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Table 3 EaP migrants labor market outcomes, in comparison with natives, EU15, EU8, EU2 and other nationals

From: Eastern partnership migrants in Germany: outcomes, potentials and challenges

 

Natives

EU15

EU8

EU2

Others

 

Employment

EaP

−0.462***

−0.206***

−0.228***

−0.162***

−0.087***

 

(0.059)

(0.030)

(0.032)

(0.045)

(0.029)

Female

−0.087***

−0.164***

−0.26***

−0.155***

−0.247***

 

(0.001)

(0.010)

(0.017)

(0.039)

(0.007)

Female × EaP

−0.053

0.023

0.117***

0.024

0.106***

 

(0.036)

(0.037)

(0.040)

(0.053)

(0.036)

 

Self-Employment

EaP

−0.125***

−0.100***

−0.219***

−0.115***

−0.056***

 

(0.018)

(0.015)

(0.021)

(0.033)

(0.013)

Female

−0.058***

−0.054***

−0.173***

−0.093***

−0.048***

 

(0.001)

(0.008)

(0.016)

(0.031)

(0.004)

Female × EaP

0.069***

0.064***

0.175***

0.098***

0.053***

 

(0.016)

(0.018)

(0.023)

(0.036)

(0.016)

 

Log-Earnings

EaP

−0.641***

−0.495***

−0.198***

−0.164**

−0.218***

 

(0.134)

(0.048)

(0.049)

(0.067)

(0.044)

Female

−0.226***

−0.31***

−0.26***

−0.145**

−0.326***

 

(0.002)

(0.019)

(0.030)

(0.056)

(0.014)

Female × EaP

0.162***

0.218***

0.201***

0.073

0.268***

 

(0.059)

(0.062)

(0.063)

(0.080)

(0.059)

 

Log-Wages

EaP

−0.634***

−0.405***

−0.154***

−0.142**

−0.159***

 

(0.138)

(0.049)

(0.051)

(0.066)

(0.047)

Female

−0.128***

−0.155***

−0.082***

−0.029

−0.141***

 

(0.002)

(0.017)

(0.026)

(0.056)

(0.012)

Female × EaP

0.186***

0.204***

0.145**

0.076

0.199***

 

(0.065)

(0.067)

(0.070)

(0.086)

(0.066)

  1. Source: Own calculations based on the German Microcensus 2009.
  2. Notes: Employment and Self-Employment models report estimate from linear probability models. Differences in various labor market outcomes of EaP nationals versus natives, EU migrants and other immigrants. *** pvalue < 0.01; ** pvalue < 0.05; * pvalue < 0.1. The regression analysis is carried conditioning on the following variables: Age: dummy variables for age categories in five-year intervals; Education: dummy variables for secondary and tertiary education; Married: dummy variable for being married; State: dummy variables for state of residence; N. Children: Number of children in the family; Female: dummy variable for being a female; and Years Since Migration: years since entrance into the country. In the Log-Earnings regressions, hours worked in reference week were also added. Variable definitions are shown in the footnote of Table 2.