TABLE 5-7 Estimates of Total Damage Due to Climate Change from Benchmark Warming (Percentage Change in Annual GDP)

Study

Temperature Change (°C)

Globale

United States

Range Across Regions

2.5-3.0°C warming benchmark

 

 

 

 

Nordhaus (1991)

3.0

NA

−1.0

NA

Cline (1992)

2.5

NA

−1.1

NA

Nordhaus (1994a)

3.0

−1.3

NA

NA

Nordhaus (1994b)

3.0

−1.9c

NA

NA

Fankhauser (1995b)

2.5

−1.4

−1.3

−4.7-−0.7

Tol (1995)

2.5

−1.0

−1.0

−8.7-0.3

Nordhaus and Yang (1996)

2.5

−1.7a

−1.1

−2.1-0.9

Plambeck and Hope (1996)

2.5

−2.5a

−1.6

−8.6-0.0

Nordhaus and Boyer (2000)

2.5

−1.5

−0.5

−4.9-0.7

Mendlesohn et al. (2000a,b)b,d

2.5

0.00.1

NA

−3.6-4.0a, −0.5-1.7a

Hope (2006)d

2.5

−1.0

−0.3

−3.1–0.3

Nordhaus (2006)b

3.0

−1.0

NA

NA

Nordhaus (2008)

2.5

−1.8

−0.7

−20.0–16.4

Other warming benchmarks

 

 

 

 

Titus (1992)

4.0

NA

−2.5

NA

Tol (2002b)

1.0

2.3

3.4

−4.1–3.7

NOTES: Positive damage estimates indicate benefits from warming. NA indicates data are not available.

aAs computed by Tol (2008).

bEstimate includes only market impacts; nonmarket impacts are not monetized.

cMedian estimate from an expert opinion survey of 19 individuals.

dThe study’s mean estimates are given.

eGlobal GDP losses are simple (unweighted) sums of regional GDP losses.

scenarios are benchmarked to a 2.5-3°C temperature increase by 2100 associated with central estimates of the likely warming from a doubling of GHG concentrations in the atmosphere. Note that Mendlesohn et al. (2000a,b) and Nordhaus (2006) include only market impacts, while the other studies also include estimates of nonmarket impacts, at least to some degree.15

Table 5-7 shows that these studies typically estimate the aggregate global market plus nonmarket impact of doubling GHG concentrations at 1-2% of lost world GDP. The aggregate impacts mask significant differences in regional impacts and in the underlying impacts for individual damage

15

Maddison (2003) and Rehdanz and Maddison (2005) estimates are not included in this table due to the incompleteness of the estimates relative to the others included. Maddison (2003) estimates the effect of temperature and precipitation on household market good impacts based on historical country-level demand data, and Rehdanz and Maddison (2005) estimate the effect of temperature and precipitation on historical country-level measures of “happiness.”



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