This paper analyzes the Brazilian case, the transient conditions of employment levels and income distribution in the country, using micro data from the Monthly Employment Survey (PME) produced by the Brazilian Institute of Geography and Statistics (IBGE) to assess the effects of macroeconomic shocks on employment and income inequality in different social segments, focusing on the possible effects of heterogeneity. Consider themselves eight social segments, differentiated according to three attributes: gender, experience and education. To relate the social indicators of employment/inequality to macroeconomic variables, adopt two types of econometric approach: vector autoregressive standard models (VAR) models and autoregressive vetorais factors (Favar), in which macroeconomic shocks are identified using sign restrictions inspired by dynamic stochastic general equilibrium (DSGE). The comparison between the results of VAR methodologies and Favar allows assess to what extent the consideration of the possible effects of heterogeneity can change qualitative results of the relationship between macroeconomic shocks and social indicators. The main results of this work are that the effect of the identified shocks: i) is statistically significant only for the Favar models, indicating the importance of segmentation to relate the shock to the social conditions; ii) have small but statistically significant effects on indicators relating to workers; iii) have heterogeneous effects by segment allowing identification of the most vulnerable segments according to the measures of employment, income or inequality; and iv) the supply shock is the only has effect on inequality of all segments.
macroeconomics employment and inequality Bayesian Favar signal restriction identification