Club convergence and clustering of U.S. energy-related CO2 emissions
•Study examines the club convergence of state-level CO2 emissions.•Two stage analysis: club convergence and conditional convergence estimates.•First stage indicates a converging club of twenty-six states.•Second stage, beta-convergence, corroborates club convergence results.•The remaining twenty-two...
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Published in | Resource and energy economics Vol. 46; pp. 62 - 84 |
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Main Author | |
Format | Journal Article |
Language | English |
Published |
Elsevier B.V
01.11.2016
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Subjects | |
Online Access | Get full text |
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Summary: | •Study examines the club convergence of state-level CO2 emissions.•Two stage analysis: club convergence and conditional convergence estimates.•First stage indicates a converging club of twenty-six states.•Second stage, beta-convergence, corroborates club convergence results.•The remaining twenty-two states’ emissions are diverging.
This study examines the convergence of energy-related carbon dioxide emissions among a panel of U.S. states between the period 1960–2010. This examination is carried out by means of a two-stage procedure. In the first stage, we conduct an endogenous grouping, regression-based convergence test. Unlike previous studies, this methodology endogenously identifies groups of states with emissions that are converging to a similar steady state growth path over time. In the second stage, we evaluate the conditional rate of convergence for the whole sample and for each club using panel data, fixed effects models that control for unobserved, time-invariant heterogeneous effects. More specifically, we examine the rates of convergence conditional on certain structural and non-structural characteristics of the state economy. Results from stage one and stage two suggest that one group of twenty-six states is converging to a unique steady-state equilibrium, and otherwise, the remaining states are diverging. Finally, we discuss different policy approaches to mitigating carbon dioxide emissions based on the club convergence hypothesis. |
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ISSN: | 0928-7655 1873-0221 |
DOI: | 10.1016/j.reseneeco.2016.09.001 |