The DOI matches its Crossref record; 5 of the 5 references it cites were found in a registry or an index.
An empirical analysis of the household consumption-induced carbon emissions in China
Abstract
Abstract As China is becoming a domestic demand oriented economy, it is pertinent to address its household consumption-induced carbon emissions for ensuring environmental sustainability. Besides, managing the household consumption-induced carbon emissions is vital to the attainment of the nation's carbon neutrality agenda of 2060. Hence, this study examines the effects of household consumption on carbon emissions using the Chinese provincial data from 1995 to 2017. The third-generation unit root and cointegration tests are employed to account for structural breaks. Moreover, simultaneously accounting for cross-sectional dependency and slope heterogeneity concerns, the short- and long-run elasticities of carbon emissions are predicted using the pooled mean group, the common correlated effects mean group and the recently developed cross-sectional augmented autoregressive distributed lag estimators. The results, in a nutshell, reveal that household consumption attributes to greater carbon emissions. Apart from household consumption, similar adverse environmental impacts of financial development are ascertained. In contrast, technological innovation and renewable energy consumption are found to curb the carbon emissions. In line with the findings, it is recommended that household consumption of direct and indirect energy should ideally be sourced from renewable resources whereby the adverse environmental impacts of household consumption in China can be reduced. Thus, investment in renewable energy production could be a key energy policy for China. Besides, levying a carbon tax on energy-intensive commodities can also be a means to further reduce the household-consumption induced carbon emissions.
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Cites
Testing for unit roots in heterogeneous panels
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Testing Weak Cross-Sectional Dependence in Large Panels
Pesaran, M. H. (2015) · Econometric Reviews · doi:10.1080/07474938.2014.956623 · Cited by 2,950
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Self-citationElzen, M. D., Fekete, H., Höhne, N., Admiraal, A., Forsell, N., Hof, A. F., Olivier, J. G. J., Roelfsema, M., & van Soest, H. (2016) · Energy Policy · doi:10.1016/j.enpol.2015.11.030 · Cited by 237
Cited by
Ma, Q., Tariq, M., Mahmood, H., & Khan, Z. (2022) · Technology in Society · doi:10.1016/j.techsoc.2022.101910 · Cited by 493
Self-citationMa, Q., Murshed, M., & Khan, Z. (2021) · Energy Policy · doi:10.1016/j.enpol.2021.112345 · Cited by 365
Self-citationQin, L., Raheem, S., Murshed, M., Miao, X., Khan, Z., & Kirikkaleli, D. (2021) · Sustainable Development · doi:10.1002/sd.2208 · Cited by 346
Self-citationMurshed, M., Ahmed, Z., Alam, M. S., Mahmood, H., Rehman, A., & Dagar, V. (2021) · Environmental Science and Pollution Research · doi:10.1007/s11356-021-15352-w · Cited by 179
Self-citationCan artificial intelligence achieve carbon neutrality? Evidence from a quasi-natural experiment
Chen, S., Zhang, S., Zeng, Q., Ao, J., Chen, X., & Zhang, S. (2023) · Frontiers in Ecology and Evolution · doi:10.3389/fevo.2023.1151017 · Cited by 23
Metadata
- Authors
- Liu, J., Murshed, M., Chen, F., Shahbaz, M., Kirikkaleli, D., & Khan, Z.
- Venue
- Sustainable Production and Consumption
- Publisher
- Elsevier BV
- Published
- 2021-04
- Volume
- 26
- Pages
- 943-957
- ISSN
- 2352-5509 (ISSN-L)
- OpenAlex
- W3120426117
- Cited by
- 202
- References
- 5
- FWCI
- 30.78
- Type
- journal article
- Language
- en
- Open access
- closed
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