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Presentation: Regulation,
Innovation and
Technology Diffusion
Claudia Temgoua
Monika Kęszczyk
Sheng Zhong
Shuyan Di
MADE 1st Year
Faculty of Economic Sciences
University of Warsaw
Contents
1
2
3
4
Introduction
Regulation will lead to innovation
Regulation may be detrimental
Conclusions & Policy Implications
1. Introduction
Our Two Hypotheses:
(1) Regulation will lead to innovation and
technology diffusion.
VS
(2) Regulation may be detrimental to innovation.
2. Regulation will lead to innovation
Brief Review: Economic growth is a consequence
of innovation.
Firstly, according to the AK model: Y = AK
Secondly, taking into account R&D: 2 cases
•Increasing the variety of products
•Improving the quality of products
2. Regulation will lead to innovation
Increasing the variety of products
•Production will be:
• The growth is unconstrained
Improving the quality of products
•The more innovation a country has had, the
more difficult to get a new one.
•Devoting more resources to innovation
2. Regulation will lead to innovation
Empirical evidence: Acemoglu & Dell (2009)
•Data: labor incomes and household expenditure for 11
countries in the Americas (Canada, Latin America and
the U.S.)
•Methodology: dominant empirical approach: Solow
model
•Findings:
•Except human capital, the residual factors are
significant
•Given the Solow model, the determinants are
technology differences
2. Regulation will lead to innovation
?
?
Innovation &
Technology
Progress
Positive
Growth
3 ways of getting innovation: R&D spending,
saving labor and purposeful activity (for example,
trade and FDI);
But,
Regulation will affect these 3 ways;
The impact is positive.
2. Regulation will lead to innovation
Once upon a time…
In a 1991 essay in Scientific American,
Michael Porter suggested:
•
environmental regulation may have a positive effect
on the performance of domestic firms relative to
their foreign competitors by stimulating domestic
innovation.
2. Regulation will lead to innovation
Two main reasons:
①Patent issue
• More and more expensive to get innovation:
firms will weigh the pros and cons of
innovation
•
Without regulatory protection of patent, firms
prefer to invest less in R&D, in order to gain
as many benefits as possible
•
Patent protection → benefits from innovation
2. Regulation will lead to innovation
Example: Huawei Technologies Co. Ltd.
•multinational networking and telecommunications
equipment supplier
•No. 2 in the global mobile infrastructure equipment
market after Cisco
•2010 Contract orders: $30 billion
•2010 Revenue $28 billion
•2010 Net income $3.6 billion
2. Regulation will lead to innovation
Example: Huawei Technologies Co. Ltd.
•The fifth most innovative company in the world (2010),
according to Fast Company
•According to the World Intellectual Property
Organization (WIPO) in 2009, Huawei was ranked as the
largest applicant under WIPO's Patent Cooperation
Treaty (PCT), with 1737 applications.
2. Regulation will lead to innovation
Two main reasons:
② Shadow economy: less regulations, larger
size of shadow economy
•
Allocative efficiency:
• Small firms: lower production level
• Less investment on human capital
• Obstacles to foreign capital
investment and technology transfer
•
Empirical evidence: Eilat and Zinnes
(2002)
2. Regulation will lead to innovation
Two main reasons:
② Shadow economy
• Empirical evidence: Eilat and Zinnes (2002)
•
Data: 25 transition countries over the
period 1990 to 1997
•
Methodology: using MTE approach to
measure shadow economy and checking
the correlations between shadow activity
and economic variables
2. Regulation will lead to innovation
Two main reasons:
② Shadow economy
• Empirical evidence: Eilat and Zinnes
(2002)
•
Findings: shadow economy has a
significantly negative and strong
correction with competitiveness
indicator, FDI, trade indicator, human
development and labor quality.
2. Regulation will lead to innovation
More empirical studies:
•ISI Web of Knowledge database (SSCI): 1191
papers
•Sort all the papers by the numbers of being
cited (from the most to the least)
2. Regulation will lead to innovation
More empirical studies:
•Jaffe & Palmer(1997)
•Modeling:
Where PACE is pollution control costs
PACE is the name of a social survey
2. Regulation will lead to innovation
More empirical studies:
•Jaffe & Palmer(1997)
•Data: Panel data, industry level, over 1975
to 1991
•Findings: environmental regulation
compliance expenditures have a significant
positive effect on R&D expenditures
2. Regulation will lead to innovation
More empirical studies:
•King & Lenox (2000)
•Findings:
•Industry self-regulation has been
proposed as a complement to
government regulation;
•But effective industry self-regulation is
difficult to maintain without explicit
sanctions
2. Regulation will lead to innovation
Bottom line:
•Two main reasons & empirical studies:
regulation will affect 3 ways of getting
innovation.
•Environmental regulation will stimulate
certain types of innovation.
•Effective industry self-regulation is difficult to
maintain without explicit sanctions
3. Regulation may be detrimental
P1. REGULATION IS BAD FOR FIRMS IN EVERY SECTORS
P1.1 Privatization, Liberalization and Free Competition
P1.2 Regulation, Total Factor Productivity (TFP), and
Misallocation
P2. MORE SPECIFIC EVIDENCES
P2.1 Information and Communication Technology (ICT)
P2.2 Pharmaceutical Industry
P2.3 Environmental Regulation (ER)
3. Regulation may be detrimental
P1. IN EVERY SECTORS
 Giuseppe Nicoletti and Stefano Scarpetta (2003):
A negative relationship between market barriers
or State control and catch-up in technology in the
manufacturing sector.
 A more liberalized, privatized country and further
away from technology leader country, the more
benefit from innovation and so in productivity.
3. Regulation may be detrimental
P1. IN EVERY SECTORS
Regulation has an indirect influence on
growth through creation of technology gap.
NO privatization, NO liberalization and NO
free competition.
Negatively affects:
the use and allocation of inputs (resources),
the spread out of new technology,
and the promotion of innovative activities.
3. Regulation may be detrimental
P1. IN EVERY SECTORS
P1.1 Privatization
Property Rights
firm owners’ motivations and objectives.
Favor networking and collaboration
managerial innovation and spread over of
new technology.
Profits increase and cost reduction.
3. Regulation may be detrimental
P1. IN EVERY SECTORS
P1.1 Liberalization
 The lower entry barriers and state control, the faster
the process of catch-up to best-practice technologies
in manufacturing industries.
 Giuseppe Nicoletti and Stefano Scarpetta (2003),
OECD countries
 Due to liberalization: Annual Multifactor Productivity
growth rate in service industries = about 0.1-0.2
percentage points. In Greece, Portugal and Italy.
 Due to removal of trade and administrative barriers:
Annual Productivity growth rate 0.1-0.2 percentage
points. In Germany, France, Italy, Greece.
3. Regulation may be detrimental
P1. IN EVERY SECTORS
P1.1 Free Competition
Positive relation between competition and
innovative activities.
 Nickell (1996), Blundell et al. (1995,
1999) and Bassanini and Ernst (2002).
However, product market competition is
hampered by state control and barrier to
entry.
3. Regulation may be detrimental
P1.2 REGULATION, TFP, MISALLOCATION
 In the real business cycle literature, regulations
have negative impacts on productivity and TFP.
 In the literature on growth and development,
misallocation potentially reduces TFP and overall
output. Moreover, misallocation can lead to income
differences.
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3. Regulation may be detrimental
P1.2 Regulation, TFP, and Misallocation
Simple Theoretical Explanation
How may regulations be detrimental to
innovation and technology diffusion?
A toy model by Charles I. Jones (2011).
“MISALLOCATION, ECONOMIC GROWTH,
AND INPUT-OUTPUT ECONOMICS”
Cobb-Douglas function:
Where, A = TFP
3. Regulation may be detrimental
P1.2 Regulation, TFP, and Misallocation
A Toy Model
 A perfect competitive market
(1.2.1)
(1.2.2)
(1.2.3)
 Decision of the labor input allocation
(1.2.4)
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3. Regulation may be detrimental
P1.2 Regulation, TFP, and Misallocation
A Toy Model
 Solving for GDP given the allocation yields:
(1.2.5)
 where TFP is given by
(1.2.6)
 Optimal allocation of labor:
(1.2.7)
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3. Regulation may be detrimental
P1.2 Regulation, TFP, and Misallocation
A Toy Model
 If production function (1.2.3) is given in a
general form:
0<σ<1
(1.2.8)
 then TFP would be:
(1.2.9)
 To simplify, we will take
σ= 1/2
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3. Regulation may be detrimental
P1.2 Regulation, TFP, and Misallocation
A Toy Model
 Figure 1 TFP and the allocation decision in a perfect market.
[Source: Charles I. Jones (2011)]
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3. Regulation may be detrimental
P1.2 Regulation, TFP, and Misallocation
A Toy Model
 In the reality, as in Chari, Kehoe and McGrattan
(2007), Hsieh and Klenow (2009), Lagos (2006),
and Restuccia and Rogerson (2003)
Distortions, for instance, taxes and regulations at
the sectoral level can aggregate up to provide
differences in TFP.
 The decision of the planner could be twisted by
the regulations into an alternative shape
(see Figure 2)
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3. Regulation may be detrimental
P1.2 Regulation, TFP, and Misallocation
A Toy Model
Regulations among plants
 Figure 2 Regulation, TFP and the allocation decision in reality.
[Source: Charles I. Jones (2011)]
3. Regulation may be detrimental
P1.2 Regulation, TFP, and Misallocation
A Toy Model
Regulations within plants
 Figure 3 Regulation, TFP and misallocation.
[Source self made]
3. Regulation may be detrimental
P1.2 Regulation, TFP, and Misallocation
 The same change of the input factor △x
results in a larger decrease of TFP in the
present of regulations than the one without.
 Does the shift of input factor △x due to the
differences in preferences?
 NO!!!
 The difference in preferences
is an endogenous outcome.
 The misallocation is caused by
the regulations within plants.
3. Regulation may be detrimental
P1.2 Regulation, TFP, and Misallocation
 Misallocation due to the regulations within
plants maybe:
 the plant manager is not the best person for the job
(Caselli and Gennaioli, 2005);
 the most talented workers within the plant are not
promoted to the appropriate positions (Lazear, 2000);
 unionization and job protection leads the firm to use
too much labor inappropriately (Schmitz, 2005), and
so on.
Regulations may lead to misallocation.
Misallocation reduces TFP.
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3. Regulation may be detrimental
P1.2 Regulation, TFP, and Misallocation
Evidences
 Regulations have negative impact on
productivity and TFP.
 Chu (2001) and Restuccia and Rogerson (2003):
government policies (regulations) at the levels of
plants and establishments lower aggregate
productivity.
 Lagos (2006): labor market policies (regulations) lead
to misallocations of labor across firms, thus, to lower
aggregate productivity.
 Chari, Kehoe and McGrattan (2007): regulations
show up as TFP shocks.
3. Regulation may be detrimental
P1.2 Regulation, TFP, and Misallocation
Evidences
 Misallocation caused by regulations
potentially reduces TFP and overall output,
also leads to income differences.
 Hsieh and Klenow (2009): misallocation across plants
within 4-digit industries may reduce TFP in manufacturing
by a factor of two to three in China and India.
 Parente and Prescott (1999), Caselli and Gennaioli (2005),
Lagos (2006), Alfaro, Charlton and Kanczuk (2008), Buera and
Shin (2008), Guner, Ventura and Xu (2008), La Porta and
Shleifer (2008), Bartelsman, Haltiwanger and Scarpetta
(2009), Vollrath (2009), Midrigan and Xu (2010),
Moll (2010), and Syverson (2010).
3. Regulation may be detrimental
P1.2 Regulation, TFP, and Misallocation
Evidences
 Charles I. Jones (2011) - intermediate goods.
 Input-Output Economic Model with imported and
domestic intermediate goods in N sectors
 Data of 480 U.S. Industries in 1997; in 2000 inputoutput data for 35 countries and 48 industries.
 The effect of misallocation can be amplified through
the input-output structure of the economy.
 A given amount of misallocation can lead to large
income differences in different countries
at different levels of development.
3. Regulation may be detrimental
P2. More Specific Evidences
ICT Industry
Prieger (2002), USA,
Innovation difference between regulated
and unregulated scenarios
= 4.3 services per year.
The expected delay effect accounts for
much of the reduction in innovation under
the CEI regime.
3. Regulation may be detrimental
P2. More Specific Evidences
Pharmaceutical Industry
Vernon (2003), US, regulation of prices
reduces R&D and thus innovation.
Annual innovative productivity falls down by
between 67 and 73% relative to baseline
(with price regulations)
Cumulative innovative output fell by between
30 and 37%.
Price controls reduce R&D investment, and
therefore innovation.
3. Regulation may be detrimental
P2. More Specific Evidences
Environmental Regulations
 Gollop and Roberts (1983), 56 U.S. electric utilities,
1973– 1979. ----ERs reduce productivity growth
by 43%.
 Smith and Sims (1985), 4 Canadian beer breweries,
1971–1980. ----Average productivity growth:
regulated–0.08%, unregulated +1.6% .
 Gray (1987), 450 U.S. manufacturing industries,
1958–1978 ---- 30% of the decline in productivity growth
in the 1970s due to ERs
3. Regulation may be detrimental
P2. More Specific Evidences
Environmental Regulations
 Berman and Bui (2001), U.S. petroleum refining
industry, 1987–1995.
Stricter regulations imply higher abatement costs.
 Gray and Shadbegian (2003), 116 U.S. paper mills,
1979–1990.
Significant reduction in productivity associated with
abatement efforts particularly in integrated paper
mills.
3. Regulation may be detrimental
P2. More Specific Evidences
Environmental Regulations
 Rassier and Earnhart (2010), 73 U.S. chemical
firms, 1995–2001.
Tighter regulations meaningfully lower profitability.
 Lanoie et al. (2010), 4,200 manufacturing facilities
in 7 OECD countries in 2003
Tighter ER increases R&D, which improves business
performance; however, direct effect of ER is
negative, and combined impact is negative innovation offsets do not offset cost of ER
4. Conclusions
 the more a country is liberalized, the more it benefits
from innovation
 privatization is a strong basis for innovation and
spread over of new technology
 liberalization has a positive impact on innovation
and technology
 regulations have a negative impact on productivity
and Total Factor Productivity (TFP)
 misallocation caused by regulations potentially
reduces TFP
4. Conclusions
 regulation affects three ways of getting innovation:
R&D spending, saving labor and purposeful activity
 shadow economy has a negative and strong
correction with competitiveness indicator, FDI, trade
indicator, human development and labor quality
 environmental regulation compliance expenditures
have a significant positive effect on R&D
expenditures
 effective industry self-regulation is difficult to
maintain without explicit sanctions
References
•Ambec, Stefan, Mark Cohen, Stewart Elgie, and Paul Lanoie (2011). “The Porter
Hypothesis at 20: Can Environmental Regulation Enhance Innovation and
Competitiveness?” Discussion paper, RFF DP 11-01.
•Charles I. Jones (2011): Misallocation, Economic Growth, and Input-output
Economics.
•Eilat, Y. & Zinnes, C., 2002, “The shadow economy in transition countries: friend or
foe? A policy perspective”, World Development, 30(7), pp. 1233-1254.
•Hsieh, Chang-Tai and Peter J. Klen, Quarterly Journal of Economics, “Misallocation
and Manufacturing TFP in China and India,”, 2009, 124 (4), 1403–1448.
•Jaffe, A., B. & Palmer, K., 1997, “Environmental regulation and innovation: A panel
data study”, Review of Economics and Statistics, 79(4), pp. 610-619.
•King, A., A. & Lenox, M., J., 2000, “Industry self-regulation without sanctions: The
chemical industry's Responsible Care Program”, Academy of Management Journal,
43(4), pp. 698-716.
•Lagos, R. (2006): “A Model of TFP,” Review of Economic Studies, 73, 983—1007.
References
•Lanoie, P., J. Lucchetti, N. Johnstone, and S. Ambec (forthcoming), Environmental
Policy, Innovation and Performance: New Insights on the Porter Hypothesis, Journal
of Economics and Management Strategy.
•Nicoletti, G. and Scarpetta, S. (2003) "Regulation, Productivity and Growth: OECD
Evidence" , Economic policy, 2003 - Wiley Online Library.
•Prieger, (2002), “ Regulation, Innovation And The Introduction of New
Telecommunications Services”, Review of Economics and Statistics, 2002 - MIT
Press.
•Restuccia, D., and R. Rogerson (2003): “Policy Distortions and Aggregate
Productivity with Heterogeneous Plants,” Manuscript, Arizona State University.
•Vernon, J. A.(2003), “Simulating the Impact of Price Regulation on Pharmaceutical
Innovation”, Pharmaceutical Development and Regulation, 2003 –
ingentaconnect.com.
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