Uncertainty Discounting for Land-Based Carbon Sequestration

By Kim, Man-Keun; McCarl, Bruce A. | Journal of Agricultural and Applied Economics, April 2009 | Go to article overview
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Uncertainty Discounting for Land-Based Carbon Sequestration


Kim, Man-Keun, McCarl, Bruce A., Journal of Agricultural and Applied Economics


The effect of stochastic factors on soil carbon makes the quantity of carbon generated under a sequestration project uncertain. Hence, the quantity of sequestered carbon may need to be discounted to avoid liability from shortfalls. We present a potentially applicable uncertainty discount and discuss difficulties that might arise in empirical use. We insist mat the variance in historical crop yields across geographical areas is used to derive a proxy variance for forming an uncertainty discount for carbon projects. Application of our approach suggests that project level uncertainty discounts would be 15-20% for the East Texas region.

Key Words: carbon seqestration, discount, uncertainty

JEL Classifications: H43, Q54

Reduction of atmospheric carbon dioxide (CO2), a major greenhouse gas (GHG), is central to addressing the climate change problem and in the formation of policies mat aim to limit atmospheric GHG levels (see discussion in IPCC 2007a,b). Land-based carbon sequestration - a process whereby plants and trees, through photosynthesis processes, trap atmospheric CO2 and fix carbon into soil and plant body mass - has drawn attention as a strategy for GHG reduction. If GHG emissions reductions are pursued, a carbon market may be created as advocated for example in the Kyoto Protocol (UNFCCC) or potential legislation like Lieberman- Warner bill (Lieberman and Warner Bill) where entities sequestering carbon may be able to generate GHG reduction credits that buying emitters can use to offset their emissions (as discussed in Butt and McCarl; Kim and McCarl).

Various studies have explored the potential of land-based carbon sequestration strategies such as afforestation, reforestation and other land use changes (Adams et al.; Parks and Hardie; Plantinga, Maudlin, and Miller; Stavins; McCarl and Schneider; Lewandrowski et al.; USERA; Lubowski, Plantinga, and Stavins; Antle et al.).1 These studies not only show considerable potential for soil based sequestration, but also indicate that the strategy might achieve GHG reduction targets at a lower cost compared with other alternatives such as developing emission abatement technologies (see Table 1 for a brief summary of the studies).

From an agricultural producer's point of view, the GHG emission credit price would be a payment that would offset the cost of implementing a carbon sequestration project. The project cost would be any foregone net income arising from altered production plus any added cost to adopt the sequestering practices. The potentially salable quantity of GHGs would equal the net volume sequestered plus any associated net GHG reduction from altered fossil fuel usage, if any. However, as argued in the next section, there also may be uncertainty discounts that should be considered. Most previous studies generally ignore uncertainty discount and thus may overestimate the salable credits and revenues arising from a carbon sequestration practice. Thus it is important to assess the magnitude of uncertainty discount to formulate the correct economics of a carbon sequestration project. This paper presents a confidence interval based uncertainty discount approach motivated by the Canadian suggestion in the international negotiations and then presents an empirical application in the context of a potential Eastern Texas project.

Uncertainty Sources

There are a variety of ways uncertainties arise in regards to the carbon sequestered by sequestration projects. Namely, Birdsey and Heath, as well as and Heath and Smith argue that the sources of uncertainty include:

* Climate and other factors such as pests, fire, and so on that induce annual production variability in the quantity of carbon sequestered at a location;

* Aggregation induced sampling error at a regional scale;

* Carbon pool measurement error; and

* Intertemporal variation in the duration and permanence of carbon sequestered in the future.

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