The U.S. Census Bureau is approaching a critical decision regarding a major facet of its
methodology for forecasting the United States population. In the past, it has relied on
alternative scenarios, low, medium, and high, to reflect varying interpretations of current
trends in fertility, mortality, and international migration to forecast population.
This approach has limitations that have been noted in the recent literature on population
forecasting. Census Bureau researchers are embarking on an attempt to incorporate
probabilistic reasoning to forecast prediction intervals around point forecasts to
future dates. The current literature offers a choice of approaches to this problem.
We are opting to employ formal time series modeling of parameters of fertility, mortality,
and international migration, with stochastic renewal processes. The endeavor is
complicated by the administrative necessity to produce a large amount of racial and
Hispanic origin detail in the population, as well as the ubiquitous cross-categories of
age and sex. As official population forecasts must meet user demand, we are faced
with the added challenge of presenting and supporting the resulting product in a way that
is comprehensible to users, many of whom have little or no comprehension of the technical
forecasting literature, and are accustomed to simple, deterministic answers. We may well
find a need to modify our strategy, depending on the realities that may emerge from the
limitations of data, the administrative requirements of the product, and the diverse needs
of our user community.