Transcript Sicherl Brussels October 5 2006

SICENTER
Ljubljana, Slovenia
Time is not on our side
Time Distance – A New View of
the Position of Europe
Lisbon Agenda and Technomics – The Dramatic Implications for Professional
Competence Building, Brussels, Fondation universitaire, October 5, 2006
Professor Pavle Sicherl
SICENTER and University of Ljubljana
Email: [email protected]; www.sicenter.si
Copyright © 1995-2006 P. Sicherl All rights reserved
Example: A Comparison of European and US
Economies Based on Time Distances
US-EU gaps in GDP per capita:
static index and time distance
100
US GDP per capita (2003=100)
95
90
85
Index
141
80
75
70
S-time-distance 18 years
US
65
60
55
50
EU15
45
EU15
40
US
35
1970 1972 1974 1976 1978 1980 1982 1984 1986 1988 1990 1992 1994 1996 1998 2000 2002
Time
Source: P. Sicherl, A Comparison of European and US Economies Based on Time
Distances, EUROCHAMBRES, Brussels, March 2005
The fact that
comparisons should
be made in two
dimensions has been
verified by the worldwide media interest in
my analysis for the
EUROCHAMBRES
Spring Business
Forum. The static
ratio of 1.41 does not
catch much attention,
while the time gap of
about two decades
obviously produced a
different perception of
reality. The same will
be true for comparing
within the EU.
Static measure and time distance show two very different
messages about importance of different components
EU15-US - Static Disparities (2003)
30
150
145
Time distance between the EU15 and the US
(years)
25
141
25
23
Index EU15=100
135
130
125
120
115
111
113
114
EU15 time lag in years
140
20
18
15
10
110
5
5
105
100
GDP per capita
Employment
Rate
Annual Hours
Worked
Productivity
(GDP per hour)
Percentage differences between US and
EU15 for employment rate, annual hours
worked and productivity per hour are
very similar. It seems as if the difficulty
of catching up would be similar in the
analysed components.
0
GDP per capita
Employment
Rate
Annual Hours
Worked
Productivity
(GDP per hour)
S-time-distances are very different, for
productivity per hour only 5 years, while
for employment rate and annual hours
worked are about a quarter of a century.
Policy analysis should expect different
difficulties of catching up in these fields.
Comparisons over many indicators can show characteristic profiles across
countries, regions, socio-economic groups, firms, etc.
Time distances in years between the USA and EU15 average for
selected indicators for 2003 (- time lead, + time lag for the USA)
-30
S-time-distance in years
-25
-20
-15
-10
-5
-18
-25
-23
-5
-23
0
10
10
Life
expectancy
females
Infant survival
rate
5
10
15
GDP per
capita
Employment
Rate
Annual Hours GDP per hour
Worked
R&D per
capita
economic indicators
© P. Sicherl 2005
Source: Interview with P.Sicherl - Semanario Economico, Lisbon, March 18, 2005
social indicators
EU catching-up: year in which EU catches up
with the US under various assumptions
2130
R&D Investment (R&D per capita)
2120
Income (GDP per capita)
2110
Productivity (GDP per employed)
Productivity (GDP per hour)
2100
Employment Rate
Year of catch up
2090
2080
2070
2060
2050
2040
2030
2020
2010
2000
0.5%
1%
1.5%
2%
2.5%
3%
3.5%
4%
4.5%
Assumed positive difference of EU15 growth rate over the US
Source: P. Sicherl, A Comparison of European and US Economies Based on Time Distances,
EUROCHAMBRES, Brussels, March 2005
5%
The generic idea for many other applications of S-time-distance
S-time-distance adds a second dimension to comparing
actual value with estimated value, forecast, budget, plan,
target, etc. and to evaluating goodness-of-fit in regressions,
models, forecasting and monitoring
e5
Variable X
S4
S5
e4
S2
e2
S3
S1
e1
Time
e3
What would be deviations in two dimensions from the
original Barcelona target if the new Lisbon 2 targets for
EU15 countries would be reached?
Share of R&D in GDP
(%)
Monitoring deviations of actual from path
to target in two dimensions
Implied path 1
to target 3%
Actual EU15
and
new target 2
Percentage deviation
of actual from path
to target
S-time-distance deviation
of actual from path to
target (in years)
2000
1.94
1.94
0.0%
0.0 years
2001
2.05
1.98
-2.7%
0.5 years
2002
2.15
1.98
-7.5%
1.5 years
2003
2.26
1.97
-12.3%
2.6 years
2004
2.36
1.95
-17.5%
3.9 years
2005
2.47
2.06
-16.7%
3.9 years
2006
2.58
2.17
-15.9%
3.9 years
2007
2.68
2.28
-15.2%
3.8 years
2008
2.79
2.38
-14.5%
3.8 years
2009
2.89
2.49
-13.9%
3.8 years
2010
3.00
2.60
-13.3%
3.8 years
S-time-distance in years: - actual ahead of path to target, + actual behind the path to target
Benchmarking and Monitoring of the Barcelona Target for GERD as % of GDP
3.5
Japan
Path to Target 1
3%
Share of R&D in GDP (percent)
3
USA
2.6%
2.5
EU15
2
Path to Target 2
EU25
1.5
China
1
0.5
0
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
Time
Barcelona target
EU25
EU15
US
JP
CH
Lisbon 2 target
S-time-distance between EU15 average and selected countries
for R&D per capita 2004
LU
SE
FR
DE
FI
DK
AT
BE
EU15
NL
UK
IE
SI
IT
Time series data too short
ES
40
CZ
SK
PT
PL
MT
HU
LT
LV
CY
GR
EE
35
© P. Sicherl 2006
more than 34 years
more than 34 years
more than 34 years
more than 34 years
more than 34 years
more than 34 years
more than 34 years
more than 34 years
more than 34 years
more than 34 years
30
25
20
15
10
5
0
-5
-10
-15
S-time-distance (years): - time lead, + time lag
-20
-25
-30
-35
-40
General conclusions on time distance measure
Time distance concept and statistical measure S-time-distance is:
- theoretically universal
- intuitively understandable
- immanently practical
“The usual matrix for comparing two lines involves differences along the
vertical axis. This can be a poor way of measuring how these trends vary in
terms of time which is on the horizontal axis… Sicherl’s several works have
presented a non-technical discussion of the theory of time distance…
As Sicherl (1973, 1993) proposes… observed time distance is a dynamic
measure of temporal disparity between the two series, intuitively clear, readily
measurable, and in transparent units….. ”
C.W.J. Granger and Y. Jeon, University of California at San Diego
“Time distance is a generic concept. That means that, as it has been the case
e.g. with spreadsheet, one cannot in advance specify all the uses to which a
generic framework can be put by imaginative users in numerous fields.”
J. Backhouse, Information Science Dpt., London School of Economics
SUMMARY: Benefits of immediate operational uses
of time distance
•
2.1 A new view in competitiveness issues, benchmarking, target setting and
monitoring for economic, employment, social, R&D and environment indicators at
the world, EU, country, regional, city, project, socio-economic groups, company,
household and individual levels
•
2.2 A broader dynamic framework for interrelating Lisbon strategy issues of
growth, efficiency, inequality and convergence
•
2.3 Enhanced semantics for policy analysis and public debate
•
2.4 Additional exploitation of databases and indicator systems
•
-
2.5 An excellent presentation and communication tool
among different levels of decision makers and interest groups
for describing of the situations, challenges and scenarios
for proactive discussion and presentation of policy alternatives to policy makers,
media, the general public and mobilizing those participating in or being affected
by the programs
for communicating the urgent need for change and reforms
-
Development is first and foremost
a process of learning:
• We should learn from others in and outside the EU – set
high benchmarks
• Time distance analysis presents an additional view, the gaps
may be very different in static measures and in time, an
important consideration for the Lisbon Strategy
• Namely, greater efficiency leading to greater dynamics could
also contribute to greater cohesion and to alleviating the
time distance dimension of inequality
• Knowledge based society needs reintegration of strategies of
firms, social partners and policies in different fields
(Lundvall 2000)