Research
Research
Abstract: I study the aggregate and distributional effects of clean energy subsidies on U.S. residential rooftop solar adoption. Using installation-level data, I estimate learning spillovers and quantify learning elasticities to discipline a heterogeneous agent general equilibrium model with incomplete markets and endogenous cost declines. Calibrated to U.S. data, the model evaluates how alternative subsidy designs and financing schemes affect adoption, aggregate welfare, and the distribution of gains across households. Uniform refundable subsidies financed by flat labor income taxes raise aggregate welfare and accelerate adoption, while income caps or nonrefundable credits reduce aggregate efficiency and can unintentionally harm lower-wealth households by slowing adoption. When local pollution damages are incorporated, subsidies become strongly progressive and universally welfare-improving. Accounting for dynamic learning and pollution externalities shows that clean energy subsidies can enhance both efficiency and equity, challenging the view that they are inherently regressive.
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.