A Bayesian Reconstruction of a Historical Population in Finland, 1647–1850
Abstract
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.
Main Authors
Format
Articles
Research article
Published
2020
Series
Subjects
Publication in research information system
Publisher
Springer
The permanent address of the publication
https://urn.fi/URN:NBN:fi:jyu-202006174250Use this for linking
Review status
Peer reviewed
ISSN
0070-3370
DOI
https://doi.org/10.1007/s13524-020-00889-1
Language
English
Published in
Demography
Citation
- Voutilainen, M., Helske, J., & Högmander, H. (2020). A Bayesian Reconstruction of a Historical Population in Finland, 1647–1850. Demography, 57(3), 1171-1192. https://doi.org/10.1007/s13524-020-00889-1
License
Funder(s)
Research Council of Finland
Research Council of Finland
Research Council of Finland
Research Council of Finland
OP Group Research Foundation
Funding program(s)
Research costs of Academy Research Fellow, AoF
Research profiles, AoF
Academy Project, AoF
Research costs of Academy Research Fellow, AoF
Foundation
Akatemiatutkijan tutkimuskulut, SA
Profilointi, SA
Akatemiahanke, SA
Akatemiatutkijan tutkimuskulut, SA
Säätiö
Additional information about funding
Open access funding provided by University of Jyväskylä (JYU). Miikka Voutilainen acknowledges financial support of OP Group Research Foundation grants 201600139, 20170130, and 20180071; Academy of Finland grant 308975; and research visit to UC Davis in 2018. Jouni Helske was supported by the Academy of Finland research grants 284513 and 312605 and 311877.
Copyright© The Authors, 2020