Modeling labor income through ICT use and sociodemographic factors: A linear regression application in Tijuana’s urban system

Abstract

In the context of increasing digitalization and labor market transformation, income generation is influenced by multiple interrelated factors, including education, age, gender, and access to digital technologies. Understanding the impact of these variables is essential for designing equitable and efficient labor systems, particularly in border cities like Tijuana, where migration and urban growth create complex socioeconomic dynamics. This study examines how sociodemographic and technological factors affect workers' income in Tijuana’s labor ecosystem. Using a linear regression model applied to survey data from 443 individuals, the analysis finds that age, years of schooling, and computer use have a positive and statistically significant effect on income, while marital status and internet access show no significant relationship. Notably, the model reveals a persistent gender wage gap, with male workers earning significantly more than their female counterparts. These findings highlight the importance of digital competencies and education as system-level drivers of income and suggest the need for targeted public policies to foster wage equity and technological inclusion in emerging urban economies.