Generating synthetic baseline populations from register data

Publication: Research - peer-reviewJournal article – Annual report year: 2012

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Generating synthetic baseline populations from register data. / Rich, Jeppe; Mulalic, Ismir.

In: Transportation Research. Part A: Policy & Practice, Vol. 46, No. 3, 2012, p. 467-479.

Publication: Research - peer-reviewJournal article – Annual report year: 2012

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Author

Rich, Jeppe; Mulalic, Ismir / Generating synthetic baseline populations from register data.

In: Transportation Research. Part A: Policy & Practice, Vol. 46, No. 3, 2012, p. 467-479.

Publication: Research - peer-reviewJournal article – Annual report year: 2012

Bibtex

@article{3596fe93ca5e425a8c5bd96431fd2990,
title = "Generating synthetic baseline populations from register data",
publisher = "Pergamon",
author = "Jeppe Rich and Ismir Mulalic",
year = "2012",
doi = "10.1016/j.tra.2011.11.002",
volume = "46",
number = "3",
pages = "467--479",
journal = "Transportation Research. Part A: Policy & Practice",
issn = "0965-8564",

}

RIS

TY - JOUR

T1 - Generating synthetic baseline populations from register data

A1 - Rich,Jeppe

A1 - Mulalic,Ismir

AU - Rich,Jeppe

AU - Mulalic,Ismir

PB - Pergamon

PY - 2012

Y1 - 2012

N2 - The paper presents a population synthesiser based on the method of Iterative Proportional Fitting (IPF) algorithm developed for the new Danish national transport model system. The synthesiser is designed for large population matrices and allows target variables to be represented in several target constraints. As a result, constraints for the IPF are cross-linked, which makes it difficult to ensure consistency of targets in a forecast perspective. The paper proposes a new solution strategy to ensure internal consistency of the population targets in order to guarantee proper convergence of the IPF algorithm. The solution strategy consists in establishing a harmonisation process for the population targets, which combined with a linear programming approach, is applied to generate a consistent target representation. The model approach is implemented and tested on Danish administrative register data. A test on historical census data shows that a 2006 population could be predicted by a 1994 population with an overall percentage deviation of 5–6% given that targets were known. It is also indicated that the deviation is approximately a linear function of the length of the forecast period.

AB - The paper presents a population synthesiser based on the method of Iterative Proportional Fitting (IPF) algorithm developed for the new Danish national transport model system. The synthesiser is designed for large population matrices and allows target variables to be represented in several target constraints. As a result, constraints for the IPF are cross-linked, which makes it difficult to ensure consistency of targets in a forecast perspective. The paper proposes a new solution strategy to ensure internal consistency of the population targets in order to guarantee proper convergence of the IPF algorithm. The solution strategy consists in establishing a harmonisation process for the population targets, which combined with a linear programming approach, is applied to generate a consistent target representation. The model approach is implemented and tested on Danish administrative register data. A test on historical census data shows that a 2006 population could be predicted by a 1994 population with an overall percentage deviation of 5–6% given that targets were known. It is also indicated that the deviation is approximately a linear function of the length of the forecast period.

KW - Population synthesising

KW - Iterative Proportional Fitting (IPF)

KW - Transport demand modelling

KW - Model forecasting

U2 - 10.1016/j.tra.2011.11.002

DO - 10.1016/j.tra.2011.11.002

JO - Transportation Research. Part A: Policy & Practice

JF - Transportation Research. Part A: Policy & Practice

SN - 0965-8564

IS - 3

VL - 46

SP - 467

EP - 479

ER -