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Table 3 Probit model estimates (marginal) of the relative probability of enrolment in AEI

From: The long-term earnings consequences of general vs. specific training of the unemployed

  Malesa) Femalesa)
Age −0.0120*  
Less than 9 years 0.3945***  
9 years of sch 0.4602***  
2-yr upp sec 0.4289*** 0.2103***
Social sci 2 years(d) 0.0943** 0.0832***
Vocation 2 years(d) 0.0848*** 0.1056***
Technology 2 years(d) −0.0450** 0.0360
Business 3 years(d) 0.1142*** 0.0696***
12 years of sch 0.3564*** 0.0686***
Business 3 years −0.0535* −0.0618**
15 years of sch 0.2542***  
Regional employm 0.9272***  
Stockholm(d) 0.0250  
Farmin/mining(d) −0.1497*** −0.0571
Construction(d) −0.1811*** −0.0627
Manufacturing(d) −0.1530*** −0.1330***
Finance/insur(d) −0.0780*** −0.0808***
Public sector(d) 0.0669*** 0.0911***
Other sector(d) −0.0566*** −0.0498***
Foreign born(d) −0.0202  
Divorced(d) −0.0236 −0.0281*
One child(d) −0.0248* 0.0417***
Two children(d) −0.0484*** 0.0764***
Three children(d) −0.0391* 0.0975***
Four children(d) −0.0482 0.0901***
Child 0–3(d) 0.0365*  
Child 7–10(d) 0.0116  
Child 11–15(d) 0.0420*  
Child >17(d) −0.0439**  
Parental 1993 −0.0537*  
Parental 1995 −0.0635**  
Parent > 0 1990(d) 0.0374  
Parent > 0 1991(d) 0.0154 −0.0199
Parent > 0 1993(d) 0.0201  
Parent > 0 1994(d) 0.0344**  
Parent > 0 1995(d) 0.0304*  
Earnings 1990 −0.0110  
Earnings 1991 −0.0226*  
Earnings 1992 0.0112  
Earnings 1993 −0.0098  
Earnings 1994 −0.0238** 0.0127
Earnings 1995 0.0830***  
Zero earn 1991(d) −0.0138  
Zero earn 1993(d) −0.0206 −0.0177
Zero earn 1994(d) −0.0149  
Unemp ben 1990 0.0776*  
Unemp ben 1991 −0.0272 −0.0615*
Unemp ben 1993 −0.0465* −0.0335*
Unemp ben > 0 1991(d) 0.0200  
Unemp ben > 0 94(d) −0.0320*  
Unemp ben > 0 1995(d) 0.0268*  
Days unemp 1992 0.0001  
Days unemp 1993 0.0001  
Days unemp 1994 0.0001***  
Days unemp 1995 −0.0000  
Max unemp 1992(d) 0.0361*  
Max unemp 1993(d) 0.0234  
Max unemp 1994(d) 0.0207  
Max unemp 1995(d) 0.0298*  
No unemp 1992(d) 0.0155  
No unemp 1993(d) 0.0347  
No unemp 1995(d) 0.0489*  
Sick leave 1990 −0.0398  
Sick leave 1992 −0.0596**  
Sick leave 1994 −0.0278 −0.0541**
Sick leave 1995 −0.0412  
Sick > 0 1990(d) 0.0215  
Sick > 0 1991(d) 0.0229* 0.0140
Sick > 0 1993(d) 0.0181 0.0180*
Sick > 0 1995(d) 0.0302*  
Social welf 1992 0.1882*  
Social welf 1993 −0.1818* −0.1113
Social welf 1994 −0.1915*  
Social welf 1995 −0.1686  
Social welf > 0 1990(d) 0.0221  
Social welf > 0 1995(d) −0.0103  
Observations 12,098 17,509
Pseudo R-squared 0.0863 0.1066
  1. (d) = dummy variable
  2. a) Earnings and transfers expressed in SEK 100,000 (2010 values). For reasons of space, coefficients not displayed include age-dummies (males) and 13 additional regional dummies. Estimates are also based on interaction variables which for males only include (Social welf. > 0 1990*UI 1995). For females, the indicator variable of 9 years of schooling is interacted with “no unemployment 1995”; five interaction variables involve “no upper secondary school” (age at immigration, sick leave 1992, social welfare 1990 and 1995 and earnings 1995); two interaction variables involve two year upper secondary school (no unemployment 1995, and age at immigration); Stockholm is interacted with sick leave benefits 1991; and finally earnings 1995 squared is also included
  3. *p < 0.05, **p < 0.01, ***p < 0.001