The economics of US greenhouse gas emissions reduction policy : assessing distributional effects across households and the 50 United States using a recursive dynamic computable general equilibrium (CGE) model

Abstract

The political economy of US climate policy has revolved around state- and district- level distributional economics, and to a lesser extent household-level distribution questions. Many politicians and analysts have suggested that state- and district-level climate policy costs (and their distribution) are a function of local carbon intensity and commensurate electricity price sensitivity. However, other studies have suggested that what is most important in determining costs is the means by which revenues from a price on carbon are allocated. This is one of the first studies to analyze these questions simultaneously across all 50 United States, household income classes and a timeframe that reflects most recent policy proposals (2015 - 2050). I use a recursive dynamic computable general equilibrium (CGE) model to estimate the economic effects of a US "cap-and-dividend" policy, by simulating the implementation of the Carbon Limits and Energy for America's Renewal (CLEAR) Act, a bill proposed by Senators Cantwell (D-WA) and Collins (R-ME) in 2009. I find that while carbon intensity and electricity prices are indeed important in determining compliance costs in some states, they are only part of the story. My results suggest that revenue allocation mechanisms and new investment trends related to the switch to low-carbon infrastructure are more influential than incumbent carbon intensity or electricity price impacts in determining the distribution of state-level policy costs. These findings suggest that the current debate in the United States legislature over climate policy, and the constellation of both supporters and dissenters, is based upon an incomplete set of assumptions that must be revisited. Finally, please note that this study does not claim to comprehensively model the CLEAR Act,. nor does it incorporate a number of important data and assumptions, including: the latest data on natural gas resources and prices, the price effects on coal of EPA greenhouse gas and mercury regulations, the most recent trends in renewable energy pricing.