Back to Search
Start Over
Outlier analysis: Natural resources and immigration policy
- Source :
- PLoS ONE, Vol 17, Iss 1, p e0261533 (2022), PLoS ONE
- Publication Year :
- 2022
- Publisher :
- Public Library of Science (PLoS), 2022.
-
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.
- Subjects :
- Economics
Science Policy
Political Science
Science
Materials Science
Social Sciences
Public Policy
Research and Analysis Methods
Biochemistry
Geographical Locations
Mathematical and Statistical Techniques
Natural Resources
parasitic diseases
Statistical Methods
Labor Mobility
Least-Squares Analysis
Materials
Human Capital
Multidisciplinary
Norway
Statistics
Biology and Life Sciences
Emigration and Immigration
Models, Theoretical
Lipids
Democracy
Europe
Petroleum
Labor Economics
People and Places
Physical Sciences
Regression Analysis
Medicine
Economics of Migration
Organic Materials
Oils
Mathematics
Research Article
Subjects
Details
- Language :
- English
- ISSN :
- 19326203
- Volume :
- 17
- Issue :
- 1
- Database :
- OpenAIRE
- Journal :
- PLoS ONE
- Accession number :
- edsair.doi.dedup.....43d0a30bbb75cdbc0f45dc3059963e63