IDEAS home Printed from https://ideas.repec.org/a/dem/demres/v28y2013i24.html
   My bibliography  Save this article

The sequential propensity household projection model

Author

Listed:
  • Tom Wilson

    (Independent researcher)

Abstract

Background: The standard method of projecting living arrangements and households in Australia and New Zealand is the ‘propensity model', a type of extended headship rate model. Unfortunately it possesses a number of serious shortcomings, including internal inconsistencies, difficulties in setting living arrangement assumptions, and very limited scenario creation capabilities. Data allowing the application of more sophisticated dynamic household projection models are unavailable in Australia. Objective: The aim was create a projection model to overcome these shortcomings whilst minimising input data requirements and costs, and retaining the projection outputs users are familiar with. Methods: The sequential propensity household projection model is proposed. Living arrangement projections take place in a sequence of calculations, with progressively more detailed living arrangement categories calculated in each step. In doing so the model largely overcomes the three serious deficiencies of the standard propensity model noted above. Results: The model is illustrated by three scenarios produced for one case study State, Queensland. They are: a baseline scenario in which all propensities are held constant to demonstrate the effects of population growth and ageing, a housing crisis scenario where housing affordability declines, and a prosperity scenario where families and individuals enjoy greater real incomes. A sensitivity analysis in which assumptions are varied one by one is also presented. Conclusions: The sequential propensity model offers a more effective method of producing household and living arrangement projections than the standard propensity model, and is a practical alternative to dynamic projection models for countries and regions where the data and resources to apply such models are unavailable.

Suggested Citation

  • Tom Wilson, 2013. "The sequential propensity household projection model," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 28(24), pages 681-712.
    • Handle: RePEc:dem:demres:v:28:y:2013:i:24
    DOI: 10.4054/DemRes.2013.28.24
    as

    Download full text from publisher

    File URL: https://www.demographic-research.org/volumes/vol28/24/28-24.pdf
    Download Restriction: no
    File URL: https://libkey.io/10.4054/DemRes.2013.28.24?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Jianguo Liu & Gretchen C. Daily & Paul R. Ehrlich & Gary W. Luck, 2003. "Effects of household dynamics on resource consumption and biodiversity," Nature, Nature, vol. 421(6922), pages 530-533, January.
    2. Leiwen Jiang & Brian C. O'Neill, 2007. "Impacts of Demographic Trends on US Household Size and Structure," Population and Development Review, The Population Council, Inc., vol. 33(3), pages 567-591, September.
    3. Geoffrey Meen & Mark Andrew, 2008. "Planning for housing in the post-Barker era: affordability, household formation, and tenure choice," Oxford Review of Economic Policy, Oxford University Press and Oxford Review of Economic Policy Limited, vol. 24(1), pages 79-98, spring.
    4. Nico Keilman & Solveig Christiansen, 2010. "Norwegian Elderly Less Likely to Live Alone in the Future," European Journal of Population, Springer;European Association for Population Studies, vol. 26(1), pages 47-72, February.
    5. Zeng Yi & James Vaupel & Wang Zhenglian, 1997. "A multi-dimensional model for projecting family households - with an illustrative numerical application," Mathematical Population Studies, Taylor & Francis Journals, vol. 6(3), pages 187-216.
    6. Juha Alho & Nico Keilman, 2010. "On future household structure," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 173(1), pages 117-143, January.
    7. Lawrence Santi, 1988. "The demographic context of recent change in the structure of American households," Demography, Springer;Population Association of America (PAA), vol. 25(4), pages 509-519, November.
    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. Nico Keilman, 2017. "A combined Brass-random walk approach to probabilistic household forecasting: Denmark, Finland, and the Netherlands, 2011–2041," Journal of Population Research, Springer, vol. 34(1), pages 17-43, March.
    2. Qiushi Feng & Zhenglian Wang & Simon Choi & Yi Zeng, 2020. "Forecast Households at the County Level: An Application of the ProFamy Extended Cohort-Component Method in Six Counties of Southern California, 2010 to 2040," Population Research and Policy Review, Springer;Southern Demographic Association (SDA), vol. 39(2), pages 253-281, April.

    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. Qiushi Feng & Zhenglian Wang & Simon Choi & Yi Zeng, 2020. "Forecast Households at the County Level: An Application of the ProFamy Extended Cohort-Component Method in Six Counties of Southern California, 2010 to 2040," Population Research and Policy Review, Springer;Southern Demographic Association (SDA), vol. 39(2), pages 253-281, April.
    2. Overman, Henry G. & Puga, Diego & Turner, Matthew A., 2008. "Decomposing the growth in residential land in the United States," Regional Science and Urban Economics, Elsevier, vol. 38(5), pages 487-497, September.
    3. Leiwen Jiang & Karen Hardee, 2011. "How do Recent Population Trends Matter to Climate Change?," Population Research and Policy Review, Springer;Southern Demographic Association (SDA), vol. 30(2), pages 287-312, April.
    4. Yi Zeng & Eric Stallard & Zhenglian Wang, 2004. "Estimating time-varying sex-age-specific o/e rates of marital status transitions in family household projection or simulation," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 11(10), pages 263-304.
    5. Solveig Christiansen & Nico Keilman, 2013. "Probabilistic household forecasts based on register data- the case of Denmark and Finland," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 28(43), pages 1263-1302.
    6. Yi Zeng & Eric Stallard & Zhenglian Wang, 2003. "Estimating time-varying sex-age-specific o/e rates of marital status transitions in family household projection or simulation," MPIDR Working Papers WP-2003-024, Max Planck Institute for Demographic Research, Rostock, Germany.
    7. Yi Zeng & Kenneth Land & Zhenglian Wang & Danan Gu, 2013. "Household and Living Arrangement Projections at the Subnational Level: An Extended Cohort-Component Approach," Demography, Springer;Population Association of America (PAA), vol. 50(3), pages 827-852, June.
    8. Juan Antonio Duro & Jordi Teixidó-Figueras & Emilio Padilla, 2017. "The Causal Factors of International Inequality in $$\hbox {CO}_{2}$$ CO 2 Emissions Per Capita: A Regression-Based Inequality Decomposition Analysis," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 67(4), pages 683-700, August.
    9. Vincent Sennes & Jacques Breillat & Francis Ribeyre & Sandrine Gombert, 2009. "Local policies for reducing the ecological impact of households: the case study of a suburban area in France," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 11(5), pages 1031-1049, October.
    10. Xue, Jin, 2014. "Is eco-village/urban village the future of a degrowth society? An urban planner's perspective," Ecological Economics, Elsevier, vol. 105(C), pages 130-138.
    11. Wang, Chengchao & Yang, Yusheng & Zhang, Yaoqi, 2012. "Rural household livelihood change, fuelwood substitution, and hilly ecosystem restoration: Evidence from China," Renewable and Sustainable Energy Reviews, Elsevier, vol. 16(5), pages 2475-2482.
    12. Goulden, Murray & Ryley, Tim & Dingwall, Robert, 2014. "Beyond ‘predict and provide’: UK transport, the growth paradigm and climate change," Transport Policy, Elsevier, vol. 32(C), pages 139-147.
    13. Catherine Potvin & Petra Tschakert & Frédéric Lebel & Kate Kirby & Hector Barrios & Judith Bocariza & Jaime Caisamo & Leonel Caisamo & Charianito Cansari & Juan Casamá & Maribel Casamá & Laura Chamorr, 2007. "A participatory approach to the establishment of a baseline scenario for a reforestation Clean Development Mechanism project," Mitigation and Adaptation Strategies for Global Change, Springer, vol. 12(8), pages 1341-1362, October.
    14. Guangdong Li & Chuanglin Fang & James E. M. Watson & Siao Sun & Wei Qi & Zhenbo Wang & Jianguo Liu, 2024. "Mixed effectiveness of global protected areas in resisting habitat loss," Nature Communications, Nature, vol. 15(1), pages 1-17, December.
    15. Philip E. Ogden & Ray Hall, 2000. "Households, Reurbanisation and the Rise of Living Alone in the Principal French Cities, 1975-90," Urban Studies, Urban Studies Journal Limited, vol. 37(2), pages 367-390, February.
    16. Niggemann, Marc & Jetzkowitz, Jens & Brunzel, Stefan & Wichmann, Matthias C. & Bialozyt, Ronald, 2009. "Distribution patterns of plants explained by human movement behaviour," Ecological Modelling, Elsevier, vol. 220(9), pages 1339-1346.
    17. Squalli, Jay, 2010. "An empirical assessment of U.S. state-level immigration and environmental emissions," Ecological Economics, Elsevier, vol. 69(5), pages 1170-1175, March.
    18. Albert Esteve & David S. Reher, 2021. "Rising Global Levels of Intergenerational Coresidence Among Young Adults," Population and Development Review, The Population Council, Inc., vol. 47(3), pages 691-717, September.
    19. Ting Li & Wenting Fan & Jian Song, 2020. "The Household Structure Transition in China: 1982–2015," Demography, Springer;Population Association of America (PAA), vol. 57(4), pages 1369-1391, August.
    20. David N. Koons & Randall Holmes & James B. Grand, 2006. "Population inertia and its sensitivity to changes in vital rates or initial conditions," MPIDR Working Papers WP-2006-040, Max Planck Institute for Demographic Research, Rostock, Germany.

    More about this item

    Keywords

    Australia; household projection; sequential propensity model; minimal household units; household scenarios;
    All these keywords.

    JEL classification:

    • J1 - Labor and Demographic Economics - - Demographic Economics
    • Z0 - Other Special Topics - - General

    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:dem:demres:v:28:y:2013:i:24. 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: Editorial Office (email available below). General contact details of provider: https://www.demogr.mpg.de/ .

    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.