Transcript Effective international policy to reduce emissions from

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
Goal: mitigate climate change cost-effectively
Pricing carbon storage in forests is critical
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?
Land at risk
0
‘Returns’ to clearing
The distribution of returns on forested
land
f(r)
Land at risk
0
‘Returns’ to clearing
• 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.
Policy option 1: provide reward for
carbon storage on all forested land
Land that will not be
protected even with
carbon price
0
‘Returns’ to clearing
Protect if r < pc
Total cost = carbon stock x carbon price
Efficient but extremely expensive.
Policy option 1: provide reward for
carbon storage on all forested land
Land at risk
0
‘Returns’ to clearing
Protect if r < pc
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
Estimated return
baseline
Land at risk
0
‘Returns’ to clearing
Can easily get most wrong
Estimated
baseline
Land at risk
0
‘Returns’ to clearing
Under offsets:
– Make a baseline mistake to the right of zero
and you get spurious credits
Can easily get most wrong
Land at risk
Under offsets:
0
‘Returns’ to clearing
– 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
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.
pc is the carbon price offered
(i) Raise pc 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 pc 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 pc 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?
f(r)
Generous
baseline
Land at risk at time t
0
‘Returns’ to clearing
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.
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