Title: Scholarship and Inventive Activity in the University: Complements of Substitutes? By Brent Goldfarb, Gerald Marschke and Amy Smith
1Scholarship and Inventive Activity in the
University Complements of Substitutes?By Brent
Goldfarb, Gerald Marschke and Amy Smith
- Discussant
- Nicola Lacetera
- Case Western Reserve University
- Department of Economics
2The paper
- Question ?0?
- Data novel panel from Stanfords biochemistry
and electrical engineering department - 1990-2000, all tenure track faculty
- Scientific productivity publication count
impact factor weighted - Inventive activities Disclosed inventions with
commercial potential - Teaching taught credits
- Statistical methods
- Count models (Poisson) OLS
- Endogeneity FE, IV VC disbursed, revenues of
colleagues. 2sls, GMM - Findings gt0
in Biochem, 0 in El. Eng.
3Contribution The question
- Relation b/w scientific and inventive activities
hot topic in the Economics of Science - Are commercial activities compatible with the
production of good science? - Can universities have multiple missions?
Research, teaching, commerce? - Political and managerial relevance
- Hicks-Hamilton (1999), Agrawal-Henderson (2002),
Geuna-Nesta (2003), Azoulay et al. (2004a,
2004b), Van Looy et al. (2004), Stephan et al.
(2005), Markiewicz-DiMinin (2005), Breschi et al
(2005), Calderini-Franzoni (2005), Calderini et
al. (2005), Murray-Stern (2005) Henderson et al.
(1998), Mowery et al. (2003)
4Contribution Limits in current studies
- Data
- Publications, Citations, Impact factor
Scientific value, truncation, relevant journals,
reasons for citations - Patents, citations squeeze existing database,
but appropriate? - Most inventions not patented, citations by
examiners - How about teaching?
- 444
- Methods and Techniques
- Simultaneity, individual heterogeneity,
unobservables. Progress, lately - Theory
- What should we expect? How do the different
incentives interact? - How to model multiple missions, peer effects,
career concerns, etc.?
5Contribution The data
- Tenure track Stanford faculty, 1990-2000, two
depts. - Publications, and I.F.-weighted avoid
truncation, consider quality - Disclosed inventions, NOT patent data at last!!
More comprehensive - Teaching record other major activity to
consider! - Small number. 15 scientists in Biochem
- How about post-docs? Big deal in Biochem. and
Engineering - Stanford representative of average/median
university? Can generalize complementarity?
Faculty quality, resources, TLO/TTO efficiency - I.F. from ISI keep journals constant?
- Disclosed inventions with commercial potential
selected sample?
6Contribution Methods and techniques
- Take Endogeneity seriously -- GREAT!
- FE, IV, GMM Wooldrigde, Arellano-Bond.
State-of-the-art techniques - Identification
- Social interactions and peer effects tricky
first stage (Mansky 2002) - Small sample bias of IV techniques (Hausman-Hahn
2002). Estimates bounce - Strength of IV show first stage (R2)? Show
Hausman (1978) test? - Orthogonality What if
Scientist ability, arrival of a star, major
finding
VC attracted (Zucker et. al)
VC activity, revenues of colleagues
Technological/ scientific shock, opportunity
Publications
More inventions
Inventions
Buy out teaching
Big grant
More research
7Contribution Theory
- Not much theoretical discussion not the aim of
this paper, but - What are the underlying theoretical/behavioral
assumptions? - Is science-invention the appropriate tradeoff?
Why not together (biotech)? How about science
and innovation, or entrepreneurship? - Are the results surprising? Expected (especially
after biotech)? - Why the difference between departments?
8Contribution Summary
- Relevant improvement in data collection
- Concerns selectivity (Stanford, valuable
inventions), variable construction (teaching
variable, I.F.), small sample - Major advances in identification
- Concerns Identification strategy, small sample
- Intriguing questions raised, e.g. difference
among depts. and measures - Major contribution!
- But keep an eye at concerns reinforce your
results, explain them, and find space in a quite
crowded research area