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<datacite:identifier identifierType="URL">https://door.donau-uni.ac.at/o:5685</datacite:identifier>

  
<datacite:titles>
  
<datacite:title xml:lang="en">Innovations in methodological approaches to estimate irregular migrant stocks and flows</datacite:title>

  
</datacite:titles>

  
<datacite:creators>
  
<datacite:creator>
  
<datacite:creatorName nameType="Personal">Rodríguez-Sánchez, Alejandra</datacite:creatorName>

  
<datacite:givenName>Alejandra</datacite:givenName>

  
<datacite:familyName>Rodríguez-Sánchez</datacite:familyName>

  
<datacite:affiliation>University of Potsdam</datacite:affiliation>

  
</datacite:creator>

  
<datacite:creator>
  
<datacite:creatorName nameType="Personal">Tjaden, Jasper</datacite:creatorName>

  
<datacite:givenName>Jasper</datacite:givenName>

  
<datacite:familyName>Tjaden</datacite:familyName>

  
<datacite:nameIdentifier nameIdentifierScheme="ORCID" schemeURI="https://orcid.org/">0000-0002-5054-3535</datacite:nameIdentifier>

  
<datacite:affiliation>University of Potsdam</datacite:affiliation>

  
</datacite:creator>

  
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<dc:language>eng</dc:language>

  
<dc:description xml:lang="en">Key points

• This chapter builds on Rodríguez-Sánchez and Tjaden (2023), who reviewed the main
methods for estimating irregular migrant stocks and flows, spanning both established and
more experimental approaches.

• Measuring irregular migration remains a fundamental challenge: the population is difficult
to observe, and even widely used methods such as residual estimation or capture–recapture
provide only partial pictures.

• Traditional techniques continue to form the backbone of the field, but improvements have
often come from incremental innovations, such as using mortality data to refine life-course
approaches, or expanding residual methods with large government databases and machine
learning.

• More novel directions, such as exploiting consular registers, driver’s licence data, or online
search behaviour, show promise in filling gaps, though these remain context-specific and
experimental.</dc:description>

  
<datacite:subjects>
  
<datacite:subject xml:lang="en">Estimation methods</datacite:subject>

  
<datacite:subject xml:lang="en">Irregular migration stocks and flows</datacite:subject>

  
<datacite:subject xml:lang="en">Innovative data sources</datacite:subject>

  
</datacite:subjects>

  
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<datacite:alternateIdentifiers>
  
<datacite:alternateIdentifier alternateIdentifierType="DOI">10.48341/g31s-vq79-05</datacite:alternateIdentifier>

  
</datacite:alternateIdentifiers>

  
<datacite:relatedIdentifiers>
  
<datacite:relatedIdentifier relatedIdentifierType="URL" relationType="IsPartOf">https://door.donau-uni.ac.at/o:5698</datacite:relatedIdentifier>

  
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<dc:format>application/pdf</dc:format>

  
<citationStartPage>65</citationStartPage>

  
<citationEndPage>74</citationEndPage>

  
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<datacite:size>1.49 MB</datacite:size>

  
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<datacite:dates>
  
<datacite:date dateType="Issued">2025-09-30</datacite:date>

  
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