Employment chances of immigrants and their children in Germany: does sense of personal control matter?

Table 1 Estimates of the employment equation

β ^D	(1)	(2)
Intercept	−1**	−1, 34**
	(−1.99, −0.04)	(−2.31, −0.31)
Age	0, 03**	0, 04**
	(0.01, 0.05)	(0.02, 0.06)
Gender	−0, 56**	−0, 59**
	(−0.70, −0.421)	(−0.72, −0.44)
Immigrant	−0, 4**
	(−0.67, −0.13)
Second generation	−0.16
	(−0.34, 0.036)
Turkish immigrant		−0, 65**
		(−1.06, −0.23)
Central European immigrant		−0.06
		(−0.60, 0.50)
EU15 immigrant		0.5
		(−0.18, 1.23)
Turkish second generation		−0, 45**
		(−0.87, −0.02)
Central European second generation		0.32
		(−0.28, 0.95)
EU15 second generation		0.16
		(−0.30, 0.64)
German second generation		−0.13
		(−0.38, 0.12)
Immigrant foreign language at home		−0.53
		(−1.19, 0.12)
Second generation foreign language at home		−0.25
		(−0.89, 0.41)
Low education	−0, 4**	−0, 37**
	(−0.58, −0.21)	(−0.56, −0.17)
High education	0, 31**	0, 28**
	(0.14, 0.47)	(0.11, 0.45)
Marital status	0.08	0.1
	(−0.07, 0.24)	(−0.06, 0.25)
Children under 16	0, 23**	0, 26**
	(0.08, 0.37)	(0.10, 0.41)

Notes: (1) 95 % Bayesian confidence intervals in brackets. These intervals contain 95 % of the posterior probability. If this interval contains 0, the effect measured by the parameter estimate is insignificant. (2) Marginal effects at any {theta,X} value can be derived from the information given (i.e. the estimates of alpha and beta). It is in the nature of probit/logit/etc. that the marginal effects are high when the probability is around 0.5 and low when it is close to zero or one
**Significance at the 95 % confidence level