Uncertainty Analysis

Abstract

Economic consequences of natural, intentional, and accidental hazards include uncertainties associated with hazardous events and the economic structure of regions affected by these events. These uncertainties may arise due to variability in an event’s magnitude, timing, duration, and location, as well as differing economic structures in various regions of interest. Quantification and propagation of these uncertainties result in probability distributions associated with various economic consequences. In this study, uncertainties associated with economic consequences are based on variability in stochastic regressors (predictor variables) within least squares and quantile regression models. Addressing uncertainties associated with regression model form (using linear predictor functions) was beyond the scope of this study. Variability in stochastic regressors may arise due to inherent randomness (aleatory uncertainty) or incomplete knowledge (epistemic uncertainty) about underlying phenomena. Epistemic uncertainty may be reduced to aleatory uncertainty with more information, whereas aleatory uncertainty is not reducible. These consequence distributions, presented within a user-friendly and readily deployable tool, may be valuable for homeland security policy-makers conducting national risk assessments and for emergency management decision-making.