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

Fixed effects (unstandardised)

 Constant

.1604***

.1589***

.1568***

 Context level (federal state-years)

  Upper secondary education

−.0021

−.0036

−.0345***

  Dual apprenticeship

−.0042

−.0103*

−.0147⁺

  Vacant jobs

−.0024

−.0022

−.0160*

  Active labour market policy

−.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 \( \left( {\tau_{{u_{0} }}^{2} } \right) \)

<.0000001

<.0000001

<.0000001

 Federal states-year slopes

  Gender \( \left( {\tau_{{u_{1} }}^{2} } \right) \)

  Citizenship \( \left( {\tau_{{u_{6} }}^{2} } \right) \)

<.0000001

<.0000001

 Residuals \( \left( {\sigma_{\varepsilon }^{2} } \right) \)

.0515478

.0515183

.0514585

ρ (intraclass correlation)