Date: 2024
Type: Article
Last place aversion, labour market competition or welfare state model? : explaining anti-immigrant sentiment in Hungary with a conjoint experiment
Political research exchange, 2024, Vol. 6, No. 1, OnlineFirst
FARKAS, Attila, KOVAREK, Dániel, FARKAS, Eszter, Last place aversion, labour market competition or welfare state model? : explaining anti-immigrant sentiment in Hungary with a conjoint experiment, Political research exchange, 2024, Vol. 6, No. 1, OnlineFirst
- https://hdl.handle.net/1814/77033
Retrieved from Cadmus, EUI Research Repository
Much ink has been spilled to explain how the relative socio-economic position of natives and immigrants might shape anti-immigrant sentiment. However, little effort has been made to pit three competing theories: last place aversion, labour market competition and the welfare state model directly against each other, despite their often-times contradicting implications. This paper tests these alternative theories in Hungary, where the 2015 migration crisis has catapulted a previously hardly salient topic into the forefront of issues on the political agenda. Utilizing a choice-based conjoint experiment, administered on a nationally representative sample of voting-age Hungarians in Spring 2021, aforementioned hypotheses are tested in a country known for its hardline stance on migration. Results suggest fears related to welfare exploits might be the most plausible explanation for widespread anti-immigrant sentiment in the Hungarian public, as the less education fictive refugee profiles showcased, the less likely respondents were to admit them. Contrarily, no evidence corroborating worries associated with labour market competition or last place aversion was found. Future research could explore whether skills mismatch makes natives less wary of labour market competition, as well as the extent to which the 2022 Russian invasion of Ukraine altered Hungarians' attitudes.
Additional information:
Published online: 27 June 2024
Cadmus permanent link: https://hdl.handle.net/1814/77033
Full-text via DOI: 10.1080/2474736X.2024.2367996
ISSN: 2474-736X
Publisher: Taylor & Francis
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