Description

We address the issue of optimal investment in “preventative capital” to mitigate episodic, mobile-source air pollution events in Utah’s Wasatch Front region. We calibrate Berry et al.'s (2015) endogenous-risk model using a unique dataset related to the region’s "red air day" episodes occurring over the past decade. Our analysis demonstrates that, under a wide range of circumstances, the optimal steady-state level of preventative capital stock – raised through the issuance of a municipal “clean air bond” that can be used to fund more aggressive mitigation efforts – meets the standard for PM2.5 concentrations with positive social net benefits. We estimate benefit-cost ratios ranging between 5.1:1 and 8.1:1, depending upon trip-count elasticity with respect to the preventative capital stock. These ratios are larger than those reported in Acharya and Caplan (2019) for northern Utah, but still lower than the range generally estimated for the 1990 Clean Air Act Amendment

OCLC

1143741661

Document Type

Dataset

DCMI Type

Dataset

File Format

.txt; .cvs

Viewing Instructions

Any software that can read or convert CSV format.

Publication Date

9-18-2019

Funder

Utah Agricultural Experiment Station

Publisher

Utah State University

Award Number

Utah Agricultural Experiment Station, UTAO-1334

Methodology

Data is secondary, compiled in comma-separated values (CSV) format. The data sources are the US Environmental Protection Agency, the Utah Division of Air Quality, the Utah Department of Transportation, and the Weather Underground.

Referenced by

Arthur Caplan and Ramjee Acharya. "Control of Episodic Air Pollution in Utah’s Wasatch Front Region Through Investment in Preventative Capital" (2020) Available at: http://works.bepress.com/arthur_caplan/131/

Start Date

1-1-2002

End Date

12-31-2013

Language

eng

Code Lists

See the Caplan_Variables_v2.csv file.

Disciplines

Agricultural Economics

License

Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 License.

Checksum

503b3fb6f5cbbf4dc775d2bfb6d1fe9d

Additional Files

README.txt (2 kB)
MD5: 06C0A6070C86ACB2C2582A6BDB39E250

wasatch_newdata.csv (616 kB)
MD5: 83ACD25C4EE0C8A1FF9200D0171C4B6C

Caplan_Variables_v2.csv (2 kB)
MD5: 95005F0D0DFE743F0B570AB470A9DCA7

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