the market before 2005, which could bias our matching results.
FAME contains basic information on all firms, such as name, registered address,
firm type and industry code. Availability of financial information varies substantiallyacross firms. In the UK, the smallest firms are legally required to report only very basic balance sheet information (shareholders’ funds and total assets). The largest firms
provide a much broader range of profit and loss information, as well as detailed balance
sheet data. In terms of numbers of firms, FAME October 2005 contains information
on around 3.1 million firms (of which 0.9 million are inactive). The FAME March 2009
data contain 3.8 million firms (of which 1 million are inactive). Inactive firms are thosethat have exited the market and belong to one of the following categories: dissolved,
3
4

See also data appendix B.
http://www.bvdep.com/en/FAME.html

3liquidated, entered receivership or declared non-trading.
In the analysis below firms are divided into size categories: micro, small andmedium-sized enterprises (SMEs) and large firms. The European Union defines firm
size categories using three criteria: employment, turnover and assets. Since total assets
are the most common financial variable in the FAME database, we primarily define firm
size according to assets. According to the EU, a SME must have total assets greaterthan Euro 2 million and less than or equal to Euro 43 million. A firm with assets below
Euro 2 million is classified as a micro firm, above Euro 43 million is classified as alarge firm. While this is the basic method of assigning firm size, we make adjustments
when employment data is available and, importantly, we also consider firms’ ownership
structure (for example, if a micro firm is owned by a large firm, it is reclassified aslarge).5
For this updated version of OFLIP, the IP data used for the construction of thedatabase comes from two different sources: the European Patent Office (EPO) PATSTAT database and Marquesa Ltd.6 Data on patent publications at the EPO, WorldIntellectual Property Organization (WIPO) and UK IP Office was downloaded fromPATSTAT version October 2008.7 OFLIP also contains trade mark data in the formof UK as well as Community trade marks, which are obtained from Marquesa Ltd.,
although these data are not used in this paper.
This paper focuses on patenting by UK firms over the period 2000 to 2007. The
three different types of patent publication are used since UK firms have a choice of
how to approach seeking patent protection. One method is to file an application at
the UK IP office, which is relatively cheap and would, if ultimately successful, provide
protection in the UK. Another option is to apply for the patent at the EPO. This is
more expensive, but the advantage is that it provides a clear route to seek subsequent
protection in member countries of the European Patent Convention (EPC) (currently
35). Another option is to ask WIPO to provide an initial examination and then publish
the patent, after which there is a procedure to ask for full examination in the (current)
139 countries that are members of the Patent Cooperation Treaty (PCT). Patents published through WIPO are referred to as PCTs.8 It can be argued that the choice of theUK, EPC and PCT routes depends on the firm’s expected value of the invention, since
the associated costs differ dramatically. However, there is relatively little empiricalevidence on this issue.
Which ever the route chosen, the initial stage of the patent system involves an application by a firm. At this stage the firm believes it has a new invention which may
be novel enough to be granted a patent. To be specific, in order to be granted a patent5

See data appendix E for a full discussion.
See Rogers, Helmers, and Greenhalgh (2007) for a description of the components of the previous
version of OFLIP.
7
See also data appendix C.
8
It is also possible that some UK firms may apply directly to the US PTO or other countries’ IP
offices. The OFLIP data currently does not contain such data.
6

4

three main criteria must be met: novelty (in the worldwide domain); it has to be asignificant inventive step (so must be non-obvious, even to experts in the field); and it
must be capable of industrial application. After an initial examination, the patent is‘published’ after approximately 18 months, which means it is made public.9
Only patent applications that have been published are visible and available to researchers (and others), hence these data can be used in studies such as this. Some ofthese publications will be granted. The time to grant varies, but the can take a numberof years. This delay is one reason why publication data are used, especially for the
analysis of smaller and start-up firms. Using the year in which the patent is granted
provides a lagging indicator of the innovative activities of the firm. It is the case, however, that many publications will not be granted. Does this represent a drawback ofusing patent publication data? In our view, for the analysis of smaller firms, it does
not: the use of patent publications is as an indicator of innovative activities. If thepatent is subsequently not granted, this may still imply that the invention was either
new-to-the-firm or new-to-the-market, hence it is still a potential indicator that thefirm is engaged in research and innovative activities.10

3

Overview of patenting in the UK

3.1

Summary statistics

Table 1 contains information on the numbers of patenting firms, the total number ofpatents, and the average number of patents per firm for the entire 2000 and 2007 period.
The columns of the table show the results for UK, EPC and PCT patent publications,while the rows indicate firm size. The top panel shows that around 4,150 large firms
published UK and EPC patents in the period (in fact 1,719 large firms had both UK and
EPC publications). Fewer large firms (3,292) published patents via the PCT system,
something which is true for all firm sizes. While the number of SMEs that publishedpatents is lower than for large firms, the numbers of micro firms is higher (e.g. 5,724
micro firms had a UK patent published). The second panel shows the total numbers ofpatent publications. Note that the total for large firms is much greater than SMEs or
micro firms separately, but that the combined SME and micro patents roughly equals
large firm activity. The final panel shows patents published per firm (i.e., the total
divided by number of firms). As might be expected, large firms have more patents withaverages above three, while SMEs and micro firms have averages below two.
9
This is the situation in the UK and EPO systems. The US system is different if the patentapplication only requests protection in the USA. The PCT system is similar to UK and EPC, althoughpublication occurs after 31 months. Also note that there is a possibility to request advanced publication(less than 18 months since the filing of the application) which is often used as a way of creating adefensive publication.
10
This simplified discussion abstracts from more complex patent filing strategies driven by strategic
motives. Strategic patenting activity may be more likely in larger firms, especially those in certain
industries. For example, see Hall and Ziedonis (2001) for large firms in the semi-conductor industry.
See also Guellec and Pottelsberghe (2007) and Granstrand (1999).

5

Table 1: Patenting activity
UK
EPC
PCT
Size
Number of Patentees
Large 4,151
4,153
3,292
SME
3,718
3,329
2,852
Micro 5,724
5,311
4,854
Number of Patents
Large 12,964 18,983
14,153
SME
6,370
8,748
5,786
Micro 8,100
9,652
8,567
Number of Patents per firm
Large
3.12
4.57
4.30
SME
1.71
2.63
2.03
Micro
1.42
1.82
1.76

Another general feature of patent data is that they are highly skewed (i.e., mostpatenting firms have only one or two patents and a few have much larger numbers).
The data for the UK are no exception. For example, of the 14,149 firms that had one ormore UK patents published over 2000 to 2007, only 154 (1.1%) had 15 or more patents
published in a year. In contrast, in 71% of cases when a firm patents in a given year it
only has one patent publication. This skewed distribution is also present for EPC andPCT publications, and also within firm size categories.
The above table shows patenting broken down by firm size. In some cases it was
not possible to allocate a firm to a firm size due to missing asset data. In particularin many of these cases the patent was published after the firm had become inactive(an inactive firm is dissolved, liquidated, in receivership or declared non-trading). Suchfirms account for around 2,500 patents (out of a total of around 96,000) over the 2000
to 2007 period. Possible reasons for this include: the firm is non-trading but owns
IPRs for tax or other reasons, failure by firms to update patent offices of dissolution,or failure to notify patent offices of takeovers or assignments. Further analysis would
be needed to understand the reasons for such cases; in particular, taking into accountof mergers and acquisitions among firms.

3.2

TrendsFor any economy, the trend in patenting activity is a closely watched indicator. The
rapid recent growth in patenting by China and South Korea, has attracted considerable
interest.11 In the cases of these and other countries, the rapid growth of patenting isseen as an indicator of innovation, technological sophistication and a leading indicatorof GDP growth and export success. In contrast, the rapid growth in patenting over11
The trends in patenting can relate to domestic or PCT applications, and also the numbers ofpatents filed at the US PTO. The basic data can be found in WIPO Patent Reports (e.g. 2007).
Reuters (2008), for example, predicted that China will overtake Japan in number of patents by 2012.

6

the last twenty years in the US has attracted much debate. Some commentators argue
that the rapid growth does not simply reflect innovation, but also strategic behaviour
by firms, which may in fact inhibit innovation. Jaffe and Lerner (2004) and Bessen
and Meurer (2008) argue strongly that the US patent system is ‘broken’ and reforms
are needed.12 In the UK, there is concern that firms do not patent as much as firms inother countries (see, for example, DTI, 2003) – and low patenting is interpreted as anindicator of relatively poor innovation.
Figure 1 shows the overall trend in patenting by summing the UK, EPC and PCT
patent publications to form a bar chart. Between 2000 and 2002, the chart shows anincrease in the total number of patent publications, but there is a subsequent dip in
2003 to 2006. The higher numbers in 2007 break with this trend, although the 2007
total is still just below 2002. Hence, these firm-level based patent data suggest littlechange in corporate patenting activity in the UK.

Figure 1: Number of patent publications, by year and type

UK Patents (pub)PCT Patents (pub)

2007

2006

2005

2004

2003

2002

2001

2000

0

No. of Publications
3,000 6,000 9,000

12,000Total patent publications (all firms)

EPO Patents (pub)A further, and related, issue concerns the trend in patenting for smaller firms. Oneof the issues mentioned in critiques of the patent system is that it does not allow smallerfirms to protect their inventions effectively. The argument is that larger firms may be
12For a concise review see Greenhalgh and Rogers (2009).

7much better able to afford the high costs (including litigation costs), as well using thepatent system strategically.13
The debate on these issues is on-going, but a key element missing in discussions is
the actual trends of large firm versus small firm patenting. The OFLIP data allows ananalysis of the differences across firm size. Figure 2 shows the total patenting activity by
year and across three different firm sizes: micro, SME and large. These size categories
are defined according to European Union definitions as discussed above. The figure
shows that total patent publications for SMEs have shown an increase over the years
2000 to 2007, with most of this growth coming from EPC and PCT publications. In
contrast, large firm patenting increases to 2002, then dipped, with the most recent year
2007 showing a recovery (again due to EPC and PCT publications). The trend for the
micro firms, in contrast, is roughly static.

20
000
20
001
20
002
20
003
20
004
20
005
20
006
20
007

20
000
20
001
20
002
20
003
20
004
20
005
20
006
20
007

20
000
20
001
20
002
20
003
20
004
20
005
20
006
20
007

0

No. o
of Publica
ations
2,000
4,000
6,000

Figure 2: Number of patent publications, by year and firm size

Large

SME

Micro

UK Patents (pub)PCT Patents (pub)EPO Patents (pub)Table 2 breaks down the patenting by micro and SMEs into different sectors (although it reports only the total number of patents, whether through the UK, EPC or
13

Weatherall, Webster and Bently (2009) review the available information on patent litigation costs
and conclude that the UK is significantly more expensive than any other European country.

8

PCT routes). In 2000, the highest levels of patenting by far were in manufacturing– the sum of high-tech, medium-tech and other manufacturing is 1,374 in 2000.14 By
2007, business services have 1,307 patent publications compared to the total of 1,445
in all manufacturing. If we compare the average patenting in 2000 and 2001, with theaverage for 2006 and 2007, the table shows a growth of 35.7%. Over the same period,
patenting in R&D services grew most rapidly (86%), compared to a 19% growth inhigh-tech and 10% growth in medium-tech. In general, it is not clear from these figures
whether the growth in patenting in R&D services reflects an outsourcing of R&D frommanufacturing as opposed to other sectors. In fact, if R&D is being contracted out tospecialist small firms it is not clear why patenting is increasing (as one might expect
the funding firm to own any IP created).

sectorTable 2: Micro and SME patenting activity, by sector
2000 2001 2002 2003 2004 2005 2006

2007

Agric./ Mining
High-techMedium-tech
Other Manufacturing
EGW, Constr.
Whole, Retail, Hotel
Transport, Telecom
Finance, Real Estate
ComputerR&D Services
Business Services
Health, Educ., Cult.

30
286
334
754
64
415
50
39
167
568
760
227

29
280
310
820
55
461
38
27
345
535
933
246

55
378
378
745
99
462
99
49
443
610
995
255

41
320
341
715
101
517
63
37
499
768
1,080
261

45
365
320
775
93
583
73
44
479
784
1,111
278

33
390
379
809
94
671
52
58
457
984
1,077
252

38
354
354
801
107
699
51
52
328
962
1,091
272

44
321
355
769
108
672
61
45
411
1,090
1,307
259

Total

3,694

4,079

4,568

4,743

4,950

5,256

5,109

5,442

3.3

When do new firms patent?

The question of when do firms use patents during their life time is not one that has
attracted much attention. For larger firms the assumption is that innovative firms use
patenting continuously, although there is a literature on how persistently large firms
innovate (see Geroski, Van Reenen and Walters, 1997). For smaller firms, and also for
new firms, it is interesting to understand when patenting occurred. Early application
implies an organised and strategic choice and that the patent is integral to the creationof the firm itself. It may even be that the patent is first filed (the priority date) before
14

High- and medium-tech are defined using OECD guidelines. High-tech industries are: pharmaceuticals SIC 2423; aircraft & spacecraft SIC 353; medical, precision & optimal instruments SIC 33;
radio, television & communication equipment SIC 32; and office, accounting & computing machinery
SIC 30. Medium-tech industries are: electrical machinery & apparatus SIC 31; motor vehicles, trailers& semi-trailers SIC 34; railroad & transport equipment SICs 352&359; chemical & chemical products
SIC 24 (excluding 2423); and machinery & equipment SIC 29.

9the incorporation date of the company.15 In such cases, any IP policies, such as freeconsultancy on IP, need to be targeted at scientists and entrepreneurs, rather thanexisting firms.

Figure 3: Age of firm when patent(s) published in 2007, by firm size

41+

36-40
3

31-35
3

26-30
2

21-25
2

16-20
1

11-15
1

3-5

6-10

-1

Firm age

0-2

41+

36-40
3

31-35
3

26-30
2

21-25
2

16-20
1

6-10

11-15
1

3-5

-1

0-2

Density
0 .05
5 .1 .15 .2 .25

SMEs

Density
0 .05
5 .1 .15 .2 .25

Large firms

Firm age

41
1+

36-4
40

31-3
35

26-3
30

21-2
25

20
16-2

11-15

6-10

3-5
3

0-2
0

-1

0

De
ensity.1.2.3

Micro firms

Firm age

Figure 3 shows three histograms of patentees (any route); one each for the large,
SME and micro firm size groups. These histograms refer to patents published in 2007
and the age of the firm in that year. Note that a few patents are published when the ageof the firm is ‘-1’ – i.e. in the year prior to when the firm was incorporated. Similarly,
many patents are published when the age of the firm is ‘0-2’, and since publication
is at least 18 months from application, this also indicates very early application. For
large firms it is clear that the age of firms that published patents in 2007 has a peakin the 6-10 year category but is distributed across the age range. SME’s show moreconcentration in the 3-5, 6-10 and 11-15 age ranges and, as might be expected, fewer
firms in the higher age ranges. This pattern is even more exaggerated for the microfirms.
The age distributions in the Figure are calculated only for the year 2007. The data
15
The data extracted from PATSTAT for this research does not, currently, contain priority date.
There is an application date, but this may not refer to the first filing date of a patent related to thepatent publication (i.e. the priority date).

10

also allow us to calculate the age distribution for each year between 2000 and 2007. Do
the data suggest that the age distribution of patentees have been changing? Overall,there is some evidence that the age of patentees has become younger. This is mostpronounced for micro firms. If we calculate the percentage of firms in the 0 to 10 yearsof age category, the average for 2000 and 2001 for micro firms was 58.2%, and thisincreased to 76.3% in 2006 and 2007. For SMEs the comparable percentages are 45.9%
and 50.0%. While for large firms the 2000 and 2001 average is 36.5% which grew to
42.3% (average of 2006 and 2007).

3.4

Technological diversity of patent portfolios

Each patent’s technology is classified according to International Patent Classification(IPC) index. The IPC is split into sections (letters A to H), then classes, sub-classes
and groups. For example, H refers to ‘electricity’, under this there are various classes(such as H01 ‘basic electric elements’). Underneath each class there are subclasses andgroups (for example, H01S ‘devices using stimulated emission’, and then H01S 3/00 is‘lasers’). Each patent can have a number of IPCs and, of course, each firm can havemore than one patent. This means that analysing IPC data can be a complex andlengthy task. This paper considers two summary measures. The first one is the main
IPC section on the published patent. In the case where the firm has one patent per
year, this is straightforward to calculate. When the firm has multiple patents in eachyear, the main IPC is the most commonly used. The second one is a measure of thediversity of the IPC’s in a firm’s patent portfolio.
Table 3 shows the percentages for each main IPC section for EPC patents applied
for over 2000 to 2007 by firm size. The table indicates that the most common IPCs
are G (Physics), A (Human Necessities), B (Performing Operations; Transporting) andC (Chemistry; Metallurgy). IPC D (Textiles; Paper) has very few patents (1.4% of
total) and class E (Fixed Constructions) has 6%. There are some differences between
firm sizes. Large firms are less active in sections A and G, but are more active in B
and F. Similar patterns exist across UK and PCT patents. Figure 5 shows how thefractions shown in the total column in Table 3 (Column 4) have changed over time (i.e.
for all firms). Figure 6 shows the same fractions but this time for only micro firms andSMEs. There is relatively little change occurring over the 2000 to 2007 period. The
one exception is that IPC A (Human Necessities) has been increasing its share.
The second measure provides a summary measure of the diversity of a firm’s patentportfolio. The results are presented in Table 4 and Appendix F discusses the methodof calculating the diversity measure. The minimum value for the index is one whichindicates that a firm has indicated only a single IPC section whereas the maximum
is eight, in which case a firm patents in all IPC sections equally. Table 4 suggeststhat the largest share of firms (around 60%) across all size categories patents only
within a single IPC section. Large firms appear to be technologically more diversified,as the share of firms with patents in only a single IPC section is 50%, whereas for
micro firms and SMEs the share is close to 70%. However, given that IPC sections are
relatively broad technological areas, this does not necessarily imply that these firms
11Table 3: IPC main category, by firm size
Large SME
(1)
(2)
A Human Necessities
13.73 18.14
B Performing Operations; Transporting
16.59 16.85
C Chemistry; Metallurgy
14.78 13.73
D Textiles; Paper
2.00
1.17
E Fixed Constructions
6.74
5.86
F Mechanical Engineering; Lighting; Heating 11.46 8.77
G Physics
17.48 19.8
H Electricity
17.22 15.68
Total
100
100

Micro
(3)
19.34
14.22
13.12
1.07
5.50
8.06
24.61
14.08
100

Total
(4)
17.2
15.67
13.82
1.40
6.00
9.35
21.04
15.52
100

are not technologically diversified. A more disaggregated analysis would be required toinvestigate further the degree of technological diversification of these firms.
Table 4: Diversity measure, EPC in 2007, by firm size
diversity d Large SME Micro Total
d=1
578
434
562
1,574
1 <d <2
385
153
181
719
2 <d <3
161
40
47
248
3 <d <440
4953
4 <d <52
3
3
8
5 <d <6
1
1
Total
1,166
634
803
2,603

3.5

Foreign ownership

The FAME database has an indicator for whether the firm is ultimately controlled bya foreign firm. The UK has experienced substantial inward foreign direct investment,
and also has high levels of R&D funded from overseas, hence there is an interest in
isolating patenting from foreign controlled firms. Also, since there is no informationon the size of the foreign owner, some of the micro firms and SMEs reported on above
will include those owned by large foreign firms. As Table 5 shows the numbers of micro
and SME patents by foreign owned firm is significant. Again, in this table the patents
are the sum of UK, EPC and PCT publications. In 2001/2002 the share of foreign
patents was 22%, rising to 25% in 2004, but falling to 16% in 2007. Hence over theentire period there is a declining share of foreign patent activity relative to domestic
firms.

12

Table 5: Patenting and foreign ownership, micro and SME only
2000 2001 2002 2003 2004 2005 2006 2007

4

Domestic
Foreign owned

3,051
643

3,306
773

3,735
833

3,869
874

3,956
994

4,333
923

4,408
701

4,680
762

Total

3,694

4,079

4,568

4,743

4,950

5,256

5,109

5,442

Performance and patenting in smaller firms

The traditional rationale for awarding patents is to provide protection so as to allow afirm to appropriate the returns from innovation. At the most basic level, greater appropriability should ensure survival, as it prevents imitators stealing the firm’s market.
More generally, greater appropriability should allow faster growth and subsequently
higher profits. There is substantial evidence that larger firms gain from patenting (e.g.
Hall, 1993), however, the evidence base for smaller firms is much more limited.
Previous analysis using the earlier version of OFLIP has revealed a number of results. Rogers et al. (2007) provided a preliminary analysis of patenting and performancefor the cohort of 130,000 SMEs active in 2001. This preliminary analysis found two
main findings of relevance here. First, SME patenting appeared to increase survival,
although the relationship was not statistically significant. Second, the growth rates
and profitability of patentees appeared to become ‘polarised’ (i.e. patentees were overrepresented in both the lowest performing and highest performing groups). One reason
why this analysis was preliminary was that the data on performance only extended to2004 (relatively soon after the patent was published in 2001). A longer time period
would be necessary to assess whether the polarisation was temporary. Another reason
was that the large heterogeneity across SMEs is likely to affect results.
Responding to the second reason, Helmers and Rogers (2008, 2009) have tested
the effects of patenting on new firms. Helmers and Rogers (2008) takes the cohortof all 162,000 firms incorporated in 2001 and analyses their survival over the subsequent five years. The paper uses both patent dummy variables and counts (for UK
or EPC publications), as well as trade mark dummy variables and counts, to test theassociation between IP activity and survival. The basic statistics show that IP active
firms are much more likely to survive. By 2005, around 80% of IP active firms survive
compared to 60% of non-IP active. Helmers and Rogers then proceed to use a Cox proportional hazard model to assess the robustness of these associations to other factors.
Their analysis controls for industry characteristics (such as growth and capital intensity), ownership (including whether foreign owned), number of directors, proximity touniversity, as well as geographical effects (regional development agency dummies, unemployment and house prices). Even when controlling for all these factors, the positive
association of patenting with survival comes through: having one or more UK or EPC
patents is associated with a reduction of hazard rate by around 40%.

13

The strong, positive associations between patenting and survival found by Helmers
and Rogers (2008) are consistent with the view that the patent system is providing some
protection against imitation. However, it is clear that uncovering any causal relationship is much more difficult. Patenting firms may have better ideas than non-patenting
firms and it may be ‘quality’ of the idea that is generating the association. In addition,some industries and sectors in the economy have much lower opportunities to patent.
In order to investigate these issues Helmers and Rogers (2009) focus on new firms in
the high and medium technology industries. They argue that all these new firms havethe potential to apply for a patent, but some choose not to for reasons of secrecy, costor they believe that the patent system is ineffective. The analysis covers all the 7,638
high- and medium-tech firms incorporated in 2000 and their patenting activity over theperiod 1999 to 2001.16 They then analyse the association between this patenting andperformance over the 2001 to 2005 period. This methodology is intended to test the link
between patenting and performance more closely. The results show that, as expected,
there is a strong positive effect of patenting and survival. Furthermore, patenting appears to raise subsequent growth rates (where growth is measured by growth in assets
2001 to 2005). The estimates suggest that patentees grow between 6% and 17% perannum faster than non-patentees.
The next section provides an overview of the growth rates of micro and SMEs in
the updated OFLIP data for 2000 to 2007. This analysis adds to our knowledge ofpatenting and performance as shown in Rogers et al. (2007) for two reasons. First,
the previous analysis was limited to performance to 2004 whereas now the data allow
analysis to 2007. Second, the finding in Rogers et al. (2007) that performance could
be polarised is explored in more detail.

4.1

High growth firms

In order to analyse high growth firms we take the cohort of firms aged ten or less in2002 and calculate their annual average growth in assets between 2002 and 2007. Usinga five-year period, rather than a three-year period, is deliberate. In some previous analysis of patentees it was found that performance in the three year period after patenting
was relatively weak in comparison to a control group. One possibility is that a young,small firm that publishes a patent is in the process of a setting up a new business which
may take longer than three years to show results. Hence, in the analysis below weassess growth over five years (2002 to 2007). The analysis looks at patenting over theperiod 2000, 2001 and 2002. Note that these years correspond to the year in which thepatent was published, not granted. Growth in assets is used since this is the variable
that has maximum coverage in the database (since small UK firms need only report
total assets and total shareholder funds).
In order to calculate growth over the period 2002 to 2007 the firm must have total
asset data in each year. This means that the analysis is conditioned on surviving firms.
16

Helmers and Rogers also take account of the fact that some firms have patents published prior toincorporation in the personal names of their directors.

14

There are 266,928 micro and SME firms, aged between 0 and 10, which survived overthe period 2002 to 2007 and have total asset data in both years.17 Of these, 1,158
had a patent published in the 2000 to 2002 period or 0.4%. This percentage does varyby sector and industry, for example in the high-tech industries the percentage is 5.5%.
There is a concern that foreign owned micro firms or SMEs are governed by different
growth dynamics, hence in the analysis below we exclude the 13,638 foreign owned
firms. This leaves 253,290 domestic owned firms in our ‘growth’ sample. Table 6 shows
the numbers of patentees by sector for the micro firms and SMEs represented in thisgrowth sample. Overall, there are 1,033 patentees in the sample. The table shows thenumbers of firms that patent via the UK, EPC and PCT routes (since firms do patent
through multiple routes the first three columns do not sum to the last column).

Table 6: Numbers of micro firms and SMEs patenting, in growth sample
UK patentees EPC patentees PCT patentees Total
Agric. / Mining
10
7
10
17
High-tech
38
30
30
62
Medium-tech
49
30
27
74
Other Manufacturing
116
80
71
186
EGW, Constr.
20
8
11
30
Whole, Retail, Hotel
40
35
28
72
Transport, Telecom
5047Finance, Real Estate85312Computer
53
35
45
87
R&D Services
53
92
89
139
Business Services
142
121
155
280
Health, Educ., Cult.
39
27
37
67
Total
573
470
510
1,033
A first issue to understand is that the distribution of annual growth rates for smallerfirms are highly skewed. The lowest growth rate in the cohort is -19.99 percent (i.e. assets approached zero in 2007), whereas the highest growth rate is over a billion percent.
The 99th percentile of the growth distribution is 817% per annum. The massive differences in growth rates means that standard regression analysis may be misleading.18
Figure 4 shows histograms of the growth distribution of patentees and non-patentees.
The plots only show firms with average annual growth rates of below 160% (which is justbelow the 95th percentile of the distribution). A comparison between them indicatesthat more of the patentees’ distribution is below zero, but it may also be that slightly
more patentees have higher growth rates. Even this basic, unconditional evidence sug17
The derivation of this 266,928 is as follows. There are 1,313,103 firms in the database in 2002
reporting total asset data; of these 887,292 are aged between 0 and 10. Removing large firms and thosewith missing SIC codes reduces this number to 675,452. Removing firms with total assets equal to zeroleaves 571,939 firms; and of these 266,928 survived and report total asset data in 2007 (47%). This
is not an accurate survival rate since many of the firms may have missing asset data due to late, orincomplete, filing of information.
18
See Helmers (2009) for an application of quantile regressions in this context.

15

gests that any association between patenting and performance may be complex.

Figure 4: Distribution of annual growth rates (2002-2007)

0DensityD
1
2

3

Patentees

-.2
2

0

.2
2

.4
4
.6
6
.8
8
1
Av. annual growth assets 2002-7

12
1.2

14
1.4

16
1.6

1.2

1.4

1.6

0

Density123

Non-patentees

-.2

0

.2

.4
.6
.8
1
Av. annual growth assets 2002-7

To provide another overview of the differences in growth rates, firms are divided
into three groups: those which experienced negative growth, those with growth between 0% and 20%, and those with growth above 20% per annum. The latter category
is generally considered ‘high growth’ (see BERR, 2008). Table 7 shows a cross tabulation of these groups and patenting. The patentees are over-represented in the negative
growth group, which reflects Figure 4, but are under represented in the middle group.
Both patentees and non-patentees have around 28% of firms in the high growth group.19
As might be expected, the pattern of results shown in Table 7 does vary between
sectors. In many sectors the pattern is over-representation in the high growth groupbut also in the low growth group. Although this polarisation result is common in mostcases the results are not statistically significant (using a Chi-squared test and 0.1 Pvalue). The two exceptions are ‘agriculture and mining’ (with only 17 patentees) and‘high-tech’. The results for high-tech are shown in Table 8. This shows that patentees
perform better that non-patentees with 40% of the 62 patentees being in the high growthgroup. Since patents might be expected to be of most help in these high-tech industries,
19

A Chi-squared test on whether the differences in the table are significant has a P-value of 0.004.

16

Table 7: Micro and SMEs asset growth 2002-2007, domestic owned, by groups
Average annual growth Patentees Non-patentees
Total
Negative growth468
106,017
106,485
45.3
42.03
42.04
0 <Growth <20261
75,58975,850
25.27
29.97
29.95
> 20 Growth304
70,651
70,955
29.43
28.01
28.01
Total
1,033
252,257
253,290

this might be expected. However, in the medium-tech sector patentees do worse than
non-patentees (only 22% are in high growth group compared to 25%). Similarly, ‘othermanufacturing’ patentees perform slightly worse. Nevertheless, it is important to stressthat these results point out only associations in the data and certainly do not imply
any causal relationships.
Table 8: High-tech micro and SMEs asset growth 2002-2007, domestic owned, by groups
Average annual growth Patentees Non-patentees Total
Negative Growth
22
537
559
35.48
43.59
43.2
0 <Growth <20
15
374
389
24.19
30.36
30.06
> 20 Growth
25
321
346
40.32
26.06
26.74
Total
62
1,232
1,294
100
100
100

5

Cohort analysis

A drawback of the previous analysis is that it focusses on a firm as the unit of analysis.
This might appear to be entirely justified, but when studying innovation or patenting
in the context of young and entrepreneurial firms, this may not be the case. Consider
the dynamics of an entrepreneurial economy. Many new ideas are generated by entrepreneurs and scientists, some of these are the basis for starting firms and a (small)
proportion of these firms survive until age ten. Of those that survive, some experience
mediocre growth while some experience good growth. The impact on employment and
GDP depends, of course, on the rate of growth. A very small number experience suchrapid and sustained growth that they become very large companies; and these havea massive impact on employment and GDP. Sometimes such firms are referred to as‘gorillas’. Economists and policymakers are particularly keen to make sure that these‘gorillas’ survive and prosper.

17

In the current context, we are interested in whether the patent system helps thecreation of such firms. Let us take an example to illustrate the issue. Suppose thepatent system plays a positive role in the creation of 100 innovative firms (who subsequently publish a patent). If 50 of these firms fail within five years, and if this is
the same rate as non-patentees, we might (wrongly) assume the patent system has
little effect.20 However, it may be that patenting firms are attempting to dramaticallychange the technology frontier (i.e. undertake radical innovation) and, in such cases,
many attempts fail. Of the surviving 50 firms suppose that 49 experience low growth:
their (expected) radical innovation is, in fact, incremental or a failure. However, oneof the patentees succeeds and ultimately becomes a very large company, creating thousands of jobs and adding significantly to GDP. What would economic analysis find in
this situation? Survival analysis finds no strong results for patentees. Growth analysis
would show one high growth firm, but 49 firms with low growth. Standard regression
analysis in this context is problematic since it normally starts by giving every firm equal
weight in the analysis. In fact, some regression models omit or give less importance
to extreme values (i.e. the high growth firm). Is this ‘1 in a 100’ scenario likely? In
short we do not know, but there is an existing literature on the highly skewed value
for patents (e.g. Schankerman and Pakes, 1986), which suggests there is some relevance.
One possibility to start an investigation into these issues is to use cohort analysis. In essence we are interested in the performance of the cohort of patentees vs.
non-patentees. These cohorts are defined by sector and age, so as to improve comparability.21 As above, the patentee cohort is made up of any domestic SME or micro firmthat published a patent in the 2000 to 2002 period. For each cohort we also calculate
the growth in total assets over the period 2002 to 2007. Using total assets of the entire
cohort means that even if a single firm grows very large this is reflected in the cohort
growth rate. Table 9 shows the cohort growth rates, for patentees and non-patentees,
broken down by age group and sector. In only a few cases does the patentee cohort out
perform the non-patentee cohort. Out of the 36 sector-age groups, in only 11 cases does
the patentee cohort outperform the the non-patentee cohort. In the high-tech sector itis only the patentees aged between 3 and 5 that out perform non-patentees (14.1% perannum compared to 5.6%). For the medium-tech sector the two older age groups ofpatentees out perform non-patentees, but for ‘other manufacturing’ none of the patentee cohorts performs better than non-patentees. The only sector where patentees dobetter across all age bands is ‘health, education, etc’.
These results suggest that, on average, the cohort of patentees do not generatesignificantly higher asset growth than non-patentees. The most basic conclusion fromthis is that patenting is not a simple way to generate high growth firms. However, it isclear that a variety of other issues and explanations may be at work. At an analyticallevel it would be interesting to refine the comparison cohort for the patentees, perhaps
using a matching estimator to control for other characteristics of the firms. Equally, it
20

Although our previous analysis suggests that patenting does help new firms to survive, there ismore mixed evidence for older firms
21
There could, of course, be further analysis to refine comparability of the cohorts, such as matching
estimators; something we leave as a possibility for future work18

would be interesting to look at group in turnover. Should the results remain robust tothese changes, there are a number of possible explanations for such findings, such as:• Patenting does not act as an indicator of the highest growth potential firms.
Secrecy and first-mover strategies, which are often highlighted in survey findings,
are more important.
• The patent system is failing to provide adequate protection against imitation,
perhaps because smaller firms cannot afford to enforce their property rights.
• Related to the previous point, the high growth potential firms may be taken overby larger firms, hence they do not show up in our data.
• The patent system is also supposed to act as a signal to financiers, hence allowing
high growth potential firms to obtain finance. This ‘signalling’ role may not beworking effectively.
• The use of patent publications, rather than grants, may hide a more significant
relationship.
These issues, of course, also relate to the analysis in the previous section and any
analysis of the performance of innovative firms.

6

Conclusion

This paper has provided an overview of the data in the latest version of the OFLIP
database. In particular, the paper has focused on patenting as an indicator of innovative and entrepreneurial firms. Focusing on micro firms and SMEs the data show thatpatenting activity has increased over the 2000 to 2007 period, although this has primarily been driven by SME activity. Despite this growth, patenting is very rare: onlyaround 0.4% of young micro firms and SMEs patent (although this share is much higher
in some sectors, e.g. 5% in high-tech sector). The analysis also finds that patenting
firms are increasingly using the EPC and PCT systems (although patenting throughthe domestic UK IP office is not falling for micro firms and SMEs in absolute terms).
The last sections of this paper are an analysis and discussion of the relationshipbetween patenting and performance. Previous research has established that patenting,and also trade marking, has a strong association with survival in newly incorporated
firms (i.e. start-ups). In addition, when focusing solely on start-ups in high-techindustries there is evidence that both survival and growth (in total assets) are improved.
However, there is little evidence for young firms in general (i.e. not just start-ups).
The previous section also outlined a number of implications and suggestions for further
analysis. If the ‘1 in 100’ story is indeed empirically relevant, a single high-growthfirm may compensate for many unsuccessful firms. However, this may imply that on
average, there will be little correlation between patenting and firm growth. Hence,the standard conditional mean estimators employed ubiquitously in the literature, willfind little correlation between patenting and firm growth. Yet, it is important not
19

to confound the lack of statistical significance for correlation between patenting andgrowth with economic significance since a single patentee succeeding may have a huge
impact on the overall economy despite the failure of a large number of other patentees.
Another issue deserving more analysis is the way in which patents serve micro firms
and SMEs. Our findings suggest some positive correlation between patenting and firm
performance, but this leaves unclear the possible channels through which patents assist
firms in succeeding relative to non-patenting firms. Future analysis should aim toinvestigate these channels and move beyond broad associations in the data.

20

References[1] Audretsch, D. B., M. C. Keilbach and E. E. Lehmann (2006). Entrepreneurship andEconomic Growth. Oxford, Oxford University Press.
[2] BERR (Department for Business Enterprise and Regulatory Reform) (2008). ‘High
Growth Firms in the UK: Lessons from an Analysis of Compartive UK Performance’.
BERR Economics Paper No. 3.
[3] Bessen, J. and M. Meurer (2008). Patent Failure. Princeton, Princeton University
Press.
[4] DTI (Department of Trade and Industry) (2003) ‘UK productivity
and competitiveness indicators 2003’. DTI Economics Paper No. 6,
http://www.dtistats.net/competitiveness5/.
[5] Geroski, P., J. Van Reenen and C. Walters (1997). ‘How Persistently Do Firms
Innovate?’ Research Policy 26: 33-48.
[6] Greenhalgh, C. and M. Rogers (2009). Innovation, Intellectual Property and Economic Growth. Princeton, Princeton University Press.
[7] Guellec, D. and B. van de la Pottelsberghe (2007). The Economics of the European
Patent System. Oxford, Oxford University Press.
[8] Granstrand, O. (1999). The Economics and Management of Intellectual Property:
Towards Intellectual Capitalism. Cheltenham, UK, Edward Elgar.
[9] Helmers C. (2009): ‘Patents, Spillovers and Firm Performance - Evidence from UK
Start-Up’, mimeo, Department of Economics, Oxford University.
[10] Helmers C. and Rogers M. (2008): ‘Innovation and the Survival of New Firms
Across British Regions’, Department of Economics Disucssion Paper Number 416,
Oxford University.
[11] Helmers, C. and M. Rogers (2009). ‘Does Patenting Help High-Tech Start-Ups?’
IPRIA Working Paper No. 6, http://www.ipria.org/publications/wp/wp2009.cfm.
[12] Hall B. (1993): ‘The Stock Market’s Valuation of R&D Investment During the
1980’s’, American Economic Review, Vol. 83, No. 2, Papers and Proceedings, pp.
259-264.
[13] Jaffe, A. (1986). ‘Technological Opportunity and Spillovers of R&D: Evidence fromFirms’ Patents, Profits and Market Value.’ American Economic Review vol. 76(5):984-1001.
[14] Jaffe, A. and J. Lerner (2004). Innovation and Its Discontents : How Our Broken
Patent System Is Endangering Innovation and Progress, and What to Do About It.
Princeton University Press.
[15] Reuters (2008). ‘China on Path to Lead World in New Patents’. Wed Dec 10, 2008.
21

[16] Schankerman, M. and A. Pakes (1986). ‘Estimates of the Value of Patent Rights
in European Countries During the Post-1950 Period.’ Economic Journal 96: 10521076.
[17] Schumpeter, J. (1942). Capitalism, Socialism, and Democracy, Harper, New York.
[18] Weatherall K., Webster E. and Bently L. (2009): ‘IP Enforcement in the UK and
Beyond: A Literature Review’, SABIP Report Number EC001.
[19] WIPO (2007). ‘Wipo Patent Report: Statistics on Worldwide Patent Activity’,
http://www.wipo.int/ipstats/en/statistics/patents/.

22

0

.05

.1

.15
5

.2

.25

Figure 5: Fraction of IPCs, by year

2000

2001

2002

2003
A
C
E
G

23

2004

2005
B
D
F
H

2006

2007

0

.05

.1

.15

.2

.25

Figure 6: Fraction of IPCs, SMEs and micro firms only, by year

2000

2001

2002

2003
A
C
E
G

24

2004

2005
B
D
F
H

2006

2007

A

Data Appendix

B

FAME

Firm-level financial data as well as information on other firm characteristics, such as location and age, are obtained from the Financial Analysis Made Easy (FAME) database.
We use two versions of FAME. In the October 2005 edition of FAME, there are around2.19 million ‘active’ firms, or companies, in the database (the words ‘firm’, ‘company’and ‘enterprise’ are used as synonyms henceforth). In the March 2009 version, there are
2.79 million ‘active’ firms. All of these firms have basic information, such as name, registered address, directors and registered number. For firms that have filed a set of annual
accounts there is also some financial data available. The extent of this financial data
varies substantially across firms, as the smallest firms legally need only report very basicbalance sheet data (namely shareholders’ funds and total assets). The largest firms provide a wide range of Profit and Loss information as well as detailed balance sheet data.
The FAME data also lists ‘inactive’ limited companies (there are around 0.9 million in
the October 2005 version and 1 million in the March 2009 version). ‘Inactive’ refers tofirms that have been dissolved, liquidated, entered receivership or declared non-trading.

C

Patent Data

The patent data used in the research comes from the European Patent Office (EPO)
Worldwide Patent Statistical Database (PATSTAT) version September 2008. We extract three types of patents, UK, EPC and PCT patents from PATSTAT. PATSTAT
combines patent information from several sources: DocDB (the EPO master bibliographic database containing abstracts and citations), PRS (the patent register for legaldata), EPASYS (the database for EP patent grant procedure data), and the EPO
patent register as well as the USPTO patent database for names and addresses of applicants and inventors. The main advantage of PATSTAT over other data sources suchas the EPO ESPACE Bulletin is its broader coverage. Importantly, it also includes
information on PCT patent applications while for example the ESPACE Bulletin doesnot.

D

Matching FAME and PATSTATThe basic method of matching was to use the company name from FAME and theapplicant name from patent data. Both a firm’s current and previous name(s) wereused for matching accounting for changes of the name of firms. Since patent records
do not include the registered number of the company it was not possible to match on
this; instead the data was matched on applicant names in the patent documents andfirm names in FAME. Matching on the basis of company name requires names to be‘standardized’ in both data sets prior to analysis (e.g. the removal of capitals andstandardized of Limited to Ltd, etc).

25

To gauge the outcome of the matching procedure requires comparison of the data
to external sources. This is difficult since there have been no comparable matches ofpatents to UK firms. Nevertheless, some insight can be gained from looking at official
data on all patenting activity. Table 10 summarizes the matches and also some official
sources for the year 2003. The official sources count all patents from UK residents,
whether corporate or personal, hence one would expect them to be greater. The official
figure for EPC patents is particularly problematic as it also contains inventors whichbiases the number upwards. Unfortunately no more accurate figure on patent publications could be obtained from the EPO. Equally, the FAME database only contains
registered firms and there are a large number of unregistered businesses in Britain.
As can be seen from the table, the number of patent publications matched is around
62 percent for UK patents and 70 percent for EPC patents. However, due to the inflated
official number for EPC patents, the relevant matching success for EPC patents iscertainly higher than 60 percent. Imperfect matches should be expected also as patents
may be held under the names of the company directors which is particularly relevant
for smaller firms (perhaps because directors filed for a patent before registering thecompany). Matching firms’ names as provided by FAME with applicant names in
PATSTAT is complicated also because names appear to have undergone some minortransformations (possibly ‘standardizations’) in PATSTAT. There are, for example,
terms that appear in FAME within brackets, e.g. ‘(uk)’, which are missing in PATSTAT
while all remaining parts of the names are identical in FAME and PATSTAT. If there
are other such systematic differences in names between the two data bases, it is not
surprising that the match for UK patents is lower than the match.

E

Defining firm size categories

The European Union defines SMEs using three criteria: employment, turnover andassets. Since total assets are the most common financial variable in the FAME database,
we define an initial firm size groups using this variable. According to the EU, an SME
must have total assets greater than Euro 2 million and less than or equal to Euro 43
million. A firm with assets below Euro 2 million is classified as a micro firm, above Euro
43 million is classified as a large firm. Sterling is converted to Euros at the rate of 0.675,
which is the average exchange rate over the 2000 to 2008 period. We then consider firmsthat have employment data (only around 3% of FAME firms report employment). Any
firm that has employment greater than or equal to 250 is reclassified as a large firm.
Next we consider firms that are subsidiaries of other firms. The FAME data contains a variable for the ‘ultimate holding company’ of any subsidiary (this is based onlast available accounts). If a micro or SME is wholly-owned by a ’large’ firm, the firm
is reclassified as a ‘large’ firm. Similarly, any micro firm wholly owned by an SME is
reclassified as an SME. In situations where a firm is owned by two or more different
sized holding firms, we reclassify it into the largest holding firm size group. Reclassifying firms according to the size of their holding company is only possible if we havethe data on holding company size. For UK holding companies, FAME has this information. However, in the case of foreign owned firms there is no data on the size of theholding company. FAME provides only limited information on the nature of foreign

26

holding companies (for example in over 80% of cases there is no information on sizeof shareholding). This presents a problem since excluding foreign owned SMEs could
remove many majority owned UK firms; however, in some cases - such as being owned
by Ford or Toshiba - it is important to know. Given this, in the analysis we do isolate
foreign-owned SME firms at certain points.
Finally, we make an adjustment for the fact that the FAME March 2009 database
does not have 2007 accounting data for a small number of firms (due to delays in filingfinancial accounts). This means, for example, that an SME in 2006 could have missing
asset and employment data in 2007, hence would be classified as a micro firm. In
general, when a firm has missing asset data it is classified as a micro firm. To avoid
this we classify such firms as the same category as the previous year (e.g. if the firm
was an SME in 2006, and has missing accounting data in 2007, it is classified as an
SME in 2007).

F

Technological diversity metrics

Drawing on the work of Jaffe (1986), we can define a vector representing the technological diversity of a patent portfolio held by a firm. Note that each patent has anumber of different classifications, meaning that even a firm with one patent may havea technological diversity. Define
Fi = (fi1 , fi2 , ..., fiK )(1)

where Fi is the percentage of firm i’s patents in patent classification k. The patentclassification is at the section level (e.g. A). The technological diversity of the firm’s
patent portfolio is now defined as
DIVi = (Fi0 Fi )−1(2)

For example, if a firm has one patent in only one IPC class, its DIV = 1. If thefirm’s single patent had two IPC classifications then DIV = 2. As the number of IPC
classifications increases as a result of either more patents or more IPCs per patent, thediversification measure increases. In our analysis we use IPC’s A to H, hence a firm
which has maximal diversity will have a share of 0.125 in each classification. This will
mean that the maximal value of the diversity measure is eight.

27

28

Table 9: Micro and SMEs growth 2002-2007, by cohorts
Patentees
Non-patentees
age 0 to 2 age 3 to 5 age 6 to 10
age 0 to 2
age 3 to 5
Agric. Mining
297.2
-8.4
21.9
6836.813.2
High tech
24.8
13.8
4.5
26.0
4.1
Medium tech
-0.3
14.1
6.3
7.4
5.6
Other Manufacturing
17.4
1.1
5.3
23.1
6.7
EGW, constr.
-10.8
-1.6
8.8
26.4
23.7
Whole,retail,hotel
8.0
4.6
5.9
16.3
11.3
Transport, telecom
19.5
-3.0
14.5
25.6
11.6
Finance, Real estate
29.4
33.9
9.8
23.7
16.2
Computer
-5.0
9.7
2.3
20.0
15.9
R&D services
52.1
4.6
1.9
98.3
48.6
Bus. services
14.9
85.5
14.8
29.3
15.9
Health,educ,cult,nie
51.3
106.2
18.8
27.7
12.1
Total
21.6
29.2
6.4
114.8
14.5

age 6 to 10
8.9
14.3
3.0
11.0
13.5
8.6
7.5
13.3
36.3
6.4
51.5
9.9
18.2

Table 10: Benchmarking the matching outcome

UKIP - UK patents
EPC - European patents

Official
Data
5,708
6,786

Matched
Data
3,555
4,793

Percentage
(%)
62.3
70.6

Notes:The number for ‘Official data’ for British-based applications published arefrom UKIP Office Facts and Figures 2004/5.
The EPC figure is obtained from PATSTAT.

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