Abstract
This paper investigates the long-term dynamic cross-correlation evolution between US economic policy uncertainty index (USEPU) and Guangdong carbon emission trading price (GDCP) from the multifractal detrended cross-correlation analysis (MF-DCCA) perspective. With the calculation of correlation statistics and fluctuation function, the beginning procedures of MF-DCCA, we find that the cross-correlation between USEPU and GDCP is significant and presents power law property. Also, with the Hurst exponent, we find that the long-horizon correlations between series are persistent. Moreover, we perform Rényi exponent and spectrum singularity check. The empirical findings reveal that the all the correlations are of multifractality and the correlation of GDCP holds the highest degree.
Highlights
It is well acknowledged that climate change is the most challenging task the human being has ever encountered
We find the existence of long-horizon cross-correlation between US economic policy uncertainty and Guangdong carbon emission trading price
We employ the Hurst exponent as the key parameter to check the persistence of correlation between Guangdong carbon emission trading price (GDCP) and US economic policy uncertainty index (USEPU)
Summary
It is well acknowledged that climate change is the most challenging task the human being has ever encountered. As an effective solution for carbon emission reduction, carbon emission trading market has been widely accepted by many countries [1] With this view, numerous studies contribute to the carbon emission trading field with regard to the mechanism and consequences of carbon emission trading market [2,3,4,5,6,7,8,9,10,11,12,13,14]. Due to the huge impact of economic policy changes, several studies link economic policy uncertainty with carbon emissions to check the correlations between them. Adams et al [31] took an investigation of economic policy uncertainty and carbon emission along with energy consumption through the autoregressive model
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