Migration and employment after an economic shock: regional characteristics and migration patterns

ABSTRACT

This study addresses the migration dynamics of workers after their workplace has closed. It analyses to what extent migration responses differ between regions with different characteristics for individuals who have been laid off due to a workplace closure. The study employs full micro-panel data for the Danish population between 2007 and 2015 and finds the following: (1) workers laid off due to a workplace closure in non-urban regions are less likely to migrate and find employment than laid-off workers from urban regions; however, (2) young laid-off individuals from non-urban areas have a greater tendency to migrate in pursuit of education.

KEYWORDS:

• migration
• urbanization
• firm closure
• labour
• education

JEL:

• J6
• O18
• R11
• R12

DISCLOSURE STATEMENT

No potential conflict of interest was reported by the authors.

Notes

1. We use the logistic regression because the outcome variable in the regression is dichotomous, that is, 0 or 1 (migration versus staying). Second, the logistic model fits the data better than the linear model because the probabilities of laid-off workers migrating have a very wide range in our data; in particular, a lot of the predicted probabilities are < 0.2 and close to 0. Thus, the alternative linear probability model may yield predicted probabilities that are > 1 or < 0, and these out-of-bounds predicted probabilities are undesirable.

2. Breen et al. (2014) point out that the interpretation and comparison of interaction terms in non-linear probability models (LPMs) can be problematic. Therefore, we test our result using an OLS model.

3. In Denmark, the public sector accounted for around 30–35% of full-time employees during the period 2007–15, and the share of workers in the public sector is roughly the same across municipalities. Some public workplaces do not have a specific address within the municipality. Thus, for these public workplaces we cannot define closures, workplace characteristics, etc.

4. A model has been tested that also includes workplaces with fewer than 10 employees. The results do not differ significantly from the model presented in this study.

5. These are treated the same as those who are laid off once.

6. See Figure A2 in Appendix A in the supplemental data online for the distribution of the different municipality categories.

7. Municipality size in 2013: 438 km² (average), 1470 km² (maximum), 8 km² (minimum) and 372 km² (standard variation). Municipality density in 2013: 589 residents per km² (average), 12,526 residents per km² (maximum), 16 residents per km² (minimum) and 1544 residents per km² (standard variation).

8. The public sector accounts for approximately 33% of all employed in Denmark.

9. Workers in farming only represent 0.5% of the entire sample. In addition, the later results on individual and workplace control characteristics, where we include employment during migration, are not significantly different from column 3.

10. These LMAs are divided into 25 regions, based on Danish commuting areas (80% of the people living in the area work there as well).