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Application of a predictive Bayesian model to environmental accounting.
1Science and Public Policy Program, University of Oklahoma, Room S-202, 100 E. Boyd Street, Norman, OK 73019, USA. rpanex@ou.edu
Journal of Hazardous Materials
|March 7, 2001
Summary
This study introduces a predictive Bayesian model to assess uncertain environmental costs, improving risk management for businesses. It helps evaluate decisions like phasing out PCB transformers by quantifying risks.
Area of Science:
- Environmental Accounting
- Risk Management
- Bayesian Modeling
Background:
- Standard accounting often overlooks significant environmental costs and uncertainties.
- Existing environmental accounting methods inadequately address highly uncertain or contingent costs.
Purpose of the Study:
- To demonstrate a predictive Bayesian model for assessing uncertain and contingent environmental costs.
- To evaluate business decisions involving environmental risks, such as PCB transformer phase-out.
Main Methods:
- Developed a spreadsheet implementation of a predictive Bayesian model.
- Incorporated historical data, engineering estimates, and subjective judgment to assess accident frequency and severity.
- Generated probability distributions for key outcomes, not just parameters.
Main Results:
- The model effectively assesses simultaneous variability and uncertainty in environmental costs.
- Comparison of model results using various risk measures provides comprehensive insights.
- Demonstrated application in evaluating the accelerated phase-out of PCB-containing transformers.
Conclusions:
- Predictive Bayesian modeling offers a robust framework for managing uncertain environmental costs.
- The approach enhances corporate environmental risk management strategies.
- This method improves decision-making for environmental investments and liabilities.