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Forecasting environmental migration to the United Kingdom: an exploration using Bayesian models

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An Erratum to this article was published on 15 October 2013

Abstract

Over the next 50 years, the potential impact of environmental change on human livelihoods could be considerable, with one possible consequence being increased levels of human mobility. This paper explores how uncertainty about the level of immigration to the United Kingdom as a consequence of environmental factors elsewhere may be forecast using a methodology involving Bayesian models. The conceptual understanding of forecasting is advanced in three ways. First, the analysis is believed to be the first time that the Bayesian modelling approach has been attempted in relation to environmental mobility. Second, the paper considers the expediency of this approach by comparing the responses to a Delphi survey with conventional expectations about environmental mobility in the research literature. Finally, the values and assumptions of the expert evidence provided in the Delphi survey are interrogated to illustrate the limited set of conditions under which forecasts of environmental mobility, as set out in this paper, are likely to hold.

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Notes

  1. Probabilistic population forecasters tend to prefer 80 % predictive intervals over, for example, 95 % ones, main arguments being that the former are more robust and less affected by the extremes and do not unnecessarily amplify the impression of uncertainty (Lutz et al. 2004: 37). Besides, as argued by Bijak (2010: 107), ‘such intervals can also provide additional warning to the forecast users, as the probability that the process will fall beyond their limits from time to time cannot be neglected’.

  2. For example, if an international body such as the United Nations were to grant legal status and rights to ‘environmental refugees’ equivalent to that of the current Geneva Convention on political refugees, then current immigration policies in United Kingdom and elsewhere would be impacted (although individual states retain a large margin of autonomy in granting the refugee status).

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Authors and Affiliations

  1. Vienna Institute of Demography, Austrian Academy of Sciences, Vienna, Austria

    Guy Abel

  2. Centre for Population Change, Social Sciences and Demography, University of Southampton, Southampton, UK

    Jakub Bijak & Arkadiusz Wiśniowski

  3. Centre for Population Change, Geography, School of Geography and Geosciences, University of St Andrews, St Andrews, UK

    Allan Findlay & David McCollum

Authors
  1. Guy Abel
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  2. Jakub Bijak
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  3. Allan Findlay
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  4. David McCollum
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  5. Arkadiusz Wiśniowski
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Correspondence to Allan Findlay.

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Abel, G., Bijak, J., Findlay, A. et al. Forecasting environmental migration to the United Kingdom: an exploration using Bayesian models. Popul Environ 35, 183–203 (2013). https://doi.org/10.1007/s11111-013-0186-8

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