Migration to secure future employment – how do workplace closures affect the geography of the workforce?

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Thispaper aims to investigate and identify how displaced workers have differentmigration patterns depending on the geographical area they live in. Based on acategorization of Danish municipalities into Urban, Intermediate and Rural thisstudy analyzes how the workforce in rural areas react compared to the workforce in urban areas when experiencing a layoff due to business closures. Mostcountries in the western hemisphere are experiencing migration flows from therural towards urban areas these years. Denmark is no exception in this respect.A major reason for this development is a growing concentration of economicactivities in urban areas partly due to uncompetitive industrial structures inmany rural regions (Hansen & Winther, 2012; Eriksson & Hansen, 2013).Relative to the rest of EU, Denmark has experienced the largest movement fromrural to urban areas in recent years. Today, 22 per cent of the Danishpopulation live in metropolitan areas. This is 6 per cent more than in 2007(KL, 2014). Several reasons may exist as to why people move toward urban areas.In many cases lack of job opportunities due to business closures has started avicious spiral in peripheral areas making these regions less attractive toreside in compared to regions that has denser labour markets. By employing fullpopulation Danish micro data including information on individuals’ workplace,residence, level of education, income, family situation etc. this studyidentify employees in workplaces that have closed down in the period 2007-2011and follow these displaced people in a two year period. Thereby the data allowsus to model the relation between individual characteristics, migration,reemployment, education decisions and geography due to changes in employmentstatus caused by a business closure. Looking at migration patterns generated bythe same type of shock at the same time in different regions, that is businessclosures registered yearly from 2007 to 2011, we can identify the differencesin migration and employment patterns across different categories of regions bylooking at the same kind of supply shock in the different regions. We model theemployment flow after displacement as an outcome of a probability model withfour possible states. The different states are unemployed, employed, ineducation and others (e.g. retired, sick pay). Due to the fact that workplace,region and individual characteristics are annual a multinomial logit model isapplied. The findings suggest that the majority of people are reemployed aftera business closure, and that the displaced workers tend to get reemployed withinthe neighboring regions to where they reside in. Findings also indicate thatreemployment and migration from rural areas are not positive related comparedto other types of regions. Moreover, the findings suggest that youngerdisplaced individuals have a tendency to migrate towards urban areas to starteducation. This suggests that for young displaced individuals migration may bedue to education as a way to upskill and thereby secure job opportunities inthe future. 
Antal sider1
StatusUdgivet - 2016
Begivenhed56th ERSA Congress - Cities & Regions: Smart, Sustainable, Inclusive? - Wien, Østrig
Varighed: 23 aug. 201626 aug. 2016


Konference56th ERSA Congress - Cities & Regions

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