Economic impacts of climate change
in Tanzania and consequences for
smallholder farming
Asbjørn Aaheim, Anton Orlov, Jennifer West
CICERO
Oslo, May 20, 2014
W h e n to p -d o w n g u y s lo o k d o w n
t h e y s e e o n ly s h it
The challenge
of combining
academic
traditions
W h e n b o tto m -u p g u y s lo o k u p
th e y s e e o n ly a s s h o le s
Integration of impacts of climate change in the GRACE model
Agric Forestry Fish … Energy … Services
Sea-level/coastal
0,000
-0,005
-0,010
-0,015
-0,020
0 1 2 3 4 5 6
Extreme events
0,00
Agriculture
Forestry
Fisheries
…
Energy (5)
…
Transport (3)
Services
Health
0,00
-0,05
-0,10
-0,05
Electricity supply
Labour
-0,10
-0,15
0
1
2
3
4
5
6
0
1
2
3
4
5
0,00
Income = Expenditures
-0,10
Capital
-0,15
-0,20
6
-0,30
Nature
-0,40
0
0,00
0,00
-0,02
-0,10
-0,20
ROW
-0,04
AFR
-0,06
-0,08
-0,30
2
3
4
5
6
3
4
5
6
Tourism
0,05
0,10
0,00
0,05
-0,05
0,00
-0,10
-0,05
-0,15
-0,10
1
2
Fisheries
0,02
0,10
0
1
Forestry
Agriculture
Rate of change
Consume Investment
0
1
2
3
4
5
6
-0,10
0
1
2
3
4
5
6
0
1
2
3
4
5
6
Benefits of reduced climate change in Sub-Saharan Africa
in 2100 (from RCP8.5 to RCP4.5)
By economic sector
400,0
200,0
0,0
-400,0
-600,0
Agriculture – alternative measures
-800,0
-1000,0
18,0
-1200,0
16,0
-1400,0
14,0
-1600,0
12,0
Trill USD
Trill USD
-200,0
10,0
8,0
6,0
4,0
2,0
0,0
Direct impacts
Volumes
Value added
Economic activity in agriculture
£
Kr
Output = f(labour, real capital, land)
€
$
Global emissions of CO2 - RCP 8.5
35
30
PgC/year
25
20
15
10
5
0
Change in annual precipitation in RCP8.5. Crop
land. MPI-ESM
6,00
80,0
70,0
5,00
60,0
4,00
50,0
Africa
3,00
ROW
2,00
mm
°C
2100
2090
2080
2070
2060
2050
2040
2030
2020
2010
2005
2000
Change in mean temperature RCP8.5. Crop
land. MPI-ESM
40,0
Africa
30,0
ROW
20,0
10,0
1,00
0,0
0,00
-10,0
2005 2015 2025 2035 2045 2055 2065 2075 2085 2095
2005 2015 2025 2035 2045 2055 2065 2075 2085 2095
Estimated rate of change in productivity of arable
land in Tanzania in RCP8.5
0,000
Rate of change
-0,050
-0,100
-0,150
-0,200
2005,0
2010,0
2015,0
2020,0
2025,0
2030,0
2035,0
2040,0
2045,0
2050,0
2055,0
2060,0
2065,0
2070,0
2075,0
2080,0
2085,0
2090,0
2095,0
2100,0
-0,250
Impact of climate change on output in
Tanzania by sector
Impact on GDP of climate change
2,00
3,00
0,00
Tanzania
ROW
-6,00
Percent
-4,00
agr
1,00
frs
0,00
fis
-1,00
ser
-2,00
ind
-3,00
col
-4,00
-8,00
ref
-5,00
-10,00
elc
2095
2085
2075
2065
2055
2045
2035
2025
2015
2005
2095
2085
2075
2065
2055
2045
2035
2025
2015
-6,00
2005
Percent
-2,00
2,00
gas
The Tanzanian farmer in National Accounts and in reality
On farm
Paid work/
search
Farm output
• Product
prices
• Wages
6.0 bill
USD
Food
7.3 bill USD
Value of sales
3.3 bill USD
Income from
other paid work
0.7 bill. USD
Other goods
2.7 bill USD
0,000
0,325
0,650
0,975
1,300
1,625
1,950
2,275
2,600
2,925
3,250
3,575
3,900
4,225
4,550
4,875
5,200
5,525
5,850
6,175
6,500
6,825
7,150
7,475
7,800
8,125
8,450
8,775
9,100
9,425
9,750
Frequency
Distribution of farms by size in Tanzania
Typical
Average
0,02
0,018
0,016
0,014
0,012
0,01
0,008
0,006
0,004
0,002
0
Farm size - ha
Impacts of 20 percent reduction in productivity of arable land on farm level
 Critical limit for minimum farm size needed to avoid nutrition contraint
increases: Here from 0.9 ha to 1.1 ha; affecting 600 thousand farms
 Constraints on selection of work place and consumption pattern tightens
emerges on larger farms, increasing from 2.9 ha to 3.65 ha, affecting 990
thousand farms
Impacts on provision of goods and consumption patterns
The average farm: 2 ha
0,6
The typical farm: 1.45 ha
0,6
Other
0,5
0,4
0,5
Output
0,4
Food market
0,3
0,2
0,3
0,2
Other income
0,1
Food farm
0,1
0,0
Provision
Consumption
Base case
Provision
Consumption
With climate change
0,0
Provision
Consumption
Base case
Provision
Consumption
With climate change
Messages:
I. Macroeconomic models provide much more information than
the answer to «what happens with GDP?». Utilizing this
additional information and the underlying assumptions may
turn conclusions to what is costly and what is beneficial
II. Macroeconomic models are building on assumptions about
individual behaviour. They thereby provide a gateway to how
individual and regional differences matter in a national context,
and can be used to consistently integrate results from research
that address different scales
… such as designing national policies to acheive goals for
individual groups who find themselves in widely different settings