Presentation on theme: "Effective international policy to reduce emissions from deforestation Suzi Kerr (and Arthur van Benthem) Motu and Stanford, Economics Earth System Science."— Presentation transcript:
Effective international policy to reduce emissions from deforestation Suzi Kerr (and Arthur van Benthem) Motu and Stanford, Economics Earth System Science 2010
Goal: mitigate climate change cost-effectively Pricing carbon storage in forests is critical Emissions reductions ≠ ‘policy’
Goal: mitigate climate change by reducing deforestation Problems with ‘offsets’ Leakage ‘Adverse selection’ Solutions and the tradeoffs involved in them.
International policy ‘proposal’ for deforestation Focus on ‘getting prices right’ –Fund used to pay for temporary reductions relative to baseline at approx global carbon price; or –Integration in cap and trade Country level targets and remote monitoring –Minimises corruption –Minimises leakage and adverse selection –Maximise domestic policy flexibility – efficiency and sovereignty Be generous to developing countries through baselines not exemptions
Why are people deforesting? ‘Returns’ to clearing 0 Land at risk
The distribution of returns on forested land Because humans have been clearing land for a long time, the ‘returns’ distribution for land that is still in forest is right censored Most forest is not at threat of deforestation in the short term. ‘Returns’ to clearing 0 Land at risk f(r)
Policy option 1: provide reward for carbon storage on all forested land Protect if r < p c Total cost = carbon stock x carbon price Efficient but extremely expensive. ‘Returns’ to clearing 0 Land that will not be protected even with carbon price
Policy option 1: provide reward for carbon storage on all forested land ‘Returns’ to clearing 0 Land at risk Protect if r < p c Total cost = carbon stock x carbon price Efficient but extremely expensive.
Policy option 2: Offsets - reward relative to a baseline Theory: minimises transfers from developed countries – only pay for real reductions Problem: uncertainty in baseline – accurate prediction of return impossible
Adverse selection: Those who participate will not be those you want to participate People participate because they can protect forest at low cost Others participate because they will be rewarded for doing nothing
Can easily get most wrong ‘Returns’ to clearing 0 Land at risk Estimated return baseline
Can easily get most wrong Under offsets: –Make a baseline mistake to the right of zero and you get spurious credits ‘Returns’ to clearing 0 Land at risk Estimated baseline
Can easily get most wrong Under offsets: –Make a baseline mistake to the right of zero and you get spurious credits –Make a mistake to the left, lose efficiency but you have no balancing of spurious credits Systematic bias – can pay a lot and achieve almost nothing ‘Returns’ to clearing 0 Land at risk
Are there intermediate solutions between very high transfers and inefficient offsets? 1.Increase scale of projects – deal with regions and countries not properties. –Many properties that would individually have had unfavourable baselines (opted out) will now be included in the programme More efficient Less rewards for doing nothing – If baseline is unfavourably biased by mistake, risk that some entire countries could opt out – loss of efficiency
2. Alter carbon price offered Suppose δ is the true marginal environmental benefit from reducing one tonne C. p c is the carbon price offered (i) Raise p c toward δ – stronger international climate agreement (ii) Lower r if possible – technical assistance Both will increase efficiency Both will reduce the share of spurious units
Other policy choices involve a trade off between efficiency and transfers to developing countries. Whose welfare are we concerned about? Welfare depends on: efficiency of mitigation amount of transfers to developing countries amount of accidental spurious credits
2. Alter carbon price offered (iii) Reduce p c below δ ? Commonly called ‘discounting’. –Simple logic – if 10% are spurious, pay 10% less on each. –But, paying less changes participation. Efficiency loss – only good projects drop out Greater share of credits spurious –Lower transfers to developing countries
2. Alter carbon price offered Suppose δ is the true marginal environmental benefit from reducing one tonne C. (iv)Raise p c above δ ? –Less efficient – some land not deforested that ‘should’ be. –Can increase participation and hence efficiency. –Larger transfers to developing countries –Fewer spurious units
3. Bias baselines deliberately (i)Bias in favour of seller – higher baseline deforestation rate. Offset with greater reductions elsewhere –Unambiguously increases efficiency –Increases transfers to developing countries
3. Bias baselines deliberately (ii) Bias in favour of buyer – lower baseline deforestation rate Require country to take some independent action before they get reward. –Can lose a lot of efficiency –Can save buyer a lot of money
‘Best’ policy option? The level of generosity needed to achieve global efficiency depends on accuracy of baseline – maximise scale Offset generous baselines with tighter targets in Annex I – Annex I could still win. ‘Returns’ to clearing 0 Land at risk at time t f(r) Generous baseline
Conclusions Effective policy to avoid deforestation could significantly lower mitigation costs There is a tradeoff between efficiency and minimising transfers to developing countries This tradeoff is minimised if scale is maximised – e.g. Country level Lowering prices or baselines reduces efficiency and shifts mitigation cost to developing countries Most efficient option is to deliberately make baselines more generous.
Conclusions Be brave: large scale Be generous: put global efficiency ahead of narrow developed country interests Then science becomes critical factor again
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