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Exploring the impacts of education and unemployment on CO2 emissions

Bibliographic Data

ID15068119
AuthorsYing Xin (0000-0001-7591-9423, Northeast Normal University), Xin Ying (Northeast Normal University), Shuobin Yang (Northeast Normal University, corresponding author), Muhammad Faisal Rasheed (0000-0002-9940-5731, University of Central Punjab)
Year2023
Volume36
Issue2
Publication date2023-07-10
Peer ReviewedYes
Open AccessYes
TypeARTICLE
VenueEconomic Research-Ekonomska Istraživanja (JOURNAL)
Journal identifiersISSN: 1331-677X • E-ISSN: 1848-9664
PublisherInforma UK Limited (PUBLISHER • GB)
DOI10.1080/1331677x.2022.2110139
OpenAlexW4292313209
LanguageEN
Citations received7
References cited68

The role of human capital and unemployment has been debated in a limited number of empirical studies that have aimed to study the discipline of environmental sustainability. Therefore, by Employing a reliable autoregressive distributed lag (ARDL) model approach, this study examines the dynamic linkage between education, unemployment, and CO2 emissions, by using the Chinese economy’s dataset from the time period pertaining to 1991–2020. The vivacious side of human capital shows that variables such as literacy rate and the average year of schooling curb CO2 emissions in the long run. Moreover, Human capital results are also based on facts in terms of their magnitude and direction. Also, empirical findings have unfolded that unemployment significantly increases CO2 emissions in the long-run. However, the short-run has estimated that the coefficients of education and unemployment provide similar results. Based on these novel findings, a wide set of economic policies are required and hence suggested for maintaining the environmental quality

Economic growth · Economics · Natural resource economics · Unemployment · Energy, Environment, and Transportation Policies · Energy, Environment, Economic Growth · Environmental Science · Fiscal Policy and Economic Growth

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Unique citing works7
Citations per year2,33
Citation span2023 - 2025 (3)
Citation velocityrecent
Highly citedNo
Citation typesNeutral: 7

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