Toward a new model for probabilistic household forecasts

Jiang, L. & O'Neill, B.C. (2004). Toward a new model for probabilistic household forecasts. International Statistical Review 72 (1) 51-64. 10.1111/j.1751-5823.2004.tb00223.x.

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Household projections are key components of analyses of several issues of social concern, including the welfare of the elderly, housing, and environmentally significant consumption patterns. Researchers or policy makers that use such projections need appropriate representations of uncertainty in order to inform their analyses. However, the weaknesses of the traditional approach of providing alternative variants to single "best guess" projection are magnified in household projections, which have many output variables of interest, and many input variables beyond fertility, mortality, and migration. We review current methods of household projections and the potential for using them to produce probabilistic projections, which would address many of these weaknesses. We then propose a new framework for a household projection method of intermediate complexity that we believe is a good candidate for providing a basis for further development of probabilistic household projections. An extension of the traditional headship rate approach, this method is based on modelling changes in headship rates decomposed by household size as a function of variables describing demographic events such as parity specific fertility, union formation and dissolution, and leaving home. It has moderate data requirements, manageable complexity, allows for direct specification of demographic events, and produces output that includes the most important household characteristics for many applications. An illustration of how such a model might be constructed, using data on the U.S. and China over the past several decades, demonstrates the viability of the approach.

Item Type: Article
Uncontrolled Keywords: Model; Probabilistic forecast; Household
Research Programs: World Population (POP)
Bibliographic Reference: International Statistical Review; 72(1):51-64 (April 2004)
Depositing User: IIASA Import
Date Deposited: 15 Jan 2016 02:16
Last Modified: 27 Aug 2021 17:18

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