What is Wrong With U.S. Manufacturing?

Gregory Tassey

Economic Analysis Office

National Institute of Standards and Technology

tassey@nist.gov http://www.nist.gov/director/planning/

October 2012

Need Institutionalized Process for Managing Science, Technology, Innovation, and Diffusion (STID) Policy:

(1) Demonstrate importance of the policy issue for economic growth

(2) Identify indicators of underperformance at the macroeconomic level Productivity growth Trade balances Corporate profits Employment and earnings

(3) Estimate underinvestment in technology as determinant of growth Specific R&D investment trends Investment by phase of the R&D cycle Technology diffusion rates Scale-up

(4) Identify causes of underinvestment using technology-based models Excessive technical and/or market risk Appropriability, information, expertise, capital market problems

(5) Develop/select policy responses and management mechanisms

Policy instruments matched with underinvestment phenomena

Metrics for policy management and impact assessment 2

3

Projected slow rate of economic growth is manifestation of inadequate long-term investments in productivity growth

For the last decade (2000-2010)

Average annual real GDP growth was 1.7 percent

U.S. private nonfarm employment declined 3.3 percent

Real disposable personal income grew 11.9 percent

Median household real income declined 7.0 percent

23.5 million people were unable to find full-time jobs, double the 12 million working in U.S. manufacturing (July 2012)

47 million Americans on food stamps (June 2012)

However, the current economic growth policy debate is focused on macrostabilization issues:

Government spending vs. deficit reduction

Monetary base expansion vs. potential inflation effects

(1) Importance of the Policy Problem – Inadequate Innovative Capacity

GDP

Long-Term Growth (smoothed pattern)

Time

Business Cycle (actual growth pattern)

Macrostabilization vs. Long-Term Growth Strategies

Gregory Tassey, “Beyond the Business Cycle: The Need for a Technology-Based Growth Strategy,” Science and Public Policy (forthcoming)

Western Economies

Asian Economies

The Great Recession

4

(1) Importance of the Policy Problem – Wrong Growth Policy Model

Economic importance of A National Strategy for Advanced Manufacturing:

As an independent economy, the value added produced by the U.S. manufacturing sector would rank 9th in the world

Important for diversification in a highly competitive global economy Contributes $1.7 trillion to GDP and employs 11 million workers High-tech service jobs are increasingly ‘‘tradeable’’ and 30 economies

have policies in place to promote service exports

Manufacturing accounts for 70% of US domestic industry-performed R&D 60% of U.S. domestic industry’s scientists/engineers 70% of patents issued to U.S. companies/residents

Loss of domestic manufacturing would erode U.S. R&D infrastructure

High-tech services must have close ties to its manufacturing base Large high-tech manufacturing firms are integrating forward into services

The majority of trade is in manufactured products—deficits for last 37 years

Yet, neoclassical economists are okay with offshoring all manufacturing

(1) Importance of the Policy Problem – Role of Domestic Manufacturing

5

The Bottom Line: The high-income economy must be the high-tech economy

1) Technology is the long-term driver of productivity growth and hence growth in real wages

2) Median wages in BLS “high-tech” occupations exceed median for all industries by 50-100 percent

3) But, the U.S. economy is in long-term decline relative to the global economy due to underinvestment in R&D, capital formation, and workforce training

4) This underinvestment is now being manifested in a range negative economic growth indicators (productivity, real income, trade, GDP)

5) High-tech sector is small part of the U.S. economy, giving it low political influence

6) Existing underinvestment phenomena must be addressed by appropriate policy instruments—requires a STID economic growth model

7) Applying such a framework demands a STID policy analysis infrastructure—hardly exists in the United States 6

(2) Underperformance – The High-Tech Economy

10,000

11,000

12,000

13,000

14,000

15,000

16,000

17,000

18,000

19,000

20,000

1960 1964 1968 1972 1976 1980 1984 1988 1992 1996 2000 2004 2008

US Manufacturing Employment: 1960–2011

Source: Bureau of Labor Statistics

No. of Workers (thousands)

7

(2) Underperformance – Manufacturing

50

70

90

110

130

150

170

190

210

230

250

1987 1990 1993 1996 1999 2002 2005 2008

Policy Focus: Multifactor Productivity Trends in Productivity and Income: U.S. Manufacturing Sector, 1987-2010

Source: Bureau of Labor Statistics

Labor Productivity

Real Hourly Compensation

Multifactor Productivity

Index

8

(2) Underperformance – U. S. Economy

-2%

0%

2%

4%

6%

8%

10%

12%

1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 31 33 35

Non-Farm Employment Growth in Post World-War-II Business Recoveries:

Percent Change from Recession Trough

Source: G. Tassey, The Technology Imperative (updated); BLS for employment data; NBER for recession trough dates

Months

from

Trough

Average of First Seven Post-

World War II Recoveries

1990-91 Recovery

2001 Recovery2009 Recovery

9

(2) Underperformance – U.S. Economy

-$99B

-$637B

-700

-600

-500

-400

-300

-200

-100

0

100

1988 1990 1992 1994 1996 1998 2000 2002 2004 2006 2008 2010

All Manufactured

Products

Advanced Technology Products

$ billions

Source: Census Bureau, Foreign Trade Division (“Trade in Goods with Advanced Technology Products” and “U.S. Trade in Goods and Services (FT900), Exhibit 15” for the manufacturing trade balance)

U.S. Trade Balances for High-Tech vs. All Manufactured Products, 1988-2011

Cumulative drain on GDP over this period is $8.25 trillion (2011 dollars)

10

(2) Underperformance – Manufacturing

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 for R&D-Intensive Industries

11

(2) Underperformance – R&D Intensity and Innovative Output

Relationship Between R&D Intensity & Real Output Growth in Manufacturing

Industry (NAICS Code)Ave. R&D Intensity,

1999-2007Percent Change in

Real Output, 2000-07Percent Change in

Real Output, 2000-09

R&D Intensive:

Pharmaceuticals (3254) 10.5 17.9 4.9

Semiconductors (3344) 10.1 17.0 1.1

Medical Equipment (3391) 7.5 34.6 39.5

Computers (3341) 6.1 109.9 147.0

Communications Equip (3342) 13.0 -40.0 -59.7

Group Ave: 9.5 Group Ave: 27.9 Group Ave: 26.6

Non-R&D Intensive:

Basic Chemicals (3251) 2.2 25.6 -7.8

Machinery (333) 3.8 2.3 -22.4

Electrical Equipment (335) 2.5 -13.4 -33.4

Plastics & Rubber (326) 2.3 -5.2 -28.0

Fabricated Metals (332) 1.4 2.6 -23.6

Group Ave: 2.5 Group Ave: 2.4 Group Ave: -23.1

Sources: NSF for R&D intensity and BLS for real output. 12

(2) Underperformance – R&D Intensity and Economic Growth

13

High-tech offshoring is a multi-step process, driven by (1) increasingly attractive skilled labor, (2) R&D and capital subsidies, and (3) supply-chain synergies

1) Originally, offshoring of manufacturing was for local-market opportunities

2) Increasingly, motivation is to access cheaper but also skilled labor

Required small amount of supporting R&D Host country frequently subsidizes plant and equipment

3) Host country gains R&D experience at “entry” tier in high-tech supply chain

4) Host country begins to integrate forward into design or backward into components

China—backward to components (from assembly) Taiwan—forward to electronic circuits (from components) Korea—forward to electronic products (from components)

4) Economic policy point: Co-location synergies are being lost in U.S. and captured in Asia Between 2011 and 2013, 81 new semiconductor fabs will begin

operations globally—six of them in the United States (SEMI)

(2) Underperformance – Maintaining Domestic Supply Chains

14

Poor Technology Life-Cycle Management: The United States has been the “first mover” and then lost virtually all market share in a wide range of materials and product technologies, including

• oxide ceramics

• semiconductor memory devices

• semiconductor production equipment such as steppers

• lithium-ion batteries

• flat panel displays

• robotics

• solar cells

• advanced lighting (e.g. OLED)

(2) Underperformance – Manufacturing

15

Trends in Manufacturing R&D Needing Policy Attention 37 consecutive years of trade deficits

Manufacturing sector’s average R&D intensity (3.7 percent) has remained flat since the mid-1980s

has not been helped by offshoring of low R&D-intensive industries

pales compared to truly “R&D-intensive” industries, whose ratios range from 5 to 22 percent

Need for effective policy response is great

most of the global economy’s $1.4 trillion annual R&D spending targets manufacturing technologies

Technology life cycles are being compressed

U.S. manufacturing firms are increasing offshore R&D at three times the rate of domestic R&D spending

Government funding of manufacturing R&D increases the sector’s R&D performance intensity from 3.7 to 4.1 percent

(2) Underperformance – Manufacturing

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: Constant for 45 Years

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. 16

(3) Underinvestment – Amount of R&D

4.46

3.92

3.61 3.56

3.36

3.103.00 2.94 2.90

2.822.72

2.402.27 2.26

1.99 1.92 1.851.70

0.0

0.5

1.0

1.5

2.0

2.5

3.0

3.5

4.0

4.5

5.0

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

National R&D Intensities, 2009 Gross R&D Expenditures as a Percentage of GDP

17

(3) Underinvestment – Amount of R&D

198.2%

99.1%

73.5% 70.9%

50.2%

28.8%24.0%

15.5%

0%

50%

100%

150%

200%

250%

China Singapore Finland Taiwan South Korea Germany Japan United States

Changes in National R&D Intensity, 1995-2009

Gregory Tassey, “Beyond the Business Cycle: The Need for a Technology-Based Growth Strategy,” Science and Public Policy (forthcoming). Data from OECD, Main Science and Technology Indicators, 2010/1. 18

(3) Underinvestment – Amount of R&D

26%

32%

41% 42%

49%

52%

58%

0%

10%

20%

30%

40%

50%

60%

70%

Australia Canada United Kingdom United States Japan Korea Germany

Source: OECD STAN Indicators 2009, "Value-added shares relative to manufacturing," Percent of manufacturing sector with 3% or greater R&D intensity, http://stats.oecd.org/index.aspx?r=228903

Shares of Domestic Manufacturing Value Added from Moderate and High R&D-Intensive Industries

19

(3) Underinvestment – Technology Intensity

-40

-30

-20

-10

0

10

20

30

40

50

60

70

1993 1995 1997 1999 2001 2003 2005 2007 2009 2011

Long-Term (“Technology Platform Research”)

Short-Term (“Current Life-Cycle Applications”)

The “Valley of Death” (New Technology Platforms) is Getting Wider Trends in Short-Term vs. Long-Term US Industry R&D, 1993-2011

Gregory Tassey, “Beyond the Business Cycle: The Need for a Technology-Based Growth Strategy,” Science and Public Policy (forthcoming). Compiled from the Industrial Research Institute’s annual surveys of member companies.

“Sea Change” Index

20

(3) Underinvestment – Composition of R&D

108.8%

84.9%

107.8%

167.7%

14.6%

26.5%

0%

20%

40%

60%

80%

100%

120%

140%

160%

180%

1960-70 1970-80 1980-90 1990-00 2000-10 2009-2011

Fixed Private Investment in Hardware & Software (growth by decade in 2005 dollars)

Source: Gregory Tassey, “Beyond the Business Cycle: The Need for a Technology-Based Growth Strategy,” (Science and Public Policy, 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) 21

(3) Underinvestment – Capital Formation

Science Base

Strategic

PlanningProduction

Market

Development

Value

Added

Entrepreneurial

Activity

“Black Box” Model of a Technology-Based Industry

Proprietary

Technology

Value

Added

Private Good Public Good

Basic Research

Applied Research

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

(4) Causes of Underinvestment – Conventional Wisdom

23

Neoclassical economics ignores market failure

rationales for government support of STID policies:

Excessive risk (increase costs)

Knowledge spillovers (reduce benefits)

Long development time (reduce benefits)

Economies of scope (reduce benefits)

Prices spillovers (reduce benefits)

Information asymmetries (increase costs)

Coordination inefficiencies (increase costs)

(4) Causes of Underinvestment – Market Failure

24

R&D

Cycle

Commercial Products

Technology Platforms: Overcoming the Early-Phase R&D Risk Spike

Risk

Basic

Research

Technology Platform

Research

Applied Research

and Development

6 years10 years Commercialization

R0

Science Base

Source: Gregory Tassey, “Underinvestment in Public Good Technologies”, Journal of Technology Transfer 30: 1/2 (January, 2005); and,

“Modeling and Measuring the Economic Roles of Technology Infrastructure,” Economics of Innovation and New Technology 17 (October, 2008)

Measurement &

Standards Infrastructure

“Valley of Death”

Risk

Spike

(4) Causes of Underinvestment – Composition of R&D

Safety

Seller Buyer

Quality

Environment

Privacy

SecurityInteroperability

Reliability

Performance

Infratechnologies for Efficient Transactions in High-Tech Markets

Market Interface

25 G. Tassey, The Technology Imperative, Edward Elgar, 2007

(4) Causes of Underinvestment – Composition of R&D

26

Federal R&D Portfolio is not Optimized for Economic Growth

Historical focus has and continues to be on “mission” R&D programs (national objectives such as defense, health, energy, space, environmental)—90 percent of federal R&D

National defense and health account for 81 percent of the federal R&D budget

Using NAICS codes to track federally funded R&D performed by industry,

75 percent of federal R&D allocated to the manufacturing sector goes to two NAICS 4-digit industries: aerospace and instruments

These two industries account for 15 percent of company-funded R&D and about 10 percent of high-tech value added

Policy Implication: While economic activity is stimulated by this skewed funding strategy, the federal portfolio is not close to being optimized for economic growth

Example: “technology platform” (proof-of-concept) research

Defense (DARPA): $3.1 billion

Energy (ARPA-e): $400 million

General economic growth (NIST’s ATP/TIP): $60 million Sources: National Science Foundation: Federal R&D Funding by Budget Function, FY 2008-10, Table 2; Science and Engineering Indicators 2010, Appendix Table 4-13; Bureau of Economic Analysis R&D Satellite Account

(4) Causes of Underinvestment – Composition of R&D

gProduction

Market

Development

EntrepreneurialActivity

Proprietary

Technologies

Proprietary

Technologies

Science Base

Technology-Element Model

Value

Added

Gregory Tassey, The Technology Imperative, 2007; and, “The Disaggregated Technology Production Function: A New Model of

Corporate and University Research,” Research Policy, 2005.

Strategic

Planning

Risk Reduction

System

Integration

Technology

PlatformsPrivate Good

Public Good

Quasi-Public

Good

27

(5) Policy Response – Technology-Element Growth Model

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

(5) Policy Response – Technology-Element Growth Model

Application of the Technology-Element Model: Nanotechnology Platforms

Science Base

Infratechnologies

Technology Platforms Product Process

Commercial Products

carbon-based nanomaterials

cellulosic nanomaterials

magnetic nanostructures

molecular nanoelectronic materials

quantum dots optical

metamaterials solid-state

quantum-effect nanostructures

functionalized fluorescent nanocrystals

quantum-confined structures

biological detection and analysis tools

in silico modeling & simulation tools

in-line measurement techniques to enable closed-loop process control

sub-nanometer microscopy

high-resolution nanoparticle detection

thermally stable nanocatalysts for high-temperature reactions

carbon nanotubes dendrimers hybrid nanoelectronic

devices ultra-low-power

devices self-powered

nanowire devices nanoparticle

fluorescent labels for cell cultures and diagnostics

metal nanoparticles & conductive polymers for soldering/bonding

nanoparticle sensors

epitaxy nanoimprint

lithography nanoparticle

manufacture rapid curing

techniques self-assembling &

self-organizing processes

scalable deposition method for polymer-fullerene photovoltaics

inkjet processes for printable electronics

purification of fluids with nanomaterials

roll-to-roll processing

hardened nanomaterials for machining/drilling

flame-retardant nanocoatings

sporting goods solar cells sunscreen/cosmetics targeted delivery of

anticancer therapies biodegradable and

lipid-based drug delivery systems

self-repairing & long-life wood composites

anti-microbial coatings for medical devices

nanoscale motion microscopes

Mixed Technology Goods Public

Technology Goods

Private

Technology Goods

29

Policy Imperative: Increase Investment in Science, Technology, Innovation, and Diffusion (STID)

New roles for governments

Compete as much as private companies

Future roles will be more complex rather than larger

Must manage the entire technology life cycle

Major real asset categories determining competitiveness:

Technology (intellectual capital)

Skilled labor (human capital)

Hardware and software (non-human capital)

Technical infrastructure (public capital)

Industry structure & behavior (organizational capital)

(5) Policy Response – R&D Intensity and Innovative Output

Needed: Total-Technology-Life-Cycle Growth Strategy

Germany has a trade surplus in manufacturing, even though compared to the United States, it has a

Approximately same R&D intensity (2.82 percent vs. 2.90 percent for U.S.)

26 percent higher average hourly manufacturing labor compensation

Reason: Germany has more comprehensive/intensively managed STID policy

Coordinated government R&D programs

Strongly integrated R&D and manufacturing

Highly skilled labor force across all technology occupations

Optimized industry structure (support for both large firms and SMEs)

Highest % of manufacturing value added from R&D-intensive industries

Other nations using similar growth strategies

U.S. projected to fall behind EU27/AP regions in nanotech products (Lux Research)

(5) Policy Response – Technology-Element Growth Model

30

New Global

Life Cycles

Old Domestic

Life Cycles

Performance/

Price Ratio

TimeA C B

Compression of Technology Life Cycles

Raises Technical and Market Risk

31 G. Tassey, The Technology Imperative, Edward Elgar, 2007

(4) Causes of Underinvestment – Life-Cycle Mismanagement

Time

Performance/Price Ratio

Life-Cycle Acceleration: Technology Platform Development

B

C′•

•

Current

Technology

New Technology

A

•

•

D

C•

Gregory Tassey, “Rationales and Mechanisms for Revitalizing U.S. Manufacturing R&D Strategies,” Journal of Technology Transfer 35 (2010): 283-333. 32

(5) Policy Response – Technology Platforms

•A

B

New

Technology

Performance/Price Ratio

Time

••

Life Cycle Market Failure: Infratechnology

Current

Technology

CC′

•C′′

•

Source: Gregory Tassey, The Technology Imperative, Edward Elgar, 2007 33

(5) Policy Response – Infratechnologies

e.g., semiconductor industry

has ~1600 standards

Production

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

Strategic

Planning

Market

Development

Entrepreneurial

Activity

Risk

Reduction

Proprietary

Technologies

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 Labs

Direct 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

Value

Added

Scale-Up

Incentives

System

Integration

Technology

Platforms

34

(5) Policy Response – Technology-Element Growth Model

35

Summary: Complexity of Modern Manufacturing Technologies Leads to Three 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 broad sector growth objectives 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 and

IP management requirements through support for technology clusters Fund research aimed at manufacturability to overcome scaling issues Target the “other” 90% of manufacturing value added (outside NAICS 3345 and 3364) Eliminate barriers to private investment in new firms (high technical risk,

appropriability, skilled labor acquisition, and process-capability barriers)

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

management techniques Increase rates of return and shorten the R&D cycle through technology clusters Build in technology transfer through cluster design and co-located supply chain

(5) Policy Response – Technology-Element Growth Model

Summary: Major Targets of Technology-Based Growth Policy

1) Increase industry’s aggregate investment in R&D and thereby leverage the Nation’s R&D intensity

2) Increase technology platform and infratechnology R&D support in early phases of R&D cycle

3) Deliver this support through more efficient policy mechanisms

4) Foster technology infrastructures that enable market entry by SMEs and adjust over technology life cycle

5) Update and expand the educational infrastructure

6) Increase the speed and breadth of the diffusion of new technologies

7) Enable rapid scale-up to commercially efficient volumes of production

8) Improve policy management techniques through planning & evaluation

36

(5) Policy Response – Technology-Element Growth Model

Advanced Manufacturing Policy Targets and Implementation Mechanisms

Policy Target Policy Action Required Specific Targets Economic Impact

Increase aggregate

investment in R&D

• Switch to a single flat 10

percent credit

• Increase government funding

• 5 percent average R&D intensity for

manufacturing sector

• Reverse 50-year decline in Federal R&D intensity

• Recognizes complementary

roles for industry and

government

Increase amount and

efficiency of proof-of-

concept research that

results in new

technology platforms

Increase efficiency of

entire R&D cycle

• Promote joint industry-

government funding of proof-

of-concept research targeted

at broad sector growth

• Promote partnering for proof-

of-concept technology

research

• Fund infratechnology research

• Expand funding through government-wide

portfolio management mechanism

• Establish regional technology-based clusters

involving universities, government, and industry

• Government laboratories

• Removes suboptimal

portfolio structure resulting

from existing set of

individual agency portfolios

• Facilitates strategic planning,

complementary asset

sourcing, risk pooling, and

rapid diffusion of technical

knowledge

Foster effective

industry structures

and supporting

technical

infrastructures

• Ensure research consortia

within clusters include SMEs

• Improve infrastructure that

supports start-ups

• Provide interface standards early in R&D cycle

• Focus financial and technical infrastructure

support on young high-tech startups

• Provide university entrepreneur training and

incubators/accelerators

• Provide infrastructure support for distribution

• Promotes market entry by

firms of all sizes, thereby

enabling maximum product

diversity and efficient system

integration

Modernize and

expand educational

infrastructure

• Adjust college curricula

• Change roles of high schools

and community colleges

• Increased STEM support through scholarships

and career promotion

• Vocational training, apprenticeships through

clusters

• Broadens and deepens

skilled labor pool

Enable rapid scale-up

to commercially

efficient production

volumes and diversity

• Expand manufacturing process

technology infrastructure

• Accelerate capital formation &

market penetration

• Support process demonstration and actual

shared production facilities

• Provide procurement specifications through

clearing house

• Investment tax credit

• Accelerates

commercialization and

market share growth,

counteracting incentives

from Asian nations 37

(5) Policy Response – Technology-Element Growth Model

38

“Sooner or later, we sit down to

a banquet of consequences”

– Robert Louis Stevenson