Journal article
Algorithms for a projection model of demographic indicators based on generalized age-dependent branching processes
Mathematical biosciences, v 57(1)
1981
Featured in Collection : UN Sustainable Development Goals @ Drexel
Abstract
Demographic indicators are not only used extensively to describe the current state of human populations, but they also enter into the formulation and implementation of population policies. Successes and⧸or failures of policies are frequently judged in terms of changes in demographic indicators over time. Using indicators in this way gives rise to a need for a methodology for projecting them over time in terms of basic determinants underlying the demographic evolution of human populations so that prospective population policies may be studied by computer simulation. The basic determinants of population dynamics considered in this paper were mortality, age at marriage, and fertility. The mathematical machinery used to incorporate these determinants into a workable one-sex mathematical system was that of generalized age-dependent branching processes. Given an initial age distribution and stationary law of evolution, algorithms for projecting three classes of indicators in time were developed. Included in the first class were the age distribution and rate of population growth. A second class included indicators of mortality, with specific attention being given to age-specific, crude, and infant death rates. Indicators of fertility made up a third class. Singled out for study were: age-specific birth rates, the total and net fertility rates, and the crude birth rate. Renewal theory was used to develop asymptotic formulas for all indicators considered; many of these formulas will be familiar to students of stable population theory. Some connections between the Leslie matrix and the projection system developed in this paper were also pointed out.
Metrics
Details
- Title
- Algorithms for a projection model of demographic indicators based on generalized age-dependent branching processes
- Creators
- Charles J. Mode - Drexel UniversityRobert C. Busby - Drexel University
- Publication Details
- Mathematical biosciences, v 57(1)
- Publisher
- Elsevier
- Resource Type
- Journal article
- Language
- English
- Academic Unit
- [Retired Faculty]
- Web of Science ID
- WOS:A1981MP38100005
- Scopus ID
- 2-s2.0-0019846815
- Other Identifier
- 991019173772304721
UN Sustainable Development Goals (SDGs)
This publication has contributed to the advancement of the following goals:
InCites Highlights
Data related to this publication, from InCites Benchmarking & Analytics tool:
- Web of Science research areas
- Biology
- Mathematical & Computational Biology