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Outlier analysis: Natural resources and immigration policy

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  • Seung-Whan Choi

Abstract

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.

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  • Seung-Whan Choi, 2022. "Outlier analysis: Natural resources and immigration policy," PLOS ONE, Public Library of Science, vol. 17(1), pages 1-13, January.
    • Handle: RePEc:plo:pone00:0261533
    DOI: 10.1371/journal.pone.0261533
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