Working Paper: NBER ID: w15239
Authors: Corbett A. Grainger; Charles D. Kolstad
Abstract: We use the 2003 Consumer Expenditure Survey and emissions estimates from an input-output model to estimate the incidence of a price on carbon induced by a cap-and-trade program or carbon tax in the US context. We present results on how much difference income deciles pay for a carbon tax as well as which industries see the largest increase in costs due to a carbon tax. We illustrate the main determinant of the regressivity: consumption patterns for energy-intensive goods. We find that a policy targeting CO2 from energy consumption is more regressive than a price on all emissions. Furthermore, on a per-capita basis a carbon price is much more regressive than calculations at the household level. We discuss policy options to offset the adverse distributional effects of a carbon emissions policy.
Keywords: carbon pricing; regressivity; consumer expenditure; income distribution
JEL Codes: H22; Q43; Q5; Q52; Q53; Q54; Q58
Edges that are evidenced by causal inference methods are in orange, and the rest are in light blue.
| Cause | Effect |
|---|---|
| Implementation of a carbon price (Q58) | Economic burden on consumers, workers, or shareholders (H22) |
| Carbon price (Q31) | Burden as a percentage of annual income for lower-income groups (H22) |
| Carbon price (Q31) | Regressivity of the policy (H23) |
| Carbon price (Q31) | Average annual payment for lowest income quintile (D31) |
| Carbon price (Q31) | Average annual payment for highest income quintile (D31) |
| Direct energy consumption (Q41) | Regressivity of a carbon price (H23) |
| Measurement of burden in terms of annual income (J17) | Regressivity of carbon pricing (H23) |
| Measurement of burden in terms of lifetime income (J17) | Regressivity of carbon pricing (H23) |
| Targeted revenue recycling strategies (H23) | Mitigation of regressivity of carbon pricing (H23) |