Entropy Based Modelling for Estimating Demographic Trends

In this paper, an entropy-based method is proposed to forecast the demographical changes of countries. We formulate the estimation of future demographical profiles as a constrained optimization problem, anchored on the empirically validated assumption that the entropy of age distribution is increasi...

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Main Authors:	Li, Guoqi, Zhao, Daxuan, Xu, Yi, Kuo, Shyh-Hao, Xu, Hai-Yan, Hu, Nan, Zhao, Guangshe, Monterola, Christopher
Format:	Online
Language:	English
Published:	Public Library of Science 2015
Online Access:	https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4575178/

id	pubmed-4575178
recordtype	oai_dc
spelling	pubmed-45751782015-09-25 Entropy Based Modelling for Estimating Demographic Trends Li, Guoqi Zhao, Daxuan Xu, Yi Kuo, Shyh-Hao Xu, Hai-Yan Hu, Nan Zhao, Guangshe Monterola, Christopher Research Article In this paper, an entropy-based method is proposed to forecast the demographical changes of countries. We formulate the estimation of future demographical profiles as a constrained optimization problem, anchored on the empirically validated assumption that the entropy of age distribution is increasing in time. The procedure of the proposed method involves three stages, namely: 1) Prediction of the age distribution of a country’s population based on an “age-structured population model”; 2) Estimation the age distribution of each individual household size with an entropy-based formulation based on an “individual household size model”; and 3) Estimation the number of each household size based on a “total household size model”. The last stage is achieved by projecting the age distribution of the country’s population (obtained in stage 1) onto the age distributions of individual household sizes (obtained in stage 2). The effectiveness of the proposed method is demonstrated by feeding real world data, and it is general and versatile enough to be extended to other time dependent demographic variables. Public Library of Science 2015-09-18 /pmc/articles/PMC4575178/ /pubmed/26382594 http://dx.doi.org/10.1371/journal.pone.0137324 Text en © 2015 Li et al http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited.
repository_type	Open Access Journal
institution_category	Foreign Institution
institution	US National Center for Biotechnology Information
building	NCBI PubMed
collection	Online Access
language	English
format	Online
author	Li, Guoqi Zhao, Daxuan Xu, Yi Kuo, Shyh-Hao Xu, Hai-Yan Hu, Nan Zhao, Guangshe Monterola, Christopher
spellingShingle	Li, Guoqi Zhao, Daxuan Xu, Yi Kuo, Shyh-Hao Xu, Hai-Yan Hu, Nan Zhao, Guangshe Monterola, Christopher Entropy Based Modelling for Estimating Demographic Trends
author_facet	Li, Guoqi Zhao, Daxuan Xu, Yi Kuo, Shyh-Hao Xu, Hai-Yan Hu, Nan Zhao, Guangshe Monterola, Christopher
author_sort	Li, Guoqi
title	Entropy Based Modelling for Estimating Demographic Trends
title_short	Entropy Based Modelling for Estimating Demographic Trends
title_full	Entropy Based Modelling for Estimating Demographic Trends
title_fullStr	Entropy Based Modelling for Estimating Demographic Trends
title_full_unstemmed	Entropy Based Modelling for Estimating Demographic Trends
title_sort	entropy based modelling for estimating demographic trends
description	In this paper, an entropy-based method is proposed to forecast the demographical changes of countries. We formulate the estimation of future demographical profiles as a constrained optimization problem, anchored on the empirically validated assumption that the entropy of age distribution is increasing in time. The procedure of the proposed method involves three stages, namely: 1) Prediction of the age distribution of a country’s population based on an “age-structured population model”; 2) Estimation the age distribution of each individual household size with an entropy-based formulation based on an “individual household size model”; and 3) Estimation the number of each household size based on a “total household size model”. The last stage is achieved by projecting the age distribution of the country’s population (obtained in stage 1) onto the age distributions of individual household sizes (obtained in stage 2). The effectiveness of the proposed method is demonstrated by feeding real world data, and it is general and versatile enough to be extended to other time dependent demographic variables.
publisher	Public Library of Science
publishDate	2015
url	https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4575178/
_version_	1613477325636108288

Entropy Based Modelling for Estimating Demographic Trends

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