Skip to content

Research at St Andrews

Assessing time series models for forecasting international migration: lessons from the United Kingdom

Research output: Contribution to journalArticle


Open Access permissions



Jakub Bijak, George Disney, Allan M. Findlay, Jonathan J. Forster, Peter W. F. Smith, Arkadiusz Wiśniowski

School/Research organisations


Migration is one of the most unpredictable demographic processes. The aim of this article is to provide a blueprint for assessing various possible forecasting approaches in order to help safeguard producers and users of official migration statistics against misguided forecasts. To achieve that, we first evaluate the various existing approaches to modelling and forecasting of international migration flows. Subsequently, we present an empirical comparison of ex post performance of various forecasting methods, applied to international migration to and from the United Kingdom. The overarching goal is to assess the uncertainty of forecasts produced by using different forecasting methods, both in terms of their errors (biases) and calibration of uncertainty. The empirical assessment, comparing the results of various forecasting models against past migration estimates, confirms the intuition about weak predictability of migration, but also highlights varying levels of forecast errors for different migration streams. There is no single forecasting approach that would be well suited for different flows. We therefore recommend adopting a tailored approach to forecasts, and applying a risk management framework to their results, taking into account the levels of uncertainty of the individual flows, as well as the differences in their potential societal impact.


Original languageEnglish
Pages (from-to)470-487
Number of pages18
JournalJournal of Forecasting
Issue number5
Early online date22 Mar 2019
Publication statusPublished - Aug 2019

    Research areas

  • International migration, Forecasting, Bayesian methods, ARIMA models, Uncertainty, Decision making

Discover related content
Find related publications, people, projects and more using interactive charts.

View graph of relations

Related by author

  1. Determinants of occupational mobility: the importance of place of work

    McCollum, D., Liu, Y., Findlay, A., Feng, Z. & Nightingale, G., 31 Oct 2018, In : Regional Studies. 52, 12, p. 1612-1623 12 p.

    Research output: Contribution to journalArticle

  2. Linking desires and behaviour of residential relocation with life domain satisfaction

    Nowok, B., Findlay, A. M. & McCollum, D., 1 Mar 2018, In : Urban Studies. 55, 4, p. 870-890

    Research output: Contribution to journalArticle

  3. Fees, flows and imaginaries: exploring the destination choices arising from intra-national student mobility

    Findlay, A., Packwood, H., McCollum, D., Evans, G. F. & Tindal, S., 2018, In : Globalisation, Societies and Education. 16, 2, p. 162-175 14 p.

    Research output: Contribution to journalArticle

  4. ‘It was always the plan’: international study as ‘learning to migrate’

    Findlay, A., Prazeres, L., McCollum, D. & Packwood, H., Jun 2017, In : Area. 49, 2, p. 192-199

    Research output: Contribution to journalArticle

Related by journal

  1. Daily Volatility Forecasts: Reassessing the Performance of GARCH Models

    McMillan, D. G. & Speight, A., Sep 2004, In : Journal of Forecasting. 23, 6, p. 449-460 12 p.

    Research output: Contribution to journalArticle

ID: 257702933