Evolution of U.S. Innovation Policy

Gregory Tassey Economic Analysis Office

National Institute of Standards and Technology

tassey@nist.gov

October 2011

2

Characteristics of U.S. Innovation Policy Largely focused on public missions: defense, energy, health, security Mission-oriented R&D accounts for ~90 percent of federal R&D budget

80 percent of federal R&D budget is defense and health

U.S. economic growth philosophy is based on “black-box” model

Government funds science and industry develops the technology (black-boxes)

Does not provide decision criteria for different policy instruments (e.g. tax incentives vs. direct funding)

Overall, role of technology in economic growth is poorly understood and thus undervalued

The Innovation Policy Challenge

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Characteristics of U.S. Innovation Policy The positive is that “innovation policy” is finally beginning to evolve into

a broader Science, Technology, Innovation, and Diffusion (STID) policy The “D” in STID includes important mid and late technology life cycle

strategies, such as scale-up and market penetration In fact, the U.S. has been underinvesting in R&D and related economic

assets for decades

This underinvestment is now being manifested in a range of negative economic growth indicators

The Innovation Policy Challenge

GDPLong-Term Growth (smoothed pattern)

Time

Business Cycle (actual growth pattern)

Long-Term vs. Short-Term Growth Trends

Source: Gregory Tassey, “Beyond the Business Cycle: The Need for a Technology-Based Growth Strategy,” forthcoming. 4

Importance of the Policy Problem

0

20

40

60

80

100

120

140

0 5 10 15 20 25

Rate of Innovation vs. R&D Intensity: Percent of Companies in an Industry Reporting Product and/or Process Innovations, 2003-2007

Index

R&D Intensity

Source: Gregory Tassey, “Beyond the Business Cycle: The Need for a Technology-Based Growth Strategy,” forthcoming. Index = sum of percent of companies in an industry reporting product innovations and percent reporting process innovations. R&D intensity data from Science and Engineering Indicators 2010 , Appendix Table 4-14 (industry and other non-federal funds for R&D); innovation data from Mark Boroush, “NSF Releases New Statistics on Business Innovation,” NSF InfoBrief, October 2010

Minimum R&D Intensity

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Importance of the Policy Problem

Relationship Between R&D Intensity and Real Output Growth

Industry (NAICS Code)Average R&D Intensity,

1999-2007Percent Change in Real Output,

2000-2007

R&D Intensive:

Pharmaceuticals (3254) 10.5 19.1

Semiconductors (3344) 10.1 15.4

Medical Equipment (3391) 7.5 28.4

Computers (3341) 6.1 106.2

Communications Equip (3342) 13.0 -42.3

Group Ave: 9.5 Group Ave: 25.4

Non-R&D Intensive:

Basic Chemicals (3215) 2.2 25.5

Machinery (333) 3.8 2.4

Electrical Equipment (335) 2.5 -13.6

Plastics & Rubber (326) 2.3 -4.5

Fabricated Metals (332) 1.4 4.9

Group Ave: 2.5 Group Ave: 2.9Sources: NSF for R&D intensity and BLS for real output. 6

Importance of the Policy Problem – Manufacturing

108.8%

84.9%

107.8%

167.7%

14.6%

0%

20%

40%

60%

80%

100%

120%

140%

160%

180%

1960-70 1970-80 1980-90 1990-00 2000-10

Fixed Private Investment (hardware & software) (growth by decade in 2005 dollars)

Source: Gregory Tassey, “Beyond the Business Cycle: The Need for a Technology-Based Growth Strategy,” forthcoming. Data from Bureau of Economic Analysis, NIPA Table 5.3.5 (includes both equipment and software) and Table 5.3.4 (price indexes for fixed private investment) 7

Underinvestment – Aggregate

0.0%

0.5%

1.0%

1.5%

2.0%

2.5%

3.0%

3.5%

1953 1957 1961 1965 1969 1973 1977 1981 1985 1989 1993 1997 2001 2005

U.S. R&D Intensity: Funding as a Share of GDP, 1953-2008

Total R&D/GDP

Federal R&D/GDP

Industry R&D/GDP

Gregory Tassey, “Rationales and Mechanisms for Revitalizing U.S. Manufacturing R&D Strategies,” Journal of Technology Transfer 35 (2010): 283-333. Data from the National Science Foundation. 8

Underinvestment – Amount of R&D

4.86

3.75 3.73

3.42 3.37

3.012.77 2.77 2.68 2.68 2.65 2.53

2.33

2.021.84 1.81 1.77

1.54

0.0

1.0

2.0

3.0

4.0

5.0

6.0

Source: OECD, Main Science and Technology Indicators, 2010.

National R&D Intensities, 2008 Gross R&D Expenditures as a Percentage of GDP

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Underinvestment – Amount of R&D

170.2%

135.1%

65.0%61.0%

42.2%

26.2%20.5%

10.4%

0%

20%

40%

60%

80%

100%

120%

140%

160%

180%

China Singapore Finland Taiwan South Korea Japan Germany United States

Source: Gregory Tassey, “Beyond the Business Cycle: The Need for a Technology-Based Growth Strategy,” forthcoming. Data from OECD, Main Science and Technology Indicators, 2010/1.

Changes in National R&D Intensity, 1995-2008

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Underinvestment – Amount of R&D

0

10

20

30

40

50

60

70

80

90

100

Australia Canada United Kingdom United States Japan Korea Germany

Low R&D (< 1%) Medium-Low R&D (1-3%) Medium-High R&D (3-5%) High R&D (> 5%)

Shares of Manufacturing Value Added by R&D Intensity

Stephen Ezell and Robert Atkinson (2011), International Benchmarking of Countries' Policies and Programs Supporting SME Manufacturers. Washington: DC: Information Technology and Innovation Foundation, September. Data from OECD, “Industry and Services STAN Database: “Value-added shares relative to manufacturing,” http://stats.oecd.org/index.aspx?r=228903

Percent

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Underinvestment – Amount of R&D

Applied R&D

Basic Research

12 Gregory Tassey, The Technology Imperative, 2007; and, “The Disaggregated Technology Production Function: A New Model of Corporate and University Research”, Research Policy, 2005.

Identifying Underinvestment – Technology-Element Growth Model

g Production MarketDevelopment

EntrepreneurialActivity

ProprietaryTechnologiesProprietary

Technologies

GenericTechnologies

Science Base

Economic Model of a Technology-Based Industry

ValueAdded

Gregory Tassey, The Technology Imperative, 2007; and, “The Disaggregated Technology Production Function: A New Model of Corporate and University Research”, Research Policy, 2005.

StrategicPlanning

Risk Reduction

System Integration

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Identifying Underinvestment – Technology-Element Growth Model

Application of the Technology-Element Model: Biotechnology

Science Base

Infratechnologies

Generic Technologies Product Process

Commercial Products

genomics immunology microbiology/

virology molecular and

cellular biology nanoscience neuroscience pharmacology physiology proteomics

bioinformatics bioimaging biomarkers combinatorial

chemistry DNA sequencing and

profiling electrophoresis fluorescence gene expression

analysis magnetic resonance

spectrometry mass spectrometry nucleic acid

diagnostics protein structure

modeling & analysis techniques

antiangiogenesis antisense apoptosis bioelectronics biomaterials biosensors functional genomics gene delivery

systems gene testing gene therapy gene expression

systems monoclonal

antibodies pharmacogenomics stem-cell tissue engineering

cell encapsulation cell culture microarrays fermentation gene transfer immunoassays implantable delivery

systems nucleic acid

amplification recombinant

DNA/genetic engineering

separation technologies

transgenic animals

coagulation

inhibitors DNA probes inflammation

inhibitors hormone

restorations nanodevices neuroactive

steroids neuro-transmitter

inhibitors protease inhibitors vaccines

Public Technology Goods

Mixed Technology Goods

Private Technology Goods

14 Gregory Tassey, The Technology Imperative, Edward Elgar, 2007

Identifying Underinvestment – Technology-Element Growth Model

Production

Gregory Tassey, “Rationales and Mechanisms for Revitalizing U.S. Manufacturing R&D Strategies,” Journal of Technology Transfer 35 (2010): 283-333.

StrategicPlanning

MarketDevelopment

EntrepreneurialActivity

RiskReduction

ProprietaryTechnologies

GenericTechnologies

Science Base

Joint Industry-Government Planning

Market Targeting Assistance and Procurement Incentives

Acceptance Test Standards and National Test Facilities (NIST)

Interface Standards (consortia, standards groups)

Technology Transfer/Diffusion (MEP)

National Labs (NIST), Consortia

Intellectual Property Rights (DoC)

National LabsDirect Funding of Firms & Universities (DARPA, ARPA-E, NRI, AMTech)

Tax Incentives

Incubators (states)

Managing the Entire Technology Life Cycle: Science, Technology, Innovation, Diffusion (STID) Policy Roles

ValueAdded

Scale-Up Incentives

System Integration

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Policy Response

Emerging Targets of R&D Policy:

Amount of R&D Create financial incentives for private companies to increase investments in R&D and

increase the R&D intensity of the manufacturing sector Increase Federal investment in research aimed at objectives relevant to private-

sector R&D targets in addition to those related to agency missions

Composition of R&D Create incentives for private-sector investment in early phases of R&D cycle Create public-private partnerships to meet industry’s long-term research needs

through support for innovation clusters Fund research aimed at manufacturability to overcome scaling issues and target the

“other” 90% of manufacturing value added (outside of NAICS 3345 and 3364) Eliminate barriers to investment in new and innovative technology-based firms (high

technical risk, appropriability, and process-capability barriers)

Efficiency of R&D Improve R&D timing and content through road mapping and portfolio management

techniques Increase rates of return and shorten the R&D cycle through technology clusters and

other forms of collaboration Build in technology transfer through cluster design and IP management 16

Policy Response