Hamrouni Daghbagi, Radhouane Hasni, Mehdi Ben Jebli
{"title":"The assessment of economic complexity and financial development on environmental quality: evidence for panel cointegration approach","authors":"Hamrouni Daghbagi, Radhouane Hasni, Mehdi Ben Jebli","doi":"10.1007/s11869-025-01757-w","DOIUrl":null,"url":null,"abstract":"<div><p>The environment plays a crucial role in mitigating ecological catastrophes by safeguarding the atmosphere. Environmental quality in developed nations is influenced by various factors, with economic complexity and financial development indices standing out prominently among other influencing factors. This study investigates the impact of economic complexity (specifically, trade and technology) and financial development (including global, institutional, and market indices) on carbon dioxide (CO<sub>2</sub>) emissions within a panel of G20 countries using multiple models. Real GDP, along with renewable and non-renewable energy consumption, serves as explanatory variables in the empirical modeling. Employing panel cointegration techniques, the study covers the period from 1999 to 2021. Empirical findings reveal that all variables are integrated of order one, and the cross-sectional dependence test (CD) suggests the application of first-generation unit root tests. Pedroni cointegration tests further confirm long-run cointegration in all models. The Fully modified OLS (FMOLS) and the Canonical Cointegrating Regression (CCR) long-run estimations indicate that global, institutional, and market financial indices, as well as the economic complexity index of trade, are associated with decreased CO2 emissions. Conversely, the economic complexity index of technology is linked to increased CO2 emissions in the long run. Interaction variables linking financial development indices with economic complexity indices have demonstrated a significant and negative impact on CO2 emissions. These results carry important policy implications, suggesting that G20 countries should prioritize export diversification toward more complex, energy-efficient products and leverage financial development to support structural transformation. Additionally, by using financial tools to enhance technological sophistication (e.g., patent quality), governments can help reverse the adverse effects of technological complexity on the environment, thereby fostering long-term CO₂ mitigation.</p></div>","PeriodicalId":49109,"journal":{"name":"Air Quality Atmosphere and Health","volume":"18 7","pages":"2111 - 2126"},"PeriodicalIF":2.9000,"publicationDate":"2025-06-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Air Quality Atmosphere and Health","FirstCategoryId":"93","ListUrlMain":"https://link.springer.com/article/10.1007/s11869-025-01757-w","RegionNum":4,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"ENVIRONMENTAL SCIENCES","Score":null,"Total":0}
引用次数: 0
Abstract
The environment plays a crucial role in mitigating ecological catastrophes by safeguarding the atmosphere. Environmental quality in developed nations is influenced by various factors, with economic complexity and financial development indices standing out prominently among other influencing factors. This study investigates the impact of economic complexity (specifically, trade and technology) and financial development (including global, institutional, and market indices) on carbon dioxide (CO2) emissions within a panel of G20 countries using multiple models. Real GDP, along with renewable and non-renewable energy consumption, serves as explanatory variables in the empirical modeling. Employing panel cointegration techniques, the study covers the period from 1999 to 2021. Empirical findings reveal that all variables are integrated of order one, and the cross-sectional dependence test (CD) suggests the application of first-generation unit root tests. Pedroni cointegration tests further confirm long-run cointegration in all models. The Fully modified OLS (FMOLS) and the Canonical Cointegrating Regression (CCR) long-run estimations indicate that global, institutional, and market financial indices, as well as the economic complexity index of trade, are associated with decreased CO2 emissions. Conversely, the economic complexity index of technology is linked to increased CO2 emissions in the long run. Interaction variables linking financial development indices with economic complexity indices have demonstrated a significant and negative impact on CO2 emissions. These results carry important policy implications, suggesting that G20 countries should prioritize export diversification toward more complex, energy-efficient products and leverage financial development to support structural transformation. Additionally, by using financial tools to enhance technological sophistication (e.g., patent quality), governments can help reverse the adverse effects of technological complexity on the environment, thereby fostering long-term CO₂ mitigation.
期刊介绍：
Air Quality, Atmosphere, and Health is a multidisciplinary journal which, by its very name, illustrates the broad range of work it publishes and which focuses on atmospheric consequences of human activities and their implications for human and ecological health.
It offers research papers, critical literature reviews and commentaries, as well as special issues devoted to topical subjects or themes.
International in scope, the journal presents papers that inform and stimulate a global readership, as the topic addressed are global in their import. Consequently, we do not encourage submission of papers involving local data that relate to local problems. Unless they demonstrate wide applicability, these are better submitted to national or regional journals.
Air Quality, Atmosphere & Health addresses such topics as acid precipitation; airborne particulate matter; air quality monitoring and management; exposure assessment; risk assessment; indoor air quality; atmospheric chemistry; atmospheric modeling and prediction; air pollution climatology; climate change and air quality; air pollution measurement; atmospheric impact assessment; forest-fire emissions; atmospheric science; greenhouse gases; health and ecological effects; clean air technology; regional and global change and satellite measurements.
This journal benefits a diverse audience of researchers, public health officials and policy makers addressing problems that call for solutions based in evidence from atmospheric and exposure assessment scientists, epidemiologists, and risk assessors. Publication in the journal affords the opportunity to reach beyond defined disciplinary niches to this broader readership.
求助内容：
应助结果提醒方式：
京公网安备 11010802042870号
