Document Type
Article
Date of Original Version
2017
Department
Environmental and Natural Resource Economics
Abstract
We introduce a model that incorporates two important elements to estimating welfare gains from groundwater management: stochasticity and a spatial stock externality. We estimate welfare gains resulting from optimal management under uncertainty as well as a gradual stock externality that produces the dynamics of a large aquifer being slowly exhausted. This groundwater model imposes an important aspect of a depletable natural resource without the extreme assumption of complete exhaustion that is necessary in a traditional single cell (bathtub) model of groundwater extraction. Using dynamic programming, we incorporate and compare stochasticity for both an independent and identically distributed as well as a Markov chain process for annual rainfall. We find that the spatial depletion of the aquifer is significant to welfare gains for a parameterization of a section of the Ogallala Aquifer in Kansas, ranging from 2.9% to 3.01%, which is larger than those found previously over the region. Surprisingly, the inclusion of stochasticity in rainfall increases welfare gains only slightly.
Citation/Publisher Attribution
Merrill, N.H., & Guilfoos, T. (2018). Optimal Groundwater Extraction under Uncertainty and a Spatial Stock Externality. American Journal of Agricultural Economics, 100(1), 220-238. doi:10.1093/ajae/aax057
Available at: https://doi.org/10.1093/ajae/aax057
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This work is licensed under a
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