The University of Southampton
University of Southampton Institutional Repository

Estimation of international migration flow tables in Europe

Estimation of international migration flow tables in Europe
Estimation of international migration flow tables in Europe
A methodology is developed to estimate comparable international migration flows between a set of countries. International migration flow data may be missing, reported by the sending country, reported by the receiving country or reported by both the sending and receiving countries. For the last situation, reported counts rarely
match due to differences in definitions and data collection systems. In this paper, data known to be of a reliable standard is used to create an incomplete migration flow table of harmonized values. Cells for which no reliable reported flows exist are then estimated from a negative binomial regression model fitted using the Expectation-Maximization (EM) algorithm. Finally, measures of precision for all missing cell estimates are derived using the Supplemented EM algorithm. Recent data on international migration between countries in Europe are used to illustrate the methodology. The results represent a complete table of comparable flows that can be used by regional policy makers and social scientists alike to better understand population behaviour and change.
constrained optimization, flow tables, international migration, migration Estimation, Negative Binomial Regression, SEM algorithm
M09/09
Southampton Statistical Sciences Research Institute
Abel, Guy J.
d35b5069-3c52-4d13-a678-1684ae1fce1e
Abel, Guy J.
d35b5069-3c52-4d13-a678-1684ae1fce1e

Abel, Guy J. (2009) Estimation of international migration flow tables in Europe (S3RI Methodology Working Papers, M09/09) Southampton, UK. Southampton Statistical Sciences Research Institute 29pp.

Record type: Monograph (Working Paper)

Abstract

A methodology is developed to estimate comparable international migration flows between a set of countries. International migration flow data may be missing, reported by the sending country, reported by the receiving country or reported by both the sending and receiving countries. For the last situation, reported counts rarely
match due to differences in definitions and data collection systems. In this paper, data known to be of a reliable standard is used to create an incomplete migration flow table of harmonized values. Cells for which no reliable reported flows exist are then estimated from a negative binomial regression model fitted using the Expectation-Maximization (EM) algorithm. Finally, measures of precision for all missing cell estimates are derived using the Supplemented EM algorithm. Recent data on international migration between countries in Europe are used to illustrate the methodology. The results represent a complete table of comparable flows that can be used by regional policy makers and social scientists alike to better understand population behaviour and change.

PDF
s3ri-workingpaper-M09-09.pdf - Other
Download (327kB)

More information

Published date: 11 May 2009
Keywords: constrained optimization, flow tables, international migration, migration Estimation, Negative Binomial Regression, SEM algorithm

Identifiers

Local EPrints ID: 66197
URI: https://eprints.soton.ac.uk/id/eprint/66197
PURE UUID: 15a87f2d-be0a-4684-9a50-2ccf6d1dd9ad

Catalogue record

Date deposited: 11 May 2009
Last modified: 19 Jul 2017 00:27

Export record

Contributors

Author: Guy J. Abel

University divisions

Download statistics

Downloads from ePrints over the past year. Other digital versions may also be available to download e.g. from the publisher's website.

View more statistics

Atom RSS 1.0 RSS 2.0

Contact ePrints Soton: eprints@soton.ac.uk

ePrints Soton supports OAI 2.0 with a base URL of https://eprints.soton.ac.uk/cgi/oai2

This repository has been built using EPrints software, developed at the University of Southampton, but available to everyone to use.

We use cookies to ensure that we give you the best experience on our website. If you continue without changing your settings, we will assume that you are happy to receive cookies on the University of Southampton website.

×