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Financial incentive benchmark for REDD+
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Financial incentive benchmark for REDD+

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Arild Angelsen, Professor of Economics at the Norwegian University of Life Sciences (UMB) and a senior associate at CIFOR, gave this presentation on 28 November 2012 at a joint CIFOR and GOFC-GOLD …

Arild Angelsen, Professor of Economics at the Norwegian University of Life Sciences (UMB) and a senior associate at CIFOR, gave this presentation on 28 November 2012 at a joint CIFOR and GOFC-GOLD (Global Observation of Forest Cover and Land Dynamics) UNFCCC COP18 side-event in Doha, Qatar. The presentation discusses relevant considerations for how to set the financial incentive benchmark (or crediting) baseline for REDD+, i.e. the benchmark for rewarding a project or country for reduced emissions. While this is ultimately a political question to be handled through negotiations, these can be done in a more systematic way, as shown in this presentation.

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  • 1. FIB for REDD+ Arild Angelsen School of Economics and Business, Norwegian University of Life Sciences (UMB), Ås , Norway &Center for International Forestry Research (CIFOR), Bogor, Indonesia arild.angelsen@umb.no COP 18 Doha 28.11.12
  • 2. School of Economics and BusinessNORWEGIAN UNIVERSITY OF LIFE SCIENCES Reference levels: BAU (technical – measuring ER) vs. FIB (financial incentive benchmark) (political – assigning ”quotas”) Forest carbon stock ’Historical baseline’) REDD credits Realised path FIB BAU baseline Time Commitment period Emissions = negative change in forest carbon stock www.umb.no
  • 3. School of Economics and BusinessNORWEGIAN UNIVERSITY OF LIFE SCIENCES Why not to set FIB = BAU baseline  Too costly (expensive)!  Key challenge: create a REDD mechanism that: – Gives strong incentives for emissions reductions – Is not too costly (cost efficient) – Is considered fair =>Is politically acceptable (effective, costs, fair – 3Es) www.umb.no 3
  • 4. 4 UNFCCC: Historical + National circumstances www.umb.noSchool of Economics and BusinessNORWEGIAN UNIVERSITY OF LIFE SCIENCES
  • 5. School of Economics and BusinessNORWEGIAN UNIVERSITY OF LIFE SCIENCES Main considerations for setting FIB Simplest: FIB=BAU 1. Additionality 2. Participation constraint (“no lose” principle) 3. Effectiveness and efficiency – Compensating only real costs 4. “Fair sharing” (equality) – Income (GDP per capita) 5. Uncertainty – Steps: lower RL if low quality data used www.umb.no 5
  • 6. School of Economics and BusinessNORWEGIAN UNIVERSITY OF LIFE SCIENCES 1. Additionality  Additionality (weak): Realized emissions < BAU  Additionality (strong): FIB ≤ BAU $ Marginal costs of REDD Price of REDD C D credits B A Emissions BAU FIB Realised REDD Credits for emissions www.umb.nosale/ comp. 6
  • 7. School of Economics and BusinessNORWEGIAN UNIVERSITY OF LIFE SCIENCES 2. No-lose principle or participation constraint  Transfer: B + C  Costs: A + B  Participation constraint: FIB set such that A ≤ C $ Marginal costs of REDD Price of REDD credits C D B A Emissions BAU FIB Realised REDD Credits for emissions www.umb.nosale/ comp. 7
  • 8. School of Economics and BusinessNORWEGIAN UNIVERSITY OF LIFE SCIENCES 3. Effectiveness  Maximize effectiveness, given participation constraint: CB set such that A = C  Compensate only real costs – Trade-offs! $ Marginal costs of REDD Price of REDD credits C D B A Emissions BAU FIB Realised REDD Credits for emissions www.umb.nosale/ comp. 8
  • 9. NORWEGIAN UNIVERSITY OF LIFE SCIENCES School of Economics and Business Options to max. effectiveness (given REDD fund) Option Elaboration Incentives Information Risk (overall require- handling reductions) ments 1.Stricter Might include a Good; Correct Medium - high Good, countries FIB safety margin to incentives on the adjust efforts account for margin (don’t based on new uncertainty affect overall information, but reductions) may also opt out) 2.Lower Reduced price per Incentives on the Low Good price tCO2e to make margin reduced; overall pay lower less emissions reductions 3.Different Example: corridor Good, payment High, must Good -iated approach mimics the MC know payment curve differentiated costs 4.Sub-FIBs Sub-FIBs for areas Good, as above High, detailed Good or sectors (drivers) information A version of the about costs option above 5.Fixed A deal about fixed Uncertain; must High Poor, REDD contract reductions and include countries fixed payment conditions target assume high risk (based on under-/over- estimated costs) achieved www.umb.no 9
  • 10. NORWEGIAN UNIVERSITY OF LIFE SCIENCES School of Economics and Business 4. Fair sharing 1. Differences in capabilities 2. Differences in responsibilities 3. REDD+ transfers for development and adaptation - Additionality?  Operationalise the benefit and cost sharing principle: – income per capita – emissions (current or accumulated) – individual assessments of capabilities and needs www.umb.no 10
  • 11. NORWEGIAN UNIVERSITY OF LIFE SCIENCES School of Economics and Business 5. Uncertainty Risk at international level between parties:  Risk REDD country: not paid for their effort – BAU higher, costs higher, policies ineffective  Risk REDD donor: pay is not additional, or high REDD rent – BAU lower, costs lower  Several options for dealing with uncertainty www.umb.no 11
  • 12. Option Elaboration Pros Cons Most applicable for1.Ex post RL formula agreed a Predictable; adj. Hard to Steps 2 & 3adjustment priori; final FIB set when made as more data establish the e.g. ag prices are known become available formula2.Corridor Gradually increasing Flexible; payments Political Steps 1–3approach payments within a RL also mimic marginal acceptability corridor cost curve3.Conser- FIB multiplied by an Lowe risk of over- Makes Steps 1–3vativeness conservativeness factor payment (hot air); REDD+ lessfactor (<1), based on data incentives to get attractive for quality better data; accepted countries with by UNFCCC; easy poor data to implement4. Renego- Renegotiate RL during Flexible, can Political Steps 1 & 2tiation the course of incorporate gaming implementation of a unforeseen factors REDD+ agreement.5.Insur- Insurance contract-based Well developed Expensive; Steps 2 & 3ance approaches in Steps 1 & markets for complex 2 insurance contract 12
  • 13. A proposal for setting FIB for result basedNORWEGIAN UNIVERSITY OF LIFE SCIENCES School of Economics and Business payments 1. Historical deforestation (RL I=FIB I) 2. Business as Usual (BAU) deforestation – Historical deforestation + National circumstances, e.g. forest cover – Adjusted BAU (RL II=FIB II) 3. Costs, based on arguments of effectiveness and efficiency; set such that transfer = costs (FIB III) 4. Fair sharing, rich (> USD1 000/capita) countries pay some share of costs, poor countries are overcompensated (FIB IV) 5. Stepwise approach, high uncertainty of underlying data impose a conservativeness factor (FIB V) www.umb.no 13
  • 14. Historic al Forest cover Costs Fair sharing Uncertainty deforest ation BAU defor FS Hist.defo Opp. (forest Defor Cost factor r rate Forest Emission costs FIB Cons. Variables cover) after adjust. (based FIB IV FIB V (FIB I= cover reductions per III factor (FIB REDD+ factor on RL I) tCO2 II=RL II) GDP)Example I: Poor, low deforestation, forest rich country Parameter value 50 % 5,0 3,0 1 000(threshold)Area (1000 ha) 350 180 000 746 373 373 597 631 504Relative to forest or land 0,33 0,35 0,28 0,19 % 72,00 % 0,41 % 0,21 % 0,21 % 0,15 0,80area % % % Emission MtCO2(100tC/ha) 128 274 137 137Value (USD million) 684 411 0,60 500REDD+ transfers (USDmillion) 684 411 - 473 - 241Example II: Rich, high deforestation, low forest cover countryParameter value 50 % 5,0 3,0 1 000Area (1000 ha) 70 000 1 000 846 423 423 677 588 529Relative to forest or land 0,97 0,84 0,76 1,43 % 28,00 % 1,21 % 0,60 % 0,60 % (0,35) 0,90area % % % Emission MtCO2(100tC/ha) 367 310 155 155Value (USD million) 5 000 776 466 0,60REDD+ transfers (USD 776 466 303 195million)
  • 15. NORWEGIAN UNIVERSITY OF LIFE SCIENCES School of Economics and Business Summary  A reasonable proposal – BAU, costs, capacities, and uncertainty – Specifications debatable  Lower FIB, but – More REDD for given international funding (effectiveness) – “Something one can afford”  Need to deal with uncertainty – Stepwise approach: • Incentives for upgrading MRV and RL system – Corridor approach: – Reduce uncertainty for both parties – mimic the MC curve (only compensate real costs) www.umb.no 15
  • 16. Based on ‘Analysing REDD+’ (chap. 16) and DECC-reporthttp://forestsclimatechange.org/AnalysingREDD+ 16

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