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Updated: Oct 13, 2025

Split Point Analysis and Uncertainty Quantification of Thermal-Optical Organic/Elemental Carbon Measurements
Published on: September 7, 2019
Carbon price prediction under output uncertainty
Na Liu1, Futie Song2
1Business School, East China University of Science and Technology, Xuhui District, Shanghai, 200237, China.
Output growth uncertainty significantly impacts climate economics. This study shows that accounting for output uncertainty in the EZ climate model leads to lower carbon prices, improving climate policy decisions.
Area of Science:
- Climate economics
- Environmental modeling
- Economic impact assessment
Background:
- Output growth uncertainty is a critical factor in climate economics, influencing emissions, temperature shifts, and economic damages.
- Existing climate models often simplify or omit the complexities of output growth uncertainty.
Purpose of the Study:
- To integrate output growth uncertainty into the EZ climate model.
- To calculate future carbon prices (marginal abatement cost) that maximize social welfare.
- To analyze the sensitivity of carbon prices to population and per capita output growth rates.
Main Methods:
- Incorporation of predicted global carbon emissions under output growth uncertainty into the EZ model.
- Calculation of optimal carbon prices for specific years (2020-2095).
- Sensitivity analysis of population growth rate and per capita output growth rate parameters.
Main Results:
- Optimal carbon prices per ton of CO2e are projected to decrease from $294.9 in 2020 to $15.4 in 2095.
- Both population and per capita output growth rates positively influence future carbon prices, with per capita output growth having a larger effect.
- Carbon prices are lower under output uncertainty compared to output certainty, with high output uncertainty driving significant carbon price volatility.
Conclusions:
- Output growth uncertainty is crucial for accurate climate economic modeling.
- The EZ climate model, incorporating output uncertainty, can inform policies for reduced carbon pricing.
- Further research into output growth uncertainty is essential for robust climate policymaking.
Related Concept Videos
Uncertainty: Overview
Prediction Intervals
However, the point estimate is most likely not the exact value of the population parameter, but close to it. After calculating point estimates, we construct interval estimates, called confidence intervals or prediction intervals. This prediction interval comprises a range of values unlike the point estimate and is a better predictor of the observed sample value, y.
Uncertainty: Confidence Intervals
Propagation of Uncertainty from Random Error
Propagation of Uncertainty from Systematic Error
Clausius-Clapeyron Equation

