Research

Working Papers 

Entrepreneurs of Emotions: Evidence from Street Vending in India    

Documents: Draft,  Ethics Appendix          

Street vending is an important source of self-employment for the urban poor. I use primary observation, survey, and experimental data from Delhi to study this market. Partnering with street vendors to randomize both prices and the passersby they solicit to try to make sales, I find that even with identical goods, child vendors are 97% more likely to make a sale and earn more than twice that of adult vendors. Despite no differences in valuation for the goods, couples and female customers are 90% and 27% more likely to buy than male customers. Females and couples are 50% more likely to be targeted by vendors than males and are charged higher prices on average (4-38%) than males. I show that these findings are consistent with a model that incorporates altruism and a cost of refusal in the buyer's decision-making. In line with this, I find that passersby are more altruistic towards children than adults in an incentivized dictator game. Additionally, requesting passersby to buy, increases the purchasing probability twofold for adult vendors and fourfold for child vendors. Survey data further confirms that vendors target females or couples, over males, because they consider who would find it harder to refuse. The paper shows that sellers strategically leverage insights about social preferences to influence buyer decision-making and this creates a source of comparative advantage for children in this market.

Credit: IconScout 

Silent Networks: The Role of Inaccurate Beliefs in Reducing Useful Social Interactions  

(with Vatsal Khandelwal),  Draft   Coverage: VoxDev    

Inaccurate beliefs about social norms can reduce useful social interactions and adversely affect an individual’s ability to deal with negative shocks. We implement a randomized controlled trial with low-income workers in urban India who lack access to formal f inancial and healthcare support. We find that the majority of individuals underestimate their community’s willingness to engage in dialogue around financial and mental health concerns. Belief correction leads to a large increase in the demand for network-based assistance. We show that the effects are driven by a reduction in the perceived costs of violating social norms arising due to concerns around reputation and insensitivity. We structurally estimate a network diffusion model and predict that our belief correction intervention will not lead to a shift in equilibrium engagement. Consistent with this, 2 years later, we find that the average beliefs of those exposed to the intervention are significantly more optimistic but still lower than the information delivered in the experiment. We compute the strength of counterfactual interventions needed to generate a sustained effect and find that belief correction can be used to generate both the demand and funding for such policies.

3G Internet and Human Capital Development

(with Samuel Stemper),  Draft     

We study the impact of global expansions in mobile internet access between 2000 and 2018 on student outcomes. We link geospatial data on the rollout of 3G mobile technology with over 2 million student test scores from 82 countries. Our findings indicate that the introduction of 3G coverage leads to substantial increases in smartphone ownership and internet usage among adolescents. Moreover, changes in 3G coverage are associated with significant declines in test scores across all subjects, with magnitudes roughly equivalent to the loss of one-quarter of a year of learning. We find suggestive evidence that a reduction in feelings of belonging, ease of making friends, and self-efficacy may explain these impacts.

Great Expectations: Experimental Evidence from Schools in Pakistan 

(with Minahil Asim and Vatsal Khandelwal),  Draft   Coverage: VoxDev 

We study the effect of communicating student-specific teacher expectations on academic performance. We randomize whether students (a) receive high-performance expectations, (b) are additionally paired with a classmate for encouragement, (c) receive information about past performance, or (d) receive no message. Expectations increase math scores by 0.19σ, with especially large effects among students who randomly received ambitious expectations and were predicted to perform poorly. Information provision has comparably large effects (0.16 σ), particularly in schools with low parental literacy. However, pairing students only improves scores when peers have similar characteristics. Our findings highlight low-cost, sustainable ways of leveraging teachers to improve performance.

The Effects of Classroom-Level Incentives: Experimental Evidence from Kenya  

(with Brandon Tan), Draft

We conduct a randomized experiment in 225 low-cost primary schools in Kenya using non-monetary incentives (certificates and badges) based on performance in Math and English. We randomize over 20,000 students to receive either individual-level, class-level, combined or no incentives. We find that class-level incentives raised test scores by 0.1-0.2 standard deviations (including on non-incentivized subjects), and student and teacher attendance by 14.5% and 6% respectively. Combined incentives are also effective in raising student performance. The effect of individual-level incentives on test scores is statistically indistinguishable from zero.

Publications

The Labor Market and Poverty Impacts of COVID-19 on South Africa, 2020

(with Ihsaan Bassier, Josh Budlender, and Rocco Zizzamia)

The South African Journal of Economics (2023), Covered by The Economist 

Other Works

The Labor Market and Poverty Impacts of COVID-19 on South Africa: An update with NIDS-CRAM Wave 2

(with Ihsaan Bassier, Josh Budlender, and Rocco Zizzamia)

Southern Africa Labour & Development Research (SALDRU) Working Paper, 2020

Estimation of Cross-Unit Spillovers in Supply-side Experiments 


(with Stefan Hut, Mahnaz Islam and Yao Pan)  Public Copy of the Draft


Amazon Science Working Paper, 2023


Presented at: MIT Conference on Digital Experimentation (2023), Amazon Machine Learning Conference (2023), Amazon Economics Summit (2023)