JRC Impact migrant workers COVID

Figure 9: Native-Migrant Probability Gap in Being in the Top Half of Labour Earnings Distribution, by Key Occupation

Probability difference vs. natives

Science and Engineering Professional Health Professionals Teaching Professionals ICT Professionals Science & Eng. Associate Professionals Health associate professionals ICT Technicians Personal Service Workers Personal Care Workers Market-oriented Skilled Agricultural Workers Food Processing, etc. Stationary Plant and Machine Operators Drivers and Mobile Plant Operators Cleaners and Helpers Labourers in Mining, Contruction, Manuf., & Transport Refuse Workers

-.4

-.3

-.2

-.1

0

.1

Low Skill

High Skill

(a) EU Mobile

Probability difference vs. natives

Science and Engineering Professional Health Professionals Teaching Professionals ICT Professionals Science & Eng. Associate Professionals Health associate professionals ICT Technicians Personal Service Workers Personal Care Workers Market-oriented Skilled Agricultural Workers Food Processing, etc. Stationary Plant and Machine Operators Drivers and Mobile Plant Operators Cleaners and Helpers Labourers in Mining, Contruction, Manuf., & Transport Refuse Workers

-.4

-.2

0

.2

Low Skill

High Skill

(b) Extra-EU

Note: The thick blue bars represent the difference in the probability of being above the median of the monthly earnings distribution between natives and migrants.The thin black bars represent the 95% con- fidence intervals. The probabilities are estimated via OLS in a model controlling for occupation, gender, educational level, age, country of residence and migration status. 16