Cargando…

Outlier analysis: Natural resources and immigration policy

This replication underlines the importance of outlier diagnostics since many researchers have long neglected influential observations in OLS regression analysis. In his article, entitled “Primary Resources, Secondary Labor,” Shin finds that advanced democracies with increased natural resource wealth...

Descripción completa

Detalles Bibliográficos
Autor principal: Choi, Seung-Whan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8758109/
https://www.ncbi.nlm.nih.gov/pubmed/35025888
http://dx.doi.org/10.1371/journal.pone.0261533
_version_ 1784632831850315776
author Choi, Seung-Whan
author_facet Choi, Seung-Whan
author_sort Choi, Seung-Whan
collection PubMed
description This replication underlines the importance of outlier diagnostics since many researchers have long neglected influential observations in OLS regression analysis. In his article, entitled “Primary Resources, Secondary Labor,” Shin finds that advanced democracies with increased natural resource wealth, particularly from oil and natural gas production, are more likely to restrict low-skill immigration policy. By performing outlier diagnostics, this replication shows that Shin’s findings are a statistical artifact. When one outlying country, Norway, is removed from the sample data, I observe almost no significant and negative relationship between oil wealth and immigration policy. When two outlying countries are excluded, the effect of oil wealth completely disappears. Robust regression analysis, a widely used remedial method for outlier problems, confirms the results of my outlier diagnostics.
format Online
Article
Text
id pubmed-8758109
institution National Center for Biotechnology Information
language English
publishDate 2022
publisher Public Library of Science
record_format MEDLINE/PubMed
spelling pubmed-87581092022-01-14 Outlier analysis: Natural resources and immigration policy Choi, Seung-Whan PLoS One Research Article This replication underlines the importance of outlier diagnostics since many researchers have long neglected influential observations in OLS regression analysis. In his article, entitled “Primary Resources, Secondary Labor,” Shin finds that advanced democracies with increased natural resource wealth, particularly from oil and natural gas production, are more likely to restrict low-skill immigration policy. By performing outlier diagnostics, this replication shows that Shin’s findings are a statistical artifact. When one outlying country, Norway, is removed from the sample data, I observe almost no significant and negative relationship between oil wealth and immigration policy. When two outlying countries are excluded, the effect of oil wealth completely disappears. Robust regression analysis, a widely used remedial method for outlier problems, confirms the results of my outlier diagnostics. Public Library of Science 2022-01-13 /pmc/articles/PMC8758109/ /pubmed/35025888 http://dx.doi.org/10.1371/journal.pone.0261533 Text en © 2022 Seung-Whan Choi https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Choi, Seung-Whan
Outlier analysis: Natural resources and immigration policy
title Outlier analysis: Natural resources and immigration policy
title_full Outlier analysis: Natural resources and immigration policy
title_fullStr Outlier analysis: Natural resources and immigration policy
title_full_unstemmed Outlier analysis: Natural resources and immigration policy
title_short Outlier analysis: Natural resources and immigration policy
title_sort outlier analysis: natural resources and immigration policy
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8758109/
https://www.ncbi.nlm.nih.gov/pubmed/35025888
http://dx.doi.org/10.1371/journal.pone.0261533
work_keys_str_mv AT choiseungwhan outlieranalysisnaturalresourcesandimmigrationpolicy