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A Bayesian Reconstruction of a Historical Population in Finland, 1647–1850
This article provides a novel method for estimating historical population development. We review the previous literature on historical population time-series estimates and propose a general outline to address the well-known methodological problems. We use a Bayesian hierarchical time-series model th...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer US
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7329763/ https://www.ncbi.nlm.nih.gov/pubmed/32519305 http://dx.doi.org/10.1007/s13524-020-00889-1 |
Sumario: | This article provides a novel method for estimating historical population development. We review the previous literature on historical population time-series estimates and propose a general outline to address the well-known methodological problems. We use a Bayesian hierarchical time-series model that allows us to integrate the parish-level data set and prior population information in a coherent manner. The procedure provides us with model-based posterior intervals for the final population estimates. We demonstrate its applicability by estimating the long-term development of Finland’s population from 1647 onward and simultaneously place the country among the very few to have an annual population series of such length available. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1007/s13524-020-00889-1) contains supplementary material, which is available to authorized users. |
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