constructing an opportunity cost curve
TRANSCRIPT
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REDD+
Constructing an opportunity cost curve
Douglas White
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REDD+
Objectives
• Discuss an opportunity cost curve
• Examine carbon-profit tradeoffs
• Introduce example
• Generate a REDD+ opportunity cost curve
• Review effect of changes in – policy
– prices
– technical coefficients
on an opportunity cost curve
(sensitivity analysis)
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REDD+
OppCost curve
• Integrates the outputs from previous chapters
– land uses
– land use changes
– carbon stocks
– profits
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REDD+
OppCost analysis process
Emission matrix(tCO2e)
Ch4
Classify land uses
Forest...
Ag
Ch5
Carbon stocks(tC/ha)
Ch6
Profits($/ha)
OppCost matrix($/tCO2e)
Ch4
Estimate land use change
(matrix of histories or trajectories)
For the vertical axis:
For the horizontal axis:
$/tC02e
tC02e
0
-
+
Ch7 Opportunity Costs
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REDD+
What is an opportunity cost curve?
-1
0
1
2
3
0 500 1000 1500 2000Cost ($
/tC
O2e)
National emission abatements &carbon enhancements (Tg CO2e/year)
“Expensive abatement options”
“Cost-effective abatement options”
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REDD+
What is an opportunity cost curve?
-1
0
1
2
3
0 500 1000 1500 2000Cost ($
/tC
O2e)
National emission abatements &carbon enhancements (Tg CO2e/year)
“Expensive abatement options”
“Cost-effective abatement options”
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REDD+
What is an opportunity cost curve?
-1
0
1
2
3
0 500 1000 1500 2000Cost ($
/tC
O2e)
National emission abatements &carbon enhancements (Tg CO2e/year)
“Expensive abatement options”
“Cost-effective abatement options”
Carbon price
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REDD+
What is an opportunity cost curve?
-1
0
1
2
3
0 500 1000 1500 2000Cost ($
/tC
O2e)
National emission abatements &carbon enhancements (Tg CO2e/year)
Logged forest
to agriculture
Logged
forest to
agroforestry
Natural
forest to
logged
forest
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REDD+
What is an opportunity cost curve?
-1
0
1
2
3
0 500 1000 1500 2000Cost ($
/tC
O2e)
National emission abatements &carbon enhancements (Tg CO2e/year)
Logged forest
to cocoa
Logged
forest to
agroforestry
Natural
forest to
logged
forest
Logged forest
to agriculture
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REDD+
Land use categories
• A mix of national, IPCC and other criteria are used to
determine categories
• To enable systematic and rigorous analysis of REDD+
opportunity costs, land use systems need to be:
– Unambiguous (pertain to only one land use category),
– A basis from which to integrate multiple types of data,
– Carbon-relevant (homogenous in C stock),
– Profit-relevant (homogeneous in profits),
– Consistent for reporting at multiple scales: global,
national, local
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REDD+
Land use categories
• Levels of homogeneity to be determined according to impact on results.
• In some instances, 5-10% difference may not greatly affect opportunity cost estimates
• Precision and rigor is a matter of discussion, increases cost of analysis
• The costs of data collection and analysis are weighed against the benefits of better estimates
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REDD+
A national opportunity cost curve
Recall that
• Such a national analysis is a useful step in
understanding the costs of carbon abatement
• The results, however, are a simplification of a
diverse reality
• A broad range of sub-national contexts typically
reveals big differences from generalized results
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REDD+
Sensitivity analysis (1)
• Why
– To check the robustness of a
quantitative analytical model
– To identify the variables that account
for more variation in the model results
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REDD+
Sensitivity analysis (2)
• Key steps:
– Prioritize a subset of variables for sensitivity analysis (e.g.
inputs, yields, prices, discount rate)
– Determine the realistic range of variation of the variable
– Examine the results of low and high estimates of each variable
– Document, compare and discuss the results
– Identify priority scenarios to consider in policy discussions
– Consider additional land use classifications to improve
precision
– Identify priority areas of research to clarify the range of
specific parameters (e.g. inputs, yields, prices)
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REDD+
Hands-on Exercise with Abacus
Context: Sumatra, Indonesia
• Different carbon stocks and profit
levels from
– land uses
– sub-regions
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REDD+
Site
context
• Batang Toru,
North
Sumatra
248,250 ha
or
2,483 km2
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REDD+
Asia example
Authors:
Hesti Lestari Tata
Meine van Noordwijk
Elok Mulyoutami
Subekti Rahayu
Atiek Widayati
Rachmat Mulia
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REDD+
Land: covers/uses
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REDD+
Land covers/uses
Area (ha) 1994 2009Undisturbed forest 159470 133563Logged forest 3312 15513Rubber agroforest 38651 30201Mixed gardens 15425 27808Coffee agroforest 15506 11576Pine plantation 1462 13470Rice paddy 11557 11700Oil palm 873 2425
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REDD+
Land cover maps 1994, 2009
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REDD+
Land use change matrix
Batang Toru, Sumatra
Undisturbed forest
Logged forest
Rubber agrofore
stMixed
gardens
Coffee agrofore
stPine
plantation Rice Oil palm
hectares
1994 2009 133563 15513 30201 27808 11576 13470 11700 2425
Undisturbed forest 159470 133563 12383 8 6245 1369 4580 1322
Logged forest 3312 0 3130 0 12 0 114 32 24Rubber agroforest 38651 0 0 30193 4283 573 3525 0 77
Mixed gardens 15425 0 0 11925 3284 87 129Coffee agroforest 15506 0 0 5343 9634 505 24
Pine plantation 1462 0 0 0 0 0 1462 0 0
Rice paddy 11557 0 0 0 0 0 0 11557
Oil palm 873 0 0 0 0 0 0 0 873
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REDD+
Carbon and profit levels
Land use Carbon NPV
Undisturbed forest 243 0
Logged forest 152 2760
Rubber agroforest 114 796
Mixed gardens 103 885
Coffee agroforest 24 1012
Pine plantation 93 1199
Rice paddy 2 242
Oil palm 40 7832
Region 1
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REDD+
Carbon-Profit Tradeoff
Undisturbed forest
Logged forest
Rubber agroforest
Mixed gardensRice paddy
Pine plantationCoffee
agroforest
Oil palm
0
1000
2000
3000
4000
5000
6000
7000
8000
9000
0 50 100 150 200 250 300
NP
V (
US
$,h
a)
Carbon stock (tC/ha)
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REDD+
Hands-on Exercise with Abacus
Land use Carbon NPV Carbon 2 NPV2
Undisturbed forest 243 0 243 0
Logged forest 152 2760 152 3450
Rubber agroforest 114 796 85.5 995
Mixed gardens 103 885 77.25 1106.25
Coffee agroforest 24 1012 18 1265
Pine plantation 93 1199 93 1199
Rice paddy 2 242 2 302.5
Oil palm 40 7832 30 9790
Carbon2 gray cells have 75% of original carbon estimateNPV2 gray cells have 125% of original NPV estimate
Region 1 Region 2
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REDD+
Batang Toru
Districts SouthTapanuli Central Tapanuli
Main plantation
commodities
Rubber, oil palm,
snakefruit, tobacco,
cinnamon, coffee, clove
Rubber, coconut,
oil palm and cocoa
Main crops Paddy rice, maize,
soybeans
Paddy rice, maize,
animals
Land holdings Paddy 0.5 ha,
Mixed garden (rubber,
sugar palm) 1-4 ha
Snakefruit 0.5-2 ha
Paddy rice 0.5 ha
Upland rice 0.5 ha
Mixed garden
(rubber, sugar palm, etc)
1- 4 ha
Rubber agroforest
1-2 ha