Purpose:

To characterize the employed population by income level in the tertiary sector in Mexico in 2005, 2020, and 2021.

Methodological design:

Using data from the National Occupation and Employment Survey, the labor market was segmented and three models of generalized ordinal logistic regression were estimated. The dependent variable was the income level, and as independent variables included age, gender, education level, employed population by occupation, formal and informal employment, company size, and subsectors.

Results:

As the workers’ age and educational level increase, the probabilities of receiving a higher income also increase. Additionally, women are less likely to reach the higher income level; however, the difference narrows in 2020 and 2021. At the same time, formal employment offers 22% less probability of earning 0 to 1 minimum wages compared to those in the informal sector. The probability of obtaining the maximum salary in a large company compared to a micro-enterprise is only 1%. The sectors with the highest probability of obtaining the highest income were social services, and government and international organizations.

Research limitations:

The models were estimated based on the National Occupation and Employment Survey using the classification of the employed population by nominal income level.

Findings:

The study reveals the segmentation of the labor market in tertiary activities, although a trend of reduction in the number of segments was detected through the reduction of probabilities.