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Job Loss and Migration: Do Family Connections Matter?

  • Terhi Maczulskij ORCID logo EMAIL logo
Published/Copyright: July 15, 2024

Abstract

This paper utilizes administrative employer–employee data to analyze the effect of job loss on interregional migration and to study how family connections, related to childhood family members and birth region preferences, shape these location choices. The results reveal that job loss due to establishment closures increases the probability of interregional migration by nearly 80 %. While local family member connections and birth region preferences pose substantial obstacles to moving, they do not necessarily lead to relocation in response to job loss. Instead, displaced workers tend to migrate to non-birth regions where they have no observed family member connections, although higher economic gains in these regions may partly offset the loss of utility resulting from these factors.


Corresponding author: Terhi Maczulskij, ETLA Economic Research, Arkadiankatu 23B, FI-00100 Helsinki, Finland; and IZA Institute of Labor Economics, Schaumburg-Lippe-Strasse 5-9, 53113 Bonn, Germany, E-mail: 

Award Identifier / Grant number: 293120

Funding source: Palkansaajasäätiö

Acknowledgments

The author wishes to thank Hannu Karhunen for his helpful comments. Financial support from the Academy of Finland Strategic Research Council project “Work, Inequality and Public Policy” (number 293120) and Palkansaajasäätiö are gratefully acknowledged.

Appendix A

(Table A1)

Table A1:

Population and unemployment rates in travel-to-work areas in 2019.

Code Name Population Unemployment rate, %
01 Helsinki 1,672,162 8.29
04 Lahti 197,845 13.07
05 Kouvola 89,942 12.58
06 Kotka 83,446 13.93
08 Turku 364,589 9.33
09 Loimaa 19,753 8.65
10 Rauma 50,842 8.25
11 Pori 123,822 11.93
12 Kankaanpää 14,946 10.75
13 Parkano 8,377 9.00
14 Tampere 477,904 9.34
15 Lappeenranta 123,913 12.00
16 Mikkeli 70,316 10.64
17 Savonlinna 45,902 13.47
19 Varkaus 25,639 13.83
20 Kuopio 169,085 10.22
21 Iisalmi 46,885 12.15
22 Joensuu 126,290 13.51
23 Nurmes 9,783 14.65
24 Närpes 10,733 4.21
25 Vaasa 113,865 7.21
26 Seinäjoki 114,424 8,03
27 Alajärvi 14,686 9.58
29 Jämsä 22,845 13.62
30 Jyväskylä 212,150 12.38
33 Kokkola 67,106 7.41
34 Raahe 34,310 9.48
35 Oulu 262,977 11.21
36 Kajaani 54,273 10.68
37 Kemi 54,088 12.75
39 Mariehamn 29,789 3.53
43 Uusikaupunki 24,347 5.85
45 Haapajärvi 9,890 7.83
  1. Numbers are based on data from Statistics Finland and own calculations. The unemployment rate is measured as the share of unemployed from the total workforce within 15–65-year-old individuals in a region.

Table B1:

Covariate balance for the variables for the non-matched and matched samples.

Non-matched data Matched data
Treatment group (displaced workers) (1) Control group (non-displaced workers) (2) t-test Treatment group (displaced workers) (3) Control group (non-displaced workers) (4) t-test
Individual characteristics
 Primary education 0.17 0.16 1.34 0.17 0.17 0.49
 Secondary education 0.61 0.63 −3.11 0.61 0.61 −0.20
 Higher education 0.22 0.21 1.34 0.22 0.22 −0.18
 Age 39.1 40.0 −9.64 39.1 39.1 −0.16
 Female 0.37 0.34 4.16 0.37 0.37 −0.32
 Married or cohabiting 0.50 0.53 −10.79 0.50 0.50 −0.60
 Children <7 years old 0.45 0.43 7.64 0.45 0.45 0.17
 Home ownership 0.69 0.75 −14.63 0.69 0.69 −0.14
 Have migrated before 0.13 0.11 2.64 0.13 0.13 0.12
 Family member in region 0.56 0.57 −0.94 0.56 0.56 −0.02
 Birth region 0.56 0.58 −3.61 0.56 0.56 −0.06
 Annual wages (in euros) 42,404 42,851 −1.34 42,404 42,295 0.91
Moved to another region by b + 2 0.032 0.017 0.032 0.019
Number of observations 51,259 4,699,103 51,259 150,583
  1. Migration status is measured in b + 2 and other variables in b − 1. t-test statistics are for equal sample means between the treatment (displaced) and control (non-displaced) groups.

Table B2:

Covariate balance for the variables for the matched sample: two groups based on residing in or outside their birth region.

Residing outside birth region Residing in birth region
Treatment group (displaced workers) (1) Control group (non-displaced workers) (2) t-test Treatment group (displaced workers) (3) Control group (non-displaced workers) (4) t-test
Individual characteristics
 Primary education 0.16 0.16 −0.79 0.18 0.17 1.28
 Secondary education 0.56 0.55 1.80 0.65 0.66 −1.94
 Higher education 0.28 0.29 −1.07 0.17 0.17 0.73
 Age 39.8 39.8 0.08 38.6 38.6 −0.24
 Female 0.39 0.39 −1.57 0.35 0.35 0.40
 Married or cohabiting 0.52 0.53 −0.36 0.47 0.47 −0.40
 Children <7 years old 0.45 0.45 1.08 0.45 0.45 −0.47
 Home ownership 0.65 0.65 0.41 0.71 0.71 −0.49
 Have migrated before 0.22 0.23 −0.43 0.05 0.05 0.78
 Family member in region 0.30 0.30 −0.01 0.78 0.78 0.03
 Annual wages (in euros) 44,614 44,373 0.49 40,638 40,395 0.72
Moved to another region by b + 2 0.049 0.030 0.018 0.010
Number of observations 22,768 66,816 28,491 83,767
  1. Migration status is measured in b + 2 and other variables in b − 1. t-test statistics are for equal sample means between the treatment (displaced) and control (non-displaced) groups.

(Figure A1)

Figure A1: 
Travel-to-work areas, based on the 2019 classification.
Figure A1:

Travel-to-work areas, based on the 2019 classification.

Appendix B

References

Ai, C., and E. Norton. 2003. “Interaction Terms in Logit and Probit Models.” Economics Letters 80: 123–9. https://doi.org/10.1016/S0165-1765(03)00032-6.Search in Google Scholar

Anderson, L. F., T. Danley, R. Eriksson, and M. Henning. 2020. “Workers’ Participation in Regional Economic Change Following Establishment Closure.” Small Business Economics 54: 589–604. https://doi.org/10.1007/s11187-018-0036-2.Search in Google Scholar

Bratsberg, B., O. Raaum, and K. Røed. 2018. “Job Loss and Immigrant Labor Market Performance.” Economica 85: 124–51. https://doi.org/10.1111/ecca.12244.Search in Google Scholar

Crescenzi, R., N. Holman, and E. Orru. 2017. “Why Do They Return? Beyond the Economic Drivers of Graduate Return Migration.” The Annals of Regional Science 59: 603–27. https://doi.org/10.1007/s00168-016-0762-9.Search in Google Scholar

Dahl, M., and O. Sorenson. 2010a. “The Migration of Technical Workers.” Journal of Urban Economics 67: 33–45. https://doi.org/10.1016/j.jue.2009.09.009.Search in Google Scholar

Dahl, M., and O. Sorenson. 2010b. “The Social Attachment to Place.” Social Forces 89: 633–58. https://doi.org/10.1353/sof.2010.0078.Search in Google Scholar

de Haas, H. 2021. “A Theory of Migration: The Aspirations-Capabilities Framework.” Migration Studies 9: 1–35. https://doi.org/10.1186/s40878-020-00210-4.Search in Google Scholar

De la Roca, J. 2017. “Selection in Initial and Return Migration: Evidence from Moves across Spanish Cities.” Journal of Urban Economics 100: 33–53. https://doi.org/10.1016/j.jue.2017.04.004.Search in Google Scholar

Eriksson, R. H., E. Hane-Weijman, and M. Henning. 2018. “Sectoral and Geographical Mobility of Workers after Large Establishment Cutbacks or Closures.” Environment and Planning A: Economy and Space 50 (5): 1071–91. https://doi.org/10.1177/0308518X18772581.Search in Google Scholar

Eurostat. 2024. Job Vacancy and Unemployment Rates - Beveridge Curve. Kirchberg: Eurostat.Search in Google Scholar

Fackler, D., and L. Rippe. 2016. “Losing Work, Moving Away? Regional Mobility after Job Loss.” Labour 31: 457–79. https://doi.org/10.1111/labr.12106.Search in Google Scholar

Faggian, A., and B. Biagi. 2011. “Editorial: Special Issue on Interregional Migration.” Spatial Economic Analysis 6 (1): 1–3. https://doi.org/10.1080/17421772.2011.542614.Search in Google Scholar

Harris, J., and M. Todaro. 1970. “Migration, Unemployment and Development: A Two-Sector Analysis.” The American Economic Review 60: 126–42.Search in Google Scholar

Huttunen, K., J. Møen, and K. Salvanes. 2018. “Job Loss and Regional Mobility.” Journal of Labor Economics 36: 479–509. https://doi.org/10.1086/694587.Search in Google Scholar

Ilyés, V., I. Boza, L. Lörincz, and R. Eriksson. 2023. “How to Enter High-Opportunity Places? The Role of Social Contracts for Residential Mobility.” Journal of Economic Geography 23: 371–95. https://doi.org/10.1093/jeg/lbac019.Search in Google Scholar

Jewell, S., and A. Faggian. 2014. “Interregional Migration ‘Wage Premia’: The Case of Creative and Science and Technology Graduates in the UK.” In Applied Regional Growth and Innovation Models. Advances in Spatial Science, edited by K. Kourtit, P. Nijkamp, and R. Stimson. Berlin, Heidelberg: Springer.10.1007/978-3-642-37819-5_9Search in Google Scholar

Lundholm, E., J. Garvill, G. Malmberg, and K. Westin. 2004. “Forced or Free Movers? The Motives, Voluntariness and Selectivity of Interregional Migration in the Nordic Countries.” Population, Space and Place 10: 59–72. https://doi.org/10.1002/psp.315.Search in Google Scholar

Maczulskij, T., and P. Böckerman. 2023. “Losing a Job and (Dis)incentives to Move: Interregional Migration in Finland.” European Urban and Regional Studies 30: 430–45. https://doi.org/10.1177/09697764231186746.Search in Google Scholar

Meekes, J., and W. Hassink. 2019. “The Role of the Housing Market in Workers’ Resilience to Job Displacement after Firm Bankruptcy.” Journal of Urban Economics 109: 41–65. https://doi.org/10.1016/j.jue.2018.11.005.Search in Google Scholar

Mulder, C., and G. Malmberg. 2014. “Local Ties and Family Migration.” Environment and Planning A 46: 2195–211. https://doi.org/10.1068/a130160p.Search in Google Scholar

Mulder, C., E. Lundholm, and G. Malmberg. 2020. “Young Adults’ Migration to Cities in Sweden: Do Siblings Pave the Way?” Demography 57: 2221–44. https://doi.org/10.1007/s13524-020-00934-z.Search in Google Scholar

Neffke, F., A. Otto, and C. Hidalgo. 2018. “The Mobility of Displaced Workers: How the Local Industry Mix Affects Job Search.” Journal of Urban Economics 108: 124–40. https://doi.org/10.1016/j.jue.2018.09.006.Search in Google Scholar

Pekkala, S. 2003. “Migration Flows in Finland: Regional Differences in Migration Determinants and Migrant Types.” International Regional Science Review 26 (4): 446–82. https://doi.org/10.1177/0160017603259861.Search in Google Scholar

Received: 2023-06-16
Accepted: 2024-06-23
Published Online: 2024-07-15

© 2024 Walter de Gruyter GmbH, Berlin/Boston

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