Gender pays gaps in times of COVID-19 in Peru: Effects beyond the average

Carlos Salas Peña; Gabriel Eduardo Moreno Veloza

doi:10.17533/udea.le.n105a359955

Authors

Carlos Salas Peña Universidad Continental
Gabriel Eduardo Moreno Veloza Universidad Externado de Colombia

DOI:

https://doi.org/10.17533/udea.le.n105a359955

Keywords:

gender pay gap, quantile regression, descomposition methods

Abstract

Empirical evidence shows that the gender wage gap remains a problem in Latin America. Women earn less, work fewer hours, and their labor market participation is heterogeneous across occupational sectors and skill levels. During the COVID-19 pandemic period, there was downward pressure on wages. This paper tests the glass ceiling and sticky floor hypotheses for two points in time, before and during the pandemic. To do so, the variation of the gender gap across the entire wage distribution was studied. First, to estimate the effect of covariates on the wage gap beyond the mean, we compared the classical conditional quantile regression approach and the unconditional quantile regression method using the recent influence function. Then, detailed RIF analysis was implemented to find the influence of each covariate on the structure and composition effects. The gap was found to be largest in the first quartiles of the wage distribution, and its magnitude increased slightly during the pandemic.

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Author Biographies

Carlos Salas Peña, Universidad Continental

Universidad Continental. Docente Investigador en la Universidad Continental.

Gabriel Eduardo Moreno Veloza, Universidad Externado de Colombia

Phd(c) en Ciencias Económicas, Estadístico, Politólogo, Magister en Ciencias Económicas, Magister
Estadística Aplicada.
Analista de datos experto, con experiencia en investigación cuantitativa y cualitativa, en planeación,
formulación y evaluación de políticas públicas en temas como: técnicas estadísticas aplicadas, minería
de datos, Big Data y machine learning. Investigador con más de 12 años de experiencia en varías áreas
del conocimiento. Experiencia de más de 10 años en análisis estadísticos robustos de indicadores e
índices laborales y socieconómicos en entidades como ONGs, DANE, Unidad para las Victimas,
Concejo de Bogotá y COTELCO.

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