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Migration Systems in Europe: Evidence From Harmonized Flow Data

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Demography

Abstract

Empirical tests of migration systems theory require consistent and complete data on international migration flows. Publicly available data, however, represent an inconsistent and incomplete set of measurements obtained from a variety of national data collection systems. We overcome these obstacles by standardizing the available migration reports of sending and receiving countries in the European Union and Norway each year from 2003–2007 and by estimating the remaining missing flows. The resulting harmonized estimates are then used to test migration systems theory. First, locating thresholds in the size of flows over time, we identify three migration systems within the European Union and Norway. Second, examining the key determinants of flows with respect to the predictions of migration systems theory, our results highlight the importance of shared experiences of nation-state formation, geography, and accession status in the European Union. Our findings lend support to migration systems theory and demonstrate that knowledge of migration systems may improve the accuracy of migration forecasts toward managing the impacts of migration as a source of social change in Europe.

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Notes

  1. The methodology and estimates are available online (www.nidi.knaw.nl/en/projects/230211/).

  2. We use the term harmonize to mean both standardization of available migration data and estimation of the remaining missing flows. We distinguish these and the methods associated with each throughout this article.

  3. 420 = 15 sending countries × 14 receiving countries × 2 reports per flow (i.e., sender and receiver).

  4. Retrieved online (http://appsso.eurostat.ec.europa.eu/nui/show.do?dataset=migr_imm5prv&lang=en and http://appsso.eurostat.ec.europa.eu/nui/show.do?dataset=migr_emi3nxt&lang=en).

  5. For emigration flows from Country A to C, D, E, and F, the standardized figures are 20 × 1.33 = 27, 175 × 1.33 = 233, 35 × 1.33 = 47, and 40 × 1.33 = 53, respectively. The standardized figures for Country B to C, D, E, and F are 25 × 1.25 = 31, 40 × 1.25 = 50, 65 × 1.25 = 81, and 100 × 1.25 = 125, respectively.

  6. The standardized flows are 55 × 1.05 = 58, 65 × 1.05 = 68, and 100 × 1.05 = 105, respectively.

  7. The standardized flows are 90 × 1.03 = 93, 75 × 1.03 = 77, and 45 × 1.03 = 46, respectively.

  8. Nordic countries: Denmark, Finland, Norway, and Sweden. Non-Nordic countries with reliable data: Austria, Germany, Netherlands, and Spain. Non-Nordic countries with semi-reliable data: Cyprus, Czech Republic, Italy, Latvia, Lithuania, Luxembourg, Poland, Slovakia, Slovenia, and the United Kingdom. Non-Nordic countries with unreliable data: Ireland, Portugal, and Romania (emigration only). Countries with missing data: Belgium, Bulgaria, Estonia, France, Greece, Hungary, and Malta.

  9. The x and y coordinates are (95, 178), (105, 196), and (143, 268) at Times 1, 2, and 3, respectively.

  10. In our analysis, 1 ≤ k ≤ 4 because pairs of sending and receiving countries with partially complete data have between one and four years of valid data from 2003 to 2007.

  11. \( {126 } = { 115}\, \times \,\,\left[ {{{{0.0{49}}} \left/ {{\left( {0.0{49 } + { }0.0{12}} \right)}} \right.}} \right] + { 173}\,\, \times \,\,\left[ {{{{0.0{12}}} \left/ {{\left( {0.0{49 } + { }0.0{12}} \right)}} \right.}} \right] \).

  12. In our analysis, the maximum value of k is 125.

  13. To save space, we show only the results of these calculations, which can be replicated by expanding the equation in Step 2. For example, the missing flow from Country F to E at Time 1 is estimated as follows: \( {148 } = { 118} \times \left[ {{{{0.0{56}}} \left/ {{\left( {0.0{56 } + { }0.0{14 } + { }0.00{5 } + { }0.00{4}} \right)}} \right.}} \right]{ } + { 13}0 \times \left[ {{{{0.0{14}}} \left/ {{\left( {0.0{56 } + { }0.0{14 } + { }0.00{5 } + { }0.00{4}} \right)}} \right.}} \right]{ } + { 45}0 \times \left[ {{{{0.00{5}}} \left/ {{\left( {0.0{56 } + { }0.0{14 } + { }0.00{5 } + { }0.00{4}} \right)}} \right.}} \right]{ } + { 263} \times \left[ {{{{0.00{4}}} \left/ {{\left( {0.0{56 } + { }0.0{14 } + { }0.00{5 } + { }0.00{4}} \right)}} \right.}} \right] \).

  14. Abel (2010) and Poulain (1993, 1999) developed harmonized migration estimates, but for fewer sending and receiving countries.

  15. N Y = 3,779 = 28 sending countries × 27 receiving countries × 5 years of data – 1 flow in cluster X.

  16. 3,760 = 28 sending countries × 27 receiving countries × 5 years of data – 20 zero flows.

  17. The Calinski Index for the three-cluster solution is 6,743.92; the Duda-Hart Index and its corresponding pseudo t-squared ratio are 0.387 and 443.80, respectively. Relative to a four-cluster (or higher-cluster) solution, with values of 4,634.51 on the Calinski Index and 0.335 and 3,252.41 for the Duda-Hart Index and pseudo t-squared ratio, respectively, the stopping rules employed suggest three optimal clusters (Milligan and Cooper 1985; Rabe-Hesketh and Everett 2006).

  18. \( R_{{MARG}}^2 = 1 - \frac{{\sum\limits_{{t = 1}}^T {\sum\limits_{{i = 1}}^n {\mathop{{\left( {\mathop{Y}\nolimits_{{it}} - \mathop{{\hat{Y}}}\nolimits_{{it}} } \right)}}\nolimits^2 } } }}{{\sum\limits_{{t = 1}}^T {\sum\limits_{{i = 1}}^n {\mathop{{\left( {\mathop{Y}\nolimits_{{it}} - \overline Y } \right)}}\nolimits^2 } } }} \), where \( \bar{Y} = \frac{1}{{nT}}\sum\limits_{{t = 1}}^T {\sum\limits_{{i = 1}}^n {\mathop{Y}\nolimits_{{it}} } } \).

  19. \( 0.{7 } = { 1}00 \times \left( {{{e}^{{0.00{7}}}}-{ 1}} \right);{ 1}0.{8 } = { 1}00 \times \left( {{{e}^{{0.{1}0{3}}}}-{ 1}} \right) \).

  20. \( -{5}.{8 } = { 1}00 \times \left( {{1}.{1}{{0}^{{ - 0.{622}}}}-{ 1}} \right) \).

  21. Recall that the MIMOSA project used covariate information, including shared language family, to estimate missing flows (Raymer and Abel 2008; Raymer et al. 2011).

  22. A summary of the IMEM is available online (http://www.norface.org/migration12.html).

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Acknowledgments

Jack DeWaard is supported by NICHD Training Grant T32-HD07014 and Center Grant R24-HD047873 to the Center for Demography and Ecology at the University of Wisconsin–Madison. James Raymer received support from the ESRC Research Centre for Population Change (Grant Reference RES-625-28-0001). The authors acknowledge the MIgration MOdeling for Statistical Analysis (MIMOSA) project in providing harmonized flow data for comparison, and comments from Theodore P. Gerber, Katherine J. Curtis, Jenna Nobles, Mary M. Kritz, Douglas T. Gurak, Joel E. Cohen, Stewart Tolnay, and three anonymous reviewers. Previous versions of this article were presented at the annual meeting of the Population Association of America on April 15, 2010 and the Integrated Modeling of European Migration (IMEM) workshop on May 27, 2011.

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Authors and Affiliations

  1. Department of Sociology, Center for Demography and Ecology, University of Wisconsin–Madison, 8128 William H. Sewell Hall, 1180 Observatory Drive, Madison, WI, 53706, USA

    Jack DeWaard

  2. Department of Sociology, Center for Demography and Ecology, University of Wisconsin–Madison, Madison, WI, USA

    Keuntae Kim

  3. Division of Social Sciences, University of Southampton, Southampton, England

    James Raymer

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Correspondence to Jack DeWaard.

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Table 4 Data descriptions, sources, and variable names
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DeWaard, J., Kim, K. & Raymer, J. Migration Systems in Europe: Evidence From Harmonized Flow Data. Demography 49, 1307–1333 (2012). https://doi.org/10.1007/s13524-012-0117-9

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