Research

Abstract: Externalities from carbon emissions and market power work in opposite directions: emissions lead to overproduction, while market power leads to underproduction. Addressing only one failure can worsen outcomes. I develop a dynamic general equilibrium model to derive an optimal output tax formula that depends on firm-level market power and carbon intensity. Calibrated to the top five carbon-intensive US sectors, the optimal tax gets significantly smaller than the tax without considering market power, as competition decreases. In a set of policy experiments, I show that policies designed for incorrect market structures could be more detrimental than not intervening at all.

I study the distributional and welfare effects of low-carbon energy technology subsidies in the context of US residential rooftop solar adoption. Although these subsidies are often viewed as regressive because wealthy households capture most of the benefits, I argue that this assessment changes once learning-by-doing spillovers are incorporated. Using installation-level data, I provide new empirical evidence on cost declines from cumulative adoption and estimate learning elasticities to discipline the model. I then develop a heterogeneous-agent DSGE model with incomplete markets, irreversible technology adoption, and adoption-driven cost reductions. Calibrated to US data, the model quantifies how subsidies shape adoption patterns, transitional dynamics, and heterogeneous welfare across the income-wealth distribution. Preliminary results suggest that, while pecuniary transfers appear regressive, the technological externalities tilt overall welfare gains toward lower-wealth households. The framework is used to evaluate alternative subsidy designs and financing strategies—such as income-capped credits, emissions taxes, and debt financing—highlighting trade-offs between efficiency, equity, and political feasibility.