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...
| Published in: | Demography (Springer Nature) Vol. 57; no. 3; pp. 1171 - 1193 |
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| Main Authors: | , , |
| Format: | Article |
| Published: |
Springer Nature
Jun2020
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| Subjects: | |
| Online Access: | View this record in EBSCOhost |
| Summary: | 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. |
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