8/3/2019 Importance Innovation Productivity
1/58
The Importance of Innovation for Productivity
Someshwar Rao, Ashfaq Ahmad, William Horsman, Phaedra Kaptein-Russell*
Micro-Economic Policy Analysis Branch
Industry Canada
March, 2001
- The views expressed in this paper are of the authors only and do not reflect in any way those of
either Industry Canada or the Government of Canada.
8/3/2019 Importance Innovation Productivity
2/58
2
1. INTRODUCTION
Rapid technological changes, the information revolution and increasing globalization of business
activities have intensified competition among countries for export markets, capital, R&D, and skilled
people. The competitive imperative is especially critical for Canada because it depends heavily on
international trade and foreign capital and competes head on with the United States, the worlds largest
and the most dynamic economy, for capital, R&D, skilled people and high-value added activities.
In the 1990s, the growth rate of real per-capita income in Canada was significantly lower than in
other OECD countries, particularly the U.S.. The most often cited reason for the phenomenal
productivity performance in the U.S. economy is its dynamism and superior innovation record. If
innovation is the key to improving growth in productivity and living standards, it is important to examine
the key drivers of innovation and understand the nature and sources of Canada=s innovation gap.
Canada=s economic performance in the 1990's lagged far behind that of the U.S. B real incomes in
Canada are currently about 30 percent below those in the U.S.. Although Canada has achieved a 10%
annual growth in nominal merchandise exports over the1990's (from $152.1 billion in 1990 to $360.0
billion in 1999), this has been due largely to a buoyant U.S. economy and the real depreciation of the
Canadian dollar. However, we cannot rely on the weak dollar and the strong US economy to improve
the living standards and quality of life of Canadians. On the contrary, the depreciating currency may
actually erode the living standards of Canadians. The reality is that 90% of the income gap between
Canada and the U.S. is due to the productivity gap. Therefore, only superior productivity performance
8/3/2019 Importance Innovation Productivity
3/58
3
will improve Canada=s international cost competitiveness on a sustained basis, raise the standard of living
and close the real income gap between Canada and the U.S..
The research to date strongly suggests that technical progress, the embodiment of innovation, is
the fundamental determinant of longer-term productivity performance, hence international
competitiveness, living standards and quality of life. The main objective of this paper is to analyze the
linkages between innovation and productivity. Our paper hopes to shed some new light on the following
four important research questions:
What does the cross-country data show about the importance of innovation for
productivity and living standards?
How strongly is inter-industry variation in manufacturing sector productivity correlated
with the key indicators of innovation activity in Canada and the United States?
What are the major determinants of innovation?
How does Canada compare with other G-7 countries in terms of the key drivers of
innovation?
The next section (section 2) of the paper provides a conceptual framework on different
8/3/2019 Importance Innovation Productivity
4/58
4
dimensions of innovation, examines the theoretical linkages between innovation and productivity, and
discusses the foundations of various forms of innovation. In section 3, he examines the relationship
between productivity and the key indicators of innovation, both internationally and across Canadian and
U.S. manufacturing industries. In section 4, we look at the international evidence on the major
determinants of innovation. Then, we compare Canadas innovation record with that of other G-7
countries, in section 5. In the last section (section 6), we summarize the main results of our research and
examine the implications of our findings.
8/3/2019 Importance Innovation Productivity
5/58
5
2. CONCEPTUAL FRAMEWORK
Key Drivers of Productivity
Labour productivity levels and real wages are strongly positively correlated across developed
and developing countries i.e.; low wage countries such as India and Pakistan also have low labour
productivity while high wage countries such as the United States and Canada exhibit high labour
productivity (see Chart 1). This central role of productivity in determining living standards and quality of
life has given rise to an extensive literature on the factors influencing its level and growth (see Stiroh
(1999) and Elias (2000) for a survey of the literature).
Modern growth theory identifies three key
determinants of productivity growth: accumulation of
physical capital, accumulation of human capital, and
rate of innovation and technological change. It is not
appropriate, however, to consider them as separate
factors, since they interact in complex ways and are
complementary in nature. Advanced technologies are
generally incorporated in the production process to
improve productivity. But new investments in
machinery and equipment, and skills development in
8/3/2019 Importance Innovation Productivity
6/58
6
the labour force are also required to use state-of-the-art technologies effectively. In short, the quantity
and quality of these three key factors, and the way in which they are organized, managed and utilized
within a firm are what determine productivity performance.
Aside from these three key determinants, a countrys business environment also matters. In
particular, framework conditions, such as openness to trade and investment, the degree of competition in
the economy, the financial system, quality of management and intellectual property protection are
important enabling factors for improving productivity. In particular, the degree of competition in a
particular country or sector may be one of the key factors, since lack of competition reduces the
pressures on firms to adopt and use advanced technologies, re-organize workplace, rationalize
production and to improve productivity.
Several recent papers done for Industry Canada on productivity issues provide an overview of
what economists know to date about productivity, and summarize what consensus that has emerged on
the drivers of productivity growth and the special role played by innovation. Harris (1999) literature
survey identifies three key productivity drivers: investment in machinery and equipment; human capital;
and openness to trade an investment, all within an overall framework where innovation creates the
opportunities for growth. He also identifies several other factors, including: innovation and technology
diffusion; and general purpose technologies, to name just two. Globerman (1999) focuses on literature
dealing with technological change as a key driver of productivity growth. He observes that there is a
growing perception that major technological developments in computing and telecommunications,
8/3/2019 Importance Innovation Productivity
7/58
7
including the emergence of the Internet will induce productivity growth. He identifies R&D expenditures
and patent intensities as proxies for this type of technological change. He too emphasizes the
importance of innovation for productivity. Morck and Yeung (1999), in their review of the economic
determinants of innovation, identify several key factors, including, among others: intellectual property
rights; the quality of corporate decision making; and a well-functioning financial system.
Innovation and Productivity
The link between innovation and productivity growth receives particular attention in the
literature. In fact, innovation is often thought of as the engine of growth because of its lasting long-run
effects on productivity. Although the conceptual links between innovation and productivity are strong
and clear, the relationship between the two is complex.
Innovation is a continuous process of discovery, learning and application of new technologies
and techniques from many sources. Many of
the techniques and processes are cumulative
and interdependent, and the technological
capacity of a firm may also be influenced by
external factors such as the educational
system, the research infrastructure and the
functioning of the capital markets.
In this context, innovation includes
8/3/2019 Importance Innovation Productivity
8/58
8
both fundamental and applied innovation. In addition, innovation can take the form of organizational and
marketing changes which expands demands for products, support existing structures for new methods of
production and increase the efficiency of the other types of innovative effort, leading to productivity
improvements. Although these are potentially very important for increasing productivity, in this paper we
will concentrate only on technological innovations, because of lack of data on these innovation activities
and resource constraints.
Fundamental innovation, often thought of as research proper, comprises the invention of new
products and processes. It is a familiar concept,
often measured by patents granted or active
patents, sometimes adjusted for quality. The R&D
intensity (the R&D/GPD ratio), an input measure,
is also used by many as a proxy for fundamental
innovation.
Investment in R&D and the accumulation
of human capital, especially the share of scientists and engineers in total labour force, are crucial
prerequisites for fostering fundamental innovation. Fundamental innovation also depends on the quality
of supporting institutions such as the knowledge infrastructure (universities, government labs, etc.), a
healthy business environment and sound market framework policies (competition and intellectual
property protection, etc.). They provide a favourable environment for innovative activity.
8/3/2019 Importance Innovation Productivity
9/58
9
Fundamental innovation, however, is only a small but important part of total innovative effort,
especially for a small open economy like Canada. The greater part of innovation actually consists of
applied innovation which occurs when new products or processes developed either in Canada or in
other countries, especially the United States are utilized, or when existing technologies are used in a new
context or in a new way.
Like fundamental innovation, applied innovation is also enhanced by investments in R&D and
human capital. In addition, investments in M&E and strong global links are important for the adoption
and diffusion of new innovative processes and
techniques. Finally, supporting institutions
provide positive feedback on the innovation
process.
8/3/2019 Importance Innovation Productivity
10/58
10
3. INNOVATION AND PRODUCTIVITY EMPIRICAL FINDINGS
International Evidence
The per capita real income and productivity levels vary a great deal across OECD countries.
The interesting question is whether differences in fundamental innovation activity explain the differences
in productivity and income levels among OECD countries. We used two measures of fundamental
innovation in this context: per-capita patents granted in the United States and per-capita active patents.
Since the United States is the largest and the most dynamic market in the world, the competition for
obtaining a patent in the US is intense. Therefore, per-capita patents granted in the US is expected to
be a good proxy for fundamental innovation. Similarly, active patents better reflect fundamental
innovation than patent applications or patents granted.
As expected, labour productivity levels are positively correlated with patent activity across
OECD countries (see Chart 2 and Table 1). Firstly, the gap between a countrys labour productivity
and the OECD average is positively correlated to the number of patents granted to nationals of that
country within the U.S.. Further, U.S. patents granted explains about 40% of cross national variations in
the productivity gap with the OECD, and a 10% increase in U.S. patents granted results in a 1.6%
increase in the countrys relative labour productivity. Secondly, GDP per capita is positively correlated
with domestic patents in force. The per capita patents in force explains about 76% of the cross national
variation in GDP, and a 10% increase in patents in force results in a 2.9% increase in GDP per capita.
We could not include developing countries in our sample because reliable data on labour
8/3/2019 Importance Innovation Productivity
11/58
11
productivity for these countries are not available. However, there is no reason to expect that the strong
positive relationship observed for the OECD countries will not hold for a sample of OECD and
developing countries.
The Canadian Evidence
In addition to the international evidence, we also examine the linkages between innovation and
productivity across two-digit manufacturing industries in Canada and the United States. We restrict our
analysis to only manufacturing industries, because productivity data for non-manufacturing industries
suffer from serious measurement problems. Furthermore, these industries are much more heterogeneous
than manufacturing industries. Since data on patents and adoption and use of advanced technologies for
individual manufacturing industries are not available, based on the discussion in Section 2, we used R&D
intensity, M&E intensity and human capital intensity as the key indicators of innovation activity. We use
two measures of productivity: output per employed person and total factor productivity (TFP) growth.
As expected, all three indicators of innovation are positively correlated with the labour
productivity level across Canadian manufacturing industries. Similarly, TFP growth is also significantly
positively correlated with the three innovation measures (see Charts 3 to 5). However, when the three
indicators of innovation are combined in regression analysis, the regression results are weak. (Table 2).
While human capital, M&E intensity and R&D intensity are jointly significant determinants of average
TFP growth across Canadian manufacturing industries, the adjusted R2 is low (0.24) and none of the
innovation indicators are individually significant regressors, although they are jointly significant at the 10%
level. When the innovation measures are regressed on average labour productivity the adjusted R2 is
8/3/2019 Importance Innovation Productivity
12/58
12
only 0.11 and none of the regressors are significant, individually or jointly. In addition, the coefficient on
R&D intensity is negative, although this is inconclusive as the t-statistic is very low on this variable.
These results give qualified evidence on the relationship between innovation and productivity in
Canada. While the innovation indicators do vary to a small degree in conjunction with both labour
productivity levels and TFP growth in Canada, the relationship is weak. Nor does the available evidence
from the regression analysis allow us to differentiate the independent effects of each type of innovative
activity on productivity. This is particularly true for R&D intensity which is highly correlated with human
capital in the regression on labour productivity levels. However the positive relationship between the
innovation indicators and average TFP growth imply that a one-time level increase in the innovation
activity may raise the productivity growth rate indefinitely.
The US Evidence
Like Canada, the correlation between the three innovation variables and labour productivity
level across US manufacturing industries is highly positive and statistically significant, but significantly
stronger than in Canadian industries (see Charts 6 to 8). On the other hand, the correlation between
TFP growth and three innovation measures are significantly weaker for the US industries.
The discrepancy between the Canadian and U.S. results is even more pronounced when we turn
to the regression results across U.S. manufacturing industries (Table 3). Again, average labour
productivity levels and average TFP growth were regressed on the three indicators of innovative activity:
8/3/2019 Importance Innovation Productivity
13/58
13
human capital, M&E intensity and R&D intensity. The adjusted R2 for the innovation indicators,
regressed on average labour productivity is 0.84, while the adjusted R2 when the innovation indicators
are regressed on TFP growth is -0.27. This important difference between the two countries is interesting
but puzzling. Perhaps it reflects the fact that the US is the technological leader and relies more heavily
on fundamental innovation to maintain productivity than Canada. If this is the case, then US TFP growth
could depend more on the rate of increase in fundamental innovation rather than the level of innovation.
At the same time Canada relies more heavily on the adoption and diffusion of new technologies and less
on fundamental innovation.
The regression results also provide an indication of which innovative activities have the strongest
effects on labour productivity levels across U.S. manufacturing industries. Again, in the U.S., like in
Canada, the coefficient on R&D intensity is negative. However, the existence of multicollinearity
between the variables, and the high correlation between R&D per employed person and average labour
productivity, indicates that the effect of R&D intensity on labour productivity levels is not easily
separated from other innovative activities. That said, it appears that M&E intensity has the strongest
effects on labour productivity levels among the U.S. manufacturing industries. The regression coefficients
indicate that a 10% increase in M&E intensity leads to a 4.3% increase in labour productivity, compared
to only a 0.3% increase in labour productivity for a 10% increase in human capital, all else held equal.
Thus, the most effective mechanism for increasing labour productivity across U.S. manufacturing
industries is achieved through increasing M&E intensity.
In conclusion, both the international and the Canada and US evidence strongly suggest that
8/3/2019 Importance Innovation Productivity
14/58
14
innovation is a key driver of productivity, and that of the innovative activities examined, M&E investment
has the strongest impact on productivity independent of the interactions of investment and productivity.
In addition, for Canada, the results also suggest that a one-time boost to innovative activity could
positively and permanently raise the productivity growth rate.
8/3/2019 Importance Innovation Productivity
15/58
15
4. DETERMINANTS OF INNOVATION
The previous section has investigated the extent to which labour productivity is determined by
innovative activity, both internationally, and across North American industries. This section now turns to
an analysis of the determinants of innovation with the aim of investigating what conditions support
innovative activity.
Fundamental Innovation
The creation of new technologies, products and processes can be measured by either the
outputs of the process, or inputs into it. Output can be proxied by patents granted per capita, or by
patents in force per capita. The most common input proxies are R&D intensity (the ratio of R&D to
GDP) and the human capital engaged in research (the share of R&D personnel in the total population).
While none of these measures are perfect indicators of fundamental innovation, there is a high degree of
correlation between them (Chart 9). Countries with high R&D and human capital intensities, such as the
US, Japan and Sweden, also have high per-capita fundamental innovation. On the other hand, countries
with low R&D/GDP ratios and low human capital intensities, such as Hungary and Spain, exhibit low
per-capital fundamental innovation. Canada ranks slightly below the middle of these two extremes.
Our conceptual framework also suggests that both fundamental and applied innovation are also
positively influenced by a number of important factors in the business environment, some of which have a
more concrete relationship with innovation than others. The first two examined here, intellectual property
protection and the strength of the domestic economy directly affect the returns to innovative activity. The
8/3/2019 Importance Innovation Productivity
16/58
16
others; quality of financial services, openness of the domestic economy, quality of technological
infrastructure and quality of management, have less direct effects on domestic innovation abilities.
The data on the quality of the business environment which has been used to investigate the
relationship between innovative outputs and the quality of the business climate, with the exception of
intellectual property rights, has come from the World Competitiveness Report (1999). The World
Competitiveness Report rates the quality of specific conditions across 47 economies internationally, and
uses the ratings to index and rank the economies on the general business conditions which support
competitiveness in a number of ways. The index of intellectual property rights has been obtained from a
study by Park and Ginarte (1997) which scores a countries patent protection based on characteristics of
the national patent regime.
In our empirical analysis, we find that both the direct and indirect business conditions are
positively and significantly correlated to fundamental innovation. Countries with strong intellectual
property protection also have higher levels of R&D intensity (Chart 13) and patents in force per capital,
as do countries with stronger domestic economies (Chart 14). Countries with better technological
infrastructure, as ranked by the World Competitiveness Index, also have higher R&D intensity and more
patents in force (Chart 17). Surprisingly, a more general infrastructure measure, which include both
physical as well as environmental infrastructure, is more closely correlated with the two measure of
fundamental innovation. The correlation between the general infrastructure indicator and R&D intensity
is 0.72, and between general infrastructure and patents in force is 0.83 compared to only 0.70 and 0.68
respectively for the technology infrastructure ranking. The degree of internationalization or global links,
8/3/2019 Importance Innovation Productivity
17/58
17
is also positively correlated with the two indicators of fundamental innovation across developed and
developing countries (see Chart 15). Countries with better capital market performance and higher
quality financial institutions also have higher levels of R&D intensity and more patents in force (Chart
16). A more specific measure on the availability of adequate financial resources for technological
development has a stronger relationship with R&D intensity: the correlation between R&D intensity and
financial resources for technology is 0.74.
While little can be said about the relative magnitude of variations in the direct and indirect
determinants of fundamental innovation, the cross-country regression analysis provides some indication
of the relative importance of each. Table 4 indicates that the direct determinants are capable of
explaining much more of the cross-country variation in fundamental innovation than are the less direct
variables. The two indicators of fundamental innovation, patents in force per 100,000 population and
R&D as a percentage of GDP, were each regressed on the direct determinants of innovation, (R&D
personnel per capita, intellectual property protection and strength of the domestic economy), on the
indirect determinants (internationalization, finance, technology infrastructure, and management), and on
the direct and indirect determinants together.
In the all-encompassing equation (1a), the adjusted R2 is 0.72, however only R&D personnel
per capita and the strength of patent rights are significant determinants of patent activity. Additionally, the
signs on strength of the domestic economy and internationalization are positive - the opposite of what is
expected for a ranked variable - but the t-statistics on these variables are very low. Equation (1b)
regresses R&D intensity on only the direct determinants of innovation; the adjusted R2 is 0.74, higher
8/3/2019 Importance Innovation Productivity
18/58
18
than the all inclusive equation (1a). Again, only R&D personnel per capita and patent rights have are
significant, however the sign on strength of the domestic economy is negative as expected. The
explanatory power of the less direct business environmental factors as a group is significantly lower, the
adjusted R2 is only 0.47. Of these factors, only the strength of technology infrastructure is a significant
determinant of R&D intensity.
Similar results are obtained when regressing on the other measure of fundamental innovation -
patents in force per 100,000 population. The combined explanatory power of both the innovation
specific factors and general business climate factors is high - the adjusted R2 is 0.79, and again, only
R&D personnel per capita and patent rights are significant determinants of fundamental innovation.
When only the group of direct determinants is regressed upon, the adjusted R2 does not fall significantly,
and all three of the direct conditions affecting fundamental innovation are individually significant.
However, when we regress patents in force on the indirect environmental conditions, the adjusted R2
falls to 0.63. While this implies that the indirect factors are more important for the patent activity
measure of fundamental innovation than for the R&D intensity measure, it also indicates that the indirect
environmental conditions have much less explanatory power than the direct influencers of innovation.
Within the group of business environmental factors, the only individually significant factor is, again, the
strength of technological infrastructure.
The implication of these findings is that the improvement of Canadas fundamental innovation
performance can be achieved, with the best results, by improving Canadas performance on innovative
inputs and business environmental conditions directly related to innovation. The World competitiveness
8/3/2019 Importance Innovation Productivity
19/58
19
rankings indicate that Canada has plenty of scope for improvement in these areas. (Box 1)
Box 1
Business Environment Measures Canadas Ranking
(out of 47)
Internationalisation1 24thR&D personnel per capita 16th
Technology infrastructure 6th
Finance 11th
Financial resources for technology
improvement
14th
Strength of the Domestic Economy 12th
(Out of 120)
Intellectual Property Rights 27th
Applied Innovation
Applied innovation is closely related to fundamental innovation. The two measures of
fundamental innovation, use of specialized robots in manufacturing and Internet users per capita, are
both positively correlated with R&D intensity across OECD countries (Chart 10). Countries that use
more advanced technologies have also devoted more resources to R&D spending.
1 In spite of Canadas high t rade openness, Canada ranks low on the internationalization measure partly because of its
poor export market diversification (the heavy reliance on the US market), the large current account deficit, lower share
of trade in commercial services in total trade and slower growth in FDI relative to the other countries ranked.
8/3/2019 Importance Innovation Productivity
20/58
20
Additionally, they also have stronger performance on other measures of innovation inputs. The
use of both advanced technologies are also positively correlated with high levels of human capital
measured by researchers in the labour force (Chart 11). Countries with a high proportion of researchers
in the labour force also use more robots in manufacturing and have high Internet usage. Similarly, applied
innovation is positively related to higher rates of physical investment in related capital (Chart 12). The
use of specialized robots is high in countries where a high proportion of GDP is invested in machinery
and equipment. Likewise, Internet usage is high in countries that invest a high proportion of GDP in
information and communications technologies (ICT).
Further evidence on the relationship between applied innovation and the conditions for
fundamental innovation across OECD countries can be obtained from the multiple regression analysis
reported in Table 5. The log of internet users per 1000 population has been regressed on ICT
investment intensity, researchers per capita and R&D intensity. The overall regression is significant, with
an adjusted R2 of 0.37. Of the innovation conditions, only ICT investment is a significant determinant of
internet use independent of the other innovative inputs. Additional tests of joint significance (not
reported) indicate that the number of researchers per capita also contribute to the explanation of internet
use per capita, but that R&D intensity does not. This indicates that applied innovation is affected most
strongly by innovative inputs which improve an economies ability to adopt an applied innovation, but that
fundamental innovation in the form of R&D intensity does not play a large part in determining the use of
applied innovation.
8/3/2019 Importance Innovation Productivity
21/58
21
Finally, there is limited evidence for a relationship between applied innovation and our business
environmental conditions. The quality of financial service industry is positively with the applied innovation
measure of Internet use with a the correlation coefficient of 0.52. The rank correlation between
technological infrastructure and internet use is 0.59 and between technological infrastructure and use of
robots is 0.31. Management quality is also positively associated with the applied innovation measure of
Internet use, with a correlation of 0.72.
In short, innovation is driven by a number of important factors: R&D intensity, investment in
M&E, human capital, technological infrastructure, intellectual property protection, strength of the
domestic economy, quality of financial institutions and quality of management.
8/3/2019 Importance Innovation Productivity
22/58
22
5. CANADAS INNOVATION PERFORMANCE: G7 COMPARISONS
The level of innovation in Canada lags behind the United States on most of the key indicators, and lags
behind other G7 economies on many. (Charts 19 to 25) Canada=s gross domestic expenditure on
research and development is below all G7 countries, with the exception of Italy. Canadians have a much
lower number of patents per capita in the US than either the Americans or Japanese. Similarly,
Canada=s expenditure on M&E as a percentage of GDP is the lowest in the G7. However, Canada=s
performance is better when investment in ICT as a percentage of GDP is compared across the G7;
Canada ranks third on this measure, just below the U.S.. Further, Canada does have a higher
proportion of R&D personnel than the US, but it still only ranks 4th among the G7.2
2However, Canada ranks 6th out of the G7 for the total R&D personnel in business per capita, only ah ead of
the UK.
There is some evidence that Canada=s innovation levels are catching up with the U.S. and other G7
economies. The innovation gap measured by GERD/GDP has narrowed between 1990 and 1997;
Canada=s R&D inensity grew at 1.4% per annum, while the other G7 economies experienced a decline.
Similarly, the M&E intensity grew faster than all other G7 economies, excepting the U.S, and Canada
tied with Italy with the fastest growing ICT intensity. Further Canada experienced the fastest average
8/3/2019 Importance Innovation Productivity
23/58
23
annual percentage growth in patents granted in the U.S. between 1992 and 1997. However, Canada
ranked behind the U.S., France and Italy in the average annual percentage growth of R&D personnel
per capita. Overall, the slow convergence of innovation indicators between Canada and the rest of the
G7 bodes well for future productivity performance.
Another mitigating factor, is Canada=s openness to international trade and investment. With a
lower capacity for domestic fundamental innovation than most of the G7, it is important that Canada be
open to the diffusion of innovation and knowledge developed elsewhere. In this respect, Canada has the
highest trade openness of any G7 country, and is second only to the US in FDI openness. However,
Canada=s international linkages are dominated by its economic relations with the US. Further, Canada
badly trails the US in all the key determinants of a healthy business climate: intellectual property
protection, strength of the domestic economy, quality of financial institutions and quality of management.
8/3/2019 Importance Innovation Productivity
24/58
24
6. CONCLUSION
Our empirical findings suggest that innovative activity (as measured by patents granted) is highly
positively related to productivity and per-capita income across developed and developing countries.
Similarly, across manufacturing industries, productivity levels are positively correlated with three key
drivers of innovation (R&D intensity, human capital intensity and M&E intensity) in Canada and the
United States. However, productivitygrowth is not significantly correlated with these variables.
Further, of the three key drivers of innovation, M&E investment intensity provides the strongest boost to
productivity levels.
Across countries, fundamental innovation (measured by per-capita patents granted) is positively
related to R&D spending and human capital. Similarly, applied innovation (proxied by the use of
advanced technologies) is positively influenced by R&D spending and investments in human capital and
machinery equipment. Both types of innovative activities are also determined by factors which shape the
general business climate : intellectual property rights, macro-economic conditions, global links, adequacy
of financial services infra-structure and the quality of management. However, it is determined that by far
the most effective means of promoting innovation is to focus on the technology sector specific conditions
that directly influence innovation.
Canada lags behind the US considerably, our largest trading partner and the main competitor for
investment, R&D, skilled people and high-value added activities, in terms of the three key drivers of
innovation : R&D; M&E and human capital. Canada also lags behind the US in all the key determinants
of a healthy business climate. However, Canada has made significant progress in the 1990's in closing
8/3/2019 Importance Innovation Productivity
25/58
25
the R&D gap. Furthermore, Canada leads the US in terms of openness, an important pre-condition for
an innovative economy (see Harris 2000).
These findings strongly suggest that to improve its competitive position and close the productivity
and real income gaps, Canada needs to close the R&D, M&E and human capital gaps and improve the
general business climate vis--vis the US.
8/3/2019 Importance Innovation Productivity
26/58
Wages and Productivity, 1993, International Evidence
Chart 1
* In manufacturing
Source: International Yearbook of Industrial Statistics, 1998
Log Scales, Thousand $U.S.
2 20 200
Labour productivity*
0.8
8
80
Wages*
Japan
U.S.
Germany
France
Italy
U.K.
India
Bulgaria
Indonesia
Egypt
Pakistan
Correlation Coefficient:0.90
8/3/2019 Importance Innovation Productivity
27/58
Real GDP Per Employed Person* andPatents Per Capita Granted in the U.S.
for OECD Countries, 1995
* OECD average is a weighted average based on 1996 PPPs.Source: Industry Canada compilations based on data from OECD
and U.S. Patent and Trademark Office.
0 1 2 3 4 5 6
Log (U.S. Patents Granted)/1,000,000 Inhabitants
3.5
4
4.5
5
Log(RealGDPPerEmployedPerson
%ofOECDaverage*)
Spain
U.S.
Switzlnd.
Japan
Sweden
New Zealand
HungaryCzech Rep.
Correlation Coefficient:
0.63
Luxembourg
Real GDP Per Capita* and Patent in Force PerCapita OECD Countries**
2 4 6 8 10
Log (Patents in Force/
100,000 Inhabitants, 1995)
8
9
10
11
Log(RealGDPPerCapita,1997)
* In US$ based on prices and PPPs in 1990** Excluding Italy and the U.K. for whom the data on patents in force arenot available
Source: Industry Canada compilations based on data from U.N.
Luxembourg
Mexico
U.S.Switzlnd.
Poland
Sweden
Turkey
Greece
Correlation Coefficient:0.87
Chart 2
8/3/2019 Importance Innovation Productivity
28/58
0 5 10 15 20 25
0
3
6
9
12
-3
R&D/GDPAverage Level, 1991-1995
TFP
1991-1997
R&D Intensity and Total Factor ProductivityGrowth in Manufacturing
AverageLabourProductivity:
Log(GDPPerEmployedPerson)
1991-1997
Printing &Publishing
Textile Electrical &Electronics
Refined Petroleum
& Coal Products
Rubber
Correlation Coefficient:0.31
Source: Industry Canada compilations based on Statistics Canada data
Chemicals& Chemical
Prod.
4 5 6 7 8 9 1010.2
10.4
10.6
10.8
11
11.2
11.4
11.6
Correlation Coefficient:0.35
R&D Spending per Worker and LabourProductivity Levels in Manufacturing
Transport
Log (R&D/Employed Person)Average Level, 1991-1995
Electrical &
Electronics
Refined Petrol.& Coal
Chemicals
& Chemical
Prod.
Printing &Publishing
Beverages
Wood
Furniture &Fixtures
Wood
TransportationEqpt.
Machinery
Machinery
Rubber
FabricatedMetals
Non-MetallicMineral
Other
Mnfg.
Chart 3
8/3/2019 Importance Innovation Productivity
29/58
0 1 2 3 4
Log (M&E/GDP), 1985-1997
0
3
6
9
-3
AverageTFPGrowth
1985-1997
RubberProducts
Clothing
RefinedPetroleum
& Coal
Paper &
Allied
Correlation Coefficient:0.33
M&E Intensity and Total Factor ProductivityGrowth in Manufacturing, 1985-1997
Primary
Textiles
M&E Spending per Worker and LabourProductivity Levels in Manufacturing,
1985-1997
6 6.5 7 7.5 8 8.5 9 9.5 10
Log (M&E/Employed Person), 1985-1997
10
10.5
11
11.5
AverageLabourProductivity:
Correlation Coefficient:0.63
Paper &Allied
Chemicals
Primary
Metal
Refined
Petroleum& Coal
Beverages
Clothing
Furniture &Fixture
Source: Industry Canada compilations based on Statistics Canada data
Wood
Textile
Plastic
Machinery
Transporation
Rubber
Electrical andElectronic
Proudcuts
Chemical and ChemicalProducts
Printing,Publishing
& Allied
PrimaryMetals
Chart 4
8/3/2019 Importance Innovation Productivity
30/58
Source: Industry Canada compilations based on Statistics Canada data
Beverage
Wood
0.5 0.7 0.9 1.1 1.3 1.5
Log (Avg. share of Employees WithUniversity Degrees)
1992-1996
10
10.5
11
11.5
12
Av
erageLabourProductivity:
Human Capital Content and LabourProductivity Levels in Manufacturing
Chemical &Chemical
Products
Electrical &
Electronic s
Correlation Coefficient:0.43
Clothing
Furniture &
Fixtures
0.5 0.7 0.9 1.1 1.3 1.5
Log (Avg.share of Employees WithUniversity Degrees)
1992-1996
0
2
4
6
8
-2
-4
AverageTFPGrowth
Printing,Publishing &
Allied
Correlation Coefficient:
0.44
Chemical &Chemical
Products
Electrical &Electronic s
RefinedPetroleum &
CoalRubber
Products
Wood
Human Capital Content and Total FactorProductivity in Manufacturing
Machinery
FabricatedMetal
Plastic
Refined Petroleum & Coal
FabricatedMetal
Furniture &Fixtures
OtherManufacturing
PrimaryTextiles
Beverage
Plastics
Chart 5
8/3/2019 Importance Innovation Productivity
31/58
0 2 4 6 8 10 12 14 16
0
2
4
6
8
10
12
14
-2
-4
R&D/GDPAverage Level, 1987-1997
Average
TFP
Growth,
1987-1997
R&D Intensity and Total Factor ProductivityGrowth in U.S. Manufacturing
Electrical &Electronics
Rubber& Plastics
Correlation Coefficient:
0.22
Instruments &Related Products
Transp. Eqpt.
Chemicals
Lumber,Wood &
Furniture
Textile &Apparel
AverageLabourProductivity:
Log(GD
PPerEmployedPerson)
1987-1997
4 5 6 7 8 9 109
9.5
10
10.5
11
11.5
12
12.5
Correlation Coefficient:
0.61
Log (R&D/Employed Person)Average Level, 1987-1997
Machinery
R&D Spending per Worker and LabourProductivity Levels in U.S. Manufacturing
Source: Industry Canada compilations based on BEA data.
Petroleum &Coal
Chemicals
Paper
Other Mnfg.
Textile &
Apparel
Electrical &Electronics
Food
Lumber &Wood Rubber
& Plastics
Chart 6
8/3/2019 Importance Innovation Productivity
32/58
0 0.5 1 1.5 2 2.5 3
Log (M&E/GDP)
1987-1997
0
4
8
12
-4
AverageTFPGrowth
1987-1997
M&E Intensity and Total Factor ProductivityGrowth in U.S. Manufacturing,
1987-1997
Correlation Coefficient:0.20
Electric &Electronics
Paper
Rubber
& PlasticsTextile &Apparel
Instruments
Lumber &Wood
Leather
Tobacco
6.5 7 7.5 8 8.5 9 9.5 10 10.5
Log (M&E/Employed Person)1985-1997
9.5
10.5
11.5
12.5
13.5
AverageLabourProductivity:
M&E Spending per Worker and LabourProductivity Levels in U.S. Manufacturing,
1987-1997
Petroleum &Coal
Chemicals
Miscel.Mnfg.
Tobacco
Correlation Coefficient:
0.73
Textile &Apparel
Leather
Source: Industry Canada compilations based on BEA data.
Electric &Electronics
Furniture &Fixtures
Machinery
Petroleum &
Coal
Chart 7
8/3/2019 Importance Innovation Productivity
33/58
0 5 10 15 20 25 30 35
Log (Average share of Employees WithUniversity Degrees)
1992-1996
0
4
8
12
-4
AverageTFPGrowth
1987-1997
Human Capital and Total FactorProductivity Growth in U.S. Manufacturing,
1987-1997
Correlation Coefficient:
-0.02
Electric &Electronics
Machinery
Rubber
& Plastics
Petroleum &Coal
Textile &
Apparel
LeatherTobacco
Chemicals
0 5 10 15 20 25 30 35
Log (Average share of Employees WithUniversity Degrees)
1992-1996
9.5
10.5
11.5
12.5
13.5
Av
erageLabourProductivity:
Human Capital and Labour Productivity Levelsin U.S. Manufacturing, 1987-1997
Petroleum &Coal
Chemicals
Paper
TobaccoCorrelation Coefficient:
0.70
Textile
Lumber &
Wood
Source: Industry Canada compilations based on BEA data.
Instruments
Electrical &
Electronics
Instruments
Lumber &Wood Printing &
Publishing
Electrical &
Electronics
Chart 8
8/3/2019 Importance Innovation Productivity
34/58
0 1 2 3 4
Gross Expenditure on R&D/GDP
1
2
3
4
5
6
Lo
g(U.S.PatentsGranted/
1,000,000Inhabitants)
R&D Intensity and PatentsPer Capita Granted in the U.S., OECD
Countries, 1995
0 0.5 1 1.5 2
Log (R&D Personnel/1,000 Population, 1997)
0
1
2
3
4
5
6
Lo
g(U.S.PatentsGranted/
1,0
00,000Inhabitants,1997)
R&D Personnel Per Capita and Patents Per CapitaGranted in the U.S.
OECD Countries, 1997
Correlation Coefficient:0.80
Sweden
JapanU.S.
Hungary
Spain
New Zealand
Italy
Source: Industry Canada compilations based on datafrom U.S. Patent and Trademark Office and OECD
Correlation Coefficient:0.77
Spain
CzechRepublic
Swede
JapanU.S.
Switzerland
Hungary
Chart 9
8/3/2019 Importance Innovation Productivity
35/58
0 1 2 3 4
Gross Expenditure on R&D/GDP, 1995
2.5
3
3.5
4
4.5
5
5.5
Log(InternetUsers/1,000Inhabitants)
1997
Internet Use and R&D IntensityOECD Countries
0 0.5 1 1.5 2 2.5 3 3.5 4
Gross Expenditure on R&D/GDP
0
1.2
2.4
3.6
4.8
6
Log(Robots/10,000
M
anufacturingWorkers)
Use of Specialized Robots inManufacturing* and R&D Intensity
OECD Countries, 1995
* Number of trajectory operated and adaptive robots.
Source: Industry Canada compilations based on data from the OECD, World Industrial Robots 1996, and International Telecommunication Union
Sweden
Japan
Correlation Coefficient:
0.75
Correlation Coefficient:
0.33
S. Korea
U.S.
Finland
Germany
Poland
Hungary
Czech Rep.
Sweden
Japan
U.S.
FranceHungary
Spain
Germany
Italy
U.K.
SouthKorea
Spain
Italy
NewZealand
Chart 10
8/3/2019 Importance Innovation Productivity
36/58
0.5 1 1.5 2
log(R&D Personnel/1,000 Population, 1997)
2
2.5
3
3.5
4
4.5
5
5.5
Log(InternetUsers/1,000Inhabitants,1997)
Internet Use and Human Capital inOECD Countries
3 3.5 4 4.5
log(Researchers/10,000 labour force, 1993)
0
0.5
1
1.5
2
2.5
3
3.5
4
4.5
5
5.5
Log(Ro
bots/10,000Mfg.Workers,1995)
Correlation Coefficient:0.71 Correlation Coefficient:
0.50
Sweden
Japan
U.S.France
Hungary
U.K.
Germany
Poland &
Czech Rep.
Japan
U.S.Sweden
Finland
Australia
Switz.
Hungary
Spain
Italy
* Number of trajectory operated and adaptive robots.
Source: Industry Canada compilations based on data from the OECD, World Industrial Robots1996, and International Telecommunication Union
Use of Specialized Robots in Manufacturing* andHuman Capital Intensity in OECD Countries
Czech Rep.
FranceSpain
Chart 11
8/3/2019 Importance Innovation Productivity
37/58
1 1.5 2 2.5 3
ICT Investmentin Hardware & Software/GDP
2
4
6
Log(InternetUsers/1,000Inhabitants,1997)
Internet Use and ICT InvestmentOECD Countries, 1995
1.5 2 2.5 3
Log (M&E/GDP)
2
3
4
5
Log(Rob
ots/10,000ManufacturingWorkers
)
Use of Specialized Robots in Manufacturing*and M&E Intensity in OECD Countries, 1995
Correlation Coefficient:0.31
S. Korea
Japan
Australia
Switzlnd.
U.S.
Spain
Finland
Correlation Coefficient:
0.65
U.S.
Australia
Sweden
Spain
Italy
Ireland
France
Switzlnd.
* Number of trajectory operated and adaptive robots.Source: Industry Canada compilations based on data from the OECD, World Industrial Robots 1996, and International Telecommunication Union
Chart 12
8/3/2019 Importance Innovation Productivity
38/58
1 2 3 4 5
Intellectual property Rights, 1995
0
1
2
3
4
-1
R&DIntensity
R&D/GDP(percent)1998
India
Iceland
Sweden
U.S.
Correlation Coefficient:0.67
R&D Intensity and Index ofIntellectual Property Rights
Source: World Competitiveness Yearbook, 1999 and Park and Ginarte (1997)
1 2 3 4 5
Intellectual property Rights, 1995
0
0.5
1
1.5
2
2.5
3
3.5
Paten
tsinforceper1000residents
(logvalues)
Correlation Coefficient:0.76
Patents in Force per capita andIndex of Intellectual Property Rights
U.S.
India
Panama
Switzerland
Iceland
Ireland
Turkey
Austria
Turkey
Tunisia
Sweden
Austria
Nethl.
Chart 13
8/3/2019 Importance Innovation Productivity
39/58
0 10 20 30 40 50
Domestic Economy
World Competitivenes Index Ranking
0
10
20
30
40
50
R&D/GDP1998
RankValues
Rank Correlation:
0.56
Strength of the Domestic Economyand R&D Intensity
France
Korea
Sweden
Japan
U.S.
Ireland
Germany
U.K.
China
Slovenia
Source: World Competitiveness Yearbook, 1999
Russia
Venezuela
0 5 10 15 20 25 30 35
Domestic EconomyWorld Competitivenes Index Ranking
0
5
10
15
20
25
30
35
Pat
entsinForcePerCapita
RankValues
Rank Correlation:
0.50
Strength of the Domestic Economyand Patents in Force
Switzerland
JapanU.S.
Ireland
Germany
Iceland
Russia
India
Sweden
China
Chart 14
8/3/2019 Importance Innovation Productivity
40/58
0 10 20 30 40 50
Internationalization
World Competitivenes Index Ranking
0
10
20
30
40
50
1998R&D/GDPRankValues
Rank Correlation:
0.42
Internationalization and R&D Intensity
Korea
Philippines
Japan
U.S.
Germany
U.K.
Hong Kong
Israel
Sweden
Slovenia
Source: World Competitiveness Yearbook, 1999
0 5 10 15 20 25 30 35
Internationalization
World Competitivenes Index Ranking
0
5
10
15
20
25
30
35
PerCapitaPatentsinForceRankValues
Rank Correlation:
0.60
Internationalization and Patents in Force
Korea
Sweden
Japan
U.S.
Germany
Israel
Switzerland
ChinaIndia
Nehterl.
Ireland
Poland
Mexico
Colombia
Poland
Venezuela
Indoenesia
Thailand BrazilTurkey
Malaysia
Chart 15
8/3/2019 Importance Innovation Productivity
41/58
0 10 20 30 40 50
FinanceWorld Competitivenes Index Ranking
0
10
20
30
40
50
1998R&D/GDPRankValues
Rank Correlation:0.59
Finance and R&D Intensity
Korea
SwedenJapanU.S.
Germany
U.K.
Hong Kong
Source: World Competitiveness Yearbook, 1999
0 5 10 15 20 25 30 35
FinanceWorld Competitivenes Index Ranking
0
5
10
15
20
25
30
35
PerCapitaPatentsinForce,RankValues
Rank Correlation:
0.80
Finance and Patents in Force
Korea
Sweden
Japan
U.S.
Germany
Switzerland
Venezuela
Indonesia
IndiaChina
BrazilTurkey
Malaysia
Chart 16
8/3/2019 Importance Innovation Productivity
42/58
0 10 20 30 40 50
Technological InfrastructureWorld Competitivenes Index Ranking
0
10
20
30
40
50
19
98R&D/GDP,RankValues
Rank Correlation:0.70
Technology Infrastructure and R&D Intensity
Source: World Competitiveness Yearbook, 1999
Venezuela
Japan
U.S. Germany
U.K.
Russia
Israel
0 5 10 15 20 25 30 35
Technological InfrastructureWorld Competitivenes Index Ranking
0
5
10
15
20
25
30
35
PerCapitaPatentsinForce,RankValues
Rank Correlation:
0.68
Technology Infrastructure andPatents in Force
Belgium
Japan
U.S.
Germany
Denmark
China
Switzerland
India
India
SwedenKorea
Indonesia
ThailandMalaysia
Switzlnd.
BrazilTurkeyMalaysia
Chart 17
8/3/2019 Importance Innovation Productivity
43/58
0 10 20 30 40 50
Management
World Competitivenes Index Ranking
0
10
20
30
40
50
1998R&D/GDP,RankValues Rank Correlation:
0.53
Management and R&D Intensity
Source: World Competitiveness Yearbook, 1999
Korea
SwedenJapan
U.S. Germany
Hong Kong
Slovenia
0 5 10 15 20 25 30 35
Management
World Competitivenes Index Ranking
0
5
10
15
20
25
30
35
PerCap
itaPatentsinForce,RankValues
Management and Patents in Force
Switzerland
JapanU.S.
Germany
Chile
Rank Correlation:0.70
Venezuela
Indonesia
ThailandColombia
Malaysia China
India
BrazilTurkey
Malaysia Mexico
Chart 18
8/3/2019 Importance Innovation Productivity
44/58
2.9
2.7
2.3 2.2
1.9
1.6
1.1
Japa
nU.
S.
German
y
Fran
ceU.K.
Cana
daIta
ly
Gross Domestic Expenditureon R&D (GERD)/GDP, 1997
(Percent)
Average Annual Growthof GERD/GDP Ratio, 1990-1997
(Percent)
Source: Industry Canada compilations using data from OECD, EAS (MSTI Database), April 1999 andScience Technology and Industry Outlook 1998, OECD
1.4
-0.6 -0.7-1.3
-2.5-2.9 -3.0
Cana
daU.
S.
Japa
n
Fran
ceU.K.
German
yIta
ly
Chart 19
8/3/2019 Importance Innovation Productivity
45/58
11.3 10.8 10.4
9.18.6 8.5
U.S.
Italy
U.K.
German
y
Fran
ce
Cana
da
4.9 4.8
1.7
0.1
-0.6-1.7
U.S.
Cana
daU.K.
Italy
Fran
ce
German
y
Real Investment in Machinery &Equipment (M&E)/GDP, 1998
(Percent)
Average Annual Growth ofReal M&E/GDP Ratio, 1990-1998
(Percent)
Note: Japan was excluded from G7 due to the lack of comparable data.Source: Industry Canada compilations using data from the OECD
Chart 20
8/3/2019 Importance Innovation Productivity
46/58
7.8 7.6 7.5 7.4
6.4
5.6
4.3
U.S. U.
K
Cana
da
Japa
n
Fran
ce
German
yIta
ly
ICT Expenditure on Hardware, Software andTelecommunications, 1997
(Percent of GDP)
Source: Industry Canada compilations based on OECD Science, Technology and IndustryScoreboard 1999, obtained from ADB database and World Information Technology Services
Alliance (WITSA)/ International Data Corporation (IDC), 1998
6.1
3.6
2.62.3 2.0
1.6 1.5
Japa
nIta
ly
Cana
da
Fran
ceU.K
U.S.
German
y
Average Annual Growth of Share of ICTExpenditures on Hardware, Softward andTelecommunications in GDP, 1992-1997
(Percent)
Chart 21
8/3/2019 Importance Innovation Productivity
47/58
R&D Personnel NationwidePer Capita, 1997
(Full Time Work Equivalent, '000s)
Average Annual Growth Rate of R&D PersonnelNationwide Per Capita, 1989-1997
(Percent)
7.1
5.6 5.5
4.84.4
3.7
2.5
Japa
n
German
y
Fran
ceU.K.
Cana
daU.
S.Ita
ly
1.7 1.3 1.3 1.2 1.0
-0.4
-1.8
U.S.
Fran
ceIta
ly
Cana
da
Japa
nU.K.
German
y
Source: Industry Canada compilations using data from Science Technology and Industry Outlook 1998, OECD
Chart 22
8/3/2019 Importance Innovation Productivity
48/58
Average patents granted to foreignersin the U.S., per 100,000 inhabitants,
1992-97
Average annual per cent growth of patentsgranted in the U.S.,
1992-1997
25.6
20.3
9.5 8.6
5.4 4.8
2.3
U.S.
Japa
n
German
y
Cana
da
Fran
ceU.K.
Italy
6.4
5.4 5.2
3.8 3.8
1.9 1.9
Cana
daU.K.
U.S.
German
y
Japa
n
Fran
ceIta
ly
Source: Trajtenberg, M. (2000) Is Canada Missing the Technology Boat
Chart 23
8/3/2019 Importance Innovation Productivity
49/58
50.645.6
24.3 23.719.0 18.0
7.1
U.K.
Canada
Germ
any
France US Ita
ly
Japa
n
Inward and OutwardFDI Stock/GDP, 1997
(Percent)
81.2
55.7 54.2
49.3 48.7
24.320.4
Canada
Germany UK
France Ita
ly US
Japa
n
Exports Plus Imports ofGoods and Services/GDP, 1998
(Percent)
Source: Industry Canada compilations using data from the OECD and the World Investment Report 1999,
Foreign Direct Investment and the Challenge of Development, United Nations.
Chart 24
8/3/2019 Importance Innovation Productivity
50/58
93.5
62.4 61.5 60.657.1 56.5 54.1
U.S.
Germ
any
Canada
France Ita
lyU.K
.
Japan
PatentR
ights
(Outo
f5)
4.9
4.2 4.0 3.9 3.83.6
3.2
U.S.
Italy
France
Japan
Germ
any
U.K.
Canada
Source: The world Competitiveness Yearbook 1999 and Park and Ginarte 1997
78.2
67.762.4 60.6
55.9 53.5 52.7
U.S.
Canada
Germ
any
U.K.
France
Japan
Italy
85.3
69.466.2 65.3
61.557.1
54.1
U.S.
Germ
any
Canada U.K
.
France
Japan
Italy
Strengthof
the
DomesticEco
nomy
(Outof10
0)
Management
(Outof100
)
CapitalMarketPerformance&
QualityofFinancia
lServices
(Outof100)
Chart 25
8/3/2019 Importance Innovation Productivity
51/58
Table 1
Innovation and Productivity: Cross Country Analysis
Equation 1 Equation 2
Intercept 4.01 *** Intercept 7.94 ***
25.68 41.01
Patents Granted 0.16 *** Patents in force 0.29 ***
3.72 8.75
Adjusted RSq 0.37 *** Adjusted RSq 0.75 ***
* Statistically significant at the 10% level
** Statistically significant at the 5% level
*** Statistically significant at the 1% level
Dependent variable: Ln (Real GDP per employed person
as % of OECD average)
Dependent variable: ln (Real GDP per Capita)
Patents Granted=ln(U.S. Patents Granted)/1,000,000 population Patents in Force = ln (patents in force/100,000 inhabitents)
8/3/2019 Importance Innovation Productivity
52/58
Table 2
Productivity and Inovation- Cross Industry evidence from the Canadian manufacturing sector
Equation 1 Equation 2
Intercept 9.49 *** Intercept -1.92
11.60 -0.53
Human Capital 0.50 Human Capital 1.70
1.29 0.48
M&E intensity 0.11 M&E intensity 0.82
1.05 0.89
R&D Intensity -0.01 R&D Intensity 0.21
-0.18 1.66
Adjusted RSq 0.11 Adjusted RSq 0.25 *
* Statistically significant at the 10% level
** Statistically significant at the 5% level
*** Statistically significant at the 1% level
Dependent variable: Average Labour Productivity - Ln
(GDP per employed person)
Dependent variable: Average TFP growth
Human Capital = ln (Average share of employees with university
Degrees)
M&E intensity = ln (M&E per employed person)
R&D intensity = ln (R&D per employed person)
Human Capital = ln (Average share of employees with university
Degrees)
M&E intensity = ln (M&E/GDP)
R&D intensity = ln (R&D/GDP)
8/3/2019 Importance Innovation Productivity
53/58
Table 3
Productivity and Inovation- Cross Industry evidence from the U.S. manufacturing sector
Equation 1 Equation 2
Intercept 7.83 *** Intercept 2.73
11.67 0.44
Human Capital 0.03 ** Human Capital 0.06
2.36 0.23
M&E intensity 0.43 *** M&E intensity -1.07
5.10 -0.33
R&D Intensity -0.14 R&D Intensity 0.09
-1.62 0.23
Adjusted RSq 0.84 *** Adjusted RSq -0.27
* Statistically significant at the 10% level
** Statistically significant at the 5% level
*** Statistically significant at the 1% level
Dependent variable: Average Labour Productivity - Ln
(GDP per employed person)
Dependent variable: Average TFP growth
Human Capital = ln (Average share of employees with university
Degrees)
M&E intensity = ln (M&E per employed person)
R&D intensity = ln (R&D per employed person)
Human Capital = ln (Average share of employees with university
Degrees)
M&E intensity = ln (M&E/GDP)
R&D intensity = ln (R&D/GDP)
8/3/2019 Importance Innovation Productivity
54/58
Table 4
Fundamental Innovation: Cross Country Evidence
Equation 1 Equation 2
1a 1b 1c 2a 2b 2c
Intercept -0.15 -0.51 2.51 *** Intercept 1.33 ** 0.56 3.33 ***
-0.23 -1.15 10.61 2.45 1.56 17.89
R&D personel per capita 0.24 *** 0.25 *** R&D personel per capita 0.09 ** 0.09 ***5.07 6.11 2.60 2.79
Intelectual property rights 0.27 * 0.33 *** Intelectual property rights 0.32 ** 0.47 ***
1.91 2.88 2.67 5.05
Domestic Economy 0.01 0.00 Domestic Economy 0.01 -0.02 **
0.70 -0.35 0.61 -2.19
Internationalization 0.00 -0.01 Internationalization 0.00 -0.02
0.37 -0.65 -0.29 -1.63
Finance -0.01 -0.02 Finance -0.01 -0.02
-0.54 -1.12 -0.84 -1.08
Technology Infrastructure 0.00 -0.04 *** Technology Infrastructure -0.02 -0.04 ***
-0.45 -2.96 -1.44 -2.96
Management -0.01 0.02 Management -0.01 0.01
-0.37 0.94 -0.44 0.70
Adjusted RSq 0.72 *** 0.74 *** 0.47 *** Adjusted RSq 0.79 *** 0.77 *** 0.63 ***
* Statistically significant at the 10% level
** Statistically significant at the 5% level
*** Statistically significant at the 1% level
Dependent variable: R&D intensity = (R&D/GDP*100)
Note that Domestic economy, internationalization, finance, technology infrastructure and management are rank indexes, with the strongest country ranked at 1. Thus the expected sign of
the coefficients are negative.
Dependent variable: ln (patents in force per 100,000)
8/3/2019 Importance Innovation Productivity
55/58
Table 5
Applied Innovation: Cross Country Evidence
Equation 1
Intercept 2.12 ***
3.10
ICT investment/gdp 0.72 **
2.70
Log of researchers/1000 population 0.33
0.57
R&D/GDP 0.19
0.63
Adjusted RSq 0.37 ***
* Statistically significant at the 10% level
** Statistically significant at the 5% level
*** Statistically significant at the 1% level
Dependent variable: ln (Log of internet users per 1000
inhabitents)
8/3/2019 Importance Innovation Productivity
56/58
26
Selected Bibliography
Adams, J.D. and A.B. Jaffe. 1996. Bounding of the Effects of R&D: An Investigation
Using Matched Establishment-Firm Data. Working Paper # 5544.
National Bureau of Economic Research, 1996.
Baily, M.N. and A.K. Chakrabarti. 1988.Innovation and the Productivity Crisis.
Washington: The Brookings Institution, 1988.
Baldwin, J., B. Diverty and D. Sabourin. 1996. Technology Use and Industrial
Transformation: Empirical Perspectives, in Technology, Information and Public
Policy. Edited by T.J.Courchene. Kingston: John Deutsch Institute for the Study of Economic
Policy, 1996, pp. 95-130.
Basant, R. and B. Fikkert. 1996. The Effects of R&D, Foreign Technology Purchaseand Domestic and International Spillovers on Productivity in Indian Firms. The
Review of Economics and Statistics, 78 (1996): 187-98.
Beede, D.N. and K.H. Young. 1998. Patterns of Advanced Technology Adoption and
Manufacturing Performance.Business Economics, 33, 2(1998): 43-8.
Bernard, A.B. and C.I. Jones. 1996. Productivity Across Industries and Countries:
Time Series Theory and Evidence. The Review of Economics and Statistics,
LXXVIII, 1 (1996): 135-46.
Bernstein, J.I. 1998. Inter-industry and US R&D Spillovers, Canadian Industrial
Production and Productivity Growth. Ottawa: Industry Canada,
Working Paper #19.
Bernstein, J.I. and P. Mohnen. 1998. International R&D Spillovers between U.S.
and Japanese R&D Intensive Sectors. Journal of International Economics, 44, 2
(1988): 315-38.
Bernstein, J.I. 1996. R&D and Productivity Growth in Canadian Communications
Equipment and Manufacturing. Ottawa: Industry Canada, Working Paper # 10.
Chan, S-H., J. Martin and I. Kensinger. 1990. Corporate Research and Development
Expenditures and Share Value. Journal of Financial Economics. Vol. 26. 1990.
Coe, D.T. and E. Helpman. 1995. International R&D Spillovers. European
Economic Review, 39, (1995): 859-87.
8/3/2019 Importance Innovation Productivity
57/58
27
Eicher, Theo S. 1996. Interaction between Endogenous Human Capital and
Technological Change. Review of Economic Studies. (63) (214): 127-145.
Elias, Gillian. 2000. The Innovation, Investment and Productivity Nexus: A Literature
Review. Staff Paper 2000-1, Micro-Economic Policy Analysis Branch. Industry
Canada.
Engelbrecht, H.J. 1997. International R&D Spillovers, Human Capital and
Productivity in OECD Economies: An Empirical Investigation. European Economic Review,
41, 8 (1977): 147-88.
Fagerberg, Jan. 1994. Technology and International Differences in Growth Rates.
Journal of Economic Literature. 32(3), 1147-76.
Fortin, Pierre. 1999. The Canadian Standard of Living: Is There a Way Up?
C.D. Howe Institute, Benefactors Lecture 1999. C.D. Howe Institute: Toronto
Giovanni, Dosi. 1998. Sources, Procedures, and Microeconomic Effects of
Innovation.Journal of |Economic Literature, 26(3), 1120, 1998.
Globerman, S. 1999. Linkages between Technological Change and Productivity
Growth. Western Washington University and Simon Fraser University.
Griliches, Z. 1998. Productivity Puzzles and R&D: Another Non-Explanation.
Journal of Economic Perspectives, 2, 4 (1988): 9-21.
Griliches, Z. 1998. The Econometric Evidence. Chicago: University of Chicago Press,
1998.
Harris, Richard G. 1999. Determinants of Canadian Productivity Growth: Issues and
Prospects. Paper prepared for the Centre for the Study of Living Standards
Industry Canada Conference on Canada in the 21st Century: A Time for Vision. Ottawa,
September 1999.
Lanjouw, Jean O., A Pakes and J. Putnam. 1998. How to Count Patents and Value
Intellectual Property: The Uses of Patent Renewal and Application Data.Journal of Industrial Economics. 46(4) 405-432.
Lenway, Stephanie, Randall Morck and Bernard Yeung. 1996. Rent Seeking,
Innovation and Protectionism and the American Steel Industry: An Empirical
Study. Economic Journal. March 106 (43%) 410-421.
Lichtenberg, Franck R. 1995. The Output Contributions of Computer Equipment
8/3/2019 Importance Innovation Productivity
58/58
28
And Personnel: A Firm-Level Analysis. Economics of Innovation and New
Technology, 1995, 3(3-4), 201-217.
Mankiw, N. Gregory. 1995. The Growth of Nations. Brookings Papers on
Economic Activity 1, 275-326.
Mohnen, P. 1992. The Relationship between R&D and Productivity Growth in Canada
and Other Major Industrialized Countries. Ottawa: Minister of Supply and
Services Canada, 1992.
Mitchell, Will, Randall Morck, Myles Shaver and Bernard Yeung. 1999. Causality
Between International Expansion and Investment in Intangibles, with Implications
for Financial Performance and Firm Survival. In Global Competition and
Market Entry Strategies, J-F Hennert (ed.), Elsevier, North-Holland, forthcoming.
Power, L. 1998. The Missing Link: Technology, Investment and Productivity. The
Review of Economics and Statistics, LXXX, 2 (1998): 300-13.
Rosenberg, Nathan. 1994. Exploring the Black Box: Technology, Economics, And
History. Cambridge: Cambridge U. Press, 1994.
Sharpe, Andrew. 1999. New Estimates of Manufacturing Productivity Growth for
Canada and the United States. Paper prepared for the Project on the Canada-U.S.
Manufacturing Productivity Gap, Centre for the Study of Living Standards.
Ottawa, March 1999.
Sterlacchi, A. 1989. R&D, Innovations and Total Factor Productivity Growth in British
Manufacturing. Applied Economics, 21 (1989): 1549-62.
Stiroh, Kevin J. 2000. Investment and Productivity Growth A Survey from the
Neoclassical and New Growth Perspectives. Occasional Paper # 24, April 2000.
Industry Canada Research Publications Program. Industry Canada.
Stiroh, Kevin J. 1998. Computers, Productivity and Input Substitution.Economic
Inquiry, XXXVI (1998): 175-91.
Trefler, Daniel. 1999. Does Canada Need a Productivity Budget? Policy Option, July-
August, pp. 66-71.
Von Tunzelmann, G.N. 1995. Technology and Industrial Progress: The Foundations of
Economic Growth Elgar Aldershot U K and Brook Field Vt