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Table 9 Two-stages regression correcting for selection bias

From: Skill mismatch among migrant workers: evidence from a large multi-country dataset

 

Whole sample

Netherlands

Germany

Probability of being a migrant

Estimate

 

Std.

Estimate

 

Std.

Estimate

 

Std.

Estimate

 

Std.

Age

0.010

***

(0.000)

0.010

***

(0.000)

0.000

 

(0.001)

−0.013

***

(0.001)

Gender (female = 1)

0.026

***

(0.006)

0.014

*

(0.006)

0.137

***

(0.017)

−0.007

 

(0.027)

Education

YES

  

YES

  

YES

  

YES

  

Continent of provenance (ref. EU15)

            

  EU12

   

0.376

***

(0.013)

0.701

***

(0.039)

0.842

***

(0.050)

  Africa

   

0.330

***

(0.013)

0.760

***

(0.033)

0.256

***

(0.073)

  C-S America

   

0.056

***

(0.010)

0.561

***

(0.023)

0.003

 

(0.044)

  Asia

   

0.457

***

(0.010)

0.742

***

(0.026)

0.438

***

(0.041)

  NAO

   

0.464

***

(0.022)

0.969

***

(0.059)

0.281

*

(0.113)

  Eur not-EU

   

0.428

***

(0.009)

−0.104

**

(0.031)

0.277

***

(0.034)

Intercept

−1.937

***

(0.026)

−2.137

***

(0.027)

−1.317

***

(0.068)

−1.150

***

(0.059)

Probability of overeducation

            

Age

0.000

 

(0.001)

−0.001

 

(0.001)

−0.003

 

(0.002)

0.009

*

(0.004)

Gender (female = 1)

0.096

***

(0.016)

0.088

***

(0.016)

0.180

***

(0.044)

0.258

**

(0.075)

Breaks

0.038

***

(0.004)

0.036

***

(0.004)

0.065

***

(0.012)

0.064

*

(0.020)

Education (ref. ISCED10)

YES

  

YES

  

YES

  

YES

  

Corporate hierarchy

YES

  

YES

  

YES

  

YES

  

Firmsize

YES

  

YES

  

YES

  

YES

  

Intercept

−0.413

***

(0.010)

−0.063

 

(0.134)

−0.956

***

(0.227)

−0.933

**

(0.287)

ath(rho)

−0.232

***

(0.034)

−0.381

***

(0.049)

0.013

 

(0.076)

−0.148

 

(0.147)

rho

−0.228

  

−0.364

  

0.013

  

−0.147

  

N

368564

  

368564

  

53583

  

22868

  
  1. Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘