Research

Published Articles


Book Chapters:


Working Papers


While it is well-acknowledged that the gendered division of labor within marriage adversely affects women's allocation of time to market work, there is less evidence on how extant social norms can influence women's work choices pre-marriage. We conduct an experiment on an online marriage market platform that allows us to measure preferences of individuals in partner selection in India.  We find that employed women receive 14.5% less interest from male suitors relative to unemployed women. In addition, women employed in `masculine' occupations are 3.2% less likely to elicit interest from suitors relative to those in `feminine' occupations. Our results highlight the strong effect of gender norms and patriarchy on marital preferences, especially for men hailing from higher castes and northern India, where communities have more traditional gender norms. These findings suggest that expectations regarding returns in the marriage market may influence women's labor market participation and the nature of market work.


We examine employer preferences for hiring men vs women using 160, 000 job ads posted on an online job portal in India, linked with more than 6 million applications. We apply machine learning algorithms on text contained in job ads to predict an employer’s gender preference. We find that advertised wages are lowest in jobs where employers prefer women, even when this preference is implicitly retrieved through the text analysis, and that these jobs also attract a larger share of female applicants. We then systematically uncover what lies beneath these relationships by retrieving words that are predictive of an explicit gender preference, or gendered words, and assigning them to the categories of hard and soft-skills, personality traits, and flexibility. We find that skills related female-gendered words have low returns but attract a higher share of female applicants while male-gendered words indicating decreased flexibility (e.g., frequent travel or unusual working hours) have high returns but result in a smaller share of female applicants. This contributes to a gender earnings gap. Our findings illustrate how gender preferences are partly driven by stereotypes and statistical discrimination. 


Inadequate banking infrastructure can exacerbate inequalities across firms. We exploit a place-based policy at scale – India’s nationwide bank expansion policy in 2005 that incentivized banks to open branches in “underbanked” districts – and employing a regression discontinuity design identify substantial increases in capital expenditures and credit growth of manufacturing establishments post-intervention. We find that establishments most likely to be credit constrained i.e., small, young and those not publicly listed drive these effects. Using novel regulatory data we find evidence in support of two mechanisms – increased hiring of bank officers and physical proximity of lenders to small, informationally opaque borrowers that explain the uptick in capital spending by small firms. 

(Previous version circulated as: Bank Branch Expansions and Capital Investment by Credit-Constrained Firms)


Exploiting President Trump's win in the 2016 Republican primary election, we estimate the impact of the ensuing uncertainty around H-1B immigration policies on the demand for workers in India. Using postings data from the largest Indian jobs platform, we find that firms more reliant on H-1B visas for filling US-based positions increase their postings for India-based jobs immediately after Trump's primary win in June, which led to increased migration policy uncertainty. This surge is attributed to heightened relocation of jobs from the US to India for occupations more amenable to offshoring. India-headquartered firms lead this change and  witness an increase in their exports.


Using nationally representative data on employment and earnings, this paper documents a fall in wage inequality in India over the last two decades. It then examines the role played by increasing minimum wages for the lowest skilled workers in India in contributing to the observed decline. Exploiting regional variation in changes in minimum wages over time in the country, we find that an increase in minimum wages by one percent led to an increase in wages for workers in the lowest quintile by 0.17%. This effect is smaller at upper wage quintiles and insignificant for the highest wage quintile. Counterfactual wage estimations show that the increases in minimum wages explain 26% of the decline in wage inequality. These findings underscore the important role played by rising minimum wages in reducing wage disparities in India.


Using firm and household-level data from India, we establish a positive association between relative female employment and firm size. We find that the proportion of female workers is higher in firms with a larger number of total employees (elasticity of 0.47) and output (elasticity of 0.1). We show that higher benefits and amenities offered by larger firms, like maternity benefits and paid leave, which are likely to be valued more by female workers, with no accompanying increase in the gender wage gap is a plausible mechanism behind our findings. We then exploit a natural experiment in the amendment of labor laws across the Indian states, which increased the firm size thresholds for the applicability of regulatory compliances. Using a difference-in-difference estimation, we find an increase in the proportion of female workers by 13% in treated states vs. control states. One of the channels behind this increase is the accompanying increase in firm size by around 5%, welfare expenses per employee by 13% and no consistent effect on the gender wage gap. Theoretically, we propose a task-based explanation that leads to greater relative demand for women in bigger firms and, consequently, higher investment by them in amenities valued by women leading to ambiguous effects on the gender wage gap.  Our results show that policies that increase firm growth, which in turn increase provision of amenities valued by women (without employer backlash), are likely to increase female employment. 



Work in Progress

1. "The unintended impacts of legislating to handle workplace sexual harassment" (with Sonia Bhalotra, Medha Chatterjee, Daksh Walia)

2. "Bridging the Miles: Spatial Factors in Job Application and Selection" (with Shekhar Tomar)

3. "Restart: Women, career breaks and firm hiring in India" (with Nandhini S)

4. "Improving women’s work opportunities: The role of skills and their complementarities in a digital world" (with Farzana Afridi, Tanu Gupta, Rachel Heath)