Nonlinear pricing and taxation complicate economic decisions by creating multiple marginal prices for the same good. This paper provides a framework to uncover consumers’ perceived price of nonlinear price schedules. I exploit price variation at spatial discontinuities in electricity service areas, where households in the same city experience substantially different nonlinear pricing. Using household-level panel data from administrative records, I find strong evidence that consumers respond to average price rather than marginal or expected marginal price. This suboptimizing behavior makes nonlinear pricing unsuccessful in achieving its policy goal of energy conservation and critically changes the welfare implications of nonlinear pricing.

This paper analyzes "attribute-based regulations," in which regulatory compliance depends upon some secondary attribute that is not the intended target of the regulation. For example, in many countries, fuel-economy standards mandate that vehicles have a certain fuel economy, but heavier or larger vehicles are allowed to meet a lower standard. Such policies create perverse incentives to distort the attribute upon which compliance depends. We develop a theoretical framework to predict how actors will respond to attribute-based regulations and to characterize the welfare implications of these responses. To test our theoretical predictions, we exploit quasi-experimental variation in Japanese fuel economy regulations, under which fuel-economy targets are downward-sloping step functions of vehicle weight. Our bunching analysis reveals large distortions to vehicle weight induced by the policy. We then leverage panel data on vehicle redesigns to empirically investigate the welfare implications of attribute-basing, including both potential benefits and likely costs.

We develop a framework to estimate willingness to pay for clean air from defensive investments on differentiated products. Applying this framework to scanner data on air purifier sales in China, we find that a household is willing to pay $1.34 annually to remove 1 μg/m3 of air pollution (PM10) and $32.7 annually to eliminate the pollution induced by the Huai River heating policy. Substantial heterogeneity is explained by income and exposure to information on air pollution. Using these estimates, we evaluate various environmental policies and quantify the value of recent air quality improvements since China declared a war on pollution in 2014.

We study the investment effects of market integration on renewable energy expansion. Our theory highlights that market integration not only improves allocative efficiency by gains from trade but also incentivizes new investment in renewable power plants. To test our theoretical predictions, we examine how recent grid expansions in the Chilean electricity market changed electricity production, wholesale prices, generation costs, and renewable investments. We then build a structural model of power plant entry to quantify the impact of market integration with and without the investment effects. We find that the market integration in Chile increased solar generation by around 180%, saved generation costs by 8%, and reduced carbon emissions by 5%. A substantial amount of renewable entry would not have occurred in the absence of market integration. Our findings suggest that ignoring these investment effects would substantially understate the benefits of market integration and its important role in expanding renewable energy.