My research lies at the intersection of applied microeconomics and finance. I am broadly interested in how the organization of places (cities, neighborhoods, and markets) shapes opportunities, financial behavior, and decision-making. I use a range of empirical tools, including spatial econometrics, natural language processing, and causal inference, to study questions across different domains.
Corporate Homeownership and Economic Mobility
[MASTERS THESIS] Uncertainty in RBI Communication and Time-Varying Spillovers in India's Financial Markets
This paper studies how uncertainty in the Reserve Bank of India's communication (RBIC) affects Indian financial markets. We focus on equity returns, the rupee–dollar exchange rate, and government bond returns over the period April 2014 to June 2024. To allow the impact of communication uncertainty to change over time, we use a Bayesian time-varying parameter VAR with stochastic volatility (TVP–VAR–SV), instead of a standard VAR with fixed coefficients. Using the MPNet transformer model, we first make a text-based uncertainty index from RBI policy statements. This index captures how RBI expresses uncertainity in their communication.
Our results show that when RBIC expresses the uncertainity, equity returns tend to fall over short horizons. In contrast, the effects on the exchange rate and government bond returns are smaller and estimated less precisely. When we compare the TVP–VAR–SV model to a traditional constant-parameter VAR, we see that the time-varying model shows sharper, state-dependent, and upfront responses to communication uncertainty, as well as limited spillovers between markets. This suggests that standard static models may understate how policy communication uncertainty influences financial prices beyond the initial announcement window. The findings highlight the importance of clear and consistent RBI communication for limiting excess volatility, especially in the equity market, and provide guidance for investors managing risks related to policy uncertainty.