Economists have long argued that a carbon tax is a cost effective way to reduce greenhouse gas emissions. Increasingly, members of Congress agree. In 2019, seven carbon tax bills were filed in Congress (Kaufman et al., 2019). In addition, the Climate Leadership Council has built bipartisan support for a carbon tax and dividend plan (Baker et al., 2017). In contrast, the Trump Administration is retreating from any climate policy and has taken steps to withdraw from the Paris Accord, citing heavy economic costs to the U.S. economy from meeting the U.S. commitments made during the Obama Administration. In his June 1, 2017 statement on the Accord, for example, the President claimed that the cost to the economy would be “close to \$3 trillion in lost GDP and 6.5 million industrial jobs…” (Trump, 2017). What is the basis for claims about the economic impact of a carbon tax? Economic impacts of a carbon tax typically are estimated using computable general equilibrium (CGE) models (as was done for the report on which Trump based his claims). These models, while helpful, make many simplifying assumptions to remain tractable, including optimization, representative agents, and simplified expectations and dynamics, so at a minimum those estimates would ideally be complemented by empirical evidence on the macroeconomic effects of carbon taxes in practice. With carbon taxes in place in twenty-five countries around the world, including some dating to the early 1990s, empirical analysis of historical experience is now possible. This paper considers carbon taxes in Europe to estimate their impact on GDP and employment.
It is standard to think that corrective taxes, responding to externalities, are generally or always better than regulatory mandates, but in the face of behavioral market failures, that conclusion might not be right. Fuel economy and energy efficiency mandates are possible examples. Because such mandates might produce billions of dollars in annual consumer savings, they might have very high net benefits, complicating the choice between such mandates and externality-correcting taxes (such as carbon taxes). The net benefits of mandates that simultaneously reduce internalities and externalities might exceed the net benefits of taxes that reduce externalities alone, even if mandates turn out to be a highly inefficient way of reducing externalities. An important qualification is that corrective taxes might be designed to reduce both externalities and internalities, in which case they would almost certainly be preferable to a regulatory mandate.
Since 1970, transportation, power generation, and manufacturing have dramatically transformed as air pollutant emissions have fallen significantly. To evaluate the causal impacts of the Clean Air Act on these changes, we synthesize and review retrospective analyses of air quality regulations. The geographic heterogeneity in regulatory stringency common to many regulations has important implications for emissions, public health, compliance costs, and employment. Cap-and-trade programs have delivered greater emission reductions at lower cost than conventional regulatory mandates, but policy practice has fallen short of the cost-effective ideal. Implementing regulations in imperfectly competitive markets have also influenced the Clean Air Act’s benefits and costs.
This note lays out the basic Susceptible-Infected-Recovered (SIR) epidemiological model of contagion, with a target audience of economists who want a framework for understanding the effects of social distancing and containment policies on the evolution of contagion and interactions with the economy. A key parameter, the asymptomatic rate (the fraction of the infected that are not tested under current guidelines), is not well estimated in the literature because tests for the coronavirus have been targeted at the sick and vulnerable, however it could be estimated by random sampling of the population. In this simple model, different policies that yield the same transmission rate β have the same health outcomes but can have very different economic costs. Thus, one way to frame the economics of shutdown policy is as finding the most efficient policies to achieve a given β, then determining the path of β that trades off the economic cost against the cost of excess lives lost by overwhelming the health care system.