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Paper short abstract

A multi-method causal analysis reflecting on how female-focused skilling expands women’s entry into work, yet pushes them into lower valued roles feminized occupations with widening wage penalties. Market-oriented training while empowering can unintentionally reproduce deeper gendered inequalities.

Paper long abstract

Using detailed occupational classification, rich covariates and multi-stage empirical approach this study investigates the heterogeneous evolution and implication of occupational gender typicality on wages and wage inequality in India. To mitigate biases arising from imperfect matching and model misspecification we employ doubly robust multivalued treatment model based on Augmented Inverse Probability Weighting Regression Adjustment. This is followed by Multinomial Endogenous Switching Regression (MESR) to account for endogenous occupational choices. Exogenous variation in occupational sorting is identified through a leave-one-out Bartik instrument, constructed by interacting district level exposure to female vocational training shocks with national skilling trends. The MESR results reveal significant wage penalties in feminized occupations, particularly for women, consistent with occupational devaluation and crowding hypotheses. At the macro level the micro-level mechanisms are validated using panel instrumental variables estimation and sequential IV 2SLS to reflect increased female participation in vocational training is causally associated with a rise in female employment and patterns of occupational feminization. This multi-level causal findings thus underscore a paradox inherent in market-oriented skilling interventions, facilitating women’s entry into the labor force, but inadvertently reproducing and exacerbating existing gender hierarchies in occupational sorting and wages. This study contributes to feminist political economy by critically engaging with the structural limitations of supply-side labor market interventions in contexts of persistent gendered stratification.