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.