Stochastic Forecasting of Demographic Components Based on Principal Component
Stochastic Forecasting of Demographic Components Based on Principal Component is a scholarly work, published in 2018 in ''Athens journal of sciences''. The main subjects of the publication include econometrics, principal component analysis, agriculture in Russia, component, and computer science. Adequate forecasts of future population developments that are based on cohortcomponent methods demand an age-and sex-specific analysis; otherwise, the structure of the future population cannot be specified correctly.Age-specific demographic measures are both highly correlated and highly dimensional.Thus, a methodology that not only considers the correlations between the random variables but also reduces the effective dimensionality of the forecasting problem is needed: principal component analysis serves both purposes simultaneously.This study presents principal component analysis, from a mathematical-statistical perspective, to users from the field of population studies.Furthermore, important aspects of time series analysis, which are vital for an accurate stochastic forecast, are explained.The application is illustrated via the simultaneous projection of selected age-and sex-specific survival rates with projection intervals for Germany, Italy, Austria, and Switzerland.