MIT Joint Program on the Science and Policy of Global Change
Abstract
Abstract in HTML and technical report in PDF available on the Massachusetts Institute of Technology Joint Program on the Science and Policy of Global Change website (http://mit.edu/globalchange/www/).We develop a forward-looking version of the MIT Emissions Prediction and Policy Analysis (EPPA) model, and apply it to examine the economic implications of proposals in the U.S. Congress to limit greenhouse gas (GHG) emissions. We find that the abatement path and CO2-equivalent (CO2-e) price in the forward-looking model are quite similar to that of the recursive model, implying that the simulation of banking behavior in the recursive model by forcing the CO2-e price to rise at the discount rate approximates fairly well the banking result obtained with the forward-looking model. We find, however, that shocks in consumption path are smoothed out in the forward-looking model and that the lifetime welfare cost of GHG policy is lower than in the recursive model, results we would expect to find given that the forward-looking model can fully optimize over time. The forward-looking model allows us to explore issues for which it is uniquely well-suited, including revenue-recycling, early action crediting, and the role of a technology backstop. We find (1) capital tax recycling to be more welfare-cost reducing than labor tax recycling because of its long term effect on economic growth, (2) potentially substantial incentives for early action credits relative to emission levels in years after a policy is announced but before it is implemented that, however, when spread over the full horizon of the policy do not have a substantial effect on lifetime welfare cost or the CO2-e price, and (3) strong effects on estimates of near-term welfare costs depending on exactly how a backstop technology is represented, indicating the problematic aspects of focusing on short-term welfare costs in a forward-looking model unless there is some confidence that the backstop technology is realistically represented.This study received support from the MIT Joint Program on the Science and Policy of Global Change, which is funded by a consortium of government, industry and foundation sponsors
