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Population projections have traditionally been done deterministically using the cohort component method, yielding a single value for each projected future population quantity of interest. Over the past decade, the United Nation Population Division has adopted a probabilistic approach to project fertility, mortality, migration and population for all countries, using Bayesian hierarchical models developed at the University of Washington. More recently the methods have been extended to be applied to subnational population projections for states and counties. The Office of Financial Management (OFM) is actively exploring the methodology for the use in the next revision of county-level demographic projections for the Washington State.

This two-part course, by one of the two core developers of the new methodology, will teach the theory and practice behind Bayesian subnational population projections. In Part I (Theory) in a lecture-style format, the ideas behind the probabilistic subnational demographic modeling will be explained. In Part II (Practice) in hands-on exercises, using data from Washington counties as an example, participants will become familiar with the suite of R packages that implements the methodology. By the end of the course, they will have a basic understanding of the methods, be able to generate projections using their own data, and visualize probabilistic projections for many quantities of interest using various output formats, such as graphs, tables, maps, and pyramids.

Prerequisites

Familiarity with basic statistical concepts.