Bayesian Reconstruction of Past Demography

Author(s): Michael Price

Year: 2018


I describe a novel, age-structured, Bayesian framework for reconstructing past demography. The framework is quite flexible and can incorporate and synthesize a wide range of data. I demonstrate its use with human burial data, where each observation can include an AMS radiocarbon measurement, an estimate of age-at-death, or both. Conceptually, the framework is useful because it addresses in a statistically principled way two vexing sources of equifinality in archaeological data: (1) the radiocarbon calibration curve and (2) the fact that even if demographic rates such as age-specific mortality, fertility, and migration are stable an infinite set of demographic histories can yield the same predicted growth rate and stable age distribution. Fortunately, not all demographic histories are equally likely and some are even impossible. I utilize theoretical and empirical knowledge from evolutionary demography and life history theory to parameterize and specify prior probabilities for alternative demographic histories. The radiocarbon and age-at-death data update these prior probabilities to give posterior probabilities, yielding a (hopefully) sensible and accurate reconstruction of past demography.

Cite this Record

Bayesian Reconstruction of Past Demography. Michael Price. Presented at The 82nd Annual Meeting of the Society for American Archaeology, Washington, DC. 2018 ( tDAR id: 442893)

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Abstract Id(s): 21653