Since many years, Statistics Belgium (Directorate General Statistics and Economic Information - DGSEI) and the Belgian Federal Planning Bureau (FPB) have annually produced official population projections for Belgium at the NUTS3 level used by official Belgian institutions and in several short-, medium-, and long-term projection models (such as economic projections, income poverty, long-term healthcare expenditures, energy, transport) and for specific projects or demands. Aside from these official population projections, interest for household projections is growing. Indeed, understanding the population in this dimension is very useful for numerous aspects of social life (expansion of single-parent households - often mothers - or of isolated households with old persons who are at higher risk of poverty problems or short of support) and of economic life (impact on consumption, taxation, housing, mobility, etc). To do so, a household projection model for Belgium, calibrated on the Belgian population projection at the NUTS 3 level, is under development. The objective of this paper is to describe the model and to present the provisional results.
The methodology proposed in this paper is part of the so-called static household models, as opposed to dynamic household models. While the latter study the transition probabilities from one state (ie. one position in a household) to another by analysing flows, the former focus on the stocks and rates of each state in the studied population. The states which are considered in the present model are individual households positions based on the LIPRO typology. This typology allows taking into account the living arrangements of each individual in the population and establishes a univocal relationship between each position within a household and the type of households to witch an individual belongs.
The paper is structured as follows. Next section presents the methodology and the hypotheses required for making the household projection up to 2060. The third section describes the provisional results of the projection. Section four includes a sensitivity analysis regarding the projection of individuals in collective households. The last section is devoted to a discussion about the results and the methodology in general.