Temporal disaggregation and restricted forecasting of multiple population time series

Abstract

This article presents some applications of time-series procedures to solve two typical problems that arise when analyzing demographic information in developing countries: (1) unavailability of annual time series of population growth rates (PGRs) and their corresponding population time series and (2) inappropriately defined population growth goals in official population programs. These problems are considered as situations that require combining information of population time series. Firstly, we suggest the use of temporal disaggregation techniques to combine census data with vital statistics information in order to estimate annual PGRs. Secondly, we apply multiple restricted forecasting to combine the official targets on future PGRs with the disaggregated series. Then, we propose a mechanism to evaluate the compatibility of the demographic goals with the annual data. We apply the aforementioned procedures to data of the Mexico City Metropolitan Zone divided by concentric rings and conclude that the targets established in the official program are not feasible. Hence, we derive future PGRs that are both in line with the official targets and with the historical demographic behavior. We conclude that growth population programs should be based on this kind of analysis to be supported empirically. So, through specialized multivariate time-series techniques, we propose to obtain first an optimal estimate of a disaggregate vector of population time series and then, produce restricted forecasts in agreement with some data-based population policies here derived.

Keywords:

• compatibility testing
• demographic forecasting
• measurement error
• multivariate time series
• preliminary series
• VAR models

Acknowledgements

The authors gratefully acknowledge the comments provided by Fátima Juárez and Ismael Sánchez to a previous version of this paper. They also thank two anonymous referees and the editor in charge for their valuable comments that helped to improve the presentation of this work. V.M. Guerrero thanks Asociación Mexicana de Cultura, A.C. for providing support to carry out this work through a Professorship on Time Series Analysis and Forecasting in Econometrics. We also acknowledge support from the MICINN Grant SEJ2007-64500.