OECD
World
Forum
onon
Key
Indicators
OECD
World
Forum
Key
Indicators
Statistics,
Statistics,Knowledge
Knowledgeand
andPolicy
Policy
Palermo,
10-13
November
2004
Palermo,
10-13
November
2004
OECD World Forum “Statistics, Knowledge and Policy”, Palermo, 10-13 November 2004
1
THE IMPACT OF STATISTICS
ON A COMPETITIVE AND
KNOWLEDGE-BASED ECONOMY
ADELHEID BÜRGI-SCHMELZ
Director General, Swiss Federal Statistical Office
OECD World Forum “Statistics, Knowledge and Policy”, Palermo, 10-13 November 2004
2
Overview
1. Introduction
2. Success Factors
2.1 The Impact of Science and Technology
2.2 The Impact of Human Capital on the Economic Well-Being
3. The Role of Official Statistics
4. Three Examples Showing the Demand for Indicators in
Swiss Politics
4.1 Carbon Dioxide Emissions
4.2 Health Care
4.3 Swiss Universities
5. Conclusion
OECD World Forum “Statistics, Knowledge and Policy”, Palermo, 10-13 November 2004
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1. Introduction
“I love the winning, I can take the losing,
but most of all I love to play.”
(Boris Becker, 1967- )
OECD World Forum “Statistics, Knowledge and Policy”, Palermo, 10-13 November 2004
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Table 1: Growth Competitiveness Index rankings and 2003 comparisons
Source: World Economic Forum Global Competitiveness Report 2004-2005
October 13, 2004.
OECD World Forum “Statistics, Knowledge and Policy”, Palermo, 10-13 November 2004
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Figure 1: Parts (in %) of economic activities in Swiss GDP 2002
Source: Swiss Federal Statistical Office
OECD World Forum “Statistics, Knowledge and Policy”, Palermo, 10-13 November 2004
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2. Success Factors
“We want to be first; not first if,
not first but; but first!”
(John F. Kennedy, 1917-1963)
OECD World Forum “Statistics, Knowledge and Policy”, Palermo, 10-13 November 2004
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Table 2:
Patent applications to the EPO by country 1998-2001
Source: Eurostat. National Patent Indicators Statistics in focus. Science and Technology. ISSN 1609-5995. 9/2004.
OECD World Forum “Statistics, Knowledge and Policy”, Palermo, 10-13 November 2004
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Gross domestic expenditure on R&D (GERD) as a percentage of GDP
1992
1996
2000
2001
2002
Australia
Austria
Belgium
Canada
Czech Republic
Denmark
Finland
France
Germany
Greece
Hungary
Iceland
Ireland
Italy
Japan
Korea
Luxembourg
Mexico
Netherlands
New Zealand
Norway
Poland
Portugal
Slovak Republic
Spain
Sweden
Switzerland
Turkey
United Kingdom
United States
1.52
1.45
..
1.64
1.72
1.68
2.13
2.38
2.40
..
1.04
1.35
1.04
1.18
2.89
2.03
..
..
1.90
1.00
..
..
0.61
1.78
0.88
..
2.59
0.49
2.02
2.65
1.66
1.60
1.80
1.68
1.04
1.85
2.54
2.30
2.25
..
0.65
..
1.32
1.01
2.78
2.60
..
0.31
2.01
..
..
0.67
..
0.92
0.83
..
2.67
0.45
1.88
2.55
1.54
1.86
2.04
1.92
1.33
..
3.40
2.18
2.49
..
0.80
2.75
1.15
1.07
2.99
2.65
1.71
0.37
1.90
..
..
0.66
0.80
0.65
0.94
..
2.57
0.64
1.84
2.72
..
1.92
2.17
2.03
1.30
2.40
3.41
2.23
2.51
0.65
0.95
3.06
1.15
1.11
3.07
2.92
..
0.39
1.89
1.18
1.60
0.64
0.85
0.64
0.95
4.27
..
..
1.86
2.74
..
1.93
..
1.91
1.30
2.52
3.46
2.20
2.52
..
1.02
3.09
..
..
3.12
2.91
..
..
..
..
1.67
0.59
0.93
0.58
1.03
..
..
..
1.88
2.67
Japan (adj.)
2.71
b,l
..
EU-25
EU-15
..
1.87
a,b
1.71
1.80
b
b
1.80
1.88
b
b
1.83
1.92
b
b
1.83
1.93
b,p
b,p
..
..
Total OECD
2.18
b
2.12
b
2.24
b
2.28
b
2.26
b,p
..
c
d,t
c
c
d,t
c
l
g
a
a,d,t
a
a
j
c
c
c
c
d
c
a
g
a
d
c
j
c
a
c
d
c
c
g
c
m
j
..
c,p
c
d
c
g
a
m
m
j
..
2003
c,p
p
p
c
d
c
g
b
c
m
j,p
..
..
1.94
..
1.87
..
..
..
..
2.50
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
2.62
c,p
b,p
c
a
b
c
d
g
h
j
l
m
p
t
Break in series with previous year for which data is available.
Secretariat estimate or projection based on national sources.
National estimate or projection adjusted, if necessary, by the Secretariat to meet OECD norms.
Defence excluded (all or mostly)
Excluding R&D in the social sciences and humanities.
Federal or central government only.
Excludes most or all capital expenditure.
Overestimated or based on overestimated data.
Underestimated or based on underestimated data.
Provisional.
Do not correspond exactly to the OECD recommendations.
b,j,p
..
Table 3: Gross domestic expenditure on R&D as a percentage of GDP.
Source : OECD, Main Science and Technology Indicators, May 2004.
OECD World Forum “Statistics, Knowledge and Policy”, Palermo, 10-13 November 2004
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Figure 2: Summary Innovation Index
Source: European Innovation Scoreboard 2003.
http://trendchart.cordis.lu/scoreboard2003/index.html
OECD World Forum “Statistics, Knowledge and Policy”, Palermo, 10-13 November 2004
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A.11.7. Social internal rates of return (RoR) for individuals obtaining a tertiary-level degree or an advanced research qualification (ISCED 5(A, B)/6)
from an upper secondary or post-secondary non-tertiary level of education (ISCED 3/4) (2001)
RoR when the individual
immediately acquires the next
higher level of education
RoR when the individual, at age 40,
begins the next higher level of
education in full-time studies
RoR when the individual returns, at
age 40, to acquire next higher level of
education in part-time studies
(duration is doubled)
OECD
countries
Males
Females
Males
Females
Males
Females
Australia
8,3
7,6
5,5
1,7
6,9
-0,1
Denmark
4,9
3,5
2,7
0,2
3,6
-0,5
Finland
10,5
8,7
8,6
5,4
8,9
4,3
Hungary
16,1
9,1
13,4
6,6
11,6
5,1
Spain
8,1
6,7
10,2
6,2
12,3
4,9
Sweden
8,2
6,5
6,5
3,9
12,7
7,6
Switzerland
6,7
4,9
--
--
4,6
1,8
United
Kingdom
12,6
13,7
6,2
10,3
11,8
10,9
United States
11,1
7,9
8,0
3,2
7,3
0,8
Table 4:
Social internal RoR
Source: OECD. See Annex 3 for notes (www.oecd.org/edu/eag2004).
OECD World Forum “Statistics, Knowledge and Policy”, Palermo, 10-13 November 2004
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Estimating the macroeconomic returns to education
A large body of empirical research has confirmed a positive link between education and
productivity. Better educated employees are generally more productive, and may raise
the productivity of coworkers…..
Studies of the macroeconomic returns to education are methodologically diverse and
based on two broad theoretical approaches. The first, a neo-classical approach, models
the relationship between the stock of education and the long-run level of GDP. Most
studies follow this tradition. A second approach derives from “new-growth” theory and
models the relationship between the stock of education and the rate of growth of GDP.
Whether increases in the stock of education primarily affect the level of output, or its
growth rate, is still unclear. Concerning the magnitude of the returns, the available
studies indicate that in the neo-classical models a one-year increase in average
education raises the level of output per capita by between 3 and 6%. Studies of the
“new-growth” variety find that the same increase in average education raises the rate of
growth of output by around 1%.
Box 1: Estimating the macroeconomic returns to education
Source: Education at a Glance: OECD Indicators – 2004 Edition. OECD Code 962004081P1. 9/2004.
http://www.oecd.org/edu/eag2004, p. 187
OECD World Forum “Statistics, Knowledge and Policy”, Palermo, 10-13 November 2004
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3. The Role of Official Statistics
“If you have knowledge, let others
light their candle with it.”
(Winston Churchill, 1874-1965)
OECD World Forum “Statistics, Knowledge and Policy”, Palermo, 10-13 November 2004
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4. Three Examples Showing the Demand
for Indicators in Swiss Politics
“Es ist nicht genug zu wissen, man muss
es auch anwenden; es ist nicht genug zu
wollen, man muss es auch tun.”
(Johann Wolfgang von Goethe, 1749-1832)
OECD World Forum “Statistics, Knowledge and Policy”, Palermo, 10-13 November 2004
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Figure 3: Carbon Dioxide Emissions according to the CO2 Law
Source: Swiss Agency for the Environment, Forests and Landscape (SAEFL)
OECD World Forum “Statistics, Knowledge and Policy”, Palermo, 10-13 November 2004
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200
Costs per visit (in SFr.)
180
160
140
120
100
R2 = 0.59
80
60
40
20
0
0.0
0.5
1.0
1.5
2.0
2.5
3.0
Number of physicians / 1000 insured persons
AG
SG
AR
SH
BE
SO
BL
SZ
BS
TG
FR
TI
GE
UR
GL
VD
GR
VS
JU
ZG
LU
ZH
NE
AI
NW
CH
OW
Figure 4: Cost per medical visit and density of physicians – general practitioners, 2003;
Source: Datenpool Santésuisse, 4/2004. Analysis: obsan 2004.
OECD World Forum “Statistics, Knowledge and Policy”, Palermo, 10-13 November 2004
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Costs per Insured (in SFr )
600
2
R = 0.80
500
400
300
200
100
0
0.0
0.5
1.0
1.5
2.0
2.5
3.0
Number of physicians / 1000 insured persons
AG
FR
LU
SH
UR
AI
AR
GE
NE
SO
VD
CH
BE
GL
NW
SZ
VS
Linéaire (lin)
BL
GR
OW
TG
ZG
BS
JU
SG
TI
ZH
Figure 5: Number of medical visits and density of physicians – specialists, 2003;
Source: Datenpool Santésuisse, 4/2004. Analysis: obsan 2004.
OECD World Forum “Statistics, Knowledge and Policy”, Palermo, 10-13 November 2004
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5. Conclusion
“For knowledge itself is power.”
(Francis Bacon, 1561-1626)
OECD World Forum “Statistics, Knowledge and Policy”, Palermo, 10-13 November 2004
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Thank you for your
attention
OECD World Forum “Statistics, Knowledge and Policy”, Palermo, 10-13 November 2004
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