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Emissions Scenarios


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4.4.4. Economic Development

The SRES scenarios span a wide range of future economic growth rates (Table 4-5) and resultant levels of economic output. The A1 scenario family, with a global GDP of US$520 to 550 trillion in 2100, delineates the SRES upper bound, whereas the A2 and B2 scenarios, with a range of US$230 to 250 trillion in 2100, represent its lower bound. The B1 scenario family is intermediary. Although the SRES scenarios span a wide range, both lower and higher global GDP levels can be found in the literature (see Chapter 2).

Uncertainties in future GDP levels are governed by the rates of future productivity growth and population growth, especially those in developing countries. Different assumptions on conditions and possibilities for development "catch-up" and for narrower per capita income gaps in particular explain the wide range in projected future economic growth rates. Given the weak inverse relationship between population growth and per capita income growth discussed in Chapter 2, uncertainties in future population growth rates tend to restrict the range of associated GDP projections. High population growth, all else being equal, lowers per capita income growth, whereas low population growth tends to increase this growth. This relationship is evident in empiric data - high per capita income countries are generally also those that have completed their demographic transition. The affluent live long and generally have few children. Notable exceptions are countries with small populations and significant income from commodity exports. Yet even assuming this relationship holds for an extended time into the future, its quantification is subject to considerable theoretic and empiric uncertainties (Alcamo et al., 1995).

As outlined above, two of the SRES scenarios explicitly explore alternative pathways of the gradually closure of existing income gaps. As a reflection of uncertainty, the development "catch-up" diverges in terms of geographically distinct economic growth patterns across the four SRES scenario families, as summarized in Tables 4-5, 4-6, and 4-7. The scenarios of rapid development and "catch-up" remain in dispute within the SRES writing team because they imply high productivity growth (see Box 4-5 and, for a contrasting viewpoint and scenario interpretation, Box 4-6). However, it is agreed that such scenarios of high productivity growth and smaller income-per-capita disparities cannot be ruled out, even if they certainly are very challenging from the perspective of recent growth experiences in a number of regions, most notably Africa. There is also agreement that the assumptions deployed for the SRES scenarios are within the range suggested by the literature (see Chapter 2). In this the highest GDP growth is up to US$700 trillion by 2100 compared to US$550 trillion in the highest SRES scenario. For scenarios developed within the context of sustainability analyses, reductions in per capita income gaps also occur faster than for any of the scenarios presented here.


Table 4-5: Historical economic growth rates (% per annum) from 1950 (Maddison, 1989, 1995; UN, 1993a, 1993b), and SRES scenarios for 1990 to 2100. Growth rates were calculated on the basis of GDP at 1990 prices and market exchange ratesa . Long-term growth rates are lower than those from 1950 to 1990 (e.g., the average annual growth rate for OECD90 countries from 1850 to 1990 was about 2.8%, and for the reforming economies in Eastern Europe and the Former Soviet Union it was about 1%; Maddison, 1989). Numbers in brackets give the minimum and maximum values of all SRES scenarios.

Economic Growth Rates (% per annum)

      1990-2050     1990-2100  

Region 1950-1990  A1 A2 B1 B2 A1 A2 B1 B2

OECD90
3.9
2.0
(1.2-2.2)
1.6
(1.0-2.1)
1.8
(1.7-2.0)
1.4
(1.3-1.6)
1.8
(0.9-1.9)
1.6
(0.9-1.7)
1.5
(1.4-1.5)
1.1
(1.0-1.3)
REF
4.8
4.1
( 2.8-4.6)
2.3
(0.6-2.3)
3.1
(2.7-3.7)
3.0
(1.9-3.3)
3.1
(2.2-3.5)
2.5
(1.6-2.5)
2.7
(2.4-2.7)
2.3
(1.6-2.5)
IND
3.9
2.2
(1.4-2.4)
1.6
(1.0-2.1)
1.9
(1.8-2.0)
1.6
(1.4-1.8)
2.0
(1.1-2.1)
1.7
(1.0-1.7)
1.6
(1.5-1.6)
1.3
(1.1-1.4)
ASIA
6.4
6.2
(5.8-6.6)
3.9
(3.8-4.8)
5.5
(5.3-6.2)
5.5
(4.2-5.7)
4.5
(4.2-4.7)
3.3
(3.3-3.7)
3.9
(3.8-4.2)
3.8
(3.6-3.9)
ALM
4.0
5.5
(4.8-5.8)
3.8
(3.3-4.1)
5.0
(4.5-5.3)
4.1
(3.3-4.4)
4.1
(3.9-4.2)
3.2
(3.1-3.4)
3.7
(3.5-3.9)
3.2
(3.0-3.6)
DEV
4.8
5.9
(5.3-6.2)
3.8
(3.5-4.4)
5.2
(4.9-5.7)
4.9
(3.7-5.0)
4.3
(4.1-4.4)
3.3
(3.3-3.6)
3.8
(3.7-4.1)
3.5
(3.3-3.7)
WORLD
4.0
3.6
(2.9-3.7)
2.3
(1.7-2.8)
3.1
(2.9-3.5)
2.8
(2.1-2.9)
2.9
(2.5-3.0)
2.3
(2.0-2.3)
2.5
(2.5-2.6)
2.2
(2.0-2.3)

Note: independent rounding.

A. In the calculations the concept of logarithmic growth rates is used.

 

Table 4-6: Income per capita (1000 US dollars at 1990 prices and exchange rates) in the world and by SRES region. Numbers in brackets give minimum and maximum values of the SRES scenarios. The range for 1990 illustrates differences in base-year calibration across models.

Income per Capita by World and Regions (103 1990US$ per capita)

    2050 2100

Region 1990 A1 A2 B1 B2 A1 A2 B1 B2

OECD90
17.8-20.6
50.1
(39.4-62.3)
34.6
(32.3-54.0)
49.8
(40.3 -52.0)
39.2
(35.1-42.2)
109.2
(69.8-115.7)
58.5
(48.0-78.7)
79.7
(70.6-84.7)
61.0
(50.1-73.2)
REF
2.2-2.7
29.3
(13.5-32.5)
7.1
(3.3-9.0)
14.3
(12.4-23.4)
16.3
(7.8-16.8)
100.9
(39.9-119.3)
20.2
(13.5-20.2)
52.2
(41.2-56.4)
38.3
(14.0-38.3)
IND
12.8-14.4
44.2
(30.7-50.0)
26.1
(22.4-41.9)
39.1
(32.5-40.8)
32.5
(27.0-34.7)
107.3
(60.3-113.5)
46.2
(37.1-64.5)
72.8
(65.3-77.7)
54.4
(42.4-61.1)
ASIA
0.4-0.6
14.9
(10.8-15.7)
2.6
(2.5-4.5)
9.0
(7.2-14.3)
8.9
(3.6-9.5)
71.9
(38.8-76.8)
7.8
(7.4-12.9)
35.7
(35.7-46.1)
19.5
(14.8-20.6)
ALM
1.3-2.1
17.5
(12.2-18.0)
6.0
(4.2-6.0)
13.6
(8.0-15.3)
6.9
(4.4-7.7)
60.9
(44.2-69.5)
15.2
(11.3-15.2)
44.9
(41.3-45.8)
16.1
(13.6-22.6)
DEV
0.7-1.1
15.9
(11.4-16.7)
3.9
(3.3-5.1)
10.9
(7.5-14.8)
8.1
(3.9-8.4)
66.5
(41.4-69.8)
11.0
(10.3-13.7)
40.2
(40.2-45.2)
18.0
(14.2-21.5)
WORLD
3.7-4.0
20.8
(14.3-21.5)
7.2
(6.0-9.9)
15.6
(12.7-19.1)
11.7
(7.7-11.9)
74.9
(43.7-77.9)
16.1
(15.9-16.9)
46.6
(46.3-49.6)
22.6
(19.2-24.5)

 

Table 4-7: Growth rates (% per year) of income per capita (using GDP at 1990 prices and exchange rates) in the world and by region. Historical data from 1950 to 1990 from Maddison (1989, 1995), UN (1993a, 1993b), and Klein Goldewijk and Battjes (1995). Numbers in brackets give minimum and maximum values of all SRES scenarios.

Growth Rates of Income Per Capita (%)

    1990-2050 1990-2100

Region 1950-1990  A1 A2 B1 B2 A1 A2 B1 B2

OECD90
2.8
1.6
(1.2-1.8)
1.1
(0.8-1.6)
1.5
(1.2-1.6)
1.2
(1.0-1.4)
1.6
(1.2-1.7)
1.1
(0.8-1.2)
1.2
(1.2-1.3)
1.1
(0.9-1.3)
REF
3.7
4.0
(2.8-4.5)
1.9
(0.5-2.2)
3.0
(2.7-3.6)
3.0
(1.9-3.3)
3.3
(2.5-3.4)
2.0
(1.5-2.0)
2.8
(2.6-2.8)
2.4
(1.6-2.6)
IND
2.9
2.0
(1.3-2.1))
1.2
(0.8-1.8)
1.7
(1.5-1.8)
1.4
(1.1-1.6)
1.9
(1.3-2.0)
1.2
(0.9-1.4)
1.5
(1.4-1.5)
1.2
(1.0-1.4)
ASIA
4.4
5.5
(5.1-5.9)
2.7
(2.7-3.6)
4.8
(4.6-5.5)
4.7
(3.3-4.8)
4.4
(3.9-4.7)
2.5
(2.4-2.9)
3.9
(3.8-4.2)
3.3
(3.1-3.4)
ALM
1.6

4.0
(3.5-4.4)

1.9
(1.7-2.2)
3.5
(3.1-3.9)
2.4
(1.7-2.7)
3.3
(3.1-3.5)
1.9
(1.8-2.1)
3.0
(2.8-3.2)
2.1
(1.9-2.5)
DEV
2.7
4.9
(4.4-5.2)
2.4
(2.3-3.0)

4.2
(3.9-4.8)

3.8
(2.5-3.9)
4.0
(3.6-4.1)
2.2
(2.2-2.6)
3.5
(3.4-3.7)
2.8
(2.6-3.0)
WORLD
2.2
2.8
(2.2-2.9)
1.1
(0.7-1.5)
2.3
(2.1-2.6)
1.8
(1.1-1.9)
2.7
(2.2-2.8)
1.3
(1.3-1.5)
2.2
(2.2-2.4)
1.6
(1.4-1.7)



Important differences remain between models in terms of 1990 base-year data on economic activity levels. Even after differences in regional definitions are accounted for, 1990 regional GDP differences between models range up to ±32% in a few cases. Such differences are particularly pronounced for developing countries, where in many cases national currencies are not freely convertible and thus important uncertainties on the applicable conversion rates remain (World Bank, 1999). Differences for OECD countries are much smaller (±3% across the models) and because of their current dominance in global economic activity (and counterbalancing effects), 1990 global GDP numbers agree well across the models (±5%). Scenario comparisons, especially at the regional level, are therefore best based on a comparison of growth rates (see Chapter 2), and the SRES scenarios are no exception.

Historical data indicate that, even though the process of economic growth is heterogeneous across countries and over time, the patterns of growth show certain similarities. Economic "catch-up" follows a general dynamic pattern, characterized by initially accelerating economic growth rates that pass through a maximum, and decline once the industrial base of an economy becomes established. This overall feature of growth dynamics is reflected in all the SRES scenarios, albeit timing and magnitude vary across the four scenario families. This variation reflects the scenario-specific storylines, as well as particular relationships to other driving-force variables, such as demographics, described in the scenario.


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