International migration is dicult to predict because of uncertainties. The
identification of sources of uncertainty and the measurement and modelling of
uncertainties are necessary, but they are not sucient. Uncertainties should be
reduced by accounting for the heterogeneity of migrants, the reasons why some
people leave their country while most stay, and the causal mechanisms that lead to those choices. International migration takes place within a context of globalisation, technological change, growing interest in migration governance, and the emergence of a migration industry. Young people are more likely than older people to respond to these contextual factors, as they are better informed, have greater self-ecacy, and are more likely to have a social network abroad than previous generations.
My aim in this paper is to present ideas for the causal forecasting of migration.
Wolfgang Lutz’s demographic theory of socioeconomic change is a good point of
departure. The cohort-replacement mechanism, which is central to Lutz’s theory, is extended to account for cohort heterogeneity, life-cycle transitions, and learning. I close the paper by concluding that the time has come to explore the causal mechanisms underlying migration, and to make optimal use of that knowledge to improve migration forecasts.
Original languageEnglish
Pages (from-to)199-218
JournalVienna Yearbook of Population Research
Volume16
Early online date29 Nov 2018
DOI
Publication statusPublished - Jun 2019

    Research areas

  • causal forecasting, international migration

ID: 9534786