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On future household structure

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  • Juha Alho
  • Nico Keilman

Abstract

Summary. We develop a method for computing probabilistic household forecasts which quantifies uncertainty in the future number of households of various types in a country. A probabilistic household forecast helps policy makers, planners and other forecast users in the fields of housing, energy, social security etc. in taking appropriate decisions, because some household variables are more uncertain than others. Deterministic forecasts traditionally do not quantify uncertainty. We apply the method to data from Norway. We find that predictions of future numbers of married couples, cohabiting couples and one‐person households are more certain than those of lone parents and other private households. Our method builds on an existing method for computing probabilistic population forecasts, combining such a forecast with a random breakdown of the population according to household position (single, cohabiting, living with a spouse, living alone etc.). In this application, uncertainty in the total numbers of households of different types derives primarily from random shares, rather than uncertain future population size. A similar method could be applied to obtain probabilistic forecasts for other divisions of the population, such as household size, health or disability status, region of residence and labour market status.

Suggested Citation

  • 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.
  • Handle: RePEc:bla:jorssa:v:173:y:2010:i:1:p:117-143
    DOI: 10.1111/j.1467-985X.2009.00605.x
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    References listed on IDEAS

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    1. Booth, Heather, 2006. "Demographic forecasting: 1980 to 2005 in review," International Journal of Forecasting, Elsevier, vol. 22(3), pages 547-581.
    2. 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.
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    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. Ala-Karvia Urszula & Hozer-Koćmiel Marta & Misiak-Kwit Sandra & Staszko Barbara, 2018. "Is Poland Becoming Nordic? Changing Trends In Household Structures In Poland And Finland With The Emphasis On People Living Alone," Statistics in Transition New Series, Polish Statistical Association, vol. 19(4), pages 725-742, December.
    3. Alho, Juha, 2014. "Nonparametric Estimation of Conditional Expectations for Sustainability Analyses," ETLA Reports 24, The Research Institute of the Finnish Economy.
    4. Jacobsen, Rasmus Højbjerg & Jensen, Svend E. Hougaard, 2014. "Future changes in age and household patterns: Some implications for public finances," International Journal of Forecasting, Elsevier, vol. 30(4), pages 1110-1119.
    5. Rasmus Højbjerg Jacobsen & Svend E. Hougaard Jensen, 2014. "Changing Age and Household Patterns: Implications for Welfare Costs in Denmark 1982 – 2007," Nordic Journal of Political Economy, Nordic Journal of Political Economy, vol. 39, pages 1-4.
    6. Urszula Ala-Karvia & Marta Hozer-Koćmiel & Sandra Misiak-Kwit & Barbara Staszko, 2018. "Is Poland Becoming Nordic? Changing Trends In Household Structures In Poland And Finland With The Emphasis On People Living Alone," Statistics in Transition New Series, Polish Statistical Association, vol. 19(4), pages 725-742, December.
    7. 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.
    8. 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.
    9. Raffaella Rubino & Arjeta Veshi, 2023. "Changing family models. the case of the Puglia region," RIEDS - Rivista Italiana di Economia, Demografia e Statistica - The Italian Journal of Economic, Demographic and Statistical Studies, SIEDS Societa' Italiana di Economia Demografia e Statistica, vol. 77(2), pages 132-142, April-Jun.

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