Archives: Research Theme

Gender Hub

The NCAER National Data Innovation Centre (NDIC) launched the Gender Hub to envisage using existing data and new data as a vehicle for engaging feminist scholars, civil society representatives, and policymakers. These stakeholders will be invited to undertake and/or guide gender-focused analyses of public policies—both women-focused and gender-neutral—in the economic, health, and educational domains in India. Some of the policies of interest include cash incentives for girls’ education, reducing inequalities in access to health services, and development of a social registry for improving access to government benefits. Activities undertaken by this hub will include enhancing access to data collected by NCAER, visiting fellowships for practitioners and researchers, and seminars addressing strategies for incorporating a gender lens in data collection processes. Sonalde Desai, Professor, and Centre Director, NCAER-NDIC, and Pallavi Choudhuri, Senior Fellow, NCAER-NDIC, will lead this initiative.

Objectives

The overall goal is to shape a data-focused research agenda in conjunction with our civil society and government partners. The team has unique access to data and statistical skills; civil society partners will offer an understanding of on-the-ground processes to help define policies that deserve evaluation and conditions that may limit policy impact; NCAER’s location within the Indian policy discourse will help to mobilise gender advocates within both the Government and the media to help disseminate the research results and establish policy linkages.

India Human Development Survey-3 (IHDS)

The India Human Development Survey (IHDS) is one of NCAER’s flagship projects and India’s only national household panel data set. The Survey has been conducted in two phases in 2004-05 and 2011-12, and the third phase is currently ongoing. IHDS-3 is funded by the US National Institutes of Health, and the collaborators in the project include NCAER’s long-standing research partner, the University of Maryland, along with the University of Michigan and Indiana University Bloomington.

The IHDS seeks to provide the first large nationwide panel for Indian households. In order to accomplish that, all the households surveyed during IHDS-1 in 2004–05 were re-surveyed in 2011–12 as part of IHDS-2. With a re-contact rate of over 83 per cent, this panel provides a unique opportunity to study changes in Indian society during an era of rapid social transformation. The IHDS is thus a highly regarded public resource with over 11,000 users in phases 1 and 2. More than 500 papers have also been published using these data.

IHDS-3 is aimed at assessing changes in an individual’s life course as well as the impact of economic changes and public policies on household well-being by studying different dimensions of human development like education, health, caste, and gender relations. Currently, questionnaire designing, data model testing, and translation are in progress for implementation of IHDS-3. Analysis of the prior phases continues with a large number of publications in 2020-21. We also continue to support data users and send monthly newsletters highlighting research undertaken using IHDS data.

Poverty Monitoring in the context of COVID-19

The COVID-19 pandemic has not only affected physical and mental health of people in India and around the world, it has impacted people’s livelihood, led to stagnation of economic growth and posed an unprecedented challenge to teaching and learning of students. Moreover, because of COVID-related pressure on the health system, the disruption of routine health services turned out to be a major area of concern in the wake of the COVID-19. With the availability of safe and efficacious vaccines and a reasonable level of vaccination coverage there is a ray of hope that the pandemic may be over soon. But the impact it has on the people of the country due to unexpected death of family members, loss of livelihood, decline in household income, school closures and inability to access temporary alternative methods of remote learning, lack of access to routine healthcare services can be long lasting. Based on the impact of COVID-19 on people’s lives, we assess the consequences faced by the vulnerable population and their risks of impoverishment. Using a combination of original qualitative data collected from a small number of affected people in India, interviews with local leaders and community development actors, and secondary data from a range of different sources, we focus on vulnerability of specific occupational groups, occupational shift during the pandemic, levels of distress and hardship experienced by the households, COVID and non-COVID health burden, limited learning activities because of school closure and online education, financial constraint to support children’s education, and issues of isolation and the lack of social bonds. Initial funding for this work is given by the ODI Chronic Poverty Advisory Network.

Delhi NCR Coronavirus Telephone Survey (DCVTS)

In order to understand and quantify the early impact of the Coronavirus pandemic and the pandemic induced lockdown, the National Data Innovation Centre conducted telephone surveys in both the urban and rural areas of Delhi National Capital Region (NCR). So far we have completed four rounds of Delhi NCR Coronavirus Telephone Survey (DCVTS). The widespread use of mobile phones in India provided us with the opportunity of conducting surveys remotely during the pandemic when there was a need for scientifically collected data for decision making. Moreover, the telephone mode of data collection coupled with computer-assisted technology satisfies the need of a quick turnaround in the absence of travel time and helps in measuring or informing policy responses in a timely manner.

Objectives:

The objectives of the first two rounds of DCVTS (DCVTS-1, April 3-6, 2020; & DCVTS-2, April 23-26, 2020) were to estimate the levels and changes over time in people’s knowledge, attitude, perception, and practiced behavior with respect to COVID-19. The surveys also estimated the impact of the Coronavirus pandemic on people’s, income, access to essential items, social life, and their coping mechanisms (NCAER National Data Innovation Centre 2020NCAER National Data Innovation Centre 2020 Desai and Pramanik April 29, 2020 Desai and Pramanik April 20, 2020; Mazumdar, Pramanik et al. May 24, 2020).

The third round, DCVTS-3, (June 15-23, 2020) focused on the ways in which the lockdowns have affected different occupational groups (Desai and Pramanik Jul 5, 2020) (Desai and Pramanik 05 Jul 2020), levels of distress and financial hardship experienced by households, how households access welfare measures during the early phases of the pandemic (Bornali Bhandari, Santanu Pramanik et al. August 3, 2020; Choudhuri and Desai November 28, 2020), challenges in getting back to work and remaining safe after the lockdowns were lifted, and trends in social distancing and risk perceptions as the lockdowns are eased.

DCVTS-4 (December 23, 2020 – January 4, 2021), launched right before the roll out of mass vaccination, explored issues such as vaccine hesitancy (Pramanik and Desai 2021, level of disruptions in routine healthcare, the extent of learning disruptions for children in the age group of 6-14 years (Banerji, Ashraf et al. February 20, 2021), occupational shifts during the pandemic, vulnerability among different occupational groups, and the levels of distress and financial hardship experienced by households and whether the most vulnerable households have had access to safety nets. An overview of the topics covered across different rounds of DCVTS is given in the figure below.


Figure: An overview of the topics covered across different rounds of DCVTS

Delhi Metropolitan Area Study (DMAS)

In a dynamic research and policy environment with a growing demand for data, it is crucial to invest in methods of data collection leading to timely, high-quality and policy-relevant data. Delhi Metropolitan Area Study (DMAS), a flagship study of NCAER National Data Innovation Centre, serves as an incubator to experiment with innovations in data collection across various substantive domains such as household income, expenditure, borrowing; labor force participation; financial inclusion; health insurance and healthcare expenditure; education; gender equality and empowerment, among others. Two key objectives of DMAS are: 1) Conducting methodological experiments in data collection involving technological innovations and innovations in questionnaire designing; and 2) Demonstrating the feasibility and usefulness of remote monitoring of data collection activities to improve data quality.

Data collection for DMAS continued from 15th February, 2019 to 14th November, 2021, with a break of one and half-year during the COVID-19 pandemic. During this time, we completed DMAS baseline survey, 3 quarterly surveys, 30 rounds of monthly telephone surveys on employment, and finally the endline. Our inability to complete the 4th quarterly survey and the endline on time (which was supposed to happen during March-May 2020) has implications on our planned experiments because of comparability issues around reference period across the two experimental groups (one group of households receiving 4 quarterly surveys and the other group getting the annual reference period endline). So we will not be able to achieve some of the original objectives we had, as one can imagine, the last round of data collection is crucial for any evaluation study. However, DMAS endline has immense potential to capture the medium to long term economic, health and educational impact of the pandemic.

Study Design and Survey Methodology:

The target geographical area for DMAS is the Delhi National Capital Region (NCR) which comprises 31 districts spread over four states, viz., Haryana (13 districts), Delhi (9 districts), Rajasthan (2 districts), and Uttar Pradesh (7 districts) . Although it may not be apparent from the name, Delhi NCR is a highly diverse region including the metropolitan areas of Delhi as well as rural areas of districts in Haryana, Rajasthan, and Uttar Pradesh. Within a state, we considered a multi-stage stratified cluster sampling design. Districts, clusters, and households were selected at the first, second, and third stages of sampling. Clusters or the secondary sampling units (SSUs) were defined as census villages in rural areas and NSS Urban Frame Survey (UFS) blocks in urban areas. The goal of the sampling design was to select representative random sample at each stages of selection.

Total number of households that completed DMAS baseline survey was 5,253. We considered equal allocation of sample across districts resulting in approximately 22 SSUs per district, with a few exceptions. Within a district, SSUs were allocated to urban (UFS blocks) and rural areas (villages) in proportion to the percentage of urban and rural households in the district. The median number of households surveyed from a SSU was 20. Equal number of households were considered from each SSU in order to manage the interviewer workload efficiently.