Gaps in Labor Income in Peru: An Explanatory Study from Labor Formality and Human Capital

Abstract

How do labor formality and human capital explain the persistent gaps in labor income across the Peruvian workforce? Drawing on individual-level data from a nationally representative survey, this study adopts a quantitative, non-experimental, cross-sectional design with an explanatory scope. Multiple regression analysis is employed to evaluate the predictive capacity of two core independent variables labor formality and human capital over monthly labor earnings, while controlling for gender, economic sector, age, and geographic region. Findings indicate that both formal employment status and higher educational levels are positively associated with increased labor income, whereas informality compounds the disadvantage of limited schooling. The full model explains 68.9 % of income variance, with formality and applied skills training emerging as the strongest predictors. The results provide empirical grounds for targeted workforce policies that address the structural determinants of income inequality in emerging labor markets.