This paper samples the data of 138 countries during the 1971–2007 period, and performs an empirical test to validate the relationship between carbon dioxide emissions and economic growth. It first performs panel data analysis and quantile regression analysis to estimate the long-run elasticity relationships, and then analyzes the short-run error correction model to verify the causal relationship between the two. The empirical results indicate the following. (1) The long-run relationship between global carbon dioxide emissions and GDP is stable, with 32.6% of the sampled countries showing cross-coupling of the two (with an elasticity value of greater than 1), 47.1% reporting relative-decoupling (with an elasticity value between 0 and 1), and 20.3% seeing absolute-decoupling (with an elasticity value of smaller than 0). (2) The quantile regression shows that long-run elasticity declines along with the rise of carbon dioxide emission quantiles. In other words, cross-coupling turns into relative-decoupling. (3) The analysis of short-run panel data and quantile regressions mostly support the feedback relationship between carbon dioxide emissions growth and economic growth. This is consistent with the hypothesis developed by Kuznets. (4) According to the results of the quantile regression, the higher the quantiles, the faster and more stable of the short-run error-correction mechanism of the adjustments from short-run disequilibrium to long-run equilibrium. (5) Under the low-quantile carbon dioxide emissions growth and economic growth, the relationship between these two is not stable of the short-run disequilibrium adjustments in the error-correction adjustment process. However, the relationship between these two is steady and feedback in the case of high quantiles. Therefore, the first priority to combat global warming is to focus on the countries with high economic growth and high carbon dioxide emissions growth.
Quality & Quantity – Springer Journals
Published: Sep 7, 2011
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