Transcript Measurement of innovation, productivity and growth

Measurement of innovation,
productivity and growth
Outline:
•How can innovation be measured?
•Illustrations of innovation statistics
•Productivity at the firm, industry and
economy level
•Comparing productivity and growth across
countries
Introduction
• The basic motivation for this chapter is to convey to students that
innovation and its implications can be measured and analysed
– There are many problems in this process, but this is true across
all of economic policy
– Without measurement & analysis, understanding and policy
will be based on rhetoric, anecdote and lobbying
• Since ‘innovation’ is defined as ‘new ideas that add value’, this
automatically means that innovation is driving force behind
growth
– Clearly some authors think of technology, or human capital, as
driving growth. These are discussed more in Chap 8, but
essentially these are different perspectives on the same
process. We argue that ‘innovation’ is a better generic term.
How can innovation be measured?
• Surveys
– Chapter discusses Community Innovation Survey
(CIS), but lecturer may be able to access
local/regional/national examples
• Input measures
– R&D is main measure (see next slide)
• Output measures
– Patents and other IP
– Ultimately, productivity and growth are the
outputs
• Note that Innovation Indexes tend to mix up inputs
and outputs in very ad hoc way
% of firms involved in innovative
activities, CIS 1998-2000
Innovative
Activities (%)
Product
innovation
New-toProcess
market product innovation
innovation
Belgium
50
40
14
31
Denmark
44
37
19
26
France
41
29
10
21
Germany
61
42
13
34
Italy
36
25
14
26
Sweden
47
32
12
20
UK
36
21
6
17
R&D
• This discussion of R&D is extended in Chap. 4
• It is possible to extend this discussion here by
– Focusing on national trends, industry breakdowns
and specific firms
– In most countries there are a few major companies
that dominate absolute amount, but amount done by
smaller companies may be very important for future
growth
– Specific R&D policies (see later discussion in Chap.11
section 11.3)
– Problems of compiling real R&D measures and cross
country measures
R&D – (OECD Frascati Manual)
S
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• Basic Research: experimental/ theoretical work undertaken
primarily to acquire new knowledge of the underlying
foundations and phenomena and observable facts, without
any particular application or use in view
• Applied Research: original investigation undertaken in order
to acquire new knowledge , directed primarily towards a
specific practical aim or objective
• Experimental Development: systematic work, drawing on
existing knowledge gained from research and practical
experience, directed to producing new materials, products
and devices; to installing new processes, systems or services;
to improving substantially those already produced or
installed.
R&D in Europe, Japan and the
United States (2003, or 2002*)
Country
R&D/GDP
%
Value of R&D
(millions of euros)
Annual Growth
of R&D (%)
EU15
1.99*
149,231
4.31*
EU25
1.93*
154,941
3.98*
Germany
2.50
43,507
2.70
France
2.19
27,727
2.36
UK
1.87*
23,314
3.52*
Japan
3.12*
87,968
2.18*
USA
2.76
227,030
2.69
R&D personnel in Europe and
Japan (2004, or 2003*)
Country
R&D
personnel/
labour force
%
R&D
personnel
(in FTEs)
Share
working
in BES %
Share
working
in GOV %
Share
working
in HES %
EU25
1.49
2,040,667
53.7
14.3
31.0
EU15
1.59
1,867,505
56.2
13.2
29.5
Germany
1.85
469,100
63.5
15.3
21.1
France
1.71*
346,078*
55.8*
14.8*
27.5*
Japan
1.66*
882,414
65.8
7.0
25.4
Patent applications by domestic residents by
country (RH scale: US & Japan)
Trademark applications by domestic residents by
country (RH scale: US & Japan)
100000
30000
90000
25000
80000
70000
20000
60000
50000
15000
40000
10000
30000
20000
50000
10000
Australia
Canada
Germany
France
United Kingdom
Japan
20
04
20
02
20
00
19
98
19
96
19
94
19
92
19
90
19
88
19
86
19
84
19
82
19
80
19
78
19
76
19
74
0
19
72
19
70
0
United States of America
Productivity and growth
To measure real output we use value added
• Value added is defined as sales minus raw materials used
• Indicates what the firm has truly produced when transforming the
raw materials into the final product
• Both sales and raw materials have to be deflated for any price
inflation when measuring over time
Definitions of partial factor productivity:
• labour productivity (value added per unit of labour)
• capital productivity (value added per unit of capital)
• High labour productivity is often largely explained by high levels of
capital per worker (e.g. in mining and the steel industry)
• High capital productivity will be present when labour is used
intensively (e.g. in developing countries with scarce capital)
Measuring total factor productivity
• This measure improves on partial factor productivity by
correcting for growth in inputs
• Derivation of total factor productivity:
Suppose value added (Y) is produced by two input
factors capital (K) and labour (L) and by total factor
productivity (A) according to:
Y = A K aL b
• Then growth of TFP is calculated by residual:
gA = gY – a gK – b gL
• Growth in TFP is equal to the growth in value added, less
a times the growth in capital input and b times the
growth in labour input
Annual average growth in GDP per hour
worked (1970-2006)
Australia
Canada
France
Germany
Italy
Japan
UK
US
1970-1980
1.5
1.8
4
3.7
4
4.2
2.7
1.6
1980-1985
2.2
1.6
3.1
2.1
1.2
2.5
2.5
1.6
1985-1990
0.2
0.4
2.7
2.5
2.3
4.2
1.4
1.3
1990-1995
2
1.4
1.9
2.9
2.1
2.3
2.8
1.1
1995-2000
2.5
2.3
2.1
2
0.9
2.1
2.3
2.2
2000-2006
1.5
1
1.4
1.4
0.2
2.1
2
2.1
1970-2006
1.6
1.5
2.7
2.6
2
3
2.3
1.7
Average growth of GDP per capita in
emerging markets
Brazil
China
India
Japan
Korea
Taiwan
Thailand
1951-1960
3.93
4.11
1.57
7.54
1.03
4.44
-0.15
1961-1970
4.34
1.45
2.69
9.74
5.82
7.04
5.07
1971-1980
5.38
4.18
1.61
3.18
5.93
7.75
4.62
1981-1990
0.21
8.43
3.48
3.43
7.90
6.59
6.08
1991-2000
0.53
9.15
3.41
1.01
5.19
5.49
3.03
2001-2004
0.09
7.44
4.19
0.72
4.09
2.16
3.97
Other economic growth resources
• There is a vast amount of productivity and
economic growth data on web that could be
used to look at specific countries, periods or
industries e.g.
– National statistical agencies
– World Bank, OECD (includes regular country
studies), IMF
– The Groningen Growth and Development Centre
– Penn World Table
Possible additional topics
There are a large number of other areas that can be mentioned,
or developed, in a course, including:
– Service sector productivity (e.g. Bosworth, B. and J. Triplett
(2003). "Productivity Measurement Issues in Services
Industries: "Baumol's Disease" Has Been Cured." The
Brookings Institution, September 1.
– IT and productivity (e.g. Triplett, J. E. (1999). "The Solow
Productivity Paradox: What Do Computers Do to
Productivity?" Canadian-Journal-of-Economics 32(2)(April
1): 309-34.
– Regulation and productivity (e.g. Crafts, N. (2006).
"Regulation and Productivity Performance " Oxford Review
of Economic Policy 22(2): 186-202.
Questions
1.
2.
3.
4.
5.
6.
List the input, and output, measures of innovation. How
should one deal with so many possible measures?
“R&D is the only important measure of innovation”. Discuss.
Choose a selection of firms, or countries, and attempt to
produce a ranking or innovation scoreboard.
What is meant by partial productivity measures? Should
only total factor productivity be used?
What measurement issues should be considered when
comparing GDP per capita across countries? What about
when comparing GDP per capita through time?
What is the use of growth accounting studies?
References
Griliches, Z. (1990) ‘Patent statistics as economic
indicators: a survey’, Journal of Economic Literature,
XXVIII (December), 1661-1707.
Lipsey, R. G. and K. I. Carlaw (2004), 'Total factor
productivity and the measurement of technological
change', Canadian Journal of Economics, 37(4), 111850.
Schreyer, P. and D. Pilat (2001) "Measuring
Productivity“, OECD Economic Studies 33: 128.
The Economist (14 Nov. 2009) Economic Focus: ‘Secret
Sauce’.