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