Date of Award
2026
Document Type
Open Access Master's Thesis
Degree Name
Master of Science in Applied Natural Resource Economics (MS)
Administrative Home Department
College of Business
Advisor 1
Jenny Apriesnig
Committee Member 1
Steven Holloway
Committee Member 2
Roman Sidortsov
Abstract
This study examines environmental compliance behavior among mining facilities regulated under the U.S. Clean Water Act (CWA). Using a national quarterly panel of National Pollutant Discharge Elimination System (NPDES)-permitted mining facilities, the analysis evaluates whether local socioeconomic and demographic indicators are associated with the likelihood that a facility enters significant noncompliance (SNC) status. Facility compliance histories are compiled from the U.S. Environmental Protection Agency’s Enforcement and Compliance History Online (ECHO) database and is merged with county- and state-level socioeconomic indicators and election data. A fixed-effects logistic regression model is used to account for time-invariant facility heterogeneity. The results suggest that SNC risk is driven primarily by temporal variation and violation history, with local socioeconomic and demographic covariates demonstrating no systematic relationship with SNC designation. These findings inform environmental justice research by clarifying how regulatory processes may interact with historical inequities in pollution exposure
Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 License.
Recommended Citation
Johnson, Eli, "MODELING DETERMINANTS OF SIGNIFICANT NONCOMPLIANCE IN THE U.S. MINING SECTOR: A FIXED EFFECTS LOGISTIC REGRESSION APPROACH", Open Access Master's Thesis, Michigan Technological University, 2026.