Research | Mitali Roy Mathur

Social Protection

Government Scheme Overload: Take-Up and Targeting in a Multi-Scheme Context

IndiaSocial Protection

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Governments in developing countries often offer a variety of social protection programs to their citizens, but take-up rates remain quite low. While researchers have studied interventions meant to improve the take-up and targeting of specific welfare schemes, little is known about how individuals navigate the entire system of welfare schemes and decide which ones to apply to. Exposure to a large quantity of welfare benefits can have countervailing effects. On the one hand, when individuals have many welfare schemes to choose from, they can make a targeted choice in applying to the benefit(s) that fit their needs the most. On the other hand, they might be overwhelmed by the sheer quantity of schemes they could apply to and not apply to any, leading them to miss out on key benefits. Therefore, studying how individuals make decisions on how many and which welfare schemes to apply to can shed light on the role that behavioral elements of choice play in a social protection setting. I will implement a randomized controlled trial that varies the number of benefits frontline workers share with informal workers in India, a country with thousands of welfare schemes. I conducted a similar pilot study with over 2,000 workers in New Delhi and found that on average, individuals went on to apply to 1 scheme upon learning about their eligibility. People who learned about one-scheme applied to 0.203 more schemes than did people who learned about multiple-schemes, translating to 498 more schemes availed. I will refine and scale this study to gather more evidence on "scheme overload" and investigate its welfare effects by analyzing how the quantity of schemes shared impacts the quantity and match-quality of schemes availed. My research highlights the importance of studying take-up in multi-scheme settings and motivates policies related to scheme convergence.

Migration

Landscaping internal migrant vulnerabilities and labor department schemes

IndiaInternal MigrationSocial Protection

Abstract

I led a research project in collaboration with the research team at Jan Sahas’s Migrants Resilience Collaborative. In this project, I built a database of different labor department welfare schemes in India. Next, I constructed a unique vulnerability index using a weighting technique to rank schemes based on vulnerabilities migrants experience tied to their demographic profiles. Finally, I designed an application in which users can enter different demographic profiles of migrants and see a ranking of types of schemes that may be most important to that migrant persona. This research contributes to the literature on optimal program design with respect to welfare targeting and lays the foundation for future research into interventions that can increase internal migrants’ take-up of specific schemes.

Gender

The Diversity of Conference Presenters in Virtual and In-Person Conferences (2017–2023)

USAAcademia

Abstract Data

We developed a publicly available dataset to document the gender and institutional affiiation of presenters, discussants, and session chairs at four major finance conferences - the AFA, SFS Cavalcade, WFA, and FMA. The data span in-person, virtual, and hybrid formats, enabling research on whether virtual conferences affect gender representation and access to prestigious speaking roles in academic finance
Understanding the challenges of female surveyors

IndiaFemale Surveyors

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I co-led an internal project with a field manager at IDinsight to understand the challenges that female surveyors face. We were interested in the gender dynamics of our field teams in order to shed light on ways in which IDinsight can improve its processes and to understand the gender dynamics of a unique form of gig work. Our learnings highlighted challenges surveyors experience while menstruating, with gender-based bias, and with safety.
Evaluating the implementation of a women’s empowerment program

IndiaProcess Evaluation

Abstract

I led the first of two rounds of a process evaluation to understand the implementation of the Strengthening Women’s Institutions for Agency and Empowerment program run by the Institute for What Works to Advance Gender Equality (IWWAGE). The program is implemented by different partners in four states and focuses on establishing gender resource centers and introducing training programs for women in self help groups. The first round entailed detailing out a theory of change to understand the program and collecting data via a phone survey on key process indicators. The results from the second round highlight the opportunities for IWWAGE to improve its program implementation while scaling.

Data Quality & Methods

Improving data quality and data use for India’s Aspirational Districts Program

IndiaPrimary Data Collection

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As a member of the Data Delta team at IDinsight, I worked on two different phases of a project with Niti Aayog as part of their Aspirational Districts Program (ADP). In the first phase, I worked on managing data quality for a primary survey of 27,000 households across 27 of the poorest districts in India. In the second phase, I worked on a team to understand the pipeline in which administrative data is collected in each district to identify potential areas of improvement in sampling, training, and data collection processes and implement automated data quality checks.
Understanding best practices to improve response rates in phone surveys in developing contexts

IndiaPhone Surveys

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During the COVID-19 pandemic, in-person primary data collection was put on hold. As part of the Data Delta innovations team at IDinsight, we began working on building systems and running small experiments to understand how best to implement high-quality phone surveys. Our research culminated in many findings on key processes for executing phone surveys: callback protocols, best times of day to call and phone survey lengths, rapport-building, and reaching women.

Behavioral Nudges

Evaluating the role of behavioral messages at improving maternal health outcomes

South AfricaRCTMaternal Health

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With IDinsight, I worked on the design of an ongoing randomized controlled trial that aims to assess the effectiveness of different types of behavioral messages on knowledge, attitudes and behaviors of pregnant and lactating women in South Africa. The study evaluates different messaging techniques that MomConnect, a maternal mobile health platform, can use to improve maternal health outcomes.
Evaluating the effectiveness of behavioral nudges at the honest reporting of COVID-19 symptoms

South AfricaRCTCOVID-19

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I worked on the analysis of a randomized controlled trial that IDinsight and Praekelt designed to understand the role of behavioral nudges in the honest reporting of COVID-19 symptoms by university-goers in South Africa. We found that an appeal for university-goers to be honest was most effective at increasing honesty in mobile HealthCheck daily self-assessment surveys. The results of this RCT highlight the small impacts that low-cost, digital interventions can have.