Journal of Forest Economics > Vol 34 > Issue 1-2

The Influence of Parametric Uncertainty on Projections of Forest Land Use, Carbon, and Markets

Brent Sohngen, Ohio State University, USA, Marwa E. Salem, RTI International, USA, Justin S. Baker, RTI International, USA, Michael J. Shell, U.S. Environmental Protection Agency, USA, Sei Jin Kim, Ohio State University, USA,
Suggested Citation
Brent Sohngen, Marwa E. Salem, Justin S. Baker, Michael J. Shell and Sei Jin Kim (2019), "The Influence of Parametric Uncertainty on Projections of Forest Land Use, Carbon, and Markets", Journal of Forest Economics: Vol. 34: No. 1-2, pp 129-158.

Publication Date: 07 Aug 2019
© 2019 B. Sohngen, M. E. Salem, J. S. Baker, M. J. Shell and S. J. Kim


Open Access

This is published under the terms of CC-BY.

In this article:
1. Introduction
2. Methods
3. Results
4. Discussions
5. Conclusion


This paper uses Monte Carlo methods and regression analysis to assess the role of uncertainty in yield function and land supply elasticity parameters on land use, carbon, and market outcomes in a long-term dynamic model of the global forest sector. The results suggest that parametric uncertainty has little influence on projected future timber prices and global output, but it does have important implications for regional projections of outputs. A wide range of outcomes are possible for timber outputs, depending on growth and elasticity parameters. Timber output in the U.S., for instance, could change by -67 to +98 million m3 per year by 2060. Despite uncertainty in the parameters, our analysis suggests that the temperate zone may sequester +30 to +79 Pg C by 2060 and +58 to +114 Pg C by 2090 while the tropics are projected to store -35 to +70 Pg C and -33 to +73 Pg C for the same time periods, respectively. Attributional analysis shows that uncertainty in the parameters regulating forest growth has a more important impact on projections of future carbon storage than uncertainty in the land supply elasticity parameters. Moreover, the results suggest that understanding growth parameters in regions with large current carbon stocks is most important for making future projections of carbon storage.



Journal of Forest Economics, Volume 34, Issue 1-2 Special issue - State of the art methods to project forest carbon stocks: Articles Overiew
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