Combining growth and level data: An estimation of the population of Belgian municipalities between 1880 and 1970
Stijn Ronsse and
Samuel Standaert
Historical Methods: A Journal of Quantitative and Interdisciplinary History, 2017, vol. 50, issue 4, 218-226
Abstract:
Economic historians that study long-term changes during the nineteenth and twentieth century are fundamentally restricted by the availability of qualitative data. As a result, researchers are forced to either impute missing data, or otherwise combine datasets in some way. In this article, we demonstrate the versatility of state-space models in addressing these problems. Not only do they enable us to compose large data series of high quality, they also provide a clear estimate of how reliable this data is, allowing any subsequent analyses to take this reliability into account. We illustrate the advantages of a state-space model using the population of Belgian municipalities as a case study. By combining growth and level data, we are able to compute yearly population statistics of over 2600 municipalities from 1880 to 1970.
Date: 2017
References: Add references at CitEc
Citations: View citations in EconPapers (2)
Downloads: (external link)
http://hdl.handle.net/10.1080/01615440.2017.1355764 (text/html)
Access to full text is restricted to subscribers.
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:taf:vhimxx:v:50:y:2017:i:4:p:218-226
Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/vhim20
DOI: 10.1080/01615440.2017.1355764
Access Statistics for this article
Historical Methods: A Journal of Quantitative and Interdisciplinary History is currently edited by J. David Hacker and Kenneth Sylvester
More articles in Historical Methods: A Journal of Quantitative and Interdisciplinary History from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst (chris.longhurst@tandf.co.uk).