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Table 1 Effect of interest on outcomes measured 6 years after graduation

From: Scars of early non-employment for low educated youth: evidence and policy lessons from Belgium

Panel A: Effect of early non-employment in the structural equation:  
   OLS 2SLS
Standard errors a Robust Cluster gp Robust Cluster gp
Outcomes:   (1) (2) (3) (4)
Salaried empl. coeff –0.00169*** –0.00169*** –0.00256 –0.00256
  se (0.00034) (0.00041) (0.00375) (0.00290)
  P-val   0.00019   0.38202
  Bootstrap P-val b   0   0.45646
  Exogeneity test P-val c     0.767
Self-empl. coeff 0.00054* 0.00054 0.00248 0.00248
  se (0.00030) (0.00041) (0.00338) (0.00258)
  P-val   0.19177   0.34175
  Bootstrap P-val   0.18619   0.37437
  Exogeneity test P-val     0.438
Overall empl. coeff –0.00115*** –0.00115*** –0.00008 –0.00008
  se (0.00021) (0.00025) (0.00207) (0.00151)
  P-val   0.00005   0.95655
  Bootstrap P-val   0   0.96697
  Exogeneity test P-val     0.467
Log earnings coeff –0.0269*** –0.0269*** –0.1002** –0.1002***
  se (0.0033) (0.0040) (0.0419) (0.0291)
  P-val   2.51E-08   0.0013
  Bootstrap P-val   0   0.0060
  Exogeneity test P-val     0.00970
Log hours worked coeff –0.0203*** –0.0203*** –0.0723** –0.0723***
  se (0.0024) (0.0029) (0.0307) (0.0207)
  P-val   9.35E-09   0.0011
  Bootstrap P-val   0   0.0060
  Exogeneity test P-val     0.0112
Panel B: Effect of the instrument in the first stage : OLS  
Outcome: Standard errors: Robust Cluster gp   
Early non-empl. coeff 5.4615*** 5.4615***   
  se (1.7273) (1.6848)   
  P-val   0.00230   
  Bootstrap P-val   0.00400   
  F stat   10.51   
  Bootstrap F stat d   9.25   
  1. Standard errors between parentheses. Panel A reports results from estimating β in Eq. (2). β is the effect of one pp increase in \(y^{0}_{it_{1}}\), i.e. the % of hours spent in non-employment in the first two and a half years after graduation relative to potential total hours if one would work full-time during the whole period. For clustered standard errors, we report the P-value and the wild bootstrap P-value. Column 1-2 (3-4) show OLS (2SLS). In 2SLS the provincial unemployment rate at graduation is used as instrument for \(y^{0}_{it_{1}}\). Panel B shows the effect of the instrument on \(y^{0}_{it_{1}}\) in the first stage and the corresponding F statistic
  2. *** p <0.01, ** p <0.05, * p <0.1
  3. aRobust accounts for heteroskedasticity. Clusters are defined by graduation year g and province of residence at graduation p (G=44 clusters)
  4. bComputed according to the wild bootstrap proposed by Davidson and MacKinnon (2010) for 999 repetitions
  5. cWith clustered standard errors, this test is defined as the difference between two Sargan-Hansen statistics: one for the equation where \(y^{0}_{it_{1}}\) is treated as endogenous and one for the equation where \(y^{0}_{it_{1}}\) is treated as exogenous. Under the null that \(y^{0}_{it_{1}}\) is exogenous, the statistic is distributed as χ 2(1)
  6. dBootstrap F statistic is the F statistic corresponding to the bootstrap P-value of the t statistic of the instrument: we rely on the equivalence between F and t distribution: for G=44, t 2(G−1)=F(1,G−1)