Forecasting International Migration in Europe: A Bayesian View

Bijak, Jakub

doi:10.1007/978-90-481-8897-0

Cited by 91 publications

(132 citation statements)

References 145 publications

(218 reference statements)

Supporting

Mentioning

128

Contrasting

Unclassified

Order By: Relevance

“…The autoregressive model forecasts future migration in terms of current and past migration, which may be viewed as implicitly incorporating the history of these factors. Also, in light of the lack of a comprehensive theory of migration (26), an empirical approach may be desirable (14).…”

Section: Discussionmentioning

confidence: 99%

Probabilistic population projections with migration uncertainty

Azose

Ševčíková

Raftery

2016

Proc. Natl. Acad. Sci. U.S.A.

View full text Add to dashboard Cite

We produce probabilistic projections of population for all countries based on probabilistic projections of fertility, mortality, and migration. We compare our projections to those from the United Nations' Probabilistic Population Projections, which uses similar methods for fertility and mortality but deterministic migration projections. We find that uncertainty in migration projection is a substantial contributor to uncertainty in population projections for many countries. Prediction intervals for the populations of Northern America and Europe are over 70% wider, whereas prediction intervals for the populations of Africa, Asia, and the world as a whole are nearly unchanged. Out-of-sample validation shows that the model is reasonably well calibrated.Bayesian hierarchical model | international migration | predictive distribution | United Nations | World Population Prospects I n this paper we describe a method for probabilistic projection of population for all countries, with a focus on accounting for uncertainty in projections of international migration. In particular, we are motivated by the needs of the United Nations (UN) Population Division in producing population projections for all countries until 2100 based on projections of fertility, mortality, and migration.A variety of forces contribute to the ebb and flow of international migration. Economic theories at varying levels of granularity indicate that migration flows can arise from individual attempts to maximize income (1, 2), household-level mitigation of risk (3, 4), or differences in global supply and demand for labor (5, 6). Individuals decide to migrate based on an assessment of push and pull factors (7), which may include migration policy (8), geopolitical conflict (9), and quality of the natural environment (10, 11). Networks of migrants provide a feedback mechanism such that migration flows tend to perpetuate themselves over time (12,13). Bijak (14) gives a thorough overview of theories and models of international migration. Despite their acknowledged role in driving migration, our model does not make use of push and pull factors, economic or otherwise, as covariates. Such factors are largely too difficult to predict in the long term to be of use. Instead, we appeal to the inertia of selfperpetuating migration patterns by modeling migration as an autoregressive process.Historically, most methods for projecting population have been deterministic. If the current population is known, broken down by age and sex, and future age-and sex-specific rates are projected for fertility, mortality, and migration, then the cohortcomponent method produces population projections (15). However, the UN Population Division now produces probabilistic projections of population, fertility, and mortality for all countries, but these projections still condition on deterministic migration projections (16, 17). The current methodology in the UN's World Population Prospects (WPP) differs from country to country but typically projects that net migration counts will remain cons...

show abstract

Section: Discussionmentioning

confidence: 99%

Probabilistic population projections with migration uncertainty

Azose

Ševčíková

Raftery

2016

Proc. Natl. Acad. Sci. U.S.A.

View full text Add to dashboard Cite

show abstract

“…Para el caso de la migración internacional se han desarrollado menos técnicas estocásticas que para la mortalidad y la fecundidad. El posible retraso metodológico se debe a la falta de información confiable, pero en los trabajos de Hyndman y Booth (2008), Bijak (2011) y García Guerrero (2014) se presentan alternativas viables, aunque el marco del que parten es un tanto distinto del modelo tpa. En efecto, analíticamente los primeros tres trabajos modelan y proyectan la migración como una variable que sólo depende del tiempo, y toda la información sobre ella está contenida en ella misma.…”

Section: Reflexiones Finalesunclassified

Análisis de los supuestos sobre la migración internacional en las proyecciones de población de México 2001-2050 y 2006-2050

Guerrero

2014

EDU

View full text Add to dashboard Cite

Distintos ejercicios prospectivos consideran que la proyección de la migración está relacionada con la presunción del éxito en diversos objetivos coyunturales de carácter económico, de ahí que en este trabajo se analicen los supuestos de proyección referentes a esta componente demográfica vinculándolos con el marco teórico subyacente y con el contexto político-económico. Se analizan las fuentes citadas en el documento metodológico y en la literatura relacionada con el tema. Algunos de los hallazgos indican que los ejercicios prospectivos examinados suponen un crecimiento económico sostenido de 5% durante la primera década del siglo xxi, con lo que la migración neta crecería a una tasa constante anual cercana a 0.22. Este supuesto está directamente relacionado con las expectativas de las coyunturas político-económicas de los dos primeros gobiernos mexicanos del siglo xxi y con el crecimiento económico alcanzado en el último quinquenio del siglo pasado. Para incrementar la confiabilidad en sus resultados se propone el uso de técnicas estocásticas para medir adecuadamente la incertidumbre asociada a la migración e incrementar así la objetividad en su

show abstract

“…Models that account for non-constant variance have been sparsely used in the demographic context (Keilman and Pham 2004;Bijak 2010). This is surprising as historical time series of demographic data often exhibit volatility due to events such as epidemics, wars or baby booms.…”

Section: Stochastic Volatility Modelmentioning

confidence: 99%