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

Ghirelli, Corinna

doi:10.1186/s40174-015-0042-1

IZA Journal of European Labor Studies

Table 10 Effect of interest for graduation period 1998–2002

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 g∗p	Robust	Cluster g∗p
Continuous outcomes: ^b		(1)	(2)	(3)	(4)
Log earnings	coeff	–0.0287***	–0.0287***	–0.1406**	–0.1406**
	se	(0.0045)	(0.0049)	(0.0666)	(0.0597)
	P-val		6.09E-06		0.027298462
	Bootstrap P-val ^c		0		0.082082082
	Exogeneity test P-val ^d				0.0306
Log hours worked	coeff	–0.0215***	–0.0215***	–0.1032**	–0.1032**
	se	(0.0034)	(0.0035)	(0.0492)	(0.0439)
	P-val		3.23E-06		0.027651497
	Bootstrap P-val		0		0.078078078
	Exogeneity test P-val				0.0318
Panel B: Effect of the instrument in the first stage : OLS
Outcome:	Standard errors:	Robust	Cluster (g*p)
Early non-empl.(% hours)	Coeff	11.9484***	11.9484***
	se	(3.4994)	(3.4918)
	P-val	0.00233
	Bootstrap P-val	0.07007
	F stat	11.70921
	Bootstrap F stat ^e	3.60923

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 at potential experience 0–2 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
***p <0.01, **p <0.05, *p <0.1
^aRobust indicates heteroskedastic-robust standard errors. Clusters are defined by graduation year g and province of residence at graduation p (G =24 clusters)
^bThe outcomes are measured at potential experience 6. For continuous outcomes we add value one before taking the log, so that non-salaried employed at the moment of evaluation are included with outcomes equal to zero after the logarithmic transformation
^cComputed according to the wild bootstrap procedure proposed by Davidson and MacKinnon (2010) for 999 repetitions
^dWith 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)
^eBootstrap 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: t ²(G−1)=F(1,G−1), with G=24

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