Volume 41 - Article 13 | Pages 367–392

Subnational population forecasts: Do users want to know about uncertainty?

By Tom Wilson, Fiona Shalley

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References

ABS (2018). Australian Statistical Geography Standard (ASGS) [electronic resource]. Canberra: Australian Bureau of Statistics.

Weblink http://www.abs.gov.au/websitedbs/D3310114.nsf ...
Download reference in RIS | BibTeX

Alders, M., Keilman, N., and Cruijsen, H. (2007). Assumptions for long-term stochastic population forecasts in 18 European countries. European Journal of Population 23(1): 33–69.

Weblink doi:10.1007/s10680-006-9104-4
Download reference in RIS | BibTeX

Bell, M., Wilson, T., and Charles-Edwards, E. (2011). Australia’s population future: probabilistic forecasts incorporating expert judgement. Geographical Research 49(3): 261–275.

Weblink doi:10.1111/j.1745-5871.2011.00702.x
Download reference in RIS | BibTeX

Bijak, J., Alberts, I., Alho, J., Bryant, J., Buettner, T., Falkingham, J., Forster, J.J., Gerland, P., King, T., Onorante, L., Keilman, N., O’Hagan, A., Owens, D., Raftery, A., Ševčíková, H., and Smith, P.F. (2015). Letter to the editor. Journal of Official Statistics 31(4): 537–544.

Weblink doi:10.1515/jos-2015-0033
Download reference in RIS | BibTeX

Billari, F.C., Graziani, R., and Melilli, E. (2012). Stochastic population forecasts based on conditional expert opinions. Journal of the Royal Statistical Society Series A: Statistics in Society 175(2): 491–511.

Weblink doi:10.1111/j.1467-985X.2011.01015.x
Download reference in RIS | BibTeX

Bongaarts, J. and Bulatao, R.A. (1999). Completing the demographic transition. Population and Development Review 25(3): 515–529.

Weblink doi:10.1111/j.1728-4457.1999.00515.x
Download reference in RIS | BibTeX

Dunstan, K. and Ball, C. (2016). Demographic projections: User and producer experiences of adopting a stochastic approach. Journal of Official Statistics 32(4): 947–962.

Weblink doi:10.1515/jos-2016-0050
Download reference in RIS | BibTeX

Guimarães, R.R. (2014). Uncertainty in population projections: The state of the art. Revista Brasileira de Estudos de População 31(2): 277–290.

Weblink doi:10.1590/S0102-30982014000200003
Download reference in RIS | BibTeX

Johnstone, K. (2015). Communicating population projections to stakeholders: A case study from New South Wales. In: Wilson, T., Charles-Edwards, E., and Bell, M. (eds.). Demography for planning and policy: Australian case studies. Cham: Springer: 71–89.

Weblink doi:10.1007/978-3-319-22135-9_5
Download reference in RIS | BibTeX

Josyln, S. and Savelli, S. (2010). Communicating forecast uncertainty: Public perception of weather forecast uncertainty. Meteorological Applications 17(2): 180–195.

Weblink doi:10.1002/met.190
Download reference in RIS | BibTeX

Keilman, N. (2008). Using deterministic and probabilistic population forecasts. In: Østreng, W. (ed.). Complexity: Interdisciplinary communications 2006/2007. Oslo: Norwegian Academy of Science and Letters: 22–28.

Download reference in RIS | BibTeX

Keilman, N. (2018). Probabilistic demographic forecasts. Vienna Yearbook of Population Research 16: 25–35.

Weblink doi:10.1553/populationyearbook2018s025
Download reference in RIS | BibTeX

Keilman, N., Pham, D.Q., and Hetland, A. (2002). Why population forecasts should be probabilistic: Illustrated by the case of Norway. Demographic Research 6(15): 409–454.

Weblink doi:10.4054/DemRes.2002.6.15
Download reference in RIS | BibTeX

Keyfitz, N. (1981). The limits of population forecasting. Population and Development Review 7(4): 579–593.

Weblink doi:10.2307/1972799
Download reference in RIS | BibTeX

Lee, R. (1999). Probabilistic approaches to population forecasting. In: Lutz, W., Vaupel, J.W., and Ahlburg, D.A. (eds.). Frontiers of population forecasting. New York: Population Council: 156–190.

Download reference in RIS | BibTeX

Lee, R., Miller, T., and Edwards, R.D. (2003). The growth and aging of California’s population: Demographic and fiscal projections, characteristics and service needs. Berkeley: Center for the Economics and Demography of Aging.

Download reference in RIS | BibTeX

Lutz, W., Sanderson, W.C., and Scherbov, S. (1998). Expert-based probabilistic population projections. Population and Development Review 24(Supplement: Frontiers of Population Forecasting): 139–155.

Weblink doi:10.2307/2808054
Download reference in RIS | BibTeX

Morss, R.E., Demuth, J.L., and Lazo, J.K. (2008). Communicating uncertainty in weather forecasts: A survey of the US public. Weather and Forecasting 23: 974–991.

Weblink doi:10.1175/2008WAF2007088.1
Download reference in RIS | BibTeX

Raftery, A.E., Li, N., Ševčíková, H., Gerland, P., and Heilig, G.K. (2012). Bayesian probabilistic population projections for all countries. Proceedings of the National Academy of Sciences 109(35): 13915–13921.

Weblink doi:10.1073/pnas.1211452109
Download reference in RIS | BibTeX

Rayer, S. (2008). Population forecast errors: A primer for planners. Journal of Planning Education and Research 27(4): 417–430.

Weblink doi:10.1177/0739456X07313925
Download reference in RIS | BibTeX

Rayer, S. and Smith, S.K. (2010). Factors affecting the accuracy of subcounty population forecasts. Journal of Planning Education and Research 30(2): 147–161.

Weblink doi:10.1177/0739456X10380056
Download reference in RIS | BibTeX

Rayer, S. and Smith, S.K. (2014). Population projections by age for Florida and its counties: Assessing accuracy and the impact of adjustments. Population Research and Policy Review 33(5): 747–770.

Weblink doi:10.1007/s11113-014-9325-x
Download reference in RIS | BibTeX

Rayer, S., Smith, S.K., and Tayman, J. (2009). Empirical prediction intervals for county population forecasts. Population Research and Policy Review 28: 773–793.

Weblink doi:10.1007/s11113-009-9128-7
Download reference in RIS | BibTeX

Rees, P. and Turton, I. (1998). Investigation of the effects of input uncertainty on population forecasting. Paper presented at the GeoComputation 98 Conference, Bristol, UK, September 17–19, 1998.

Download reference in RIS | BibTeX

Simpson, L., Wilson, T., and Shalley, F. (2018). The shelf life of sub-national population forecasts, from Australia to England. Darwin: Northern Institute, Charles Darwin University (Working Paper 03/2018).

Weblink https://www.cdu.edu.au/sites/default/files/th ...
Download reference in RIS | BibTeX

Statistics Netherlands (2017). Forecast: 18.4 million inhabitants in 2060 [electronic resource]. The Hague: Statistics Netherlands.

Weblink https://www.cbs.nl/en-gb/news/2017/51/forecas ...
Download reference in RIS | BibTeX

Statistics New Zealand (2008). How accurate are population projections? An evaluation of Statistics New Zealand population projections, 1991–2006. Wellington: Statistics New Zealand.

Weblink http://archive.stats.govt.nz/browse_for_stats ...
Download reference in RIS | BibTeX

Statistics New Zealand (2016). National population projections: 2016(base)–2068. Wellington: Statistics New Zealand.

Weblink https://www.stats.govt.nz/information-release ...
Download reference in RIS | BibTeX

Stoto, M.A. (1983). The accuracy of population projections. Journal of the American Statistical Association 78(381): 13–20.

Weblink doi:10.1080/01621459.1983.10477916
Download reference in RIS | BibTeX

Tayman, J. (2011). Assessing uncertainty in small area forecasts: State of the practice and implementation strategy. Population Research and Policy Review 30(5): 781–800.

Weblink doi:10.1007/s11113-011-9210-9
Download reference in RIS | BibTeX

United National Economic Commission for Europe (UNECE) (2018). Recommendations on communicating population projections. Geneva: UNECE.

Weblink https://www.unece.org/fileadmin/DAM/stats/pub ...
Download reference in RIS | BibTeX

Wilson, T. (2012). Forecast accuracy and uncertainty of Australian Bureau of Statistics state and territory population projections. International Journal of Population Research 2012(419824): 1–16.

Weblink doi:10.1155/2012/419824
Download reference in RIS | BibTeX

Wilson, T. (2013). Quantifying the uncertainty of regional demographic forecasts. Applied Geography 42: 108–115.

Weblink doi:10.1016/j.apgeog.2013.05.006
Download reference in RIS | BibTeX

Wilson, T. (2018). Communicating population forecast uncertainty using perishable food terminology. Darwin: Northern Institute, Charles Darwin University (Research Brief RB03/2018).

Weblink http://www.cdu.edu.au/sites/default/files/res ...
Download reference in RIS | BibTeX

Wilson, T., Brokensha, H., Rowe, F., and Simpson, L. (2018). Insights from the evaluation of past local area population forecasts. Population Research and Policy Review 37(1): 137–155.

Weblink doi:10.1007/s11113-017-9450-4
Download reference in RIS | BibTeX

Wisniowski, A. and Raymer, J. (2016). Bayesian multiregional population forecasting: England. Paper presented at the Joint Eurostat/UNECE Work Session on Demographic Projections, Geneva, Switzerland, April 18–20, 2016.

Download reference in RIS | BibTeX

World Meteorological Organization (2008). Guidelines on communicating forecast uncertainty. Geneva: WMO.

Weblink https://library.wmo.int/doc_num.php?explnum_id=4687
Download reference in RIS | BibTeX

Yamauchi, M., Koike, S., and Kamata, K. (2017). How accurate are Japan’s official subnational projections? Comparative analysis of projections in Japan, English-speaking countries and the EU. In: Swanson, D.A. (ed.). The frontiers of applied demography. Dordrecht: Springer: 305–328.

Weblink doi:10.1007/978-3-319-43329-5_15
Download reference in RIS | BibTeX

Ševčíková, H. and Raftery, A.E. (2012). bayesPop: Probabilistic population projection R package: Version 1.0–3 [electronic resource]. Vienna: R Foundation for Statistical Computing.

Weblink http://CRAN.R-project.org/package=bayesPop
Download reference in RIS | BibTeX