Purpose – To estimate gender disparity in high school dropouts when households experience financial shocks, this study aims to extend the simple decision-making process of school dropouts to allow for the multiplicity of dropout choices concerning gender in households having exactly one boy and one girl in high school. We also account for heterogeneity in the households choosing the baseline “no dropout” category and resulting bias in the estimated effects of variables by comparing Baseline Inflated Multinomial Logit (BIMNL) models developed by Bagozzi and Marchetti (2017), with Multinomial Logit (MNL) models. Methodology – Filtering households from publicly available India Human Development Survey (IHDS) datasets having exactly one boy and one girl in high school, we estimate MNL and BIMNL models and compare their average partial effects (APE) and econometric performance. Findings – We find that households facing shocks due to marriage or crop failure are more likely to drop out the girl. BIMNL only could capture the association of crop failure with the dropout of girls. Econometrically BIMNL models performed better than MNL. Practical implications – Deployment of these sophisticated econometric tools can enable a more effective examination of gender disparities in school dropouts to draw effective policy interventions in the backdrop of financial shocks due to Covid-19 or geopolitical crises across the world. Originality – This study uniquely contributes by deploying BIMNL models to account for household heterogeneity and resulting baseline bias in the estimated APEs of variables in the context of the multiplicity of dropout choices concerning gender.
Soumik Biswas, Indian Institute of Management Lucknow Noida Campus, India
Kaushik Bhattacharya, Indian Institute of Management Lucknow Noida Campus, India
About the Presenter(s)
Mr Soumik Biswas is a University Doctoral Student at Indian Institute of Management Lucknow Noida Campus in India
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