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Bayesian Reconstruction of Past Populations and Vital Rates by Age for Developing and Developed Countries

Mark C Wheldon and Adrian Elmes Raftery

September 2012 CSSS Working Paper #117

Abstract

Abstract

We extend Bayesian population reconstruction, a recent method for estimating past populations by age, with fully probabilistic statements of uncertainty. It simultaneously estimates age-specific population counts, fertility rates, mortality rates and net international migration flows from fragmentary data while formally accounting for measurement error. As inputs, Bayesian reconstruction takes initial bias-reduced estimates of age-specific population counts, fertility rates, survival proportions and net international migration. We extend the method to apply to countries without censuses at regular intervals. We also develop a method for using it to assess the consistency between model life tables and available census data, and hence to compare different model life table systems. We show that the method works well in countries with widely varying levels of data quality by applying it to reconstruct the past female populations by age of Laos, a country with little vital registration data where population estimation depends largely on surveys, Sri Lanka, a country with some vital registration data, and New Zealand, a country with a highly developed statistical system and high-quality vital registration data.

Keywords: Bayesian hierarchical model, Fertility, International migration, Model life table, Mortality, Vital registration data