Emissions Scenarios - IPCC

Scenario Driving Forces 123
0.15
0.10 -
Log (real per capita
GDP)
Figure 3-11: Residual GDP per capita growth rates as a
function of GDP per capita (log scale). The residual growth
rate is that per capita GDP growth not explained by other
factors such as education, terms-of-trade, institutional factors,
etc., in Barro's multi-factor analysis of per capita GDP
growth. Data source: Barro, 1997.
2-3% per year. It may take an economy 27 years to reach 50%
of steady-state levels (the productivity frontier) and some 90
years to achieve 90% of that level. Based on this convergence
criterion alone, it may well take a century (given all other
factors set favorably) for a poor economy to catch-up to levels
that prevail in the industrial countries today, never mind the
levels that might prevail in affluent countries 100 years in the
future. Barro's analysis indicates a threshold GDP per capita
level at approximately US$3000 per year. Below that level,
additional productivity growth potentials result from catch-up;
beyond that level, higher per capita GDP levels make further
productivity growth ever more difficult to achieve (as indicated
by the negative values of the residual GDP per capita growth
rates in Figure 3-11).
Given the wide range in historical experiences and the slow
rates of convergence suggested by neoclassic growth theory, it
is not surprising that the available scenario literature takes a
cautious view on economic catch-up. Whereas convergence
tendencies are generally evident in scenario assumptions (see
the signiñcantly higher GDP per capita growth rates for
currently developing countries compared to industrial
countries in Figure 3-10), long-term convergence rates are low.
For instance, from all six IS92 scenarios only one (IS92e)
assumes that developing countries outside China may
eventually reach present OECD income levels, and even in this
most optimistic scenario it is assumed to occur only after 2080
(Pepper et al., 1992). Even in this convergence scenario per
capita income differences remain large - a factor of five by the
end of the simulation horizon (US$31,000 per capita GDP per
year in developing countries outside China versus US$150,000
OECD average). In an influential critique Parikh (1992)
referred to the IS92 scenario series as being "unfair to the
South," a point also taken up in the evaluation of the IS92
scenarios. Alcamo et al. (1995) concluded that new IPCC
scenarios "will be needed for exploring a wide variety of
economic development pathways, for example, a closing of the
income gap between industrial and developing countries." With
a few notable exceptions (e.g., the scenario developed by
Lazarus et al. (1993) and the Case С scenarios presented in
IIASA-World Energy Conference (WEC) (IIASA-WEC,
1995) and Nakicenovic etal. (1998a)), the challenge to explore
conditions and pathways that close the income gap between
developing and industrial regions appears to have been
insufficientiy taken up in the scenario literature, a gap this
report aims to begin to fill. Chapter 4 describes two scenarios
in which the ratios between regions of GDP/capita decline and
the absolute differences increase.
3.3.4.7. Economic Productivity and Energy and Materials
Intensity
Evidence suggests that the physical input of energy or
materials per unit of monetary output (materials or energy
intensity) follows an inverted U-curve (lU hypothesis) as a
function of income. For some materials the lU-hypothesis
(Moll, 1989; Tilton, 1990) holds quite well. The underiying
explanatory factors are a mixture of structural change in the
economy along with technology and resource substitution and
innovation processes. Recent literature illustrates material
consumption that rises faster than GDP in well-developed
countries in a relationship better described as N-shaped (de
Bruyn and Opschoor, 1994; de Bruyn, et al, 1995; Suri and
Chapman, 1996; Ansuategi et al, 1997). A similar lU curve is
observed for modem, commercial energy forms (Darmstadter
et al, 1977; Goldemberg et al, 1988; Martin, 1988;
IIASA-WEC, 1995; Watson et al, 1996; Judson et al, 1999),
although the initially rising part of commercial energy
intensity stems from the substitution of traditional (inefficient)
energy fonns and technologies by modem commercial energy
forms (see also the discussion of the "environmental Kuznets
curve" for traditional air pollutants in Section 3.1, also an
inverted U-shaped curve). The resultant aggregate total
(commercial plus non-commercial) energy intensity shows a
persistent declining trend over time, especially with rising
incomes (Watson et al, 1996; Nakicenovic et al, 1998a).
Empirical evidence thus suggests that, all else being equal,
energy and materials intensities are closely related to overall
macroeconomic productivity. In other words, higher
productivity (GDP per capita) is associated with lower energy
and materials intensity (lower use of energy and materials per
unit of GDP).
Figure 3-12 shows material intensity versus per capita income
data for 13 world regions for some metals (Van Vuuren et al,
2000; see also the discussion in de Vries et al, 1994). Figure
3-13 shows a similar curve for total energy intensity (including
traditional non-commercial energy forms) for 11 world