Environmental Economics and Uncertainty: Review and a Machine Learning Outlook

In Oxford Research Encyclopedia of Environmental Science. Oxford University Press. https://doi.org/10.1093/acrefore/9780199389414.013.572

24 Pages Posted: 21 May 2020 Last revised: 2 Sep 2020

See all articles by Ruda Zhang

Ruda Zhang

University of Southern California

Patrick Wingo

National Energy Technology Laboratory

Rodrigo Duran

affiliation not provided to SSRN

Kelly Rose

National Energy Technology Laboratory

Jennifer Bauer

National Energy Technology Laboratory

Roger Ghanem

affiliation not provided to SSRN

Date Written: April 23, 2020

Abstract

Economic assessment in environmental science concerns the measurement or valuation of environmental impacts, adaptation, and vulnerability. Integrated assessment modeling is a unifying framework of environmental economics, which attempts to combine key elements of physical, ecological, and socioeconomic systems. Uncertainty characterization in integrated assessment varies by component models: uncertainties associated with mechanistic physical models are often assessed with an ensemble of simulations or Monte Carlo sampling, while uncertainties associated with impact models are evaluated by conjecture or econometric analysis.

Manifold sampling is a machine learning technique that constructs a joint probability model of all relevant variables which may be concentrated on a low-dimensional geometric structure. Compared with traditional density estimation methods, manifold sampling is more efficient especially when the data is generated by a few latent variables. The manifold-constrained joint probability model helps answer policy-making questions from prediction, to response, and prevention. Manifold sampling is applied to assess risk of offshore drilling in the Gulf of Mexico.

Keywords: data-driven models, diffusion manifolds, environmental economics, environmental valuation, probability model, manifold sampling, oil spills

JEL Classification: Q51, Q53

Suggested Citation

Zhang, Ruda and Wingo, Patrick and Duran, Rodrigo and Rose, Kelly and Bauer, Jennifer and Ghanem, Roger, Environmental Economics and Uncertainty: Review and a Machine Learning Outlook (April 23, 2020). In Oxford Research Encyclopedia of Environmental Science. Oxford University Press. https://doi.org/10.1093/acrefore/9780199389414.013.572, Available at SSRN: https://ssrn.com/abstract=3583911

Ruda Zhang (Contact Author)

University of Southern California ( email )

2250 Alcazar Street
Los Angeles, CA 90089
United States

Patrick Wingo

National Energy Technology Laboratory ( email )

3610 Collins Ferry Rd
Morgantown, WV 26507
United States

Rodrigo Duran

affiliation not provided to SSRN

Kelly Rose

National Energy Technology Laboratory ( email )

3610 Collins Ferry Rd
Morgantown, WV 26507
United States

Jennifer Bauer

National Energy Technology Laboratory ( email )

3610 Collins Ferry Rd
Morgantown, WV 26507
United States

Roger Ghanem

affiliation not provided to SSRN

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