Using Age and Spatial Flow Structures in the Indirect Estimation of Migration Streams
Using Age and Spatial Flow Structures in the Indirect Estimation of Migration Streams
This paper presents a modeling strategy for describing and estimating interregional migration flows. The categorical log-linear model is used to demonstrate various approaches to estimation, including direct and indirect methods. And estimates of known data on interdivisional migration patterns in the United States during the 1995-2000 period are used to illustrate the effectiveness of the various log-linear models. The important aspects of the modeling strategy presented in this paper include parameter interpretation, incorporation of auxiliary or a priori information, and assessment of the various model predictions. The results show that capturing the interactions between origins and destinations are very important for accurate predictions.
Southampton Statistical Sciences Research Institute, University of Southampton
Raymer, James
ed2973c1-b78d-4166-baf3-4e18f1b24070
Rogers, Andrei
ed63d88a-6d71-4284-8d18-a0cd4a802371
27 September 2005
Raymer, James
ed2973c1-b78d-4166-baf3-4e18f1b24070
Rogers, Andrei
ed63d88a-6d71-4284-8d18-a0cd4a802371
Raymer, James and Rogers, Andrei
(2005)
Using Age and Spatial Flow Structures in the Indirect Estimation of Migration Streams
(S3RI Applications and Policy Working Papers, A05/07)
Southampton, UK.
Southampton Statistical Sciences Research Institute, University of Southampton
36pp.
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Monograph
(Working Paper)
Abstract
This paper presents a modeling strategy for describing and estimating interregional migration flows. The categorical log-linear model is used to demonstrate various approaches to estimation, including direct and indirect methods. And estimates of known data on interdivisional migration patterns in the United States during the 1995-2000 period are used to illustrate the effectiveness of the various log-linear models. The important aspects of the modeling strategy presented in this paper include parameter interpretation, incorporation of auxiliary or a priori information, and assessment of the various model predictions. The results show that capturing the interactions between origins and destinations are very important for accurate predictions.
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Published date: 27 September 2005
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Local EPrints ID: 17457
URI: http://eprints.soton.ac.uk/id/eprint/17457
PURE UUID: 09898c28-51a7-4121-bb0d-9e3a75c854a8
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Date deposited: 27 Sep 2005
Last modified: 20 Feb 2024 03:20
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Author:
James Raymer
Author:
Andrei Rogers
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