Abstract
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.
Keywords
Climate change uncertainty, Land use change, SCEQ method, Stochastic modeling, Global cropland expansion, Agricultural productivity, Agricultural economics
Date of this Version
6-19-2024
Recommended Citation
Steinbuks, Jevgenijs; Cai, Yongyang; Jaegermeyr, Jonas; and Hertel, Thomas W., "Assessing Effects of Climate and Technology Uncertainties in Large Natural Resource Allocation Problems" (2024). Department of Agricultural Economics Faculty Publications. Paper 115.
https://docs.lib.purdue.edu/agedocs/115
Included in
Economics Commons, Food Security Commons, Food Studies Commons
Comments
This is the publisher PDF of Steinbuks, J., Cai, Y., Jaegermeyr, J., and Hertel, T. W.: Assessing effects of climate and technology uncertainties in large natural resource allocation problems, Geosci. Model Dev., 17, 4791–4819, 2024. Published CC-BY by Copernicus Publications, the version of record is also available at DOI: 10.5194/gmd-17-4791-2024.