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What Can We Know
about the World’s Future?:
Long-term Assessment of SocioEconomic Development
Mikhail Dmitriev
Center for Strategic Research
Moscow, 13 October 2006
ABOUT THE PROJECT
These are the very preliminary
findings of the Center for
Strategic Research on global
long-term development trends
This project is designed as a
policy oriented empirical
research, rather than a
theoretical study
2
Bird’s Eye View
on Economic Growth
-10,000
-5,000
Source: Charles Jones
0
2,000
5,000
3
Economic Growth
Before the Industrial Revolution
• Wages in Athens in 328 B.C. were roughly
the same as in Britain in 15th century
• Wages in Ancient Rome of Diocletian in
the year 302 A.D. were at least as high as
in France at the eve of the French
Revolution in 1790
• Real wage in England was nearly
unchanged from its level in 1300
4
Economic Growth
Before the Industrial Revolution
Per Capita Consumption
0
0
0
-1
19
00
17
00
15
00
13
00
11
00
85
0
20
0
-2
50
600
550
500
450
400
350
300
250
200
-1
00
0
600
550
500
450
400
350
300
250
200
1990 US Dollars
1990 US Dollars
Per Capita Consumption
Year
0
5
-2
0
0
2
0
5
8
0
0
11
0
0
13
0
0
15
0
0
17
0
0
19
Year
Source: Charles Jones
5
Economic Growth
Over the Very Long Run
• Endogenous growth theoretical
framework implies that modern
economic growth may be a
temporary deviation from the static
growth pattern
• Some of the models suggest that
fast economic growth may come to
a halt by the beginning of the next
century
6
Economic Growth
in the 20th Century and Beyond
Source: Charles Jones
7
Economic Growth During
Industrial Revolution
• Industrial revolution caused
economic divergence of the world
• Repercussions of such divergence
could still have been observed in
the second half of the 20th century
8
World Income Distribution
Source: Charles Jones
9
Divergence and Predictability
• Divergence makes long-term global
development less predictable
• In divergence phase the outcome of
global development is decided
mainly by the fast growing frontier
economies
• Anything beyond the productivity
frontier is difficult to predict from
the evidence of the past
10
Convergence and Modern Growth
•
Initial economic divergence
during Industrial Revolution
created vast convergence
opportunities
• These opportunities now
come into being at a global
scale
11
Global Income Distribution since 1960
0.7
0.6
0.5
1960
1970
1980
1990
2000
0.4
0.3
0.2
0.1
0
100
1000
10000
Source: Center for Strategic Research
100000
12
Convergence and Modern Growth
• Convergence makes long-term global
development more predictable
• During convergence the outcome of
global development is determined to
much extend by economies which are
catching up
• In the modern world over two thirds of
incremental value added is created deep
inside the productivity frontier (China
alone is creating twice as much
13
incremental value added as the US)
Convergence and Predictability
• Socio-economic development inside
the frontier is easier to predict from
the past experience
• The long-term progress of frontier
economies is still difficult to predict
but they are mature and less dynamic
than in the past
• In the next two decades many of them
may not necessarily go too far beyond
the modern frontier
14
Convergence and Predictability
Luxemburg
Russia I
GDPppp
USA,
Norway
Russia II
Russia II
Portugal
Mexico
Source: Vladimir Mau
15
Convergence
and Predictability
For the time being,
world may become a
more predictable place
16
Socio-Economic indicators
Indicators
1
Political rights
2
Civil liberties
3
Voice and accountability
4
Political instability and violence
5
Government effectiveness
6
Regulatory burden
7
Rule of law
8
Graft
9
Property rights index
10
Business regulation index
11
Corruption
12
Bureaucratic delays
13
Tax compliance
14
Log of infant mortality
15
Log of school attainment
16
Infrastructure quality
17
Transfers and subsidies/GDP
18
Government consumption/GDP
19
SOE index
Form of realtionship to GDP
Regression with time
effects
Linear regression
Linear regression
Source
Barro
“Determinants of
democracy”
Roumeen Islam
and Montenegro
“What determines
the quality of
institutions”
La Porta “Quality of
governance”
17
Socio-Economic indicators
Indicators
20
21
Government enterprises and investment
as a percentage of total investment
23
Top marginal tax rate
24
Size of Government
25
Legal Structure and Security of Property
Rights
26
Average annual growth of the money
supply in the last five years minus average
annual growth of real GDP in the last ten
years
Standard inflation variability in the last five
years
28
Standard inflation variability in the last five
years
29
Recent inflation rate, Freedom to own
foreign currency bank accounts
domestically and abroad
Access to Sound Money
30
Source
General government consumption
spending as a percentage of total
consumption
Transfers and subsidies as a percentage
of GDP
22
27
Form realtionship to
GDP
Регрессия с
распределенными
лагами, наши расчеты
База данных с
сайта Economic
Freedom of the
World
18
Socio-Economic indicators
Indicators
20
23
General government consumption
spending as a percentage of total
Transfers
and subsidies as a percentage
consumption
of
GDP
Government enterprises and investment
as a percentage of total investment
Top marginal tax rate
24
Size of Government
25
Legal Structure and Security of Property
Rights
Average annual growth of the money
21
22
26
27
28
29
30
Form realtionship to
GDP
Regression with time
effects
Source
Economic
Freedom of the
World
supply in the last five years minus average
Standard
inflation
variability
thelast
lastten
five
annual growth
of real
GDP ininthe
years
Standard inflation variability in the last five
years
Recent inflation rate, Freedom to own
foreign currency bank accounts
Access
to Sound
Money
domestically
and abroad
Indicators
31
Taxes on international trade
32
Regulatory trade barriers
33
34
Actual size of trade sector compared to
expected
Differencesize
between official exchange rate
35
and
black market
rate
International
capital
market controls
36
Freedom to Trade Internationally
37
Credit Market Regulations
38
Labor Market Regulations
39
Business Regulations
40
Regulation of Credit, Labor, and Business
Form of realtionship to
GDP
Source
19
Socio-Economic indicators
Indicators
41
Average years of primary schooling
42
Average years of total schooling
43
Index Gini
44
Fractionalization of GDP
45
Corruption
46
47
Share of slum dwellers in urban
population
CO2emission,
48
Waterpollution
49
HIV
50
Malaria
51
Tuberculosis
52
Global Insight risk ratings
53
Poverty headcount
54
Poverty headcount in percent of total
population
Number of terrorist attacks
55
56
Genocide and other indicatiors of political
violence
Form of realtionship to
GDP
Linear regression
Source
Barro-Lee
CSR
Regression with
thresholds
Nonlinear regression
Regression with
thresholds
Regression with
thresholds
Regression with nonlinear effects
Regression with
thresholds
Transparency
International, CSR
UN-Habitat
World Development
Indicators, CSR
Global Insight,
CSR
Abadie “Poverty,
Political Freedom
and the Roots of
Terrorism”
Peace
and Conflict
biannual Reports,
20
Socio-Economic indicators
• All in all, we considered about 100
different economic, social, and
political indicators
• They cover a broad array of issues,
including:
•
•
•
•
•
•
•
The state of public and private institutions
Public finance
Business and financial risks
Trade openness
Political system and political stability
Health, education, and environment
Poverty, and social exclusion
21
Socio-Economic indicators
• Almost all indicators from our
sample have a strong statistical
relationship to GDP per capita
• Some of these indicators have a
high probability to stay within
certain value range below (above)
certain GDP thresholds
22
Socio-Economic indicators
Political Rights
8
7
6
5
4
3
2
1
0
0
5000
10000
15000
Political rights
20000
25000
Полиномиальный (Political rights)
30000
35000
40000
23
Socio-Economic indicators
Government Effectiveness
3.00
2.00
1.00
0.00
0
5000
10000
15000
20000
25000
30000
35000
40000
-1.00
-2.00
-3.00
Government Effectiveness
Полиномиальный (Government Effectiveness)
24
Socio-Economic indicators
Corruption
3.00
2.50
2.00
1.50
1.00
0.50
0.00
0
5000
10000
15000
20000
25000
30000
35000
40000
-0.50
-1.00
-1.50
-2.00
Control of Corruption
Полиномиальный (Control of Corruption)
25
Socio-Economic indicators
Freedom to Trade Internationally
12.0
10.0
8.0
6.0
4.0
2.0
0.0
0
5000
10000
15000
Freedom to Trade Internationally
20000
25000
30000
35000
40000
Полиномиальный (Freedom to Trade Internationally)
26
Socio-Economic indicators
Global Insight Overall Country Risk
6
5
4
3
OVERRISK
OVERRISKF
2
1
0
0
10000
20000
30000
40000
50000
GDPPC
27
Socio-Economic indicators
Deaths in Military Conflicts
7
6
5
4
3
2
1
0
0
5000
10000
15000
20000
25000
30000
35000
40000
45000
Lg(number of victims)
28
Socio-Economic indicators
Water Pollution
.024
WATERPOLLUTIONPC
.020
.016
.012
.008
.004
.000
0
20000
40000
60000
GDPPC
29
Socio-Economic indicators
Cases of Tuberculosis
1000
TUBERCULOSIS
800
600
400
200
0
0
20000
40000
60000
80000
GDPPC
30
Global GDP Growth Scenario
Density, Per Capita GDP on PPP
0.7
0.6
0.5
2000
2010
2020
2030
0.4
0.3
0.2
0.1
0
100
1000
10000
100000
31
Global GDP Growth Scenario
• Our scenario of global economic
growth, as well as other available
scenarios (Goldman Sachs, BP,
Global Insight), demonstrate rapid
conditional convergence
• Hence, when we project the
indicators from our sample, they
tend to converge over time towards
developed societies,
notwithstanding of growth
scenario we use
32
Socio-Economic Projections
Political Rights
0.7
0.6
0.5
0.4
0.3
0.2
0.1
0
0-0.2
0.2-0.4
2000
0.4-0.6
2010
0.6-0.8
2020
0.8-1.0
2030
33
Socio-Economic Projections
Civil Liberties
0.45
0.4
0.35
0.3
0.25
0.2
0.15
0.1
0.05
0
0-0.2
0.2-0.4
2000
0.4-0.6
2010
0.6-0.8
2020
0.8-1.0
2030
34
Socio-Economic Projections
Political Instability
0.7
0.6
0.5
0.4
0.3
0.2
0.1
0
0-0.2
0.2-0.4
2000
0.4-0.6
2010
0.6-0.8
2020
0.8-1.0
2030
35
Socio-Economic Projections
Government Effectiveness
0.7
0.6
0.5
0.4
0.3
0.2
0.1
0
0-0.2
0.2-0.4
2000
0.4-0.6
2010
0.6-0.8
2020
0.8-1.0
2030
36
Socio-Economic Projections
Regulatory Burden
0.8
0.7
0.6
0.5
0.4
0.3
0.2
0.1
0
0-0.2
0.2-0.4
2000
0.4-0.6
2010
0.6-0.8
2020
0.8-1.0
2030
37
Socio-Economic Projections
Rule of Law
0.7
0.6
0.5
0.4
0.3
0.2
0.1
0
0-0.2
0.2-0.4
2000
0.4-0.6
2010
0.8-1.0
0.6-0.8
2020
2030
38
Socio-Economic Projections
Graft (Corruption)
0.7
0.6
0.5
0.4
0.3
0.2
0.1
0
0-0.2
0.2-0.4
2000
0.4-0.6
2010
0.6-0.8
2020
0.8-1.0
2030
39
Socio-Economic Projections
Global Insight Overall Country Risk
0.4
0.35
0.3
0.25
0.2
0.15
0.1
0.05
0
0-0.2
0.2-0.4
2000
0.4-0.6
2010
0.6-0.8
2020
0.8-1.0
2030
40
Socio-Economic Projections
Global Insight Economic Risk
0.4
0.35
0.3
0.25
0.2
0.15
0.1
0.05
0
0-0.2
0.2-0.4
2000
0.4-0.6
2010
0.6-0.8
2020
0.8-1.0
2030
41
Socio-Economic Projections
Global Insight Political Risk
0.45
0.4
0.35
0.3
0.25
0.2
0.15
0.1
0.05
0
0-0.2
0.2-0.4
2000
0.4-0.6
2010
0.6-0.8
2020
0.8-1.0
2030
42
Projections for Africa
Political Rights
0.6
0.5
0.4
0.3
0.2
0.1
0
0-0.2
0.2-0.4
2000
0.4-0.6
2010
0.6-0.8
2020
0.8-1.0
2030
43
Endogenuity Problem
i
• Strong endogenous effects mean that the
direction of causal relationship between
our indicators and economic growth
remain unclear
• Only few successful causality tests are
available from economic literature
• Whether institutions determine growth,
or vice versa, remains unclear
• We are not prepared to attack this
fundamental problem in our study
44
Endogenuity Problem
i
• We are trying to avoid this problem
by containing our objectives
• By convention, we do not intend to
predict long-term economic growth
• We are only trying to assess, how
much economic, social and political
transformation could be realistically
expected for any given growth
scenario
45
Frontier Societies
i
• The scale of almost all available
institutional indicators is
normalized to frontier societies
• It is meaningless to use these
indicators beyond the existing
productivity frontier
• Over the long run, we can tell little
or nothing on what may happen to
developed world
46
Major conclusions
• Fast economic convergence makes global
socio-economic development more
predictable over the long run
• Our approach allows to reasonably
predict socio-economic patterns only
deep inside the productivity frontier
• Our research framework does not allow
to assess:
• Long-term economic growth rates even inside
the productivity frontier
• Long-term socio-economic progress of
47
developed economies
Major conclusions
• In almost all feasible economic growth
scenarios world in 2030 is likely to become
much safer, healthier, and even happier place
to live in
• The world may become much less corrupt,
much less violent, and much more
democratic, but not necessarily much more
environmentally friendly
• Business risks worldwide may sharply
decline, economies may become more opened
and global capital market – much more
efficient and penetrating
48
The Next Steps
• These are very preliminary
findings
• Our next steps on technical
issues may include:
• Extending the pool of socioeconomic
indicators
• More panel data and tests on timeeffects
• Integration of generational value
transfers to our research framework
49
The Next Steps
• Non-technical steps:
•Mapping economic, social,
political, and security environment
for the regions of the world
•Assessment of implications for
international trade, capital, and
labor markets, global financial and
political architecture
•Review of implications for Russia
50