Causality for Risk Analysts: Improving Our Understanding of How the World Works

Louis Anthony Cox
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Louis Anthony Cox: Cox Associates

Chapter Chapter 1 in Improving Risk Analysis, 2012, pp 3-58 from Springer

Abstract: Abstract Acting effectively in an uncertain world requires two main skills: predicting the probable consequences of alternative courses of action and choosing actions that make preferred consequences more likely. Risk analysis supports and applies both skills. It provides a framework to enable its practitioners to assess the probable consequences of alternative choices (including the status quo), to communicate technical findings and remaining uncertainties effectively to different audiences, and to use the results to advise risk managers and policy makers about what to do next. These three core components of risk assessment, risk communication, and risk management are making risk analysis invaluable in widely diverse applications. Prominent application areas include project risk management, enterprise risk management, nuclear and aviation safety, community-based disaster preparation and planning, health effects research, drug development, product safety assessment, ecotoxicology, regulatory program evaluation, public health, and other areas of applied risk research and management.

Keywords: Bayesian Network; Granger Causality Test; Causal Interpretation; Dynamic Bayesian Network; Bayesian Network Model (search for similar items in EconPapers)
Date: 2012
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DOI: 10.1007/978-1-4614-6058-9_1

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