Affiliations 

  • 1 School of Economics and Management, Guangdong University of Petrochemical Technology (GUTP), Maoming, 525000, China
  • 2 School of Accounting and Finance, Faculty of Business and Law, Taylor's University Malaysia, Subang Jaya, Malaysia
  • 3 School of Finance and Accounting, Fuzhou University of International Studies and Trade, Fuzhou, China. jianfengsheng@fzfu.edu.cn
Environ Sci Pollut Res Int, 2023 Mar;30(15):42753-42765.
PMID: 34652619 DOI: 10.1007/s11356-021-16818-7

Abstract

There is a shred of evidence of environmental degradation in the form of carbon emissions to behave differently when tested with different macroeconomic variables. This paper aims to examine the long-run and short-run association between natural resource rent, financial development, and urbanization on carbon emission from the context of the USA during 1995-2015 with the help of a contemporary and innovative approach named quantile autoregressive distributed lagged model (QARDL). The stated approach is applied due to the fact that non-linearity is observed for the study variables. The findings indicated that the higher financial development (0.304), natural resource rent (0.102), and urbanization (0.489) have a positive impact on the environmental degradation in the region of USA during long-run estimation in the stated quantiles of the study. This would indicate that higher financial development, urbanization, and natural resources are putting more environmental pressure on the economy of the USA. Similarly, the findings under short-run estimation confirm that past and lagged values of carbon emission, financial development, natural resource rent, and urbanization are significantly determining the current values of the carbon emission. For this reason, it is suggested that the government requires some immediate steps of the USA to control the harmful effect of such financial development, more urbanization, and higher natural resource rent as well. This would indicate the reflection of some green strategies in all three explanatory variables to generate some fruitful environmental outcomes.

* Title and MeSH Headings from MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine.