Publication Abstracts

Steinbuks et al. 2024

Steinbuks, J., Y. Cai, J. Jaegermeyr, 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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