Bio
I’m a postdoctoral researcher at Precision Development (PxD). My research focuses on rural markets for labor, credit, and information; the role of gender in these markets; and farmer adaptation to climate change through these markets.
At PxD, I lead innovative research projects on digital information services to enhance farmers’ climate resilience and gender inclusivity in India, utilizing my skills in research design, data analysis, stakeholder engagement, and fundraising to drive impactful agricultural and developmental solutions.
I received a PhD from the Department of Agricultural and Resource Economics at the University of California, Berkeley in August, 2020.
Curriculum Vitae (Updated November 2024)
Email: vaishnavi.s@gmail.com
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Publications
(with Vivian Hoffmann, Vijayendra Rao, and Upamanyu Datta)
Journal of Development Economics, January 2021
Abstract (click to expand): Provision of low-cost credit to the poor through self-help groups (SHGs) has been embraced as a key poverty-reduction strategy in developing countries, but evidence on the impact of this approach is thin. Using a randomized program rollout over 180 panchayats, we evaluate the impact of a government-led SHG initiative in the Indian state of Bihar. Two years after the start of the program, we find a dramatic increase in SHG membership, borrowing from SHGs, and a corresponding decline in the use of informal credit. Fewer informal lenders are operating in treatment villages, and those who do charge lower interest rates. While these credit market impacts could lead to substantial improvements in economic well-being over time, the short-run impact of the program on such outcomes is modest.
Working Papers
(with Shawn Cole, Tomoko Harigaya)
Working Paper
Abstract (click to expand): Weather-induced risk reduces farmers' incomes, and climate change is increasing such risk. Accurate short-to-medium-range rainfall forecasts, which predict weather between zero and fifteen days ahead, can mitigate this risk by helping farmers better time activities or take precautionary measures. But, this requires that farmers accurately interpret, trust and act on forecasts. Through lab-in-the-field and real-world experiments, this paper evaluates how farmers form beliefs about upcoming weather, and about forecasts themselves as they learn from forecast outcomes. Our findings indicate that (1) there is high demand for voice-call based weather forecasts measured as willingness-to-pay elicited in an incentive-compatible Becker–DeGroot–Marschak, and as take-up of a real-world service; (2) farmers' beliefs about upcoming weather incorporate information in forecasts both in hypothetical decision-making scenarios and in the real-world; (3) farmers update their beliefs about the (in)accuracy of forecasts following incorrect forecasts both in incentivized experimental games with scenarios that mimic real-world decision making, and in the real-world --- relying on forecasts less after erroneous predictions; (4) light-touch information interventions to improve probability comprehension, highlight that forecasts are not guarantees, and make climate change salient do not increase demand, use or trust in the service.
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(with Shawn Cole, Tomoko Harigaya)
Abstract (click to expand): Making customized, accurate weather forecasts more accessible to farmers can aid adaptation to climate change. For farmers to make more informed decisions through the agricultural season with the aid of forecasts, forecasts need to be customized to best communicate information relevant for farmers’ decision-making at different times in the year. Relying on lab-in-the-field and real-world experiments in a mobile-phone based weather forecasting service for farmers in South India, this paper identifies how farmers interpret and act on probabilistic information, and how farmers use and respond to forecasts in varying formats.
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(with Orazio Attanasio, Anjini Kochar, and Aprajit Mahajan)
NBER Working Paper. 31245
Abstract (click to expand): Evaluations of group savings and lending programs have largely focused on average impacts, rather than distributional impacts — finding modest effects on long-term economic well-being. In this paper, we exploit the randomized roll-out of a self-help group lending program in rural Bihar, India (Hoffmann et al., 2021) to demonstrate that well-functioning groups facilitate risk-sharing within rural communities. We find no impact of the program on risk-sharing, measured as a reduction in the variance of consumption growth, in the aggregate. However, the program significantly improves risk-sharing in regions where it had greater institutional capacity and was better implemented. Building on our theoretical framework, we provide evidence of a specific channel of impact: program quality and pre-existing scale improve the quality and functioning of groups, which in turn increase the insurance value of the program to communities.
Ideas for India Blogpost
Working Paper
Abstract (click to expand): A majority of household borrowing in developing countries is from informal lenders. In this paper, I exploit exogenous weather-induced shocks to household credit demand and variation in bank credit supply to demonstrate that informal moneylenders rely on bank credit to ease lending capital constraints in rural India. I document that informal moneylenders use loans from banks as lending capital, and they increase borrowing from banks following weather-induced increases in household credit demand. Moreover, following an equivalent demand shock, districts with higher predicted bank credit supply see larger increases in household borrowing from moneylenders than those with lower predicted bank credit supply — driven by changes in moneylender supply rather than in household demand for credit overall. These results help explain the persistence of informal credit since they indicate that, rather than competing with informal moneylenders, banks effectively collaborate with them.
Ideas of India Podcast
Ideas for India Blogpost
Abstract (click to expand): Federal and state governments in India have relied on women’s Self-Help Groups (SHGs) to provide access to low-cost credit and savings with the dual intent of financial inclusion and women’s empowerment. I focus on one such SHG initiative in the state of Bihar, Jeevika, and exploit the randomized roll-out of the program to evaluate its impact on women’s labor supply. I find that the program had mixed effects across caste categories. Women from more privileged households increased their labor supply, while both women and men from disadvantaged households decreased their labor supply. The decline in labor supply among disadvantaged households is driven by reduced participation in agricultural wage labor, and is associated with an increase in agricultural labor wage rates. These results suggest that better access to finance reduces the need to sell labor as a coping mechanism for women from more vulnerable households; while allowing women from privileged households to increase their labor force participation in more ‘suitable’ occupations.
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