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  • Project contributors: Bijak J, Hilton J, Smith P, Forster J, Dodd E, Wisniowski A,

    This Project is part of the following research programme/s:

    Population estimation and forecasting


    The aim of this research is to continue developing the pathbreaking models and tools made during CPC-I on dynamic population forecasting models, particularly in the context of demographic uncertainty. Dynamic population models provide a general and flexible platform for modelling and analysing population change over time. They allow the combination of all the main components of population change by age and sex with various transitions that population groups may experience throughout their life course. The transitions may include those between states of residences, employment, marriage or health.

    The models developed in this project extend existing multi-state models by (1) including all of the main demographic components of change (i.e., fertility, mortality and interregional migration) and their (expected) variations over time, (2) by allowing interactions to occur between various state transitions that occur throughout the life course, e.g., health and marital statuses, residential and employment statuses, or marital and employment statuses, and (3) by including uncertainty using statistical modelling approaches for rates and categorical data.

    Publications & Activities

    An Integrated Framework For Bayesian Population Forecasting
    International Society for Bayesian Analysis (ISBA) (2018). (Edinburgh, UK)
    Authors: Hilton J, Forster J, Dodd E, Smith P, Bijak J,

    Modelling the unforeseeable: limits and advances in migration forecasting
    Seminar on Population Projections and Demographic Trends (2018). (Eurostat, Luxembourg)
    Authors: Bijak J,

    An Integrated Framework For Bayesian Population Forecasting
    36th International Symposium on Forecasting (2016). (Santander, Spain)
    Authors: Hilton J, Bijak J, Dodd E, Forster J, Smith P,

    An Integrated Framework For Bayesian Population Forecasting
    International Society for Bayesian Analysis (ISBA) (2016). (Sardinia, Italy)
    Authors: Smith P, Bijak J, Dodd E, Forster J, Hilton J,

    Modelling Migration: Review and Assessment
    First International Conference on "EU and Global Asylum-Related Migration Research – Gaining an Overview" (2016). (Floriana, Malta)
    Authors: Bijak J,

    Empirical Evaluation of Migration Forecasting Methods
    Conference of European Statisticians: Joint Eurostat/UNECE Work Session on Demographic Projections (2016). (Geneva)
    Authors: Bijak J,

    Uncertain Population Forecasting. A Case for Practical Uses.
    New Techniques and Technologies for Statistics (NTTS) conference (2015). (Brussels)
    Authors: Bijak J, Aberts I, Alho J, Bryant J, Buettner T, Falkingham J, Forster J, Gerland P, Keilman N, King T, O'Hagan A, Onorante L, Owens D, Raftery A, Ševcíková H, Smith P,

    Dealing with uncertainty in migration research
    Turkish Migration Conference 2014 (2014). (Regent's University, London)
    Authors: Bijak J,

    Incorporating model uncertainty into fertility schedule estimates for population forecasting
    European Population Conference 2014 (2014). (Budapest, Hungary)
    Authors: Forster J, Bijak J, Smith P,

    Uncertainty in international migration studies: A Bayesian view
    Trinity 2014 Seminar Series: 'Research Methods in Demography and Beyond' (2014). (Oxford Institute of Population Ageing)
    Authors: Bijak J,

    Predicting Migration: Practices, Pitfalls and Perspectives
    Joint KNOMAD-UN Population Division Seminar on the role of Migration in Population Modeling (2014). (United Nations, New York)
    Authors: Bijak J,

    Uncertainty in international migration studies: A Bayesian view
    Invited seminar (2014). (School of Mathematics, University College Dublin)
    Authors: Bijak J,

    European Migrations: Uncertain Present, Uncertain Future?
    Centre d'Estudis Demografics 30th Anniversary Lecture Series (2014). (Centre d'Estudis Demografics, Barcelona)
    Authors: Bijak J,

    Use of probabilistic forecasts; with focus on population applications