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Professor, IØR, UMB, Ås & Senior Associate, CIFOR, Indonesia

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1 Professor, IØR, UMB, Ås & Senior Associate, CIFOR, Indonesia
REDD Arild Angelsen Professor, IØR, UMB, Ås & Senior Associate, CIFOR, Indonesia

2 Forests and global warming
Forests and climate change Forests and global warming

3 Share of GHG emission


5 It’s getting hot

6 Range of other estimates
How much hotter? CO2 concentration IPCC 2001 Range of other estimates 400 650 1000

7 Emissions reduction (ER) = Actual emissions - Reference levels
Institutt for økonomi og ressursforvaltning Payment based on ER Emissions reduction (ER) = Actual emissions - Reference levels

8 Why include Reducing Emissions from Deforestation and forest Degradation (REDD) in a global climate regime BIG: 1/5 of GHG emissions, but not included in global climate regime CHEAP: (Stern report) Negative - $5/ton 50 % red: USD 5-15 billion But problems of implementation (transaction costs) QUICK: Stroke of pen reforms No deep restructuring of economy or new technoloigy A wooden bridge to a clean energy future WIN-WIN Large transfer Good governance? Institutt for økonomi og ressursforvaltning

9 Reducing Emissions from Deforestation and forest Degradation (REDD)
Institutt for økonomi og ressursforvaltning

10 Forest management types
Global readiness funds (e.g. FCPF, UN-REDD, bilateral initiatives) Global funds (e.g. Global Facility, FIP) International carbon markets (e.g. Kyoto AAU market, EU-ETS, …) INCENTIVES INSTITUTIONS Regular budgets (national or sub-national government) REDD fund (national or sub-national) Verification Sub-national projects Policies and Measures (PAM) Performance payments (e.g. PES) Monitoring, Reporting Forest management types Carbon rights holder Other stakeholders State (production) Concession holder Energy users INFORMATION State (conservation) National & sub-national government agencies Environmental services users Private Land owner Farmers Community Community Consumers Others Others Others

11 REDD in a global climate agreement
What is REDD: Aid PES CAT Agreement on some broad principles in Copenhagen – maybe! “Technical solutions exist, it’s a question of political will” ???? Distribution Hold-out game

12 Scope of REDD Changes in: Reduced negative change Enhanced positive change Forest area (hectare) Avoided deforestation Aforestation & reforestation (A/R) Carbon density (carbon per hectare) Avoided degradation Forest regeneration & rehabilitation (carbon stock enhancement) Forest carbon (C) = forest area (ha) * carbon density (C/ha)

13 Finding the right scale? Credit to countries, projects or both?
Nested approach: Sequential: first project, then national Simultaneous: both coexist The most flexible: Harmonization issues Credit sharing Institutt for økonomi og ressursforvaltning

14 Finding the money Voluntary market Compliance carbon markets (offsets)
CSR Individuals Compliance carbon markets (offsets) UNFCCC ETS US Global fund Bilateral donors Auctioning of emission quotas (AAU) Taxes (carbon, air travel, …) Institutt for økonomi og ressursforvaltning

15 Finance: Current carbon markets
Institutt for økonomi og ressursforvaltning

16 MRV Institutt for økonomi og ressursforvaltning

17 MRV … The technologies are (almost) there
But they come at a cost, sometimes a very high cost MRV not an hindrance for moving ahead, but impose limitations for what we can do IPCC guidelines fairly good for deforestation, less developed for degradation Reward better MRV (e.g. the level of discounting) Institutt for økonomi og ressursforvaltning

18 Reference level Should we pay for 100% of the emissions reduction, or a smaller percentage of them? The two meanings of baseline: 1. Business as Usual (BAU) baseline a technical prediction of what would happen without REDD benchmark to measure the impact of REDD policies 2. Crediting baseline (= reference level) benchmark for rewarding the country (or project) if emissions are below that level (or penalize if above, depending on liability) like an emission quota in a CAT system

19 How to predict (BAU) deforestation?
National historical deforestation National circumstances: Forest cover, reflecting stage in forest transition GDP/capita War, disasters, …. Other factors? Population Commodity prices Ex ante adjustment Brazil being rewarded due to the economic crisis Institutt for økonomi og ressursforvaltning

20 Reference levels Forest carbon stock
Time Past emissions (historical baseline) Realized path Crediting baseline BAU baseline Commitment period REDD credits Forest carbon stock Institutt for økonomi og ressursforvaltning

21 How to set reference levels
Main principle: BAU + common but differentiated responsibilities Crediting baseline < BAU: A balance between: The risk of ’tropical hot air’ and higher effectiveness REDD participation and acceptability “Positive incentives” (UNFCCC) No-lose systems No liability REDD: move from IPES to CAT Who owns the REDD rent? Institutt for økonomi og ressursforvaltning

22 Costs and reference levels
Carbon price determines reductions RL determines overall pay & participation $/tC Marginal costs of AD Carbon price REDD rent REDD costs Change in tC (forest cover) BAU defore-station Ref. level Realized reduced defore-station

23 A proposal (Meridian report, Norwegian UNFCCC submission)
Reference levels based on: Historical natioanal deforestation National forest cover GDP/capita (or LDC) Global additionality (scaling) factor (global RL < global BAU) OSIRIS scenarios: Scenario National historical deforestation Forest cover GDP per capita/ LDC quota Global additionality scaling factor Funding (USD billions/year) Meridian 1 (M-1) 100 5 M-2 20 M-3 10 M-4 M-1 w/ scaling 90 5, 10, 20 80 70 60 50

24 What are the implications?
USD 5 billions in a fund based approach Large distributional impacts Deviations from BAU reduce effectiveness (reduced participation)

25 …. …. implications? Global additionality scaling might increase effectiveness, particularly at high funding levels Generous reference levels have a costs (e.g. 100 to 130 % scaling (option 4), with USD 5bn reduce global emission reductions from 42 to 29%)

26 National REDD policies
Institutt for økonomi og ressursforvaltning

27 Appropriate deforestation?
Some deforestation ok: benefits > costs But strong externalities.... ... and policy failures $ Production net benefits after policy distortions Production net benefits Environmental costs Note that most of the env. costs are at the global level, so private or even communal property will not help. Alos important whether the value of forest area is in the land or the timber and other forest products. Markets rarely exist, to understand deforestation enough to look at the first curve Property rights: why open access? Include transaction costs to enforse property rights, not worth it -> open access). Make figure. A B C deforestation market failure policy failure C: actual deforestation; A: optimal deforestation

28 3. A framework for an agent-based analysis of causes of deforestation
Distinguish variables at different levels(e.g. in regression analysis) Think within a cause-effect framework Avoid ’cheap’ political explanations Focus on micro-level models (level 1-3) Microeconomic defor. models We focus on the microeconomic part, that’s where most significant conclusions are. Basic microeconomic theory: Preferences + constraints = choice So, look at economic incentives and the constraints.

29 Some key issues in economic modelling of deforestation
Smallholders or large actors: “the needy or the greedy” Deforestation an investment or dis-investment; agent or national/global level modelling Frontier deforestation (open access) vs. mgt. of land with secure property rights Subsistence (population) or market approach

30 a. Subsistence approach
Basic relationship (needs = production) sN = xH <=> H =s N/x What drives deforestation (higher H)? poverty (reach subsistence level s) population growth (increase in N) low productivity (x) Dev. Agencies, NGOs, ICDP

31 b. Market approach (von Thünen)
What drives deforestation? high prices (p) high productivity (x) low wages (alt.empl.) (w) small access costs (q) extension: forest clearing gives property rights Basic economic tehory Von Thunen, 1826

32 Comparison Subsistence (pop.) approach: Market approach:
Farmers clear forest to survive Ignore consumption aspirations Ignore migration effects Development (aid) community Market approach: Farmers clear forest because it is profitable Unconventional results: intensification, discount rates, land reforms, credit programmes Different policy implications

33 Extension of market approach
Homesteading, land races Constraints at the farm level Several farming systems Environmental effects Costs of property rights

34 Introducing forest rent
Deforestation A Global + local + private forest benefits Local + private forest benefits Agricultural rent Value B D C Private forest benefits

35 Capture forest rent Much of forest rent is a public good.
Key question: how to “internalize externalities” Institutional arrangements (CFM) Markets (PES) - Assumes property rights allocated and secure

36 Policies for reduced deforestation
Policy Effectiveness (forest conservation) Direct costs of policy (efficiency) Effect on inequality/ poverty Agricultural yield Political viability 1.Reduce (extensive) agriculture rent Depressing agric prices High Negative Very negative Very low Creating off-farm opportunities Medium/high Neutral/positive Uncertain Support to intensive agric sector Moderate/ high Positive Selective support to extensive agric Uncertain/ moderate Moderate Ignore extensive road building Low/ moderate More secure property rights Medium Moderate/ high 2.Increase forest rent and its capture Higher price of forest products Low Positive/uncertain Small CFM – capture local public goods Low/medium PES – capture global public goods Potentially high Uncertain/positive 3.Protected areas

37 In the end: REDD is a game
What game is it? A collective action game The development aid game Very high expectations The very different perceptions and interests “Squeeze the lemon” (developing countries): get as much $$$ for as little action as possible Avoid massive $$$ transfers (developed countries): get as much action for as little $$$ as possible Institutt for økonomi og ressursforvaltning

38 Main players Northern governments Southern governments NGOs (divided)
Climate benefits Use as offset Southern governments Dramatic impacts of CC Quick and big money NGOs (divided) Concern about market flooding & buying out Project funding Indigenous & local people Elite capture, buying forests Opportunities for making money Private sector CSR Cheap offsets Institutt for økonomi og ressursforvaltning

39 5. Norway: 15 billion kroner (perhaps)
It’s a good idea Climate change is real Important to stop deforestation Money can make things move forward Buy credibility and influence Development aid as a political instrument High risk of being naïve in two ways: Can money buy forests? Super-optimistic about what aid can do Previous aid projects a mixed success Beware the game played Conditionality: performance-based support Long term targets as the only feasible way

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