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[journal article]

dc.contributor.authorVilerts, Karlisde
dc.contributor.authorKrasnopjorovs, Olegsde
dc.contributor.authorBrekis, Edgarsde
dc.date.accessioned2019-03-20T12:38:55Z
dc.date.available2019-03-20T12:38:55Z
dc.date.issued2017de
dc.identifier.issn2082-6737de
dc.identifier.urihttps://www.ssoar.info/ssoar/handle/document/61836
dc.description.abstractWe employ EU-SILC micro data for Latvia to study how returns to education changed during the economic crisis of 2008-2009 and afterwards. We found that returns to education increased significantly during the crisis and decreased slightly during the subsequent economic recovery. The counter-cyclical effect was evident in nearly all population groups. After the crisis, education became more associated than before with a longer working week and a higher employment probability. Furthermore, we show that returns to education in Latvia are generally higher in the capital city and its suburbs than outside the capital city region, as well as for citizens of Latvia than for resident non-citizens and citizens of other countries, but lower for males and young people. Wage differential models reveal a relatively large wage premium for higher education and a rather small one for secondary education. Estimates obtained with instrumental variable (IV) models significantly exceed the OLS estimates.de
dc.languageende
dc.subject.ddcWirtschaftde
dc.subject.ddcEconomicsen
dc.subject.otherreturns to education; Mincer coefficient; wage differentials model; higher education wage premium; instrumental variablesde
dc.titleReturns to Education During and After the Economic Crisis: Evidence from Latvia 2006-2012de
dc.description.reviewbegutachtet (peer reviewed)de
dc.description.reviewpeer revieweden
dc.source.journalComparative Economic Research
dc.source.volume20de
dc.publisher.countryPOL
dc.source.issue1de
dc.subject.classozArbeitsmarktforschungde
dc.subject.classozLabor Market Researchen
dc.subject.thesozLettlandde
dc.subject.thesozLatviaen
dc.subject.thesozWirtschaftskrisede
dc.subject.thesozeconomic crisisen
dc.subject.thesozHochschulbildungde
dc.subject.thesozuniversity level of educationen
dc.subject.thesozLohnde
dc.subject.thesozwageen
dc.subject.thesozLohnhöhede
dc.subject.thesozwage levelen
dc.subject.thesozMessungde
dc.subject.thesozmeasurementen
dc.subject.thesozEinkommensunterschiedde
dc.subject.thesozdifference in incomeen
dc.subject.thesozökonomisches Modellde
dc.subject.thesozeconomic modelen
dc.subject.thesozBerufserfahrungde
dc.subject.thesozprofessional experienceen
dc.subject.thesozgeschlechtsspezifische Faktorende
dc.subject.thesozgender-specific factorsen
dc.rights.licenceCreative Commons - Namensnennung, Nicht kommerz., Keine Bearbeitung 3.0de
dc.rights.licenceCreative Commons - Attribution-Noncommercial-No Derivative Works 3.0en
internal.statusformal und inhaltlich fertig erschlossende
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dc.type.stockarticlede
dc.type.documentZeitschriftenartikelde
dc.type.documentjournal articleen
dc.source.pageinfo133-157de
internal.identifier.classoz20101
internal.identifier.journal1472
internal.identifier.document32
internal.identifier.ddc330
dc.identifier.doihttps://doi.org/10.1515/cer-2017-0008de
dc.description.pubstatusVeröffentlichungsversionde
dc.description.pubstatusPublished Versionen
internal.identifier.licence19
internal.identifier.pubstatus1
internal.identifier.review1
dc.description.miscFDBde
internal.dda.referenceexcel-database-6@@journal article%%92
ssoar.urn.registrationfalsede


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