Análisis gráfico de distribución salarial en hombres y mujeres controlando por factores socioeconómicos

Camilo Santa Cruz
June 2023

Distribución salarial por rama de actividad

SPMN = Salario neto A4 = SEXO A4 = 0: Mujer A4 = 1: Hombre

Agriculture and minery

Gaps in agriculture and minery

Gaps in agriculture and minery

Manufacturing and electricity

Gaps in manufacture and electricity sectors

Gaps in manufacture and electricity sectors

Water and sanitation and construction

Gaps in Water and construction sectors

Gaps in Water and construction sectors

Commerce - transport and storage sectors

Gaps in commerce and transport and storage sectors

Gaps in commerce and transport and storage sectors

Telecommunications and finance & insurance

Gaps in telecommunications and finance and insurance

Gaps in telecommunications and finance and insurance

Gaps in agriculture and minery

Gaps in agriculture and minery

Agriculture and minery

Gaps in agriculture and minery

Gaps in agriculture and minery

Scientific activies and support administrative sectors

Gaps scientific activities and support and administrative sectors

Gaps scientific activities and support and administrative sectors

Public defense and education

Gaps Public defense and education

Gaps Public defense and education

Assistance and entertainment

Gaps in human assitence and entertainment

Gaps in human assitence and entertainment

Services and homes as employees

Gaps in Other services and homes as employees

Gaps in Other services and homes as employees

Distribución salarial por condición de aseguramiento

Gaps controlling for insurance condition or no

Gaps controlling for insurance condition or no

Distribución salarial por trabajadores que trabajan en región central

Gaps controlling for working on central region or no

Gaps controlling for working on central region or no

Distribución salarial por pertenencia o no a sindicato

Gaps controlling for belonging to a workers sindicate

Gaps controlling for belonging to a workers sindicate

Distribución salarial por dominio de idioma inglés

Gaps controlling for language command

Gaps controlling for language command

Distribución salarial por tiempo de trabajo completo y no completo

Gaps controlling with full time

Gaps controlling with full time

Firm size

Gaps controlling with Firm size

Gaps controlling with Firm size

University degree

Gaps controlling for full time job

Gaps controlling for full time job

Secondary school

Gaps controlling with secondary school

Gaps controlling with secondary school

Zone

Gaps controlling with Zone

Gaps controlling with Zone 

#set.seed(123)
# Randomly select 2946 observations from the dataset of men
#men_sample <- Brechas1[sample(nrow(Brechas1), 2988), ]
#men_sample1 <- reg_hombres$model[sample(nrow(reg_hombres$model), 2988), ]
#men_sample2 <- reg_hombres$model[sample(nrow(reg_hombres$model), 2988), ]
#men_sample3 <- reg_hombres$model[sample(nrow(reg_hombres$model), 2988), ]