Demographic dimensions of wage disparities: a stochastic frontier approach to labor market in São Paulo City (Brazil)

Abstract This study investigates wage disparities for 6.34 million workers from São Paulo city (Brazil) during the years 2018 to 2020 using Stochastic Frontier methods to estimate changes in the underpayment levels across demographic dimensions. The results indicate that closing the underpayment gap has the potential to yield an average salary increase of 1.12 times, with a range spanning from 1.02 to 4.82 times within the sample. Additionally, the results underscore lower levels of underpayment among white and male workers, while migrant workers and those with reported disabilities tend to experience higher levels of underpayment. Furthermore, the study unveils a trend of decreasing potential wages over time, marked by a sharp -19.34% reduction in 2020, primarily attributed to the impact of the COVID-19 outbreak. Simultaneously, there is a notable reduction in the average underpayment, with a substantial decline occurring in 2019. In conclusion, this research advances the existing literature by utilizing Stochastic Frontier models to assess underpayment and provides valuable insights into the intricate dynamics of wage disparities - a critical issue that plays a pivotal role in fostering socioeconomic development.