A methodology for projecting sparse populations and its application to remote Indigenous communities

Alfred Michael Dockery, Mark N. Harris, Nicholas Holyoak, Ranjodh B. Singh

Research output: Contribution to journalArticlepeer-review


A new method is proposed for generating projections for sparse populations by locality, age cohort and gender. An adaptation of the cohort replacement method, the approach uses a Tobit model with varying censoring limits to model population changes by cohort. As an applied example, projections are generated for 2016 Indigenous populations in communities in regional and remote Australia, and then compared to actual 2016 Census population counts. We argue the approach has considerable potential, with the model performing well in out-of-sample projection while offering projections at a much finer-grained level of disaggregation than currently available to planners and policy-makers.

Original languageEnglish
Number of pages25
JournalJournal of Geographical Systems
Early online date28 Jul 2020
Publication statusE-pub ahead of print - 28 Jul 2020

Bibliographical note

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.


  • Australia
  • Cohort replacement
  • Indigenous
  • Population modelling
  • Population projections
  • Regional and remote

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