Disaggregatton in population forecasting: Do we need it? And how to do it simply

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Abstract
Many argue that the case for disaggregation by age is so compelling as to be almost self‐evident. However, in addition to the many reasons why disaggregation might be appropriate, there are also a number of reasons why direct forecasts of the total population might be better. We point out that one can always disaggregate after the forecast, rather than as part of the forecast Some of the issues raised could be illuminated by comparative empirical work, and there is room for valuable research of this sort Nonetheless, on the assumption that most people will continue to use cohort component type procedures, we have described a method for reducing the dimensionality of the forecasting problem by parsimoniously modeling the evolution over time of the age schedules of vital rates. This method steers a middle course between forecasting aggregates and forecasting individual age specific rates: we reduce the problem to forecasting a single parameter for fertility and another one for mortality. We have described a number of refinements and extensions of those basic methods, which preserve their underlying structure and simplicity. In particular, we show how one can fit the model more simply, incorporate lower bounds to the forecasts of rates, disaggregate by sex or race, and prepare integrated forecasts of rates for a collection of regions. We also discuss alternate approaches to forecasting the estimated indices of fertility and mortality, including state‐space methods. These many versions of the basic method have yielded remarkably similar results.

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