IDEAS home Printed from https://ideas.repec.org/p/wop/iasawp/ir97048.html
   My bibliography  Save this paper

Sensitivity Analysis of Expert-Based Probabilistic Population Projections in the Case of Austria

Author

Listed:
  • W. Lutz
  • S. Scherbov

Abstract

The traditional way of dealing with uncertainty in population projections through \f2high\f1 and \f2low\f1 variants is unsatisfactory because it remains unclear what range of uncertainty these alternative paths are assumed to cover. Probabilistic approaches have not found their way into \f2official\f1 population projections. This paper proposes an expert-based probabilistic approach (random scenario approach) that seems to meet important criteria for successful application to national and international projections: 1) it provides significant advantages to current practice, 2) it presents an evolution of current practice rather than a discontinuity, 3) it is scientifically sound, and 4) it is applicable to all countries. In a recent \f2Nature\f1 article (Lutz et al. 1997) this method was applied to 13 world regions. This paper discusses the applicability to national projections by directly taking the alternative assumptions defined by the Austrian Statistical Office. Sensitivity analyses that resolve some methodological questions about the approach are also presented.

Suggested Citation

  • W. Lutz & S. Scherbov, 1997. "Sensitivity Analysis of Expert-Based Probabilistic Population Projections in the Case of Austria," Working Papers ir97048, International Institute for Applied Systems Analysis.
  • Handle: RePEc:wop:iasawp:ir97048
    as

    Download full text from publisher

    File URL: http://www.iiasa.ac.at/Publications/Documents/IR-97-048.pdf
    Download Restriction: no

    File URL: http://www.iiasa.ac.at/Publications/Documents/IR-97-048.ps
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Lee, Ronald D., 1993. "Modeling and forecasting the time series of US fertility: Age distribution, range, and ultimate level," International Journal of Forecasting, Elsevier, vol. 9(2), pages 187-202, August.
    2. Alho, Juha M., 1990. "Stochastic methods in population forecasting," International Journal of Forecasting, Elsevier, vol. 6(4), pages 521-530, December.
    3. Wolfgang Lutz & Warren Sanderson & Sergei Scherbov, 1997. "Doubling of world population unlikely," Nature, Nature, vol. 387(6635), pages 803-805, June.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. D. Bauer & G. Feichtinger & W. Lutz & W.C. Sanderson, 1999. "Variances of Population Projections: Comparison of Two Approaches," Working Papers ir99063, International Institute for Applied Systems Analysis.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Booth, Heather, 2006. "Demographic forecasting: 1980 to 2005 in review," International Journal of Forecasting, Elsevier, vol. 22(3), pages 547-581.
    2. Prskawetz, A. & Kogel, T. & Sanderson, W.C. & Scherbov, S., 2007. "The effects of age structure on economic growth: An application of probabilistic forecasting to India," International Journal of Forecasting, Elsevier, vol. 23(4), pages 587-602.
    3. Vanella, Patrizio, 2017. "Age- and Sex-Specific Fertility in Germany until the Year 2040 - The Impact of International Migration," Hannover Economic Papers (HEP) dp-606, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät.
    4. Nico Keilman & Dinh Quang Pham & Arve Hetland, 2002. "Why population forecasts should be probabilistic - illustrated by the case of Norway," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 6(15), pages 409-454.
    5. Ortega, Jose Antonio & Poncela, Pilar, 2005. "Joint forecasts of Southern European fertility rates with non-stationary dynamic factor models," International Journal of Forecasting, Elsevier, vol. 21(3), pages 539-550.
    6. Tuljapurkar, Shripad & Boe, Carl, 1999. "Validation, probability-weighted priors, and information in stochastic forecasts," International Journal of Forecasting, Elsevier, vol. 15(3), pages 259-271, July.
    7. Nico Keilman & Dinh Quang Pham, 2000. "Predictive Intervals for Age-Specific Fertility," European Journal of Population, Springer;European Association for Population Studies, vol. 16(1), pages 41-65, March.
    8. Wolfgang Lutz & Sergei Scherbov, 1998. "An Expert-Based Framework for Probabilistic National Population Projections: The Example of Austria," European Journal of Population, Springer;European Association for Population Studies, vol. 14(1), pages 1-17, March.
    9. D. Bauer & G. Feichtinger & W. Lutz & W.C. Sanderson, 1999. "Variances of Population Projections: Comparison of Two Approaches," Working Papers ir99063, International Institute for Applied Systems Analysis.
    10. Oberhofer, Walter & Reichsthaler, Thomas, 2004. "Modelling Fertility: A Semi-Parametric Approach," University of Regensburg Working Papers in Business, Economics and Management Information Systems 396, University of Regensburg, Department of Economics.
    11. EL-HOUJJAJI, Hind & ECHAOUI, Abdellah, 2020. "Assessing the financial sustainability of parametric pension system reforms: The case of Morocco," MPRA Paper 98912, University Library of Munich, Germany.
    12. Alho, Juha, 2008. "Aggregation across countries in stochastic population forecasts," International Journal of Forecasting, Elsevier, vol. 24(3), pages 343-353.
    13. David Lam, 2011. "How the World Survived the Population Bomb: Lessons From 50 Years of Extraordinary Demographic History," Demography, Springer;Population Association of America (PAA), vol. 48(4), pages 1231-1262, November.
    14. repec:mpr:mprres:3780 is not listed on IDEAS
    15. Lim, Terence & Lo, Andrew W. & Merton, Robert C. & Scholes, Myron S., 2006. "The Derivatives Sourcebook," Foundations and Trends(R) in Finance, now publishers, vol. 1(5–6), pages 365-572, April.
    16. Patrick M. Carr & Greta G. Gramig & Mark A. Liebig, 2013. "Impacts of Organic Zero Tillage Systems on Crops, Weeds, and Soil Quality," Sustainability, MDPI, vol. 5(7), pages 1-30, July.
    17. Alan J. Auerbach & Ronald Lee, 2009. "Notional Defined Contribution Pension Systems in a Stochastic Context: Design and Stability," NBER Chapters, in: Social Security Policy in a Changing Environment, pages 43-68, National Bureau of Economic Research, Inc.
    18. Jeff Tayman & Stanley Smith & Jeffrey Lin, 2007. "Precision, bias, and uncertainty for state population forecasts: an exploratory analysis of time series models," Population Research and Policy Review, Springer;Southern Demographic Association (SDA), vol. 26(3), pages 347-369, June.
    19. Krauß, Michael & Kraatz, Simone & Drastig, Katrin & Prochnow, Annette, 2015. "The influence of dairy management strategies on water productivity of milk production," Agricultural Water Management, Elsevier, vol. 147(C), pages 175-186.
    20. Meng Xu & Helge Brunborg & Joel E. Cohen, 2017. "Evaluating multi-regional population projections with Taylor’s law of mean–variance scaling and its generalisation," Journal of Population Research, Springer, vol. 34(1), pages 79-99, March.
    21. Alho, Juha M., 2014. "Forecasting demographic forecasts," International Journal of Forecasting, Elsevier, vol. 30(4), pages 1128-1135.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:wop:iasawp:ir97048. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Thomas Krichel (email available below). General contact details of provider: https://edirc.repec.org/data/iiasaat.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.