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Table 2 Linear multilevel modelling results for the NEET probability of youth aged from 15–19 years (J = 63; n = 16,942)

From: Small differences matter: how regional distinctions in educational and labour market policy account for heterogeneity in NEET rates

Variables Model 1 Model 2 Model 3 Model 4 Model 5
Fixed effects (unstandardised)
 Constant .0558*** .0543*** .1604*** .1589*** .1568***
 Context level (federal state-years)
  Upper secondary education   −.0022 −.0021 −.0036 −.0345***
  Dual apprenticeship   −.0110*** −.0042 −.0103* −.0147+
  Vacant jobs   .0006 −.0024 −.0022 −.0160*
  Active labour market policy   −.0058** −.0037+ −.0023 .0053
 Individual level
  Gender (1 = female)    −.0080* −.0048 −.0081*
  More than 30,000 inhabitants    Reference group Reference group Reference group
  5001 to 30,000 inhabitants    −.0014 −.0014 −.0012
  Up to 5000 inhabitants    −.0126* −.0124* −.0123*
  Country of birth (1 = Austria)    −.0270** −.0268** −.0259**
  Citizenship (1 = Austria)    −.0852*** −.0856*** −.0822***
  Third quarter (1 = yes)    .0140** .0141** .0144**
  Motherhood (1 = yes)    .1820*** .1825*** .1806***
 Cross-level interactions
  Gender * upper secondary education     .0029  
  Gender * dual apprenticeship     .0123*  
  Gender * vacant jobs     −.0004  
  Gender * active labour market policy     −.0028  
  Citizenship * upper secondary education      .0352***
  Citizenship * dual apprenticeship      .0114
  Citizenship * vacant jobs      .0147*
  Citizenship * active labour market policy      −.0100
Random effects (variance components)
 Federal states-year intercept \( \left( {\tau_{{u_{0} }}^{2} } \right) \) .0001597 .0000465 <.0000001 <.0000001 <.0000001
 Federal states-year slopes
  Gender \( \left( {\tau_{{u_{1} }}^{2} } \right) \)      
  Citizenship \( \left( {\tau_{{u_{6} }}^{2} } \right) \)     <.0000001 <.0000001
 Residuals \( \left( {\sigma_{\varepsilon }^{2} } \right) \) .0531975 .0532090 .0515478 .0515183 .0514585
ρ (intraclass correlation) .0029924**     
  1. +p < .1
  2. * p < .05
  3. ** p < .01
  4. *** p < .001