Determinantes del ingreso laboral en Colombia: una aproximación a partir de un modelo aditivo de localización, escala y forma (GAMLSS)

Human capital theory posits a central hypothesis: there is a direct relationship between individuals' levels of education and their productivity, which in turn leads to higher earnings. To evaluate this hypothesis, the economic literature commonly estimates the Mincer equation using the classical linear regression model. In this paper, both the traditional approach and a GAMLSS model with the Dagum distribution are estimated for wage earners in private firms and the public sector in Colombia in 2024. The hypothesis that an individual's rate of return increases with years of education, and that it rises with years of experience up to a certain point in the life cycle before declining, is confirmed by both the linear regression and the GAMLSS model. Model selection is based on the Generalized Akaike Information Criterion (GAIC), and the results show that the GAMLSS provides a better fit than the linear regression model.