Structuringreference levels
across scales:
Case studies fromIndonesia and Peru
Jonah Busch, Ph.D. (Conservation International)
FFPRI International Technical Seminar
Waseda UniversityTokyo, Japan
Wednesday, February 8, 2012

Fundamental challenge ofnational strategy for REDD+:
Under UNFCCC rules for REDD+, net emissions reductions fromforests will ultimately be accounted for at the national scale
However, many decisions that lead to deforestation are made byactors at the regional, local, or household (“sub-national”) scale
How can a country structure economic incentives for REDD+ sothat actors across scales are encouraged to reduce emissions,and discouraged from increasing emissions?

National Economic Incentive Structure for REDD+:
WHO is paid HOW MUCH for doing WHAT?
ACCOUNTING SCALE: the administrative level at which net
emission reductions are calculated and payments are madeSUB-NATIONAL REFERENCE LEVELS: the level of emissions
below which regions could be paid for reductions
REVENUE SHARING: the portion of international income fromcarbon payments that would accrue to regions that reduce
emissions, and the portion that would remain with the national
governmentRESPONSIBILITY SHARING: the extent to which actors would bepenalized for increasing emissions, and the extent to which thenational government would bear the cost of these increases
through reduced international paymentsReference levels are the benchmark for payment:
Payment = (reference level – emissions) * carbon price
Accounting
PeriodEmissions

Reference
Period?

?

?
?

future businessas-usual scenario

historical emissions
reference levelcountry receives
compensation

Reduction inEmissions
MRV-ed Emissions

1990

2005

Adapted from Mollicone et al, 2007

startendTime

Poorly structured incentives can lead toREDD+ program budget shortfall
Change inemissions fromdeforestation(million tCO2e)

No penalty
for increasing
emissions+4
Reference Level-6
National govt
pays districts
for grossemission reductions-10

Internationalbuyers pay
national govt
for netemission
reductions

NationalBudget
Shortfall

District 1

District 2

NationalTotal

Incentive policy #1: Raise ACCOUNTING SCALE
to reward aggregate performance
Change inemissions fromdeforestation(million tCO2e)

No penalty
for increasing
emissions+4
Reference Level-6
National govt
pays districts
for grossemission reductions-10

Internationalbuyers pay
national govt
for netemission
reductions

National
BudgetShortfall

District 1

District 2

NationalTotal

Incentive policy #2: Set SUBNATIONAL REFERENCE LEVELS
to accurately approximate future business-as-usual emissions:
Change in
Remove windfall profits andemissions fromincentivize broad participation
deforestation(million tCO2e)

No penalty
for increasing
emissions

Reference Level

National govt
pays districts
for grossemission reductions

Internationalbuyers pay
national govt
for netemission
reductions

National
BudgetShortfall

District 1

District 2

NationalTotal

Change inemissions fromdeforestation(million tCO2e)

Incentive policy #3: SHARE REVENUE
resulting from local emission reductions
across scales from local to national
No penalty
for increasing
emissions+4
Reference Level

-6-10

$10/t

National govt
pays districts
for grossemission reductions$8/t

Internationalbuyers pay
national govt
for netemission
reductions

National
BudgetShortfall

District 1

District 2

NationalTotal

Incentive policy #4: SHARE RESPONSIBILITY
for costs resulting from local emission increases
Change inacross scales from national to local
emissions fromdeforestation(million tCO2e)
+4

-$0/t

-$2/t

No penalty
for increasing
emissions

Reference Level-6National govt
pays districts
for grossemission reductions-10Internationalbuyers pay
national govt
for netemission
reductions

NationalBudget
Shortfall

District 1

District 2

NationalTotal

Comparing alternative economic
incentive structures for REDD+
using OSIRIS-Indonesia
Click-of-a-button decision support tool toestimate and map the impacts of alternative
REDD+ policy decisions on:-deforestation (ha/yr)-emission reductions (tCO2e/yr)-national and local revenue ($/yr)
Benefits:-free-MS Excel interface-transparent-open-source-peer-reviewed, published, scientific-online: http://www.conservation.org/osiris

1. OBSERVED DEFORESTATION, 2000-2005(Hansen, 2008)
Deforestation: 687,000 ha/yr
Emissions: 860 million tCO2e/yr
KALIMANTANSUMATRASULAWESI

PAPUA

JAVA

KALIMANTAN

2. LIKELY DEFORESTATION WITHOUT RED(unofficial “reference scenario”)
Deforestation: 693,000 ha/yr
Emissions: 803 million tCO2e/yr

SUMATRASULAWESI

PAPUA

JAVA
KALIMANTANKALIMANTANSUMATRA

3. LIKELY DEFORESTATION WITH RED ($10/tCO2e)
Deforestation: 557,000 ha/yr
SULAWESI
Emissions: 581 million tCO2e/yr
SULAWESI
Revenue: $2.2 billion.yrPAPUA

SUMATRAJAVA
SULAWESI

PAPUA

Well-structured voluntary REDD+
nearly as effective as cap-and-trade(1) Basic PES-style voluntary incentives
Site-scale accounting;historical reference levels(2) District-scale accounting;historical reference levels(3) District-scale accounting;projected reference levels(4) District-scale accounting;projected reference levels+20% revenue sharing(5) Well-structured voluntary incentives
District-scale accounting;projected reference levels+20% revenue sharing+20% responsibility sharing(6) District-scale accounting
projected reference levels minus 10%+20% revenue sharing+20% responsibility sharing(7) Mandatory incentives, e.g. Cap & Trade
District-scale accounting;projected reference levels minus 10%
0% revenue sharing
100% responsibility sharing(8) District-scale accounting;projected reference levels minus 26%
0% revenue sharing
100% responsibility sharing

PES

Well-structured
VoluntaryCAT

Key messages• International REDD+ payments would be earned based on net emission
reductions at the national level. But since many land use decisions are
made locally, a structure of economic incentives for REDD+ is needed• Cap-and-trade for REDD+ at $10/tCO2e would provide greatest emission
reductions (211 MtCO2e/yr) and budget surplus ($1 billion/yr), andeffectiveness would not rely on accurately predicting future deforestation• Basic PES-style voluntary sub-national incentives for REDD+(62 MtCO2e/yr) can leave the national government with a severe budget
shortfall (-$6.2 billion/yr), due to error in setting reference levels• Well-structured voluntary incentives can be nearly as effective(175 MtCO2e/yr) as mandatory incentives, while producing a budgetsurplus ($331 million/yr), by:Aggregating accounting to higher jurisdictional scale (e.g. province or department)• Projecting reference levels to approximate future business-as-usual emissions• Sharing revenues that accrue from emission reductions with national government• Sharing responsibility for costs that accrue from emission increases with local actors•

Indonesia

Spatially prioritizing REDD+ pilots:
Mapping expected distribution ofabatement under REDD+ at $10/tCO2e
OSIRIS tools available for:-Indonesia-Peru-Madagascar-Bolivia-MexicoPeru

Case study from Peru• Patchwork of REDD+ projects aiming
to sell credits on voluntary markets(VCS with CCBS)• Some projects have overlappingleakage-accounting boundaries
under VCS methodologies

San Martin• Different regions moving ahead on
REDD+ at different speeds, led by
San Martin and Madre Dios (REDD+Social and Environmental Standards)
Madre de Dios

• Need for nesting– harmonization ofreference levels across scales, basedon projections of future deforestation
and bottom-up approach(see Peru R-PP, March 2011)

Case study from Peru
Phase 1• patchwork of individual projects, each withown projected reference level

Phase 2San Martin• regions develop projected reference levels
when they are capable• within regions, existing projects canmaintain validated reference levels for aninterim time period

Phase 3• within regions, projects’ reference levels
have been reconciled with regionalreference levels• national reference level is constructed bybottom-up summation of regionalreference levels

Madre de Dios

Thank you!
ありがとうございました

Thanks to:Forestry and Forest Products Research Institute
Norwegian Agency for Development Cooperation
Comments and feedback welcome:
http://www.conservation.org/osiris
jbusch@conservation.org

Case study from Indonesia• 4th greatest greenhouse gas emission reduction potential• (WRI CAIT, 2010)• 3rd most tropical forest (FAO, 2010)• 1st most endemic forest birds (Birdlife International, 2010);
1st most endemic forest mammals (Schipper et al, 2008);
6th most endemic forest amphibians (Stuart et al, 2004)• A global market for RED could provide Indonesia withrevenue of $1.9-5.1 billion annually (authors’ calculations
based on Piris-Cabezas, 2010; Busch et al, 2010)• 26-41% emission reduction commitment by 2020• May, 2010: $1 billion Norway-Indonesia Letter of Intent

OSIRIS-Indonesia model• Data on forest cover, forest cover change, emission factors, terrain, access,protected status, concession boundaries, potential agricultural revenue
compiled for ~200,000 3km x 3km grid cells across all of Indonesia• Relationship between potential carbon revenue and deforestation
determined econometrically using observed forest cover loss (2000-2005)• National government sets REDD+ economic incentive structure• (accounting scale; reference levels; revenue sharing; responsibility sharing)• 401 forested districts respond to incentives by choosing whether or not toparticipate in REDD+, and choosing where and how much to deforest• Market feedbacks produce “leakage” of deforestation• Spatial distribution of deforestation in equilibrium used to calculate
emissions and national and local revenue, under alternative national
REDD+ incentive structures

Central revenue can fund nationalpolicies and measures for REDD+
1. Removal of subsidies for deforestation and forest degradation
2. Tax land clearance
3. Strategic road planning
4. Improve forest law enforcement
5. Improve tenure security
6. Devolve forest management to local communities
7. Forest certification
8. Conservation concessions
9. Strengthen the protected area network
10. Payments for environmental services
11. Funding fire prevention programmes
12. Sustainable forest management/ improved forest planning
13. Support for reduced impact logging (RIL)
14. Reforest degraded land
15. Alternative livelihood programmes
16. Agricultural intensification
17. Support community forestry
18. Improve off-farm employment
Source: Peskett et al, “Making REDD Work for the Poor,” 2008.

PREDICTED district deforestation, 2000-2005, (ha/5yrs)

1,000,000

100,000

10,0001,00010010n=401
R=0.65
1110

100

1,000

10,000100,000

OBSERVED district deforestation, 2000-2005 (ha/5yrs)

1,000,000

Sensitivities• Functional form
• Included variables• Policy decisions• Model parameters-Carbon price-Price elasticity of demand
for frontier agriculture(intranational leakage)-Exogenous agricultural priceincrease (international leakage)-Peat emission factor-Social preference foragricultural revenue-National reference level-District level start-up costs-Site-level transaction costs

Expected spatial distribution of abatement
under REDD+ at $10/tCO2e (tCO2e/ha)

KALIMANTANSULAWESIPAPUASUMATRA
JAVA

Where is the carbon, AND where can money change behavior?

The road ahead• Zoning and agricultural policy• Degradation and reforestation• Safeguards for REDD+ (DEFRA)• Long-term incentives for REDD+• Risk management mechanisms• Complementary agricultural policies• Matching payments for biodiversity,
water and other ecosystem services• Green economic development• Open for discussion!...