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Table 8 Complete estimations on binary outcomes

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

  Second stage  
Outcomes: a Salaried empl. Self-empl. Overall empl.
  OLS 2SLS OLS 2SLS OLS 2SLS
Clustered standard errors: gp gp gp gp gp gp
  (1) (2) (3) (4) (5) (6)
Early non-empl. –0.00169*** –0.00256 0.00054 0.00248 –0.00115*** –0.00008
  (0.00041) (0.00290) (0.00041) (0.00258) (0.00025) (0.00151)
UR_pe6 0.00481 0.00404 0.01081 0.01253 0.01562 0.01657*
  (0.02385) (0.02209) (0.01947) (0.01765) (0.01020) (0.00999)
lin_grad_year –0.00253 –0.00009 –0.01367 –0.01911 –0.01621 –0.01920
  (0.03120) (0.03028) (0.02544) (0.02343) (0.01397) (0.01340)
lin_grad_year |trend>3 0.02993 0.02680 0.00338 0.01032 0.03331* 0.03712**
  (0.04020) (0.04043) (0.03029) (0.02903) (0.01832) (0.01813)
lin_grad_year |trend>6 –0.01720 –0.01695 0.01884 0.01829 0.00164 0.00134
  (0.02568) (0.02477) (0.02503) (0.02252) (0.01457) (0.01375)
d_province2 –0.22288** –0.22144** 0.17666* 0.17347** –0.04621 –0.04797
  (0.09844) (0.09548) (0.09049) (0.08719) (0.04174) (0.03996)
d_province3 –0.17150*** –0.18038*** 0.13845** 0.15820** –0.03304 –0.02218
  (0.06193) (0.06407) (0.06588) (0.06577) (0.03720) (0.04285)
d_province4 –0.11409** –0.11292** 0.10736** 0.10477** –0.00673 –0.00816
  (0.04892) (0.04910) (0.04459) (0.04794) (0.02450) (0.02611)
d_province5 0.04132 0.04158 –0.06171 –0.06229 –0.02039 –0.02071
  (0.06183) (0.06032) (0.04557) (0.04483) (0.03418) (0.03449)
lin_calend_year_prov2 0.01976 0.01966 –0.01544 –0.01521 0.00432 0.00445
  (0.01597) (0.01524) (0.01253) (0.01214) (0.00565) (0.00651)
lin_calend_year_prov3 –0.00496 –0.00387 0.00501 0.00259 0.00005 –0.00128
  (0.01207) (0.01140) (0.01565) (0.01376) (0.00716) (0.00690)
lin_calend_year_prov4 0.01299 0.01231 –0.01369 –0.01217 –0.00070 0.00014
  (0.01118) (0.01157) (0.00964) (0.01055) (0.00642) (0.00679)
lin_calend_year_prov5 –0.00608 –0.00602 0.01656 0.01642* 0.01048** 0.01041**
  (0.01074) (0.01027) (0.01012) (0.00967) (0.00471) (0.00491)
avg_UR_pe3-6 –0.08309** –0.08489** 0.03333 0.03733 –0.04976* –0.04756*
  (0.04062) (0.04005) (0.03418) (0.03230) (0.02622) (0.02516)
Min_UR_pe0-6 –0.01193 –0.01089 0.00452 0.00222 –0.00741 –0.00867
  (0.06247) (0.05970) (0.05849) (0.05672) (0.02769) (0.02854)
Birth cohort76 0.00488 –0.00741 0.01471 0.04204 0.01959 0.03462
  (0.04397) (0.06402) (0.03588) (0.05434) (0.02535) (0.03517)
Birth cohort78 0.02309 0.01743 –0.00086 0.01173 0.02223 0.02916
  (0.03666) (0.04407) (0.03059) (0.03645) (0.01745) (0.02152)
live in single-parent –0.00309 0.00220 –0.03561 –0.04736 –0.03870 –0.04516
  (0.05525) (0.05471) (0.05233) (0.05472) (0.03217) (0.03371)
Not live with parents 0.02521 0.02631 –0.01502 –0.01748 0.01019 0.00883
  (0.02900) (0.02995) (0.02753) (0.03031) (0.01581) (0.01592)
HH members aged 0–11 –0.00246 –0.00124 0.00596 0.00325 0.00350 0.00201
  (0.01217) (0.01251) (0.01277) (0.01265) (0.00574) (0.00627)
HH members aged 12–17 0.02291* 0.02265* –0.01252 –0.01196 0.01039 0.01070
  (0.01185) (0.01173) (0.01041) (0.01069) (0.00709) (0.00683)
HH members aged 18–29 0.00009 0.00240 0.00374 –0.00139 0.00384 0.00101
  (0.01152) (0.01355) (0.01034) (0.01150) (0.00604) (0.00688)
HH members aged 30–64 –0.01697 –0.01752 –0.02276 –0.02152 –0.03972 –0.03904
  (0.05212) (0.05087) (0.04874) (0.04896) (0.02847) (0.02961)
HH members aged 65+ –0.02001 –0.01884 0.00730 0.00469 –0.01271 –0.01414
  (0.04165) (0.04136) (0.03573) (0.03540) (0.02182) (0.02205)
Father education –0.00132 –0.00099 0.00045 –0.00030 –0.00087 –0.00128
  (0.00198) (0.00226) (0.00202) (0.00213) (0.00160) (0.00170)
Mother education –0.00971*** –0.00904** 0.00937*** 0.00787** –0.00034 –0.00116
  (0.00341) (0.00417) (0.00294) (0.00327) (0.00181) (0.00210)
Years of delay in sec.edu 0.00440 0.00919 –0.02391** –0.03456* –0.01952*** –0.02537*
  (0.01275) (0.02067) (0.01070) (0.01764) (0.00702) (0.01381)
Technical edu 0.01038 –0.00031 0.02957 0.05333 0.03995*** 0.05301**
  (0.03694) (0.04459) (0.03180) (0.04181) (0.01452) (0.02678)
Vocational edu 0.00818 –0.00144 0.03776 0.05914 0.04594*** 0.05770**
  (0.03164) (0.04096) (0.02700) (0.04065) (0.01546) (0.02569)
Apprenticeship/PT edu –0.06240 –0.07366 0.08533* 0.11033** 0.02292 0.03667
  (0.05336) (0.06364) (0.04311) (0.05434) (0.02842) (0.03967)
Constant 1.41749*** 1.45409*** –0.15519 –0.23651 1.26230*** 1.21757***
  (0.35242) (0.37325) (0.32471) (0.34533) (0.20910) (0.22952)
Observations 1,902 1,902 1,902 1,902 1,902 1,902
R-squared 0.04170 0.03730 0.03098 0.00332 0.05818 0.03540
Exogeneity test P-val b   0.767   0.438   0.467
  1. Standard errors between parentheses. Columns 1–6 report the results from estimating Eq. (2) by OLS (odds columns) and 2SLS (even columns). The first stage regression is reported in Table 7 (Column 5). All estimations report cluster-robust standard errors by graduation year g and province of residence at graduation p (G=44). Even columns report the exogeneity test for early non-employment (\(y^{0}_{it_{1}}\)), which is measured at potential experience 0–2
  2. ***p <0.01, **p <0.05, *p <0.1
  3. aThe binary outcomes are measured at potential experience 6
  4. bWith clustered standard errors, the exogeneity 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). This statistic is not corrected for the problem of few clusters