Capalbo, Susan (Montana State University, Dept. of Agricultural Economics and Economics, Bozeman, MT, 59717-2920; Phone: 406-994-5619; Fax: 406-994-4838; Email:


Estimating the Economic Potential for Agricultural Soil Carbon Sequestration in the Central U.S. Using an Aggregate Econometric-Process Simulation Model


J. Antle, S. Capalbo*, K. Paustian


As the scientific evidence supporting the hypothesis of anthropogenic global warming and climate change has grown, so has the demand for viable greenhouse gas (GHG) mitigation strategies. Research has shown that agricultural GHG mitigation could offset a relatively small proportion of total U.S. emissions and that agricultural soil carbon sequestration could be cost effective. Studies of economic potential for soil carbon sequestration conducted to date have been based on either field-scale economic simulation models covering relatively small regions where such data are available (e.g., cites) or on sectoral models. However, site-specific field-scale or farm-scale data are not generally available for large regions of the U.S. and other countries; nor are the data and parameters available to implement sectoral models for many regions of the world. Consequently, analysis of economic potential for agricultural soil carbon sequestration has been limited to selected regions within the U.S. and for selected sectors. The purpose of this paper is to develop and apply a method to assess economic potential for agricultural GHG mitigation that can be implemented using existing secondary data, such as the agricultural census data available in the U.S. and many other regions of the world, combined with widely-available estimates of soil carbon stocks derived from biophysical simulation models such as Century (cites) or from simpler estimation methods. This economic methodology utilizes the principle of opportunity cost on which detailed micro-economic analysis of agricultural GHG mitigation potential is also based. However, in place of simulation models based on site-specific field-level or farm-level data, the method proposed here is based on the estimation of conventional econometric profit function models with agricultural census data aggregated to the county scale for a region such as the central U.S. We also use this model to investigate the importance of two issues that have been identified as potentially critical in the assessment of carbon sequestration potential, namely the impact of spatial scale at which carbon stocks and changes are estimated, and the effects of transaction costs on economic feasibility of soil carbon sequestration contracts. Simulations for the central U.S. show that reduction in fallow and conservation tillage adoption in the wheat system could generate up to about 1.7 million MgC/yr, whereas increased adoption of conservation tillage in the corn-soy-feed system could generate up to about 6.2 million MgC/yr at a price of $200/MgC. Due to the relatively high price elasticity of response, at least half of this potential could be achieved at relatively low carbon prices (less than $100 per ton). The aggregate econometric-process model used in this analysis was found to produce estimates of economic potential for soil carbon sequestration potential similar to results produced by much more data-intensive, field-scale models. This result suggests that this simpler, aggregate modeling approach can produce credible estimates of soil carbon sequestration potential.