Economic Impacts of Climate Change for South Africa:
An Economywide Perspective to 2050
Channing Arndt (UNU-WIDER)
with many others
UNU-WIDER Development Under Climate Change
• Analytical work completed for: – Zambeze River Valley
– Vietnam
– Carbon tax in collaboration with NT
• Current collaborative process in South Africa to consider climate change impacts and potential adaptation strategies.
Integrated
Modeling Framework
CLIRRUN/PITMAN
WRYM
IRRDEM/Smith IPSS
ADJUSTED FOR
RSA MODELS
GCM HFDs
LTAS Scenarios
Water supply to
urban and industry
Development/
Demand
Scenario(s)
Water supply (Local
hydropower)
Baseline
Climate
Scenario(s)
Perspective on Work
• Questions: – What are the implications of climate change for growth and development
prospects?
– What are the potentially large impact channels?
– How much should the National Treasury allocate to climate change adaptation over the next two decades in order to offset negative economic impacts?
– How do we meet development goals in the context of climate change?
• State of progress in modeling : – System is functioning (mechanically)
– Needs refinement, QC & QA
– A series of illustrative results are available
– On a good timeline for report completion by end March
Trade Remittances
Foreign markets
Government
Loans
Taxes
Consumption
spending Taxes &
social grants
Taxes
Economic growth Household welfare
Incomes
Consumption Production Product markets
Payments Agriculture
Services
Rural
Urban
Factor markets
Industry
Productivity
Human/physical capital
Public
investment Foreign
investment
Private
investment
Benchmark Data
• 2002 Social Accounting Matrix – 2002 Supply-Use Table
– 2002 Census of Commercial Agriculture (large-scale farms)
– 2000 Population Census
– 2000 Income and Expenditure Survey
– 2002 Standard Industrial Database (SASID)
• 2000/2005 Water Accounts
Sectors
Economic Structure
Crops and Water Use
Water Management Areas
Cape Town
Durban
Johannesburg
Matching Water and Economic Data
CPT
DBN
JHB
CPT
DBN
JHB
Integrated
Modeling Framework
CLIRRUN/PITMAN
WRYM
IRRDEM/Smith IPSS
ADJUSTED FOR
RSA MODELS
GCM HFDs
LTAS Scenarios
Water supply to
urban and industry
Development/
Demand
Scenario(s)
Water supply (Local
hydropower)
Baseline
Climate
Scenario(s)
Climate Change Impact Channels
• World commodity prices
• Agriculture – Crop yield deviations; and irrigation water supply
• Non-irrigation water supplies – Affect non-agriculture production and households
• Road infrastructure – Costs to maintain the same road network
• Sea level rise – SLR reduces crop land and damages coastal infrastructure
• Energy – Domestic and regional hydropower supply?
Agriculture and Irrigation
• CGE measures direct and indirect impacts – Reallocation of crop land in response to changing crop productivity and
water resource constraints
– Change in food imports in response to changing domestic production and world food prices
– Effects on downstream processing
Baseline “No Climate Change” Scenario
• Define a baseline growth scenarios (or a set of scenarios) – Population and labor supply growth (by skill groups)
– Urbanization rates
– Sector and WMA-level productivity growth
• Water demand projections – Fix industrial, commercial and residential water demand
– Residual allocated to irrigated agriculture
• Historical weather repeats itself (50 years)
PRELIMINARY RESULTS
FOCUS ON AGRICULTURE/WATER IMPACT CHANNEL UNDER UNCONSTRAINED
EMISSIONS
Agricultural Share of GDP
05
10
15
Den
sity
.94 .96 .98 1 1.02 1.04Ratio
Relative to xw
Var= AgshrX Scenario=xa
Agricultural GDP
24
68
10
12
Den
sity
.95 1 1.05Ratio
Relative to xw
Var= AgGDPX Scenario=xa
Non-Agricultural GDP 1
00
150
200
250
Den
sity
1.004 1.006 1.008 1.01 1.012Ratio
Relative to xw
Var= QVAXNonAg Scenario=xa
Both Industry and Services Expand Slightly as Agriculture Releases Resources
Industry Services
50
100
150
200
250
Den
sity
1.004 1.006 1.008 1.01 1.012Ratio
Relative to xw
Var= QVAXManu Scenario=xa
100
150
200
250
300
Den
sity
1.004 1.006 1.008 1.01 1.012Ratio
Relative to xw
Var= QVAXServ Scenario=xa
Real Value Added in Agriculture (Dry Land)
11
.52
2.5
Den
sity
.7 .8 .9 1 1.1 1.2Ratio
Relative to xw
Var= QVAXDry Scenario=xa
Real Value Added in Agriculture (Irrigated Land)
46
81
01
2
Den
sity
.95 1 1.05 1.1Ratio
Relative to xw
Var= QVAXIrr Scenario=xa
Diversity of Impacts on Agriculture Across WMAs
WMA 17 – Consistent Losses WMA 5 – Mostly Gains
05
10
15
20
Den
sity
.92 .94 .96 .98 1Ratio
Relative to xw
Var= QVAXAgw17 Scenario=xa
12
34
5
Den
sity
.9 1 1.1 1.2 1.3Ratio
Relative to xw
Var= QVAXAgw5 Scenario=xa
GDP Impact
50
100
150
200
Den
sity
1.002 1.004 1.006 1.008 1.01 1.012Ratio
Relative to xw
Var= GDPfcX Scenario=xa
This distribution will likely shift to the left when other channels, such as roads and SLR are incorporated.
Expectations at this Point
• Based on the impact channels considered, we expect: – Mild negative implications for overall GDP growth
– Increased costs to maintain the same transport infrastructure
– Potentially strong economic impacts for
• Dry land agriculture (broad confidence intervals)
• Water availability in certain WMAs
• Infrastructure on a localized basis
• Particular zones vulnerable to sea level rise
• The cumulative economic impact of excluded impact channels is likely negative but not very large in a macroeconomic sense