We show how techniques of data dimension reduction can be used to predict patterns of household dynamics in a multi-country context. Probabilistic household forecasts are presented for Denmark, Finland, Germany, the Netherlands, and Norway, spanning the period 2011-2041. Starting point is the population of each country broken down by age, sex, and household position as reported in the census round of 2011. Future trends in fertility, mortality and international migration are taken from official population forecasts. For changes in household structure we rely on time series of household data. Long series of household data, in which the population is broken down by household position, age, and sex, are available for Denmark (1981-2007) and Finland (1988-2009) from the population registers in these countries. For the Netherlands the series are rather short (1995-2011). Annual shares of the population by household position, age, and sex for the three time series countries are modeled using an approach that builds on Brass’ relational model originally developed to model the age pattern of mortality. We find that the household shares can be modelled as Random Walks with Drifts (RWD), independent of country. The Brass approach preserves the age patterns of the household shares. Future household shares are found by extrapolating the RWD processes. This results in household share forecasts, as well as standard errors of the forecasts. Correlations across ages and between men and women are estimated from model residuals. No time series data are available for Germany or Norway. For Germany, we use household transition rates borrowed from Denmark and Finland, but adjusted to cohabitation and marriage levels from the German Generation and Gender Survey. For Norway, we have household transition rates for the year 2010 from the population register. Future household patterns for these two countries are computed by using the multistate household model LIPRO, in which the household transition rates are applied to the household pattern from the census. Uncertainty parameters are borrowed from the time series analyses for Denmark, Finland and the Netherlands. The results show a continuation of current trends towards more and smaller households, often driven by increasing numbers of persons who live alone. The number of households increases faster than population size, which leads to falling average household size. A very consistent finding is that larger households are easier to predict than smaller households, at least when uncertainty is considered in a relative sense
