With a growing economy and declining poverty, India faces a curious challenge in providing a social safety net to its citizens. Using data from three rounds of the India Human Development Survey (IHDS), collected in 2004-05, 2011-12, and 2022- 24, this paper shows that households face considerable transition in and out of poverty as the economy grows. Historically, India’s approach to social safety nets has involved identifying the poor and providing them with priority access to various social protection programs that include both in-kind and cash assistance—however, the nature of poverty changes with economic growth. This churn in households’ economic circumstances makes it difficult to identify and target the poor precisely.
Using unique, newly collected, panel data, this paper makes three observations about India’s anti-poverty programs: (1) Identification of households as poor (now dubbed priority households) relies on identification exercises carried out every 10-15 years and assumes that poverty status is relatively static. However, results presented in this paper document a substantial transition in and out of poverty. (2) This ex-ante identification of needy households leads to relatively weak correlation between households’ actual economic status and access to social safety nets. This should not be assumed to be an example of elite capture but rather an artefact of a static program design. (3) Recognition of exclusion and inclusion errors led to an advocacy for a vast expansion of the population eligible for benefits. It was assumed that this expansion will reduce exclusion of the poorest, even if it leads to greater inclusion of the non-poor. However, experience of the National Food Security Act 2013, documented in this paper, shows that even as the proportion of households owning a Below the Poverty Line (BPL) card grew from 41 percent to 60 percent between 2011-12 and 2022-23, 30 percent of the poor were left out. This suggests that addressing inclusion and exclusion errors may be difficult, particularly in an era of economic growth. Social safety nets may need to be redesigned in a way that is responsive to changing economic conditions and unexpected events, both at the individual and the community levels.
India has made remarkable strides in expanding access to education for girls over the past few decades. Enrolment rates for girls in primary and secondary schools have risen significantly, and gender gaps in literacy have narrowed. Girls have surpassed boys even in gross enrolment in higher education. However, this educational success has not translated into a proportional increase in female labour force participation.
As India seeks to enhance its innovation ecosystem, it is worthwhile to pay attention to opportunities and lessons from the self-inflicted wounds on American science.
Above all, trust in government is the key to successfully implementing difficult decisions during emergencies.
This March marks five years since the world stopped. On March 11, 2020, the World Health Organisation (WHO) declared Covid a pandemic. On March 24, the Government of India declared a nationwide lockdown, one of the most stringent globally. With five years and much water under the bridge, it is easy to forget the gasping breaths, millions of deaths, and shuttered businesses. That is, until the next disaster strikes. Can we learn from that painful experience to prepare for the next disaster, whether it is a black swan event like the pandemic, a tsunami, or a drought?
This paper explores ‘gatekeeping’, the phenomenon where access to a sample person in the household is controlled by another person. Gatekeeping of female persons is especially an issue in societies governed by gendered social norms. It can increase survey error by reducing response rates and potentially increasing non-response bias, and can increase measurement error when gatekeepers insist on providing proxy responses. We contribute to the sparse literature on gatekeeping by using data from a telephone survey of migrants in India and focusing on the sample of female married-out migrants. We estimate the prevalence of gatekeeping, compare outcomes of calls made to gatekept versus non-gatekept cases, and model the likelihood of a proxy interview. We estimate that gatekeeping of females in telephone surveys is in the range of 56%–65%, with gatekept calls much more likely to result in proxy interviews. We find that older and more-educated women are less subject to gatekeeping and that male and married interviewers are associated with a greater likelihood of gatekeeping. We discuss implications of these results for survey practice.
