Assessing the Uncertainty of Land Based Carbon Sequestration: A Parameter Uncertainty Analysis with a Global Land Use Model
AbstractThis paper analyzes the effect of uncertainty in several key parameters on the marginal costs of carbon sequestration in forests. These parameters include the land supply elasticity, which governs the conversion of land from agriculture to forests and vice versa; parameters of the forest biomass yield function; parameters of the forest carbon density function; and parameters of the costs functions for accessing inaccessible land. Monte Carlo techniques are thus used to turn the global forest model with no probability (e.g., Sohngen & Mendelsohn, 2003; 2007) into a proper probability model through Latin hypercube sampling. For this paper, we have restricted our analysis to consideration of probability distributions for only two of the parameters described above. Specifically, these are the parameters of the forest biomass yield function and the land supply elasticity. The importance index and the least square linearization are used to determine the relative contribution of input parameters to the model results. Five hundred model runs in one simulation were performed with covariability among the parameters. The Monte Carlo simulations indicated that most of the uncertainty in forest area in developed countries relates to uncertainty in parameters of the biomass function while in developing countries, where deforestation is more important (e.g., Brazil), the simulation showed the parameters of land supply elasticity to have the most important implications for carbon supply. These results are perhaps not too surprising but they do point to the need to empirically estimate land supply elasticities in regions like Brazil, where such estimates are not currently available in the literature. The results also provide information that can be used to estimate uncertainty intervals for carbon sequestration cost functions.
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Bibliographic InfoPaper provided by Agricultural and Applied Economics Association in its series 2009 Annual Meeting, July 26-28, 2009, Milwaukee, Wisconsin with number 49416.
Date of creation: 2009
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Uncertainty Analysis; Global Land Use Model; Carbon Sequestration; Monte Carlo simulations; Resource /Energy Economics and Policy;
This paper has been announced in the following NEP Reports:
- NEP-ALL-2009-05-16 (All new papers)
- NEP-CMP-2009-05-16 (Computational Economics)
- NEP-ENE-2009-05-16 (Energy Economics)
- NEP-ENV-2009-05-16 (Environmental Economics)
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- Brent Sohngen & Robert Mendelsohn, 2003. "An Optimal Control Model of Forest Carbon Sequestration," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 85(2), pages 448-457.
- Lubowski, Ruben & Plantinga, Andrew & Stavins, Robert, 2005.
"Land-Use Change and Carbon Sinks: Econometric Estimation of the Carbon Sequestration Supply Function,"
Working Paper Series
rwp05-001, Harvard University, John F. Kennedy School of Government.
- Lubowski, Ruben N. & Plantinga, Andrew J. & Stavins, Robert N., 2006. "Land-use change and carbon sinks: Econometric estimation of the carbon sequestration supply function," Journal of Environmental Economics and Management, Elsevier, vol. 51(2), pages 135-152, March.
- Lubowski, Ruben N. & Plantinga, Andrew J. & Stavins, Robert N., 2005. "Land-Use Change and Carbon Sinks: Econometric Estimation of the Carbon Sequestration Supply Function," Working paper 225, Regulation2point0.
- Massimo Tavoni & Valentina Bosetti & Brent Sohngen, 2007.
"Forestry and the Carbon Market Response to Stabilize Climate,"
2007.15, Fondazione Eni Enrico Mattei.
- Tavoni, Massimo & Sohngen, Brent & Bosetti, Valentina, 2007. "Forestry and the carbon market response to stabilize climate," Energy Policy, Elsevier, vol. 35(11), pages 5346-5353, November.
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