Publication Abstracts
Steinbuks et al. 2024
Steinbuks, J., Y. Cai,
, and T.W. Hertel, 2024: Assessing effects of climate and technology uncertainties in large natural resource allocation problems. Geosci. Model Dev., 17, no. 12, 4791-4819, doi:10.5194/gmd-17-4791-202.The productivity of the world's natural resources is critically dependent on a variety of highly uncertain factors, which obscure individual investors and governments that seek to make long-term, sometimes irreversible, investments in their exploration and utilization. These dynamic considerations are poorly represented in disaggregated resource models, as incorporating uncertainty into large-dimensional problems presents a challenging computational task. In this paper, we apply the SCEQ algorithm (Cai and Judd, 2023) to solve a large-scale dynamic stochastic global land resource use problem with stochastic crop yields due to adverse climate impacts and limits on further technological progress. For the same model parameters and bounded shocks, the range of land conversion is considerably smaller for the dynamic stochastic model than for deterministic scenario analysis.
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BibTeX Citation
@article{st02620c, author={Steinbuks, J. and Cai, Y. and Jaegermeyr, J. and Hertel, T. W.}, title={Assessing effects of climate and technology uncertainties in large natural resource allocation problems}, year={2024}, journal={Geoscientific Model Development}, volume={17}, number={12}, pages={4791--4819}, doi={10.5194/gmd-17-4791-202}, }
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RIS Citation
TY - JOUR ID - st02620c AU - Steinbuks, J. AU - Cai, Y. AU - Jaegermeyr, J. AU - Hertel, T. W. PY - 2024 TI - Assessing effects of climate and technology uncertainties in large natural resource allocation problems JA - Geosci. Model Dev. JO - Geoscientific Model Development VL - 17 IS - 12 SP - 4791 EP - 4819 DO - 10.5194/gmd-17-4791-202 ER -
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