Print

Synopsis

Bayesian population reconstruction is a method for estimating past populations by age with fully probabilistic statements of uncertainty. It simultaneously estimates age-specific population counts, vital rates, and net migration from fragmentary data while formally accounting for measurement error. As inputs, it takes bias-reduced initial estimates of age-specific population counts, vital rates and net migration, and expert opinion about measurement error informed by data where available. We describe the new approach in the context of existing methods and demonstrate its flexibility by showing that it works well in countries with widely varying levels of data quality by applying it to very different countries, namely Laos and New Zealand. Remaining challenges and future directions will be discussed.

Bio

Mark Wheldon is Lecturer of Biostatistics at the Auckland University of Technology and Biostatistician at the Centre for Clinical Research and Effective Practice (CCRep) at Middlemore Hospital, both in Auckland, New Zealand. He has a PhD from the Department of Statistics at the University of Washington. His research includes the development of statistical methods for demography, with a focus on Bayesian models. His current work in this area involves the development of new methods to estimate fertility, mortality, and migration from multiple, noisy data sources. He continues to collaborate with demographers at the United Nations. As Biostatistician at CCRep, he collaborates with other researchers on health-related studies in a range of areas.