Disaggregation in population forecasting: do we need it? And how to do it simply.
"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." (SUMMARY IN FRE)
Lee
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Carter
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Tuljapurkar
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D017677:Age Distribution; D000367:Age Factors; D003469:Culture; D003710:Demography; D005006:Ethnicity; D005298:Fertility; D005544:Forecasting; D005843:Geography; D008962:Models, Theoretical; D009026:Mortality; D011153:Population; D011154:Population Characteristics; D011157:Population Dynamics; D015203:Reproducibility of Results; D012106:Research; D012107:Research Design; D012737:Sex Factors; D013223:Statistics as Topic
Age Distribution; Age Factors; Cultural Background; Demographic Factors; Estimation Technics; Ethnic Groups; Fertility; Geographic Factors; Measurement; Models, Theoretical; Mortality; Population; Population Characteristics; Population Dynamics; Population Forecast; Population Projection; Reliability; Research Methodology; Sex Factors; World