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Natalia Zinovyeva

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UNIVERSITIES AND INDUSTRIAL INNOVATION: EMPIRICAL EVIDENCE Natalia Zinovyeva Foundation for Applied Economic Research - FEDEA – PowerPoint PPT presentation

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Title: Natalia Zinovyeva


1
UNIVERSITIES AND INDUSTRIAL INNOVATION EMPIRICAL
EVIDENCE
  • Natalia Zinovyeva
  • Foundation for Applied Economic Research - FEDEA

2
Motivation
  • Lisbon strategy Investing in RD, Boosting
    innovation, Better education and skills
  • Close interactions between government, university
    and industry
  • Which form should they take?

3
Theoretical arguments
  • Market failures
  • Suboptimal allocation of resources to knowledge
    production
  • Causes
  • Fundamental uncertainty in research outcomes
  • Non-proprietary nature of knowledge
  • Information asymmetries between users and
    producers
  • System failures
  • Inefficiencies in interaction among agents
  • Suboptimal supportive structures
  • Causes
  • Lock-ins in existing networks
  • Structural inertia
  • Failures in infrastructural provision

4
Correction strategies
  • Government as a risk taker direct procurement of
    research
  • Incentives public procurement, taxation relives,
    university labs, government funding
  • IPR legislation
  • Enabling collaborative schemes
  • Collaboration between university and industry

5
Evidence on system failure?
  • Edwin Mansfield (1991, 1998)
  • 2 samples of 76 major American firms for
    1975-1985 and 1986-1994

6
Role of university in knowledge clusters
  • Silicon Valley beginning in 1938 from
    Hewlett-Packard - a spin-off of Stanford
    University
  • Route 128 knowledge cluster since the 1930s MIT
    has spawned 4,000 companies employing more than a
    million people
  • Do these cases represent a rule or an exception?

7
Methodologies
  • Descriptive evidence
  • Surveys and case studies
  • Econometric studies

8
1. Descriptive evidence on technology transfer
  • Claim that university presence is important
  • Route 128 (Dorfman 1983)
  • Silicon Valley and Route 128 (Saxenian 1985)
  • Cambridge, UK (Wicksteed 1985)
  • Counter-examples
  • High technology centers in England (Breheny and
    McQuaid 1987)
  • Some US centers (Colorado Springs and Portland)
    (Rogers and Larsen 1984)
  • John Hopkins University (Feldman 1994)

9
2. Survey and case study evidence Effect of
university on firms location
  • Several studies find that firms consider
    university presence as an important factor for
    firms location
  • Premus 1982 60 of surveyed US firms
  • Schmenner 1982 52
  • Other studies on the US
  • Counter-examples
  • Howells 1984 only 2.6 of firms in
    pharmaceuticals in England indicate university as
    their first reason for choosing location, ¾ that
    it is not significant
  • Gripaios et al. 1989 only 9 indicate any
    university effect in the Plymouth region,
    England.

10
2. Survey and case study evidence Effect on
innovation activity
  • Mansfield (1991, 1998)

11
3. Econometric evidence Effect of university in
high-tech location
  • Claim that university is important for high
    technology location
  • Glasmeier (1991)
  • 247 US metropolitan statistical areas in 1982
  • Dependent variable High tech employment
  • University variable number of colleges
  • Controls climate, housing prices, property tax,
    wage rate, migration, educational options,
    freeway density, poverty rate,..
  • Method OLS
  • No effect on high tech location
  • (Markusen et al, 1986)
  • 264 US metropolitan statistical areas in 1977
  • Dependent variable High tech employment
  • University variable university RD
  • Controls climate, housing prices, property tax,
    educational options, freeway density, business
    services
  • Method OLS

12
3. Factors determining the effect of university
on high-tech location (Cont.)
  • Sectors
  • Some evidence of positive effect in various
    sectors
  • Electrical and Electronic Equipment (Bania et
    al., 1993)
  • Biotechnology (Audretsch and Stephan 1996, Zucker
    et al. 1998)
  • Ambiguous evidence
  • Chemicals and instruments
  • Ownership structure
  • Headquarters consider important proximity to
    universities, branch plants no (Malecki, 1986)
  • Firm size
  • Big firms tend to locate close to universities
    (Rees 1991)

13
3. Econometric evidence Effect of university on
private innovation activity
  • Positive effect of universities in the US
  • State level (Jaffe, 1989)
  • 29 states in 8 years
  • Dependent variable Number of industrial patents
  • Independent variables Academic RD investment
  • Private RD investment
  • Controls Population size, year dummies
  • Method 3SLS.
  • Instruments number of private and public
    universities (in Academic RD equation) and
    manufacturing VA (in Private RD equation)
  • Feldman (1994) and Feldman and Florida (1994)
    confirm the findings of Jaffe using innovation
    count data
  • Metropolitan statistical areas (Bania et al.
    1992, Varga 1998)
  • Within a metropolitan area (Sivitanidou and
    Sivitanides 1995)

14
3. Econometric evidence Effect of university on
private innovation activity (Cont.)
  • Positive effect of universities in Europe
  • France
  • Autant-Bernard 2001
  • Austria
  • Fisher and Varga 2002
  • Italy
  • Audretsch and Vivarelly 1994
  • Cowan and Zinovyeva 2007

15
More on the channels of technology transfer
  • The most important channels through which firms
    benefit from university research publications,
    conferences, informal information channels, and
    consulting (Cohen et al., 1998).
  • Informal interactions (Bercovitz and Feldman,
    2006)
  • Even in pharmaceuticals firms heavily rely on
    these channels (Gambardella, 1995)

16
How academic research differentiate from any
other RD company?
  • Different researchers Balconi, Breschi, Lissoni
    (2004)
  • Academic inventors are more persistent and more
    central
  • Networks hosting scientists are larger and more
    connected than other research networks
  • Different research output Henderson, Jaffe,
    Trajtenberg (1998)
  • University patenting between 1965 and 1988
  • Until mid-1980s university patents were more
    cited, cited by more technologically diverse
    patents
  • Why they are different?
  • Self-selection
  • Other selection
  • Incentives
  • Tasks

17
Summary
  • Academic basic knowledge takes long time before
    being used in innovation activity
  • Both basic and applied academic research is
    important for industrial innovation activity
    (local, regional, national) in the short run
  • Academic research output has the features of
    general purpose knowledge/technology

18
Possible risks of increasing university-industry
collaboration and challenges for future research
  • Crowding out of basic research
  • Limiting the freedom of academic research
  • Decline in scholar productivity
  • Affecting the culture of university oriented on
    public good creation
  • Restriction on the dissemination of research
    results (Example patents on research tools
    (genetic materials) in biology)
  • High cost of administrative support and
    reorganization
  • Science becoming inappropriate for graduate
    research
  • Decreasing quality of education
  • Public institutional expenditures on instruction
    declined by 6, - on research rose 4
  • Crowding out of private research (professors as
    cheap labor for industry)

19
Thank you for your attention!
  • Contact Natalia Zinovyeva
  • nzinovyeva_at_fedea.es
  • Foundation for Applied Economic Research (FEDEA)
  • c/Jorge Juan, 46
  • 28001 Madrid

20
Summary of identification problems in the
econometric analysis
  • University effects ?? Industrial innovation
  • (Universities might be created in response to
    the needs of regional industry in human capital)
  • Academic research ?? Industrial innovation
  • (Academics might themselves benefit from
    interaction with innovative industrial sector by
    getting more and better research ideas and
    opportunities)
  • Location unobserved heterogeneity
  • Separating the direct effect of academic research
    from the effect of teaching and ultimately
    graduates human capital

21
CZ 2007 Hypotheses
  • New universities have a positive effect on
    regional innovation in the short-run.
  • Some of this effect corresponds to the spillover
    effect via traditional channels like academic
    patenting and publishing activity.
  • New universities might push firms to rely more on
    collaboration with academics as a source of
    scientific knowledge rather than on own effort on
    searching the scientific literature.

22
Main features of the paper
  • The effect of new university departments in
    sciences, medicine and engineering in Italy
    during 1985-2000
  • Short-term effect of new university departments
    the channel corresponding to graduates human
    capital is excluded
  • According to Italian Ministry of Education the
    decision about the distribution of university
    departments across Italian regions was largely
    independent of any features of regional economy

23
Observatory for the evaluation of the university
system 1997
  • The rule by which new institutions were created
    does not seem to have followed the logic of
    tailoring university development to territorial
    specificities. It seems not to have made
    reference to a demand for university education,
    nor to the demand for graduates or to existing
    infrastructure. So, at least to a large
    extent, the prevalent logic was the one of
    incremental expansion and distribution "by drops
    of rain", without giving evaluation opportunity
    to the suppressed initiatives

24
Number of new departments open between 1984 and
2000 by regional demand for corresponding
professions
25
Number of new departments Sciences, Medicine,
Engineering
26
The estimation models
With fixed effects for each university and
discipline
27
Data
  • 20 Italian regions during 1985-2001
  • Number of university departments (Sciences,
    Chemistry and Pharmacy, Agriculture, Medicine,
    Veterinary, Engineering, Architecture) Italian
    National Statistical Bureau
  • Regional economic characteristics GDP,
    population, RD expenditure
  • Innovation activity from KEINS EP-INV database
    (Lissoni, Sanditov, Tarasconi, 2006)
  • Academic and Industrial Patents
  • Patent citations
  • Non-Patent Literature (NPL) citations
  • Academic publications ISI Thompson Science
    Citation Index

28
Annual change in the number of industrial patents
29
Number of patents conditional negative binomial
30
Academic publications conditional negative
binomial
31
The channels of the university effect on
short-term industrial patenting
32
Evidence of crowding-out? Non-patent literature
citation intensity by industrial patents
33
Summary and conclusions of CZ 2007
  • New universities positively affect regional
    innovation activity
  • Industrial Patenting responds within 3-4 years
  • Academic patenting and scientific activity
    increases already after 1-2 years
  • Part of the increase in industrial patents
    (around 30 percent) is explained by the
    corresponding growth of academic research
  • Negative correlation between new universities and
    NPL citation potential crowding-out of resources
    devoted by industry to searching the academic
    literature. If this is the case, it might
    suppress firms continued development of
    absorptive capacity.

34
Descriptive evidence
  • 1988-2003 academic patents quadruple 800 to 3200
  • 1992-2003 number of US scientific publications
    flat, causing US decline in world article output
    from 38 to 30
  • 1988-2003 number of US patents referenced in
    scientific articles increased dramatically

35
Share of industrial RD expenditures in total
university RD expenditures and the share of
expenditures spent on basic research, US 1953-2006
SOURCE  National Science Foundation/Division of
Science Resources Statistics, Survey of Research
and Development Expenditures at Universities and
Colleges, FY 2006.
36
(No Transcript)
37
Individual level evidence how academic
scientific productivity changes after academics
engagement in collaboration with industry?
  • Zucker, Darby, several co-authors (1998a, 1998b,
    2000)
  • Star scientists collaborating with or employed by
    firms, or who patent, have significantly higher
    citation rates than pure academic stars
  • Thursby and Thursby (2007)
  • 3,241 faculty from six major US universities from
    1983 through 1999
  • probability that a faculty member will disclose
    an invention increased tenfold, the portion of
    research that is published in basic journals
    remained constant
  • Link, Siegel, Bozeman (2006)
  • Academics who allocate a relatively higher
    percentage of their time to grants-related
    research are more likely to engage in informal
    commercial knowledge transfer
  • Lowe and Gonzalez-Brambila (forthcoming, 2007)
  • 15 research institutes
  • Faculty entrepreneurs in general are more
    productive researchers than control groups in
    terms of publication rate and the impact of their
    publications
  • Productivity does not decrease following the
    formation of a firm

38
The Relationship between Academic Research,
Teaching Quality and Graduates Employment
Outcomes
  • Sylos Labini and Zinovyeva (2007)
  • Several surveys of Italian university graduates
    in 1995-2001
  • Rich information on individual quality and
    socioeconomic background
  • No negative effect of academic patenting activity
    at the faculty level on teaching quality and
    graduates employment outcomes

39
Public and Private RD complements or
substitutes?
  • David, Hall, Tool (2000)
  • Concern Main focus in the literature is on
    publicly funded research performed in academic
    institutions, and nothing on its comparison with
    the impacts of publicly sponsored RD conducted
    under contract by industrial corporations
  • Public funding of research might crowd out
    private research via its generic impacts on the
    price of research and development inputs that are
    in inelastic supply
  • Not taking onto account price (researchers wage)
    effect leads to overestimation of positive
    effects of public RD expenditures
  • Investment displacement It is likely to exist
    the lobby for subsidies for projects with high
    private marginal rates of return, which would
    enable firms correspondingly to reduce their own
    outlays (because RD activities are heterogeneous
    rather than homogeneous)

40
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42
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