Earnings trajectories during a crisis in a segmented labor market: Argentina (2019–2023) - Agustin Salvia; Santiago Poy (Humanities & Social Sciences Communications)
Abstract This study aims to dynamically analyze changes in labor income in Argentina before, during, and after the COVID-19 pandemic, in order to characterize the economic trajectories of workers and assess their relationship with occupational inequality during such period. By employing panel data from a national urban survey, we implemented a novel methodological strategy that combines latent growth curve (LGC) models to define income trajectories and multinomial logistic regression analysis so as to evaluate the determinants of these trajectories. After extensive analysis, the results confirm the existence of divergent trajectories. On the one hand, downward trajectories primarily affect socially disadvantaged workers in the informal sector. On the other hand, stable or upward trajectories are observed mainly among individuals employed in formal economic units, particularly those with medium or high levels of education. These findings support the literature that highlights the regressive impact of labor market segmentation and social inequalities on income and employment opportunities for certain groups of workers in economies characterized by structural heterogeneities at both the productive and occupational levels.