I am an applied microeconomist. My research spans (i) political economy,
where I study how political institutions shape policy design and implementation;
(ii) development and culture, where I study how norms and informal institutions
influence behavior and policy effectiveness; and (iii) gender, where I study
the sources of gender gaps in household decisions and labor market outcomes.
I use both experimental and observational methods, drawing on administrative
data, text-as-data, and machine-learning tools. I currently work on projects
in India, Denmark, and the United Kingdom.
I will join Princeton University as a postdoctoral researcher in September 2026.
This paper examines whether expanding women’s political representation
affects marital practices in rural India. Exploiting the reservation of
village council leadership positions for women under India’s 1992
constitutional amendment, I show that exposure to female leaders delays
marriage by improving women’s economic opportunities, but also increases
dowry payments. The increase in dowry is concentrated in more patriarchal
settings, where the social costs of delayed marriage are higher. The
results suggest that political empowerment can shift marital behavior,
but that its effects are constrained—and partly offset—by entrenched
social norms.
(ii) Government by Discussion: Deliberation, Media, and Policy-Making
This paper studies whether parliamentary deliberation affects policy-making,
and whether its effects depend on public exposure. Using quasi-random variation
from the computerized ballot that determines which policies are discussed during
Question Hour in the Indian Parliament, we show that debated issues are more likely
to appear in subsequent bills and that related bills progress faster through the
legislative process. These effects are substantially stronger when debate receives
media coverage. Reductions in news attention cut the policy impact of debate by
roughly half, implying that public exposure is an important mechanism through which
deliberation shapes policy.
(iii) The Cultural Premium: How Cultural Distance, Economic Contributions and Value Alignment Shape Immigration Attitudes
This paper quantifies a cultural premium in immigration attitudes: the
additional income a culturally distant immigrant must earn to be equally
preferred to a culturally close immigrant for remaining in the host country.
Using a representative survey experiment in the United Kingdom, we estimate
that this premium exceeds £20,000 when the immigrant’s personal values are
unobserved, but falls by 73% when respondents learn that his values align
with UK norms. Information on value alignment also reduces concerns about
cultural erosion by 35%. The findings indicate that opposition to culturally
distant immigrants reflects, to a large extent, beliefs about their underlying
values rather than origin per se.
(iv) Postpartum Depression and the Motherhood Penalty
(with Sonia Bhalotra, N. Meltem Daysal, Louis Fréget, Jonas Cuzulan Hirani, Mircea Trandafir, Miriam Wüst, and Tom Zohar)
This paper studies how postpartum depression affects mothers’ labor-market
trajectories after childbirth. Using Danish administrative records linked to
validated postpartum depression screenings, we show that depressed and
non-depressed mothers follow similar pre-birth employment trends but diverge
sharply after birth, generating persistent employment gaps. These effects are
larger for less educated mothers and for women in less family-friendly jobs.
The results identify postpartum depression as an important and unequal
contributor to the motherhood penalty.
Publications
(i) Exponential Growth Bias in the Prediction of COVID-19 Spread and Economic Expectation
This paper studies exponential growth bias in beliefs about COVID-19
transmission and examines how reducing this bias affects economic expectations
and risky investment. Using four experimental interventions, we show that simple
feedback and forecast information substantially reduce misperceptions about
epidemic growth. Correcting the bias also dampens expectations of macroeconomic
deterioration and reduces risky investment. The results highlight how errors in
processing non-linear growth can shape economic beliefs and choice under uncertainty.
(ii) Exponential-Growth Prediction Bias and Compliance with Safety Measures Related to COVID-19
(with Ritwik Banerjee and Joydeep Bhattacharya; Social Science & Medicine, 2020)
This paper studies exponential-growth prediction bias in beliefs about COVID-19
transmission and its implications for compliance with protective behavior. Using an
incentivized online experiment spanning countries at different stages of the pandemic,
we show that respondents systematically underestimate infection growth, and that larger
bias is associated with lower compliance with safety measures. A simple information
intervention that presents prior case counts in raw numbers rather than graphs
significantly reduces the bias. The findings suggest that how epidemic information
is presented can improve risk perception and public-health behavior.