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IP and SMEs: Australian Evidence

Dr. Paul H. JensenUniversity of Melbourne

WIPO Expert Panel on IP and SMEs,Geneva, 17-18th September 2009

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I will cover two recent research projects which have analysed the use and effectiveness of IP by Australian firms

1. Factors Affecting the Use of Intellectual Property Protection by SMEs in Australia (Jensen & Webster 2006)

2. IP, Technological Conditions and New Firm Survival (Jensen et al. 2008; 2010)

OVERVIEW

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OBJECTIVES

The Australian Govt. commissioned IPRIA:“…to determine whether the level of intellectual property protection by Australian SMEs is at sub-optimal levels, and the reasons for this...”

There are 3 key components to the study:– How does the existing level of IPR protection by

SMEs compare with that of large companies?– What is the optimal level of IPR use? If there are

differences in IPR use, does this imply market failure?

– What inhibits SMEs’ use of the IPR system?

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METHODOLOGY

The methodology involved:– Consultation with key stakeholders – Analysis of IP Australia database on patents,

trade marks & registered designs to establish level of activity

– Surveying 100 SME “Innovation Partners” and “Innovation Advisors” to identify factors inhibiting SMEs’ use of IPRs

– Conduct 10 case studies of SMEs I will focus on: IPR activity levels, survey

results Other results are available in Jensen &

Webster (2006)

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AUSTRALIAN SMEs

SME definition: <200 employees & <$200m assets

According to ABS data, there are 608,000 SMEs and 3,000 large firms in Australia

SMEs are important to the Australian economy:– Employ 69% of total workforce– Account for 49% of value-added– Own approximately 15% of business assets

SMEs: mainly in manufacturing, retail trade and business services

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DATA ISSUES

“Matching” IP administrative data to IBISWorld and AOD data on firm characteristics, since there is no universal firm-level dataset in Australia

Excluding individuals from the analysis, the matching rates across the various IPRs were:– Patents (60% of Aust. company applications)– Trade marks (50% of Aust. company applications)– Designs (40% of Aust. company applications)

No evidence of any systematic bias. That is, matched sample is representative.

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IP APPLICATION RATES

IPR Count/’000 Employees

Type of IPR Large SME

Patent applications, 2000/01 0.35 0.38

Trade mark applications, 2000/01 2.44 4.19

Design applications, 2000/01 0.22 0.32

Note the use of a rate not just a count of IPRs Controlling for the number of employees:

– SMEs’ use of patents/designs is comparable to large firms– SMEs apply for significantly more TMs than large firms

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OBSERVATIONS

Results seem to run counter to the conventional wisdom since SMEs do not appear to be disadvantaged in their use of IPRs

But we can’t draw any strong conclusions whether this represents “optimal” levels of IPR use. Why?

Because we don’t have an independent measure of innovative activity by large and small firms

It may be the case that SMEs do far more innovation, but don’t take out as many patents

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SURVEY METHOD

Two surveys of IP stakeholders were conducted:– Innovation Partners (50 organisations): venture

capitalists, CRCs, business incubators…– Innovation Advisors (50 organisations): IP lawyers,

patent and trade mark attorneys, COMET advisors…

All were asked their view on factors affecting IP usage by SMEs

Response rate of 49% and no systematic bias across respondents

Respondents asked a number of questions and rated their responses on a 1-5 Likert scale

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RESULTS: USE OF IPR

Rank-Ordered Reasons Score

Attract investors 4.47

Protection against imitation 4.45

Build competitive advantage 4.25

Protection in overseas markets 4.22

Protect brand value 4.02

Establish a foothold in the market 3.33

Increase market share 3.22

Send a signal to the market 2.94

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OBSTACLES FOR SMEs

Rank-Ordered Factors Score

Cost of enforcement 4.27

Cost of application 3.75

Limited managerial resources 3.32

Nature of the technology 3.11

Uncertainty over whether IP rights will be upheld 3.04

Concerns regarding disclosure 3.00

Speed of product innovation 2.96

Uncertainty regarding benefits of IP protection 2.87

Lack of awareness of IP system 2.69

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IP EFFECTIVENESS

Rank-Ordered Effectiveness Score

Patents 4.09

Licensing arrangements 3.83

Trade/service marks 3.17

Confidentiality agreements 3.13

Copyright 2.89

Business method patents 2.47

Innovation patents 2.43

Registered designs 2.35

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CONCLUSIONS

SMEs don’t appear to have a problem using the IP system vis-à-vis large firms

Enforcement costs are the most important inhibiting factor, but it is not clear whether these are more (or less) of a barrier than for large firms

Future work on innovation measurement may provide stronger conclusions

Availability of firm-level panel data continues to be a major obstacle to good empirical analysis

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IP, Technological Conditions and New Firm Survival

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MOTIVATION International empirical evidence suggests that:

– Firm survival has important effects on market structure, productivity growth and technological change

– Innovation, firm size (size-at-birth) and organisational structure are important determinants of firm survival

Problems with existing survival studies:– Selection bias: only “successful” innovation considered– Omitted variable bias: technological conditions matter– Fail to capture industry dynamics

In this paper, we:– Map patterns of entry/exit using data 1997-2003– Link these data with other firm-, industry- and macro-

level data in order to analyse the determinants of survival

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OBJECTIVE We answer the following questions:

– Firm Level: How does innovation shape survival for new vis-a-vis incumbent firms?

– Industry Level: How does the speed of technological change in an industry affect relative survival rates?

– Macro Level: Are new firms more susceptible to business cycle effects than incumbent firms?

Firm survival modeled using a piecewise-constant exponential hazard function

Data: unbalanced panel of 260,000 companies alive at some stage during 1997-2003– Numerous cohorts of entrants– Time-varying industry-level measure of tech

conditions– Firm-level measures of IP stocks and flows– Some aggregate macroeconomic fluctuation

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DATA Our dataset consists of:

– 261,262 companies alive during 1997-2003 as determined by ASIC registration/deregistration data

The data were linked (by company name) to: – IP Australia data to construct IP stocks/flows– Yellow Pages in order to get ANZSIC codes– Parent/subsidiary concordance – Companies that changed name treated as ongoing

entities 67% of ASIC records matched to Yellow Pages

– Cafes under-represented since company ≠ trading name

– Yellow Pages filters out “non-trading” companies The following ABS data also linked into the

dataset:– Industry-level profit margin– GDP, interest rates and – ASX stock market index

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DESCRIPTIVES Death is defined as deregistration of an ACN

or disappearance from the Yellow Pages Age profile: companies vary from 0 to 124 yrs

old Trends in birth/death rates:

– Births are decreasing over the period– Deaths are increasing over the period– But net entry rate is positive overall

Year Stock(number)

Birth Rate (% of stock)

Death Rate (% of stock)

1997 219,318 12.1 1.6

1998 236,958 10.4 2.5

1999 250,911 9.5 3.0

2000 264,680 8.0 3.2

2001 269,864 5.7 4.2

2002 271,861 5.9 4.2

2003 272,576 6.1 4.1

Total 1,786,168 8.1 3.3

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EMPIRICAL MODEL

Piecewise exponential hazard function Company age (years) is the unit of time

analysis Incumbents are defined as any company born

prior to 1990 who we observe in 1997-2003 New firms are defined as new ACNs 1997-2003 Our set of explanatory variables xi consists of:

– Patent/trade mark stocks (i.e. renewals): (log+1) yrs– Patent/trade mark flows (i.e. applications): lagged

number of applications (log+1) (“Shadow of death”)– Size dummy (all IBIS firms are large)– Parent and subsidiary dummies– Private/public firm dummy– 1-digit ANZSIC industry dummies

)'exp()()|( 0 βxx ii thth

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Other explanatory variables are:– Gross industry entry rate: # entrants relative to #

incumbents (proxies intensity of competition or barriers to entry)

– Risk: industry profit margin over the tangible capital-output ratio (proxies capital intensity)

– Industry innovativeness (i.e. technological conditions), a weighted index of R&D expenditure/employment, IP applications and labour productivity (to proxy process innovations). Measures the speed of technological change

– Macro conditions: factor of ∆GDP and ∆∆GDP– Interest rate: 90-day bank bill rate– Stock market: ASX index

Model is estimated separately for incumbent/new firms and the relative effects are compared

EMPIRICAL MODEL (2)

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RESULTS (1)

Dep. Var: Probability of Firm Death MODEL 1

Explanatory Variables New Firms Incumbent Firms

PATENTAPPS (f) -0.088 0.257**

TMAPPS (f) -0.034 -0.082*

PATENTSTOCK (f) -0.026 -0.024**

TMSTOCK (f) -0.059** -0.029**

LARGE (f) -0.451+ -0.450**

PRIVATE (f) -0.297** 0.097*

SUBSIDIARY (f) 0.440** 0.263**

PARENT (f) 0.044 -0.387**

RISK (i) -0.008 0.025**

GROSSENTRY (i) 0.046** 0.015*

INDINNOV (i) -0.341** 0.014

INTEREST RATE (e) 0.697** 0.119**

MACRO (e) -1.223** -0.495**

STOCKMKT (e) -0.331** -0.016**

Industry dummies Yes Yes

No. of Observations 322,798 1,043,432

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RESULTS (2) Firm size (crudely measured) matters: larger

firms are much more likely to survive Entry begets exit, especially for new firms.

Maybe low barriers to entry, but high barriers to survival

BUT: in industries characterised by rapid technological change, new firms are more likely to survive

All macro factors are significant, but the relative effect is greater for new firms:– Increase in interest rates increase hazard rate, but

new firms are more vulnerable– Increase in GDP aids all firms, but provides a

greater boost for new firms– New firms are more susceptible to stock market falls

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CONCLUSIONS

No simple linear relationship between innovation and performance

Results demonstrate the importance of separating innovation investments (IP flows) from innovation capital (IP stocks)

New firms play an important role in technological change: in fast-moving industries, new firms drive the “gale of creative destruction”

New firms are particularly sensitive to changes in macroeconomic conditions