ECC3640 Chap.3 Climate Cost-Benefit Analysis
Climate Cost-Benefit Analysis
Climate Cost-Benefit Analysis joins the damage and mitigation sides of policy. In the course's Quiggin framework, atmospheric concentration is the policy variable, total cost equals climate damage plus abatement cost, and the cost-minimising target occurs where marginal damage equals marginal abatement cost. The corresponding marginal value is the long-run carbon price.
The model is deliberately stylised, which makes its assumptions visible: reference concentration, business-as-usual concentration, damage curvature and abatement curvature all change the target. The result is therefore an organised comparison of assumptions rather than a policy fact independent of calibration.
Sensitivity analysis shows whether a recommendation survives plausible alternatives.
Read the diagram as a minimisation problem. Moving toward a tighter concentration target raises abatement effort and its associated cost, while reducing expected climate damage. Total cost is the vertical sum of those components.
At an interior optimum, a small additional unit of abatement saves the same amount of marginal damage that it costs. If marginal damage is higher, a tighter target is justified; if marginal abatement cost is higher, the model favours a looser target. Boundary solutions remain possible when the curves do not cross in the feasible range.
The equality condition is not a universal numerical answer.
Damage curvature governs how rapidly losses increase as concentration rises, while abatement curvature governs how quickly mitigation becomes costly as the target tightens. The business-as-usual benchmark and reference concentration define how much adjustment the model asks the economy to make. Discounting, risk and omitted non-market values can shift the estimated damage side.
A useful sensitivity analysis varies one assumption, explains the direction of movement in marginal curves, and states the implied change in the preferred target and carbon value. Policy evaluation should also distinguish a long-run shadow value from the observed price of a particular tax or permit market. The framework clarifies trade-offs; its credibility still depends on transparent inputs and explicit limits.
What this chapter covers
- 01
Integrated assessment models
- 02
Climate damage costs
- 03
Abatement costs
- 04
Marginal damage
- 05
Marginal abatement cost
- 06
Optimal concentration
- 07
Carbon price
- 08
Sensitivity analysis
Worked example · free
Solve a Quiggin-style target
- +1Write G* = (kA × GBAU + kD × G0) ÷ (kA + kD).
- +1Calculate the numerator as 0.20 × 660 + 0.30 × 360 = 240.
- +1Calculate the denominator as 0.50 and obtain G* = 480 ppm.
- +1Compute MD = 2 × 0.30 × (480 − 360) = 72.
- +1Compute MAC = 2 × 0.20 × (660 − 480) = 72.
- +1Interpret equality as the minimum-total-cost condition, not scientific certainty.
Key terms
- Integrated Assessment Model
- A framework that links climate, economic damage and mitigation cost components to compare policy pathways under explicit assumptions.
- Marginal Damage
- The extra welfare loss associated with one additional unit of the climate policy variable.
- Marginal Abatement Cost
- The extra resource cost of achieving one additional unit of emissions reduction or concentration control.
- Optimal Concentration
- The modelled concentration that minimises total damage plus abatement cost under the selected calibration.
- Carbon Price
- The marginal value of an emissions reduction at the policy target, read from the equal marginal damage and abatement cost.
- Sensitivity Analysis
- A systematic check of how a model result changes when uncertain or contested inputs are varied.
Climate Cost-Benefit Analysis FAQ
Why does the optimum satisfy equal marginal values?
If marginal damage exceeds marginal abatement cost, tighter policy avoids more harm than it costs. If abatement cost exceeds damage, the proposed tightening is too expensive. Equality marks the interior minimum.
What happens when the damage coefficient rises?
The target moves toward the lower reference concentration because additional concentration becomes more costly. The direction check helps detect a reversed coefficient or concentration anchor.
Is the modelled carbon price an observed market price?
No. It is the marginal value implied by the model calibration at the chosen target. An actual tax or permit price also reflects institutional design and market conditions.
Why run sensitivity analysis?
A point estimate can hide dependence on damage, technology, baseline or discounting assumptions. Sensitivity analysis identifies the drivers and shows whether the policy ranking is robust.
Exam move
Memorise the model logic before the algebra: tighter policy raises abatement cost and avoids damage, so the optimum equates the two margins. Write the general solution from memory, then solve several fresh parameter sets with every substitution shown. After each result, run two checks: confirm that the target lies between the reference and business-as-usual concentrations, and verify MD equals MAC.
Practise directional sensitivity without a calculator by asking which anchor receives more weight when a coefficient rises. Keep positive calibration inputs separate from normative choices such as discounting. In extended matching, reject an option that calls the result a physical threshold or treats one calibration as certain.
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