Toward a New Model for Probabilistic Household Forecasts

Abstract

Summary 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.

"Contributions of household projection method in the Brazilian context

“…The differences between ECCM and HRM in each scenario were less than 5%, however as Leiwen and O'Neill (2004) argue, the so-called "variant approach", that is, the practice of varying a demographic component input to study the behavior of a projection result is difficult to reproduce in household projections and we cannot have a reasonable explanation for those differences between ECCM and HRM. According to the authors, in this type of projection there is a large number of input variables besides fertility, mortality and migration that are potential influencers of the results.…”