Skip to main content

Table 2 Categorical Principal Component Analysis – Two-dimensional solution

From: The architecture of national boundary regimes: mapping immigration and citizenship policies in 23 democracies 1980–2010

Variables

Dimension IRO

Dimension CRI

Labour entry

.79

−.23

Labour stay

.80

−.20

Family entry

.80

.11

Family stay

.81

.18

Asylum entry

.72

−.07

Asylum stay

.76

.10

Strength of jus soli

−.17

.83

Residence duration requirement (reversed)

.05

.84

Multiple citizenship toleration

.06

.57

Further naturalisation requirements

−.02

.65

Eigenvalue

3.69

2.30

Explained variance

36.86

22.97

Cronbach’s alpha

.81

.63

Model Eigenvalue

5.98

 

Model explained variance

59.83

 

Model Cronbach’s alpha

.93

 
  1. N = 713 country-years; principal component analysis for categorical data (CATPCA) using selected policy components measuring the openness of immigration regimes according to IMPIC (Helbling et al. 2017) and the policy components of CITRIX (original dataset based on temporal expansion of selected items from MIPEX and based on the data by Stadlmair (2017) and Fitzgerald et al. (2014) and DEMIG and GLOBALCIT) measuring the inclusiveness of citizenship regimes variable principal normalisation; solution with VARIMAX rotation and Kaiser normalisation; entries are component loadings and model parameters; component loadings > 0.5 bold