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Activity Number: 151
Type: Invited
Date/Time: Monday, August 10, 2015 : 10:30 AM to 12:20 PM
Sponsor: Social Statistics Section
Abstract #314574
Title: From Bayesian Forecasts to Decisions
Author(s): Arkadiusz Wisniowski* and Jakub Bijak and Jonathan J. Forster
Companies: ESRC Centre for Population Change and ESRC Centre for Population Change and ESRC Centre for Population Change
Keywords: Bayesian forecasts ; elicitation ; decision making ; demography
Abstract:

There is a growing awareness amongst decision makers that single number and scenario-based demographic forecasts are inadequate for their purposes. In parallel, developers of forecasting methodology have increasingly adopted Bayesian approaches which can coherently summarise uncertainty. However, the utilisation of the resulting probabilistic forecasts in the decision-making processes remains underdeveloped. How do we then help users to fully utilise the probabilistic forecasts in their decision making process? One possible answer consists of eliciting the loss functions from the decision makers and applying Bayesian decision theory to deliver bespoke decision advice and support. In this paper, we describe a framework to develop a two-way communication with decision makers, whose priorities inform the loss function, and to whom the resulting forecasts are communicated back in a user-friendly form. We illustrate our approach with a real-world decision example and contrast it with a scenario-based alternative.


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