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Biographic forecasting: bridging the micro-macro gap in population forecasting. / Willekens, F.J.

In: New Zealand Population Review, Vol. 31, 2005, p. 77-124.

Research output: Scientific - peer-reviewArticle

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Willekens, F.J. / Biographic forecasting: bridging the micro-macro gap in population forecasting.

In: New Zealand Population Review, Vol. 31, 2005, p. 77-124.

Research output: Scientific - peer-reviewArticle

BibTeX

@article{79811aa277d24e29bded263ffabe2083,
title = "Biographic forecasting: bridging the micro-macro gap in population forecasting",
abstract = "The paper outlines a new model for demographic projections by detailed population categories that are required in the development of sustainable (elderly) health care systems and pension systems. The methodology consists of a macro-model (MAC) that models demographic changes at the population level and a micro-model (MIC) that models demographic events at the individual level. Both models are multistate models that rely on rates of transition between states of existence or stages of life. MAC focuses on transitions among functional states by age and sex. The transitions determine the distribution of cohort members among functional states. The output of MAC consists of cohort biographies. MIC addresses demographic events and other life transitions at the individual level. It is a micro-simulation model that produces individual biographies. This paper describes approaches to functional population projection and provides a detailed description of the multistate model. It also contains an overview of the MicMac project.",
author = "F.J. Willekens",
year = "2005",
volume = "31",
pages = "77--124",
journal = "New Zealand Population Review",

}

RIS

TY - JOUR

T1 - Biographic forecasting: bridging the micro-macro gap in population forecasting

AU - Willekens,F.J.

PY - 2005

Y1 - 2005

N2 - The paper outlines a new model for demographic projections by detailed population categories that are required in the development of sustainable (elderly) health care systems and pension systems. The methodology consists of a macro-model (MAC) that models demographic changes at the population level and a micro-model (MIC) that models demographic events at the individual level. Both models are multistate models that rely on rates of transition between states of existence or stages of life. MAC focuses on transitions among functional states by age and sex. The transitions determine the distribution of cohort members among functional states. The output of MAC consists of cohort biographies. MIC addresses demographic events and other life transitions at the individual level. It is a micro-simulation model that produces individual biographies. This paper describes approaches to functional population projection and provides a detailed description of the multistate model. It also contains an overview of the MicMac project.

AB - The paper outlines a new model for demographic projections by detailed population categories that are required in the development of sustainable (elderly) health care systems and pension systems. The methodology consists of a macro-model (MAC) that models demographic changes at the population level and a micro-model (MIC) that models demographic events at the individual level. Both models are multistate models that rely on rates of transition between states of existence or stages of life. MAC focuses on transitions among functional states by age and sex. The transitions determine the distribution of cohort members among functional states. The output of MAC consists of cohort biographies. MIC addresses demographic events and other life transitions at the individual level. It is a micro-simulation model that produces individual biographies. This paper describes approaches to functional population projection and provides a detailed description of the multistate model. It also contains an overview of the MicMac project.

M3 - Article

VL - 31

SP - 77

EP - 124

JO - New Zealand Population Review

T2 - New Zealand Population Review

JF - New Zealand Population Review

ER -

ID: 424557