Regional and socioeconomic inequalities in access to pre-primary education in India: evidence from a recent household survey.

In India, the National Education Policy 2020 recommends ensuring universal access to high-quality early childhood care and education for children aged 3-6 years by 2030. Using the 75th round of National Statistical Office data (2017-2018), this paper analyses the regional and socioeconomic inequalities in access to pre-primary education. Also, we investigate the specific role of households' economic status and educational attainment in explaining these inequalities. We find considerable regional (rural/urban) and socioeconomic inequalities in access to pre-primary education in India, with girls and children belonging to historically disadvantaged social groups (scheduled castes and scheduled tribes) less likely to attend early childhood education, particularly in rural areas. We find that a substantial portion of the rural-urban gap in access to pre-primary education can be removed by controls for households' economic condition and household head's educational status. In addition, we find gender and socioeconomic inequalities in the household investment in early years education. These findings highlight the need to put policy efforts and commitments to reducing barriers to accessing pre-primary education for children in disadvantaged conditions in India.

Government health insurance and spatial peer effects: New evidence from India.

What is the role of spatial peers in diffusion of information about health care? We use the implementation of a health insurance program in Karnataka, India that provided free tertiary care to poor households to explore this issue. We use administrative data on location of patient, condition for which the patient was hospitalized and date of hospitalization (10,507 observations) from this program starting November 2009 to June 2011 for 19 months to analyze spatial and temporal clustering of tertiary care. We find that the use of healthcare today is associated with an increase in healthcare use in the same local area (group of villages) in future time periods and this association persists even after we control for (1) local area fixed effects to account for time invariant factors related to disease prevalence and (2) local area specific time fixed effects to control for differential trends in health and insurance related outreach activities. In particular, we find that 1 new hospitalization today results in 0.35 additional future hospitalizations for the same condition in the same local area. We also document that these effects are stronger in densely populated areas and become pronounced as the insurance program becomes more mature suggesting that word of mouth diffusion of information might be an explanation for our findings. We conclude by discussing implications of our results for healthcare policy in developing economies.