Bio
Welcome! I am a Ph.D. candidate in the Department of Economics at University College London.
I work on econometrics, empirical industrial organization, and computational economics.
I will be on the 2025-26 job market.
Curriculum Vitae (updated March 2026)
Working Papers
Job Market Paper
Abstract (click to expand): Estimation and counterfactual analysis in dynamic structural models rely on assumptions about the dynamic process of latent variables, which may be misspecified. We propose a framework to quantify the sensitivity of scalar parameters of interest (e.g., welfare, elasticity) to such assumptions. We derive bounds on the scalar parameter by perturbing a reference dynamic process, while imposing a stationarity condition for time-homogeneous models or a Markovian condition for time-inhomogeneous models. The bounds are the solutions to optimization problems, for which we derive a computationally tractable dual formulation. We establish consistency, convergence rate, and asymptotic distribution for the estimator of the bounds. We demonstrate the approach with two applications: an infinite-horizon dynamic demand model for new cars in the United Kingdom, Germany, and France, and a finite-horizon dynamic labor supply model for taxi drivers in New York City. In the car application, perturbed price elasticities deviate by at most 15.24% from the reference elasticities, while perturbed estimates of consumer surplus from an additional $3,000 electric vehicle subsidy vary by up to 102.75%. In the labor supply application, the perturbed Frisch labor supply elasticity deviates by at most 76.83% for weekday drivers and 42.84% for weekend drivers.
Current Version: June 2025
Abstract (click to expand): Estimation and counterfactual experiments in dynamic discrete choice models with large state spaces pose computational difficulties. This paper develops a novel model-adaptive approach to solve the linear system of fixed point equations of the policy valuation operator. We propose a model-adaptive sieve space, constructed by iteratively augmenting the space with the residual from the previous iteration. We show both theoretically and numerically that model-adaptive sieves dramatically improve performance. In particular, the approximation error decays at a superlinear rate in the sieve dimension, unlike a linear rate achieved using conventional methods. Our method works for both conditional choice probability estimators and full-solution estimators with policy iteration. We apply the method to analyze consumer demand for laundry detergent using Kantar's Worldpanel Take Home data. On average, our method is 51.5% faster than conventional methods in solving the dynamic programming problem, making the Bayesian MCMC estimator computationally feasible.
(with Lichao Chen, and Lars Nesheim)
Current Version: March 2026
Abstract (click to expand): The European Union Emissions Trading System is set to substantially increase the effective carbon price faced by airlines. To quantify the impact of this carbon regulation on the European airline industry, we estimate a two-stage model of airline competition with endogenous route entry and pricing using European data on market shares and prices. Counterfactual simulations reveal that the impacts of carbon pricing are highly asymmetric across carrier types and market segments: network contraction is most severe for regional carriers, whose flight frequencies decline by up to 73%, while low-cost carriers' networks remain comparatively resilient. The simulations also show that the policy redistributes welfare geographically, with consumer surplus in medium- and long-haul markets declining by up to 86%, compared with up to 45% in short-haul markets. We find that the tax burden falls predominantly on airlines, whose profits decline by 12--56% across scenarios, while carbon tax revenue of $0.7--2.3 billion and a social value of avoided CO2 emissions of $0.37--1.09 billion partially offset the welfare losses. These results demonstrate that carbon regulation can achieve meaningful environmental gains in airline markets, though at significant cost to industry profits and consumer welfare.
Work in Progress
Multi-industry Dynamic Spatial Competition: Spillover Effects and Land Price
(with Victor Aguirregabiria and Lars Nesheim)
Sequential Estimation of Dynamic Discrete Choice Models with Unobserved Heterogeneity
(with Hiro Kasahara and Katsumi Shimotsu)
This website is adapted from Gautam Rao’s website.
