Abstract
In Europe, the monitoring and management of migration flows are high on the political agenda. Evidence-based monitoring calls for adequate data, which do not exist. The sources of data on international migration differ significantly between countries in Europe and the initiatives to improve data collection and produce comparable data, including new legislation, did not yield the expected outcome. Scientists have developed statistical models that combine quantitative and qualitative data from different sources to derive at estimates of migration flows that account for differences in definition, undercoverage, undercount and other measurement problems. Official statisticians are reluctant to substitute estimates for measurements. This article reviews the progress made over the last decades and the challenges that remain. It concludes with several recommendations for better international migration data/estimates. They range from improved cooperation between actors to innovation in data collection and modelling.
References
1.
Aalen, O.O. 1975. Statistical Inference for a Family of Counting Processes . PhD thesis. Berkeley: University of California.
2.
Aalen, O.O., Ø. Borgan, and H.K. Gjessing. 2008. Survival and Event History Analysis. A Process Point of View . New York: Springer. Doi: https://dx-doi-org.web.bisu.edu.cn/10.1007/978-0-387-68560-1.
3.
Abel, G.J. 2010. “Estimation of International Migration Flow Tables in Europe.” Journal of the Royal Statistical Society A 173(4): 797–825. Doi: https://dx-doi-org.web.bisu.edu.cn/10.1111/j.1467-985X.2009.00636.x.
4.
Abel, G.J. 2013. “Estimating Global Migration Flow Tables Using Place of Birth Data.” Demographic Research 28(18): 504–546. Doi: https://dx-doi-org.web.bisu.edu.cn/10.4054/DemRes.2013.28.18.
5.
Abel, G.J. 2016. “Estimates of Global Bilateral Migration Flows By Gender Between 1960 and 2015”. International Migration Review published online: August 13, 2018. Doi: https://doi.org/10.1111/imre.12327.
6.
Abel, G.J. and N. Sander. 2014. “Quantifying Global International Migration Flows.” Science 343(1520): 1520–1522. Doi: https://dx-doi-org.web.bisu.edu.cn/10.1126/science.1248676.
7.
Andersen, P.K., Ø. Borgan, R. Gill, and N. Keiding. 1993. Statistical Models Based on Counting Processes . New York: Springer, ISBN: 978-0-387-94519-4. Doi: https://dx-doi-org.web.bisu.edu.cn/10.1007/978-1-4612-4348-9.
8.
Armstrong, J.S. 2001. “Standards and Practices for Forecasting.” In Principles of Forecasting: A Handbook for Researchers and Practitioners , edited by J.S. Armstrong, Norwell, MA: Kluwer Academic Publishers (Springer): 679–732. ISBN: 978-0-7923-7930-0. Doi: https://dx-doi-org.web.bisu.edu.cn/10.1007/978-0-306-47630-3.
9.
Azose, J.J. and A.E. Raftery. 2015. “Bayesian Probabilistic Projection of International Migration.” Demography 52: 1627–1650. Doi: https://dx-doi-org.web.bisu.edu.cn/10.1007/s13524-015-0415-0.
10.
Azose, J.J., H. Sevčíková, and A.E. Raftery. 2016. “Probabilistic Population Projections with Migration Uncertainty.” PNAS (Proceedings of the National Academy of Sciences of the United States of America) 113(23): 6460–6465. Doi: https://dx-doi-org.web.bisu.edu.cn/10.1073/pnas.1606119113.
11.
Beauchemin, C. 2013. Statement Prepared for the Informal Hearings for High-level Dialogue on International Migration and Development (New York, July 15, 2013) . Paris: International Union for the Scientific Study of Population (IUSSP). Available at: https://iussp.org/sites/default/files/IUSSP_Statement_UN_HLD_InformalHearings_InternationalMigration_10July.pdf (accessed February 2019).
12.
Beauchemin, C. 2014. “A Manifesto for Quantitative Multi-sited Approaches to International Migration.” International Migration Review 48(4): 921–938. Doi: https://dx-doi-org.web.bisu.edu.cn/10.1111/imre.12157.
13.
Beauchemin, C. 2018. Migration between Africa and Europe . Cham: Springer. Doi: https://dx-doi-org.web.bisu.edu.cn/10.1007/978-3-319-69569-3.
14.
Beauchemin, C. and B. Schoumaker. 2016. “Micro Methods: Longitudinal Surveys and Analysis.” In International Handbook of Migration and Population Distribution , edited by M.J. White: 175–204. International Handbooks of Population 6. Dordrecht: Springer. Doi: https://dx-doi-org.web.bisu.edu.cn/10.1007/978-94-017-7282-2_9.
15.
Betts, A. 2011. Global Migration Governance . Oxford: Oxford University Press. Doi: https://dx-doi-org.web.bisu.edu.cn/10.1093/acprof:oso/9780199600458.001.0001.
16.
Bijak, J. 2011. Forecasting International Migration in Europe. A Bayesian View . New York: Springer.
17.
Bijak, J. and J. Bryant. 2016. “Bayesian Demography 250 Years After Bayes.” Population Studies 70(1): 1–19. Doi: https://dx-doi-org.web.bisu.edu.cn/10.1080/00324728.2015.1122826.
18.
Bijak, J. and A. Wiśniowski. 2010. “Bayesian Forecasting of Immigration to Selected European Countries By Using Expert Knowledge.” Journal of the Royal Statistical Society A 173(4): 775–796. Doi: https://dx-doi-org.web.bisu.edu.cn/10.1111/j.1467-985X.2009.00635.x.
19.
Bilgili, Ö. 2014. “Migrants’ Multi-sited Social Lives.” Comparative Migration Studies 2(3): 283–304. Doi: https://dx-doi-org.web.bisu.edu.cn/10.5117/CMS2014.3.BILG.
20.
Bilsborrow, R.E., G. Hugo, A.S. Oberai, and H. Zlotnik. 1997. International Migration Statistics: Guidelines for Improving Data Collection Systems . Geneva: International Labour Organization. ISBN 9221095177.
21.
Bilsborrow, R.E. 2016. “Concepts, Definitions and Data Collection Approaches.” In International Handbook of Migration and Population Distribution , edited by M. White, 31–40. International Handbooks of Population 6. Dordrecht: Springer. Doi: http://dx. doi.org/10.1007/978-94-017-7282-2_7.
22.
Bocquier, P. 2016. “Migration analysis using demographic surveys and surveillance systems.” International Handbook of Migration and Population Distribution , edited by M. White. International Handbooks of Population 6. Dordrecht: Springer: 205–223. Doi: https://dx-doi-org.web.bisu.edu.cn/10.1007/978-94-017-7282-2_10.
23.
Boswell, C. 2016. Report of the conference “Understanding and tackling the migration challenge: the role of research”, Brussels, 4–5 February 2016. European Commission, CG Research and Innovation. Doi: https://dx-doi-org.web.bisu.edu.cn/10.2777/111442. Available at: https://ec.europa.eu/research/social-sciences/pdf/other_pubs/migration_conference _report_2016.pdf#view=fit&pagemode=none (accessed February 2019).
24.
Brierley, M.J., J.J. Forster, J.W. McDonald, and P.W.F. Smith. 2008. “Bayesian Estimation of Migration Flows.” In International Migration in Europe. Data, Models and Estimates , edited by J. Raymer and F. Willekens, 149–174. Chichester: Wiley. ISBN: 978-470-03233-6. Doi: https://dx-doi-org.web.bisu.edu.cn/10.1002/9780470985557.
25.
Burgman, M.A. 2016. Trusting Judgements. How to Get the Best Out of Experts . Cambridge: Cambridge University Press. Doi: https://dx-doi-org.web.bisu.edu.cn/10.1017/CBO 9781316282472.
26.
Brooks, S., Gelman, A., Jone, G.I., and X-L. Meng (Eds.). 2011. Handbook of Markov Chain Monte Carlo . Boca Rotan: Chapman & Hall (Taylor & Francis). ISBN 9781420079418.
27.
Caarls, K. 2016. NORFACE Research Programme on Migration. Migration in Europe: social, economic, cultural and policy dimensions. 2009–2014. Summary Report. Available at: https://pure.knaw.nl/portal/files/2869025/2016_Caarls_NWO_Summary_Report_NORFACE_final.pdf See also http://cordis.europa.eu/result/rcn/160917_en. html (accessed February 2019).
28.
Cantisani, G. and M. Poulain. 2006. “Statistics on Population With Usual Residence.” In THESIM: Towards Harmonised European Statistics on International Migration , edited by M. Poulain, N. Perrin, and A. Singleton: 181–201. Louvain-la-Neuve: Presses Universitaires de Louvain. ISBN 2-930344-95-4. Available at: http://www.seemig.eu/downloads/resources/THESIMFinalReport.pdf (accessed February 2019).
29.
Cantisani, G., S. Farid, D. Pearce, and N. Perrin. 2009. Guide on the Compilation of Statistics on International Migration in the Euro-Mediterranean Region , Publication MEDSTAT II. Paris: Ed. ADETEF. Available at: http://www.unhcr.org/50a4f84d9.pdf (accessed February 2019).
30.
Chater, N., J.B. Tenebaum, and A. Yuille. 2006. “Probabilisitc Models of Cognition: Conceptual Foundations.” Trends in Cognitive Sciences 10(7): 287–291. Doi: https://dx-doi-org.web.bisu.edu.cn/10.1016/j.tics.2006.05.007.
31.
Chebon, S., C. Faes, F. Cools, and H. Geys 2017. “Models for zero-inflated, correlated count data with extra heterogeneity: when is it too complex?” Statistics in Medicine 36(2): 345–361. Doi: https://dx-doi-org.web.bisu.edu.cn/10.1002/sim.7142.
32.
Cohen, J., M. Roig, D.C. Reuman, and C. GoGwilt. 2009. “International Migration Beyond Gravity: A Statistical Model for Use in Population Projections.” PNAS (Proceedings of the National Academy of Sciences of the USA) 105(40): 15269–15274. Doi: https://dx-doi-org.web.bisu.edu.cn/10.1073/pnas.0808185105.
33.
Congdon, P. 1993. “Approaches to Modelling Overdispersion in the Analysis of Migration.” Environment and Planning A 25(10): 1481–1510. Doi: https://dx-doi-org.web.bisu.edu.cn/10.1068/a251481.
34.
Congdon, P. 2001. Bayesian Statistical Modelling . Chichester: Wiley. Doi: https://dx-doi-org.web.bisu.edu.cn/10.1068/a251481.
35.
Courgeau, D. 1973. “Migrants et Migrations.” Population 1: 95–129. English version published as Population Selected Papers No. 3, October 1979. Doi: https://dx-doi-org.web.bisu.edu.cn/10.2307/1530972.
36.
Davies, R.B. and C.M. Guy. 1987. “The Statistical Modeling of Flow Data When the Poisson Assumption is Violated.” Geographical Analysis 19(4): 300–314. Doi: https://dx-doi-org.web.bisu.edu.cn/10.1111/j.1538-4632.1987.tb00132.x.
37.
De Beer, J., J. Raymer, R. van der Erf, and L. van Wissen. 2010. “Overcoming the Problems of Inconsistent International Migration Data: A New Method Applied to Flows in Europe.” European Journal of Population 26: 459–481. Doi: https://dx-doi-org.web.bisu.edu.cn/10.1007/s10680-010-9220-z.
38.
De Brauw, A. and C. Carletto. 2012. In Improving the Measurement and Policy Relevance of Migration Information in Multi-Topic Household Surveys . Washington D.C: Living Standard Measurement Study. World Bank. Available at: http://siteresources. worldbank.org/INTLSMS/Resources/3358986-1199367264546/Migration_Data_v14.pdf (accessed February 2019).
39.
DeWaard, J., K. Kim, and J. Raymer. 2012. “Migration Systems in Europe: Evidence from Harmonized Flow Data.” Demography 49(4): 1307–1333. Doi: https://dx-doi-org.web.bisu.edu.cn/10.1007/s13524-012-0117-9.
40.
DeWaard, J., J.T. Ha, J. Raymer, and A. Wiśniowski. 2017. “Migration From New-accession Countries and Duration Expectancy in the EU-15: 2002–2008.” European Journal of Population 33(1): 33–53. Doi: https://dx-doi-org.web.bisu.edu.cn/10.1007/s10680-016-9383-3.
41.
Disney, G. 2014. Model-Based Estimates of UK Immigration . PhD Thesis. Southampton: University of Southampton.
42.
Disney, G., A. Wiśniowski, J.J. Forster, P.W.F. Smith, and J. Bijak. 2015. Evaluation of Existing Migration Forecasting Methods and Models , Report for the Migration Advisory Committee, ESRC Centre for Population Change. Southampton: University of Southampton. Available at: https://assets.publishing.service.gov.uk/government/uploads/system/uploads/attachment_data/file/467405/Migration_Forecasting_report.pdf (accessed February 2019).
43.
Dumont, J.-C. and G. Lemaitre. 2005. “Counting Immigrants and Expatriates in OECD Countries.” OECD Economic Studies 3(1): 49–83. Doi: https://dx-doi-org.web.bisu.edu.cn/10.1787/eco_studies-v2005-art3-en.
44.
European Commission. 2009. The Production Method of EU Statistics: A Vision for the Next Decade. Communication from the Commission to the European Parliament and the Council of 10 August 2009. COM(2009) 404 final. Available at: http://eur-lex.europa.eu/LexUriServ/LexUriServ.do?uri=COM:2009:0404:FIN:En:PDF (accessed February 2019).
45.
European Commission. 2013. Proposal for a Regulation of the European Parliament and of the Council Establishing an Entry/Exit System (EES) to Register Entry and Exit Data of Third Country Nationals Crossing the External Borders of the Member States of the European Union . COM(2013) 95 final. Available at: http://eur-lex.europa.eu/legal-content/EN/TXT/?uri=celex%3A52013PC0095 (accessed February 2019).
46.
European Commission. 2016a. Research & Innovation Projects in Support of European Policy: Migration and Mobility . Brussels: European Commission. DG Research and Innovation. EUR 27592 EN. Available at: http://ec.europa.eu/research/social-sciences/pdf/project_synopses/ki-na-27-592-en.pdf (accessed February 2019).
47.
European Commission. 2016b. Proposal for a Regulation of the European Parliament and of the Council Establishing an Entry/Exit System (EES) to Register Entry and Exit Data and Refusal of Entry Data of Third Country Nationals Crossing the External Borders of the Member States of the European Union and Determining the Conditions for Access to the EES for Law Enforcement Purposes and Amending Regulation (EC) No 767/2008 and Regulation (EU) No 1077/2011 . COM(2016) 194 final. 2016/0106 (COD). 6th April 2016. Available at: http://eur-lex.europa.eu/legal-content/EN/TXT/?uri=CELEX%3 A52016PC0194 (accessed February 2019).
48.
European Commission. 2017. 2017 Report on Equality Between Women and Men in the EU . Brussels: European Commission, Directorate-General for Justice and Consumers. Doi: https://dx-doi-org.web.bisu.edu.cn/10.2838/52591.
49.
European Statistical System. 2015. ESS Vision 2020. Building the Future of European Statistics . Luxembourg: Publication Office of the European Union. Available at: http://ec.europa.eu/eurostat/web/ess/about-us/ess-vision-2020 (accessed February 2019).
50.
Eurostat. 2017. Households International Migration Surveys in the Mediterranean countries (MED-HIMS). Available at: http://ec.europa.eu/eurostat/web/europeanneighbourhood-policy/enp-south/med-hims (accessed February 2019).
51.
Evans, M., N. Hastings, and B. Peacock. 2000. Statistical Distributions . Third Edition. New York: Wiley ISBN: 0-471-37124-6 (Fourth edition: Forbes, C., M. Evans, N. Hastings and B. Peacock 2011. Statistical distributions . Hoboken, Jew Jersey: Wiley ISBN: 978-0-470-39063-4).
52.
Fay, M.P. and S. Kim. 2017. “Confidence intervals for directly standardized rates using mid-p gamma intervals.” Biometrical Journal 59(2): 377–387. Doi: https://dx-doi-org.web.bisu.edu.cn/10.1002/bimj.201600111.
53.
Fiorio, L., G. Abel, J. Cai, E. Zagheni, I. Weber, and G. Vinué. 2017. “Using Twitter Data to Estimate the Relationship Between Short-term Mobility and Long-term Migration.” In Proceedings of the 2017 ACM on Web Science (WebSci ’17, Troy, New York). Doi: https://dx-doi-org.web.bisu.edu.cn/10.1145/3091478.3091496.
54.
Flowerdew, R. and M. Aitkin. 1982. “A Method of Fitting the Gravity Model Based on the Poisson Distribution.” Journal of Regional Science 22: 191–202. Doi: https://dx-doi-org.web.bisu.edu.cn/10.1111/j.1467-9787.1982.tb00744.x.
55.
Frank, M. 2016. “Was Piaget a Bayesian? Analogies Between Piaget’s Theory of Development and Formal Elements in the Bayesian Framework.” Blog. Available at: http://babieslearninglanguage.blogspot.be/2016/04/was-piaget-bayesian.html (accessed February 2019).
56.
Gerland, P. 2015. “Migration, Mobility and Big Data. An Overview.” Paper presented at the GMG International Conference “Harnessing migration, remittances and diaspora contributions for financing sustainable development.” New York, 26–27 May 2016. Available at: http://www.globalmigrationgroup.org/sites/default/files/GMG_2015_UNPD- PG_Migration.pptx (accessed February 2019).
57.
Goodman, L.A. 1961. “Statistical methods for the mover-stayer model.” Journal of the American Statistical Association 56(296): 841–868. Doi: https://doi.org/10.1080/01621459.1961.10482130.
58.
Gopnik, A. and E. Bonawitz. 2015. “Bayesian Model of Child Development.” WIREs Cognitive Science 6: 75–86.
59.
Gopnik, A. and J.B. Tenenbaum. 2007. “Bayesian Networks, Bayesian Learning and Cognitive Development.” Developmental Science 10(3): 281–287. Doi: https://dx-doi-org.web.bisu.edu.cn/10.1111/j.1467-7687.2007.00584.x.
60.
Griffith, D.A. and R. Haining. 2006. “Beyond Mule Kicks: The Poisson Distribution in Geographical Analysis.” Geographical Analysis 38: 123–139. Doi: https://doi.org/10.1111/j.0016-7363.2006.00679.x.
61.
Hanea, A.M., M.F. McBride, M.A. Burgman, and others et al. 2016. “Investigate Discuss Estimate Aggregate for Structured Expert Judgement.” International Journal of Forecasting 33(1): 267–279. Doi: https://dx-doi-org.web.bisu.edu.cn/10.1016/j.ijforecast.2016.02.008.
62.
Hastings, W.K. 1970. “Monte Carlo sampling methods using Markov chains and their applications.” Biometrika 57(1): 97–109. Doi: https://doi.org/10.1093/biomet/57.1.97.
63.
Howson, C. and P. Urbach. 1989. Scientific Reasoning. The Bayesian Approach . La Salle, Illinois: Open Court Publishing Company. ISBN: 9780812695786.
64.
Hughes, C., E. Zagheni, G. Abel, and others. 2016. Inferring Migrations: Traditional Methods and New Approaches Based on Mobile Phone, Social Media, and Other Big Data. Feasibility Study on Inferring (Labour) Mobility and Migration in the European Union from Big Data and Social Media Data , Report prepared for the European Commission, Programme for Employment and Social Innovation “EaSI” (2014–2020). Brussels: European Commission. Catalog N.:KE-02-16-632-EN-N. Available at: http://ec.europa.eu/social/main.jsp?catId=738&langId=en&pubId=7910&type=2&furtherPubs =yes (accessed February 2019).
65.
IOM. 2010a. “Migration and Transnationalism: Opportunities and Challenges. Background Paper for the Workshop ‘Migration and Transnationalism: Opportunities and Challenges’.” Geneva, 9–10 March 2010. Geneva: International Organization for Migration, International Dialogue on Migration. Available at: http://www.iom.int/idmtransnationalism (accessed February 2019).
66.
IOM. 2010b. “Final Report of the Workshop ‘Migration and Transnationalism: Opportunities and Challenges’.” Geneva, 9–10 March 2010. Geneva: International Organization for Migration, International Dialogue on Migration. Available at: http://www.iom.int/idmtransnationalism (accessed February 2019).
67.
IOM. 2011. Glossary On Migration . International Migration Law Series No. 25. Second edition, Geneva: International Organization for Migration (IOM). Available at: https://publications.iom.int/system/files/pdf/iml25_1.pdf (accessed February 2019).
68.
Jacobs, R.A. and J.K. Kruschke. 2011. “Bayesian Learning Theory Applied to Human Cognition.” WIREs Cognitive Science 2: 8–21. Doi: https://doi.org/10.1002/wcs.80.
69.
Jensen, E.B. 2013. A Review of Methods for Estimating Emigration . Report of the Suitland Working Group on Migration Statistics. Washington D.C: Population Division, U.S. Census Bureau. Available at: https://www.census.gov/content/dam/Census/library/working-papers/2013/demo/jensen-01.pdf (accessed February 2019).
70.
Johansson, L. and T. Johansson. 2016. “Register for Mapping Circular Migration.” Statistics Sweden Dokumenttyp 2015-12-14. Paper presented at the European Population Conference, Mainz, August 2016. Stockholm: Statistics Sweden. Available at: https://epc2016.princeton.edu/papers/160528 (accessed February 2019).
71.
Kelly, J. 1987. “Improving the Comparability of International Migration Statistics: The Contribution of the Conference of European Statisticians from 1971 to Date.” International Migration Review 21(4): 1017–1037. Doi: https://doi.org/10.1177%2F019791838702100406.
72.
King, R. and A. Lulle. 2016. Research on Migration: Facing Realities and Maximising Opportunities. A Policy Review . Brussels: European Commission, DG Research and Innovation. Doi: https://dx-doi-org.web.bisu.edu.cn/10.2777/414370 (PDF). Available at: https://ec.europa.eu/research/social-sciences/pdf/policy_reviews/ki-04-15-841_en_n.pdf (accessed February 2019).
73.
Klabunde, A. and F.J. Willekens. 2016. “Decision-making in Agent-based Models of Migration: State of the Art and Challenges.” European Journal of Population 32(1): 73–97. Doi: https://doi.org/10.1007/s10680-015-9362-0.
74.
Klabunde, A., S. Zinn, F. Willekens, and M. Leuchter. 2017. “Multistate Modelling Extended By Behavioural Rules: An Application to Migration.” Population Studies 71(Supplement 1): S51–S67. Doi: https://doi.org/10.1080/00324728.2017.1350281.
75.
Knauth, B. 2011. “Migration statistics mainstreaming.” Proceedings of the 58th World Statistical Congress 2011 (Dublin) ; The Hague: International Statistical Institute. Available at: http://2011.isiproceedings.org/papers/650162.pdf (accessed February 2019).
76.
Kotowska, I.E. and I. Villán Criado. 2015. Migration/migrants/integration . European Statistical Advisory Committee, Doc 2015/1176 (manuscript).
77.
Kraler, A. and D. Reichel. 2010. Statistics on Migration, Integration and Discrimination in Europe. PROMINSTAT Final Report . Available at: http://cordis.europa.eu/docs/publications/1243/124376691-6_en.pdf and http://www.prominstat.eu/drupal/node/64 (accessed February 2019).
78.
Kraszewska, K., and D. Thorogood. 2010. Migration Statistics Mainstreaming . Working Paper, Joint UNECE/Eurostat Work Session on Migration Statistics, Geneva, 14–16 April 2010. Available at: http://www.unece.org/stats/documents/2010.04.migration.html#/ (accessed February 2019).
79.
Kupiszewska, D. and B. Nowok. 2008. “Comparability of Statistics On International Migration Flows in the European Union.” In International Migration in Europe: Data, Models and Estimates , edited by J. Raymer and F. Willekens, 41–72. Chichester: Wiley. ISBN: 978-470-03233-6. Doi: https://doi.org/10.1002/9780470985557.
80.
Laczko, F. and M. Rango. 2014. “Can Big Data Help Us Achieve a ‘Migration Data Revolution’?” Migration Policy Practice (IOM) 4(2): 20–29. ISSN 2223-5248. Available at: http://publications.iom.int/system/files/pdf/mpp16_24june2014.pdf (accessed February 2019).
81.
Lanzieri, G. 2014a. “Filling the ‘Migration Gaps’ –– Can Research Outcomes Help Us Improve Migration Statistics?” Prepared by the Statistical Office of the European Union (Eurostat) and presented at the Sixty-second plenary session of the Conference of European Statisticians, Paris, 9–11 April 2014. ECE/CES/2014/31. Available at: http://www.unece.org/stats/documents/2014.04.ces.html#/ and https://www.researchgate.net/publication/260096802_Filling_the_%27migration_gaps%27_-_can_research_outcomes_help_us_improve_migration_statistics (accessed February 2019).
82.
Lanzieri, G. 2014b. “Test of an Estimation Method for Annual Migration Flows Between EU-EFTA Countries.” Prepared by the Statistical Office of the European Union (Eurostat) and presented at the Sixty-second plenary session of the Conference of European Statisticians, Paris, 9–11 April 2014. Working Paper No. 9. Available at: https://www.unece.org/fileadmin/DAM/stats/documents/ece/ces/ge.10/2014/mtg1/WP_9_Eurostat.pdf (accessed February 2019).
83.
Lanzieri, G. 2017a. “Summary Methodology of the 2015-Based Population Projections. Technical Note.” Luxembourg: Eurostat ESTAT/F-2/GL. 3 March 2017. Available at: http://ec.europa.eu/eurostat/cache/metadata/Annexes/proj_esms_an1.pdf (accessed February 2019).
84.
Lanzieri, G. 2017b. “Methodology for the Migration Assumptions in the 2015-based Population Projections. Technical note.” Luxembourg: Eurostat ESTAT/F-2/GL. 5 July 2017. Available at: http://ec.europa.eu/eurostat/cache/metadata/Annexes/proj_esms_an3.pdf (accessed February 2019).
85.
Liu, M.M., M.J. Creighton, F. Riosmena, and P. Baizán. 2016. “Prospects for the Comparative Study of International Migration Using Quasi-longitudinal Micro-data.” Demographic Research 35(26): 745–782. Doi: https://doi.org/10.4054/DemRes.2016.35.26.
86.
MEDSTAT Committee for the Coordination of Statistical Activities. 2011. The HIMS Project (Household International Migration Survey) . MEDSTAT Committee for the Coordination of Statistical Activities, 18th Session Luxembourg, September 2011. Available at: http://unstats.un.org/unsd/accsub/2011docs-18th/SA-2011-24-HIMSEurostat.pdf. See also the Eurostat website: http://ec.europa.eu/eurostat/web/european-neighbourhood-policy/enp-south/med-hims (accessed 9 February 2019).
87.
Metropolis, N., A.W. Rosenbluth, M.N. Rosenbluth, A.H. Teller, and E. Teller 1953. “Equations os state calculations by fast computing machines.” Journal of Chemical Physics , 21:1087–1092. Doi: https://doi.org/10.1063/1.1699114.
88.
Miller, P.H. 1983. Theories of Developmental Psychology . San Francisco: W.H. Freeman and Co. ISBN: 0-7167-1432-9 (6th edition 2016 ISBN: 978-1429-278980).
89.
Nowok, B. 2008. “Evolution of Migration Statistics in Selected Central European Countries.” In International Migration in Europe. Data, Models and Estimates , edited by J. Raymer and F. Willekens, 73–87. Chichester: Wiley.
90.
Nowok, B. 2010. Harmonization By Simulation: A Contribution to Comparable International Migration Statistics in Europe . Amsterdam: Rozenberg Publishers. ISBN: 978-90-367-4549-9. Available at: http://www.rug.nl/research/ursi/prc/research/popspace/migrationeurope?lang=en (accessed February 2019).
91.
Nowok, B. and F. Willekens. 2011. “A Probabilistic Framework for Harmonisation of Migration Statistics.” Population, Space and Place 17: 521–533. Doi: https://doi.org/10.1002/psp.624.
92.
ONS. 2015. Long-term International Migration Estimates. Methodology Document . London: Office of National Statistics. Available at: https://www.ons.gov.uk/peoplepopulationandcommunity/populationandmigration/internationalmigration/methodologies/longterminternationalmigrationestimatesmethodology (accessed February 2019).
93.
ONS. 2016. Note on the Difference Between National Insurance Number Registrations and the Estimate of Long-term International Migration: 2016 . London: Office of National Statistics. 12 May 2016. Available at: https://www.ons.gov.uk/peoplepopulationandcommunity/populationandmigration/internationalmigration/articles/noteonthedifferencebetweennationalinsurancenumberregistrationsandtheestimateoflongterminternationalmigration/2016 (accessed February 2019).
94.
Payne, E.H., J.W. Hardin, L.E. Egede, V. Ramakrishnan, A. Selessie, and M. Gebregziabher. 2017. “Approaches for dealing with various sources of overdispersion in modeling count data: Scale adjustment versus modeling.” Statistical Methods in Medical Research 26(4): 1802–1823. Doi: https://doi.org/10.1177/0962280215588569.
95.
Perfors, A., J.B. Tenenbaum, T.L. Griffiths, and F. Xu. 2011. “A Tutorial Introduction to Bayesian Models of Cognitive Development.” Cognition 120: 302–321. Doi: https://doi.org/10.1016/j.cognition.2010.11.015.
96.
Pinsky, M.A. and S. Karlin. 2011. An Introduction to Stochastic Modeling: Fourth edition . Academic Press (Elsevier). ISBN 978-0233814162. Doi: http://doi.org/10.1016/C2009-1-61171-0.
97.
Pisică, S. 2016. “Intra-EU Data Exchange – A Method for Improving Migration Statistics.” Paper presented at the Eurostat conference “Towards more agile social statistics”, Luxembourg, 28–20 Nov 2016. (Manuscript).
98.
Poulain, M. 1991. “Un project d’harmonisation des statistiques de migration internationales au sein de la Communauté Européenne. (A project for the harmonisation of international migration statistics in the European Community)” Revue Européenne des Migrations Internationales 7(2): 115–138. Doi: https://doi.org/10.3406/remi.1992. 1039.
99.
Poulain, M. 1993. “Confrontation des Statistiques de Migrations Intra-Européennes: Vers plus d’Harmonisation? (Confronting the statistics on inter-European migration: Towards a greater harmonization?).” European Journal of Population 9(4): 353–381. Doi: https://doi.org/10.1007/BF01265643.
100.
Poulain, M. 1999, Confrontation des statistiques de migration intra-européennes: vers une matrice comple`te?, Eurostat Working paper, n° 3/1999/E/N°5. Luxembourg: Eurostat. Available at: https://ec.europa.eu/eurostat/documents/3888793/5812665/KS-AP-01-016-DE.PDF/8e80d930-61c7-419a-9cec-34fa7343526a (accessed February 2019).
101.
Poulain, M. 2008. “European Migration Statistics: Definitions, Data and Challenges.” In Mapping Linguistic Diversity in Multicultural Contexts , edited by M. Barni and G. Extra, 43–66. Berlin/New York: Mouton de Gruyter. Doi: https://doi.org/10.1515/9783110207347.1.43.
102.
Poulain, M. and L. Dal. 2008. Estimation of Flows Within the Intra-EU Migration Matrix . Report for the MIMOSA project. Available at: http://mimosa.cytise.be/Documents/Poulain_2008.pdf (accessed February 2019).
103.
Poulain, M. and A. Herm. 2011. Guide to Enhancing Migration Data in West and Central Africa . Geneva: International Organization for Migration (IOM). Available at: http://publications.iom.int/system/files/pdf/dataguide_layout_101111.pdf (accessed February 2019).
104.
Poulain, M. and A. Herm. 2013. “Central Population Registers as a Source of Demographic Statistics in Europe.” Population 68(2): 215–247. Doi: https://doi.org/10.3917/popu.1302.0215.
105.
Poulain, M. and C. Wattelar. 1983. “Les migrations intra-européennes: à la recherche d’un fil d’Ariane au travers des 21 pays du Conseil de l’Europe (Migration between the 21 countries members of the Council of Europe: Searching for the best estimation).” Espace, Populations et Sociétés 1(2): 11–26. Doi: https://doi.org/10.3406/espos. 1983.910.
106.
Poulain, M., Perrin, N., and A. Singleton (Eds.). 2006. THESIM: Towards Harmonised European Statistics on International Migration . Louvain-la-Neuve: UCL Press. ISBN 2-930344-95-4. Available at: http://www.seemig.eu/downloads/resources/THESIM FinalReport.pdf (accessed February 2019).
107.
Radermacher, W. and D. Thorogood. 2009. “Meeting the Growing Needs for Better Statistics on Migrants.” Paper presented during DGINS Conference “Migration – Statistical Mainstreaming”, Malta, 30 September – 1 October. Available at: http://ec. europa.eu/eurostat/documents/1001617/4339944/mainstreaming-w-radermacher.pdf/e3edaf 52-d5f6-471d-a26e-6f3e4a4516f0 (accessed February 2019).
108.
Ravlik, M. 2014. Determinants of International Migration: A Global Analysis . Higher School of Economics Research Paper WP BRP 52/SOC/2014. Moscow: Higher School of Economic Research. Ravlik, Maria, Determinants of International Migration: A Global Analysis (October 2, 2014). Higher School of Economics Research Paper No. WP BRP 52/SOC/2014. Doi: https://dx-doi-org.web.bisu.edu.cn/10.2139/ssrn.2504441.
109.
Raymer, J. (on behalf of the IMEM team). 2012. “Information Exchange and Modelling: Solutions to Imperfect Data on Population Movements.” Economic Commission for Europe, Conference of European Statisticians, Work Session on Migration Statistics, 17–19 October 2012, Geneva. Available at: https://www.unece.org/fileadmin/DAM/stats/documents/ece/ces/ge.10/2012/WP_14_USH_updated_by_R.pdf (accessed February 2019).
110.
Raymer, J. and F. Willekens (Eds.). 2008. International Migration in Europe. Data, Models and Estimates . Chichester: Wiley. ISBN: 978-0-470-03233-6. Doi: https://doi.org/10.1002/9780470985557.
111.
Raymer, J., A. Wiśniowski, J.J. Forster, P.W.F. Smith, and J. Bijak. 2013. “Integrated Modeling of European Migration.” Journal of the American Statistical Association 108(503): 801–819. Doi: https://doi.org/10.1080/01621459.2013.789435.
112.
Robert, C. and G. Casella. 2010. Introducing Monte Carlo Methods with R . New York: Springer. Doi: https://doi.org/10.1007/978-1-4419-1576-4.
113.
Romanian Institute for Research on National Minorities. 2014. National Policy Recommendations on the Enhancement of Migration Data for Romania . Report Prepared in the Project ‘SEEMIG Managing Migration and Its Effects – Transnational Actions Towards Evidence Based Strategies’. Available at: http://www.seemig.eu/downloads/outputs/SEEMIGPolicyRecommendationsRomania.pdf (accessed February 2019).
114.
Schoorl, J.J., L. Heering, I. Esveldt, G. Groenewold, R. van der Erf, A. Bosch, H. de Valk, and B. de Bruijn. 2000. Push and Pull Factors of International Migration. A Comparative Report . Luxembourg: Eurostat. Available at: https://www.nidi.nl/shared/content/output/2000/eurostat-2000-theme1-pushpull.pdf (accessed February 2019).
115.
Schoumaker, B. and C. Beauchemin. 2015. “Reconstructing Trends in International Migration with Three Questions in Household Surveys: Lessons from the MAFE Project.” Demographic Research 32(35): 983–1030. Doi: https://dx-doi-org-s.web.bisu.edu.cn/10.4054/DemRes.2015.32.35.
116.
Skaliotis, M. and D. Thorogood. 2007. “Migration Statistics and Globalisation: Challenges for the European Statistical System.” Paper presented at the 93rd DGINS Conference “The ESS response to globalisation. Are we doing enough?”, Budapest, 20–21 September 2007. Available at: http://www.ksh.hu/pls/ksh/docs/eng/dgins/programme.html (accessed February 2019).
117.
Statistics Netherlands. 2016. Usual Residence Population Definition: Feasibility Study The Netherlands . The Hague: Statistics Netherlands. Available at: https://www.cbs.nl/media/_pdf/2017/08/statistics-netherlands-feasibility-study.pdf (accessed February 2019).
118.
TEMPER Team. 2015. Report of the International Workshop on Methodological Challenges for the Study of Return and Circular Migration . Event Review Series No. 1. Available at: http://www.temperproject.eu/wp-content/uploads/2015/06/Event-Review-1-2015.pdf (accessed February 2019).
119.
Tourmen, C. 2016. “With or Beyond Piaget? A Dialogue Between New Probabilistic Models of Learning and the Theories of Piaget.” Human Development 59: 4–25. Doi: https://doi.org/10.1159/000446670.
120.
UNECE. 2010. “Guidelines for Exchanging Data to Improve Emigration Statistics.” Paper prepared for the Task Force “Measuring emigration using data collected by the receiving country”. Geneva: United Nations Economic Commission for Europe. Available at: http://www.unece.org/index.php?id=17456 (accessed February 2019).
121.
UNECE. 2012. Final Report of the UNECE Task Force on Analysis of International Migration Estimates Using Different Length of Stay Definitions . UNECE, Conference of European Statisticians, 16th plenary session, Paris, 6–8 June 2012. Available at: http://www.unece.org/stats/migration/estimates.html.
122.
UNECE. 2016. Defining and Measuring Circular Migration. Prepared by the UNECE Task Force on Measuring Circular Migration , ECE/CES/STAT/2016/5. Geneva: United Nations Economic Commission for Europe. Available at: http://www.unece.org/index.php?id=44717 (accessed February 2019).
123.
UNECE-CES Task Force on Population Projections. 2016. Key Recommendations and Good Practices in the Communication of Population Projections . Geneva: Conference of European Statisticians, April 2016. Available at: https://www.unece.org/fileadmin/DAM/stats/documents/ece/ces/ge.11/2016/WP_28_TF_Report_v5_WithAppendix_. pdf (accessed February 2019).
124.
United Nations. 1998. Recommendations on Statistics of International Migration . Statistical Papers Series M, No. 58, Rev. 1. New York: Statistics Division, United Nations Statistical Office. ISBN 92-1-161408-2. Available at: https://unstats.un.org/unsd/publication/seriesm/seriesm_58rev1e.pdf (accessed February 2019).
125.
United Nations General Assembly. 2016. New York Declaration for Refugees and Migrants . UN General Assembly, A/Res/71/1, 3 October 2016. Available at: http://refugeesmigrants.un.org/declaration (accessed February 2019).
126.
Valente, P. 2010. “Census Taking in Europe: How are Population Counted in 2010?” Population and Societies (Paris: Institut National d’Études Démographiques (INED)). No. 467. Available at: https://www.ined.fr/fichier/s_rubrique/19135/pesa467.en.pdf (accessed February 2019).
127.
Van Dalen, H.P., G. Groenewold, and J.J. Schoorl. 2005. “Out of Africa: What Drives the Pressure to Emigrate?” Journal of Population Economics 18: 741–778. Doi: https://doi.org/10.1007/s00148-005-0003-5.
128.
Van der Erf, R. and N. Van der Gaag. 2007. An Iterative Procedure to Revise Available Data in the Double Entry Migration Matrix for 2002, 2003 and 2004 . Discussion Paper, Netherlands Interdisciplinary Demographic Institute, The Hague. Available at: http://mimosa.cytise.be/ (accessed February 2019).
129.
Willekens, F. 1983. “Log-linear Modeling of Spatial Interaction.” Papers of the Regional Science Association 52: 187–205. Doi: https://doi.org/10.1111/j.1435-5597.1983. tb01658.x.
130.
Willekens, F. 1994. “Monitoring International Migration Flows in Europe. Towards a Statistical Data Base Combining Data from Different Sources.” European Journal of Population 10(1): 1–42. Doi: https://doi.org/10.1007/BF01268210.
131.
Willekens, F. 1999. “Modeling approaches to the indirect estimation of migration flows: From entropy to EM.” Mathematical Population Studies 7(3): 239–278. Doi: https://doi.org/10.1080/08898489909525459.
132.
Willekens, F. 2008. “Models of Migration: Observations and Judgements.” In International Migration in Europe. Data, Models and Estimates , edited by J. Raymer and R. Willekens, 117–147. Chichester: Wiley. Doi: https://doi.org/10.1002/9780470985557.ch6.
133.
Willekens, F. 2014. Multistate Analysis of Life Histories with R . Cham: Springer. ISBN: 978-3-319-08382-7. Doi: https://doi.org/10.1007/978-3-319-08383-4.
134.
Willekens, F. 2016a. “Migration Flows: Measurement, Analysis and Modeling.” In International Handbook of Migration and Population Distribution , edited by M. White. International Handbooks of Population 6, 225–241. Dordrecht: Springer. Doi: https://doi.org/10.1007/978-94-017-7282-2_11.
135.
Willekens, F. 2016b. “The Decision to Emigrate: A Simulation Model Based on the Theory of Planned Behaviour.” In Agent-based Modelling in Population Studies: Concepts, Methods and Applications , edited by A. Grow and J. van Bavel, 257–299. Dordrecht: Springer. Doi: https://doi.org/10.1007/978-3-319-32283-4_10.
136.
Willekens, F. and J. Raymer. 2008. “Conclusion.” In International Migration in Europe. Data, Models and Estimates , edited by J. Raymer and F. Willekens, 359–369. Chichester: Wiley. Doi: https://doi.org/10.1002/9780470985557.ch16.
137.
Willekens, F., D. Massey, J. Raymer, and C. Beauchemin. 2016. “International Migration Under the Microscope.” Science 352(6288): 897–899. Doi: https://doi.org/10.1126/science.aaf6545.
138.
Willekens, F., A. Pór, and R. Raquillet. 1981. “Entropy, Multiproportional, and Quadratic Techniques for Inferring Detailed Migration Patterns from Aggregate Data.” IIASA Reports. A Journal of International Applied Systems Analysis 4: 83–124. ISSN 0250-7625. Available at: http://pure.iiasa.ac.at/id/eprint/1561/1/IA-81-401.pdf (accessed February 2019).
139.
Willekens, F., S. Zinn, and M. Leuchter. 2017. “Emigration Rates from Sample Surveys. An Application to Senegal.” Demography 54(6): 2159–2179. Doi: https://doi.org/10.1007/s13524-017-0622-y.
140.
Wiśniowski, A. 2017. “Combining Labour Force Survey Data to Estimate Migration Flows: The Case of Migration from Poland to the UK.” Journal of the Royal Statistical Society A 180(Part 1): 185–202. Doi: https://dx-doi-org.web.bisu.edu.cn/10.1111/rssa.12189.
141.
Wiśniowski, A., J. Bijak, S. Christiansen, J.J. Forster, N. Keilman, J. Raymer, and P.W.F. Smith. 2013. “Utilising Expert Opinion to Improve the Measurement of International Migration in Europe.” Journal of Official Statistics 29(4): 583–607. Doi: https://doi.org/10.2478/jos-2013-0041.
142.
Wiśniowski, A., J.J. Forster, P.W.F. Smith, J. Bijak, and J. Raymer. 2016. “Integrated Modelling of Age and Sex Patterns of European Migration.” Journal of the Royal Statistical Society A 179(4): 1007–1024. Doi: https://dx-doi-org.web.bisu.edu.cn/10.1111/rssa.12177.
143.
Yiu, S., V.T. Farewell, and B.D.M. Tom. 2017. “Exploring the Existence of a Stayer Population with Mover-stayer Counting Process Models: Application to Joint Damage in Psoriatic Arthritis.” Applied Statistics. Series C 66(4): 669–690. Doi: https://doi.org/10.1111/rssc.12187.