Bayesian Probabilistic Projection of International Migration

Demography

Volumn 52, Issue 5, 2015, Pages 1627-1650

  Azose, Jonathan J ^a   Raftery, Adrian E ^a  

^a UNIVERSITY OF WASHINGTON   (United States)

Author keywords

Autoregressive model; Bayesian hierarchical model; Markov chain Monte Carlo; World population prospects

Indexed keywords

AGE DISTRIBUTION; BAYES THEOREM; HUMAN; MARKOV CHAIN; MIGRATION; MONTE CARLO METHOD; POPULATION DYNAMICS; SEX RATIO; TIME FACTOR; TRENDS; UNITED NATIONS;

AGE DISTRIBUTION; BAYES THEOREM; EMIGRATION AND IMMIGRATION; HUMANS; MARKOV CHAINS; MONTE CARLO METHOD; POPULATION DYNAMICS; SEX DISTRIBUTION; TIME FACTORS; UNITED NATIONS;

EID: 84944515910     PISSN: 00703370     EISSN: 15337790     Source Type: Journal    
DOI: 10.1007/s13524-015-0415-0     Document Type: Article

References (33)

1. Abel, G. J. (2010). Estimation of international migration flow tables in Europe. Journal of the Royal Statistical Society: Series A (Statistics in Society),173, 797–825.
2. Abel, G. J. (2013). Estimating global migration flow tables using place of birth data. Demographic Research, 28(article 18), 505–546. doi:10.4054/DemRes.2013.28.18
3. Abel, G. J., Bijak, J., Forster, J. J., Raymer, J., Smith, P. W., & Wong, J. S. (2013). Integrating uncertainty in time series population forecasts: An illustration using a simple projection model. Demographic Research, 29(article 43), 1187–1226. doi:10.4054/DemRes.2013.29.43
4. Abel, G. J., & Sander, N. (2014). Quantifying global international migration flows. Science, 343, 1520–1522.
5. Alkema, L., Raftery, A. E., Gerland, P., Clark, S. J., Pelletier, F., Buettner, T., & Heilig, G. K. (2011). Probabilistic projections of the total fertility rate for all countries. Demography,48, 815–839.
6. Bijak, J. (2006). Forecasting international migration: Selected theories, models, and methods. Dordrecht, The Netherlands: Springer.
7. Bijak, J., & Wiśniowski, A (2010). Journal of the Royal Statistical Society: Series A (Statistics in Society), 173, 775–796.
8. Brücker, H., & Siliverstovs, B. (2006). On the estimation and forecasting of international migration: How relevant is heterogeneity across countries? Empirical Economics,31, 735–754.
9. Cohen, J. E. (2012). Projection of net migration using a gravity model. In Proceedings of the XXVII IUSSP International Population Conference. Paris, France: International Union for the Scientific Study of Population. Retreived from http://www.iussp.org/sites/default/files/eventcallforpapers/IUSSPsession020CohenProjectionNetMigrationGravityModelUNPopDiv2012corrected.pdf
10. Committee for Development Policy and United Nations Department of Economic and Social Affairs. (2008). Handbook on the least developed country category: Inclusion, graduation, and special support measures. New York, NY: United Nations.
11. Congdon, P. (2010). Random-effects models for migration attractivity and retentivity: A Bayesian methodology. Journal of the Royal Statistical Society: Series A (Statistics in Society),173, 755– 774.
12. Esipova, N., Ray, J., & Publiese, A. (2011). Gallup world poll. The many faces of global migration (No 43). Geneva, Switzerland: International Organization for Migration.
13. Fertig, M., & Schmidt, C. M. (2000). Aggregate-level migration studies as a tool for forecasting future migration streams (Rapport technique No 183). Bonn, Germany: Institute for the Study of Labor.
14. Hatton, T. J., & Williamson, J. G. (2002). What fundamentals drive world migration? (Rapport technique). Cambridge, MA: National Bureau of Economic Research.
15. Hatton, T. J., & Williamson, J. G. (2005). Global migration and the world economy: Two centuries of policy and performance. Cambridge, UK: Cambridge University Press.
16. Hyndman, R. J., & Booth, H. (2008). Stochastic population forecasts using functional data models for mortality, fertility and migration. International Journal of Forecasting, 24, 323–342.
17. Kim, K., & Cohen, J. E. (2010). Determinants of international migration flows to and from industrialized countries: A panel data approach beyond gravity. International Migration Review, 44, 899–932.
18. Lutz, W., & Goldstein, J. R. (2004). Introduction: How to deal with uncertainty in population forecasting. International Statistical Review, 72, 1–4.
19. Massey, D. S., Arango, J., Hugo, G., Kouaouci, A., Pellegrino, A., & Taylor, J. E. (1993). Theories of international migration: A review and appraisal. Population and Develop- ment Review, 19, 431–466.
20. Plummer, M. (2003). JAGS: A program for analysis of Bayesian graphical models using Gibbs sampling. In K. Hornik, F. Leisch, & A. Zeileis (Eds.), Proceedings of the 3rd international workshop on distributed statistical computing (pp. 20–22). Vienna, Austria: Austrian Association for Statistical Computing and the R Foundation for Statistical Computing.
21. Raftery, A. E., Chunn, J. L., Gerland, P., & ŠevčíLková, H. (2013). Bayesian probabilistic projections of life expectancy for all countries. Demography, 50 (777), 801.
22. Raftery, A. E., Li, N., ŠevčíLková, H., Gerland, P., & Heilig, G. K. (2012). Bayesian probabilistic population projections for all countries. Proceedings of the National Academy of Sciences, 109(13915), 13921.
23. Raymer, J., & Rogers, A. (2007). Using age and spatial flow structures in the indirect estimation of migration streams. Demography, 44, 199–223.
24. Richmond, A. H. (1988). Sociological theories of international migration: The case of refugees. Current Sociology, 36, 7–25.
25. Rogers, A. (1990). Requiem for the net migrant. Geographical analysis, 22, 283–300.
26. Rogers, A., & Castro, L. J. (1981). Model migration schedules. Laxenburg, Austria: International Institute for Applied Systems Analysis.
27. ter Heide, H. (1963). Migration models and their significance for population forecasts. Milbank Memorial Fund Quarterly, 41, 56–76.
28. United Nations Population Division. (2011). World population prospects: The 2010 revision. New York, NY: United Nations.
29. United Nations Population Division. (2013). World population prospects: The 2012 revision. New York, NY: United Nations.
30. United Nations Population Division. (2014). Probabilistic population projections based on the World Population Prospects: The 2012 revision. New York, NY: United Nations.
31. U.S. Social Security Administration (2013). The 2013 annual report of the board of trustees of the federal old-age and survivors insurance and federal disability insurance trust funds (Annual report). Washington, DC: Social Security Administration.
32. Wheldon, M. C., Raftery, A. E., Clark, S. J., & Gerland, P. (2013). Estimating demographic parameters with uncertainty from fragmentary data. Journal of the American Statistical Association, 108, 96–110.
33. Wright, E. (2010). 2008-based national population projections for the United Kingdom and constituent countries. Population Trends,139, 91–114.