The effect of EPU, trade policy, and financial regulation on CO2 emissions in the United States: evidence from wavelet coherence and frequency domain causality techniques


Kirikkaleli D., Alola A. A.

Carbon Management, vol.13, no.1, pp.69-77, 2022 (SCI-Expanded) identifier

  • Publication Type: Article / Article
  • Volume: 13 Issue: 1
  • Publication Date: 2022
  • Doi Number: 10.1080/17583004.2021.2014361
  • Journal Name: Carbon Management
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Social Sciences Citation Index (SSCI), Scopus, Academic Search Premier, CAB Abstracts, Chemical Abstracts Core, Compendex, Environment Index, Greenfile, INSPEC, Veterinary Science Database, Directory of Open Access Journals
  • Page Numbers: pp.69-77
  • Keywords: CO2 emission, financial regulation, trade policy, uncertainty, United States
  • Istanbul Gelisim University Affiliated: Yes

Abstract

© 2022 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group.The present study unearths the causal effect of economic policy uncertainty (EPU), trade policies, and financial regulation on CO2 emissions in the United States. Based on this aim, the frequency domain causality and wavelet coherence tests are employed while answering the following questions: (i) Do EPU, trade policy, and financial regulation lead to CO2 emission in the United States, and (ii) if so, why? The findings from wavelet coherence reveal that changes in EPU, trade policies and financial regulation significantly lead to changes in CO2 emissions at different frequency levels, meaning that EPU, trade policies, and financial regulation are important predictors for the CO2 emission in the United States. The consistency of the findings from wavelet coherence is confirmed by the outcomes of frequency domain causality. To the best of our knowledge, until now, no study has explored the causal effect of economic policy uncertainty, trade policies, and financial regulation on the CO2 emission in the United States using single data set and wavelet coherence approach, which allows capturing both the long and short-run causality among the time series variables while combining time and frequency domain causality approaches. Therefore, the present study is likely to attract great interest from policy-makers and researchers in this field. At the same time, it is likely to start a new debate.