The DOI matches its Crossref record; 49 of the 49 references it cites were found in a registry or an index.
Environmental cost of natural resources utilization and economic growth: Can China shift some burden through globalization for sustainable development?
Abstract
This study aims to investigate the relationship between CO 2 emissions in China and its prospective determinants, namely economic growth, globalization, financial development, and natural resources during the period from 1980 to 2017. We present more detailed analyses across multiple econometric approaches within a multivariate system, e.g., the Bayer‐Hanck combined cointegration approach, the ARDL bounds test approach, ARDL estimates in short run and long run, robustness check by cointegration regressions (i.e., FMOLS, DOLS, CCR), and Granger causality approach in the frequency domain. Our results show that economic growth and natural resources have a positive impact on CO 2 emissions in China, although globalization contributes to improving its environmental quality. Meanwhile, there is no statistical evidence that CO 2 emissions in China could be affected by financial development. The causality analysis reveals that globalization, economic growth and natural resources all lead to CO 2 emissions in the long run, while financial development only causes the short‐run CO 2 emissions, which further demonstrate our findings. Such findings are meaningful for policymakers to achieve the sustainable development in China.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Co-integration and error correction: representation, estimation and testing
Engle, R. F., & Granger, C. W. J. (1987) · Econometrica · doi:10.2307/1913236 · Cited by 32,007
Bounds testing approaches to the analysis of level relationships
Pesaran, M. H., Shin, Y., & Smith, R. J. (2001) · Journal of Applied Econometrics · doi:10.1002/jae.616 · Cited by 20,385
Estimation and Hypothesis Testing of Cointegration Vectors in Gaussian Vector Autoregressive Models
Johansen, S. (1991) · Econometrica · doi:10.2307/2938278 · Cited by 11,116
Further Evidence on the Great Crash, the Oil-Price Shock, and the Unit-Root Hypothesis
Zivot, E., & Andrews, D. W. K. (2002) · Journal of Business & Economic Statistics · doi:10.1198/073500102753410372 · Cited by 5,737
A Simple Estimator of Cointegrating Vectors in Higher Order Integrated Systems
Stock, J. H., & Watson, M. W. (1993) · Econometrica · doi:10.2307/2951763 · Cited by 5,013
Statistical Inference in Instrumental Variables Regression with I(1) Processes
Phillips, P. C. B., & Hansen, B. E. (1990) · The Review of Economic Studies · doi:10.2307/2297545 · Cited by 4,909
Error‐correction Mechanism Tests for Cointegration in a Single‐equation Framework
Banerjee, A., Dolado, J., & Mestre, R. (1998) · Journal of Time Series Analysis · doi:10.1111/1467-9892.00091 · Cited by 2,305
How economic growth, renewable electricity and natural resources contribute to CO2 emissions?
Balsalobre-Lorente, D., Shahbaz, M., Roubaud, D., & Farhani, S. (2018) · Energy Policy · doi:10.1016/j.enpol.2017.10.050 · Cited by 1,501
Self-citationBekun, F. V., Alola, A. A., & Sarkodie, S. A. (2019) · Science of The Total Environment · doi:10.1016/j.scitotenv.2018.12.104 · Cited by 1,385
Canonical Cointegrating Regressions
Park, J. Y. (1992) · Econometrica · doi:10.2307/2951679 · Cited by 1,374
Jalil, A., & Feridun, M. (2011) · Energy Economics · doi:10.1016/j.eneco.2010.10.003 · Cited by 1,214
Environment Kuznets curve for CO2 emissions: A cointegration analysis for China
Jalil, A., & Mahmud, S. F. (2009) · Energy Policy · doi:10.1016/j.enpol.2009.07.044 · Cited by 1,208
Shahbaz, M., Nasir, M. A., & Roubaud, D. (2018) · Energy Economics · doi:10.1016/j.eneco.2018.07.020 · Cited by 1,189
Self-citationGlobalization and the Environment: Determinants of Firm Self-Regulation in China
Christmann, P., & Taylor, G. (2001) · Journal of International Business Studies · doi:10.1057/palgrave.jibs.8490976 · Cited by 1,098
The impact of financial development on carbon emissions: An empirical analysis in China
Zhang, Y.-J. (2011) · Energy Policy · doi:10.1016/j.enpol.2011.02.026 · Cited by 1,095
Testing for short- and long-run causality: A frequency-domain approach
Breitung, J., & Candelon, B. (2006) · Journal of Econometrics · doi:10.1016/j.jeconom.2005.02.004 · Cited by 942
Danish, Baloch, M. A., Mahmood, N., & Zhang, J. W. (2019) · Science of The Total Environment · doi:10.1016/j.scitotenv.2019.05.028 · Cited by 939
Combining non‐cointegration tests
Bayer, C., & Hanck, C. (2013) · Journal of Time Series Analysis · doi:10.1111/j.1467-9892.2012.00814.x · Cited by 647
CO2 emissions, energy consumption, trade and income: A comparative analysis of China and India
Jayanthakumaran, K., Verma, R., & Liu, Y. (2012) · Energy Policy · doi:10.1016/j.enpol.2011.12.010 · Cited by 617
Acheampong, A. O., Adams, S., & Boateng, E. (2019) · Science of The Total Environment · doi:10.1016/j.scitotenv.2019.04.353 · Cited by 607
Nasir, M. A., Duc Huynh, T. L., & Xuan Tram, H. T. (2019) · Journal of Environmental Management · doi:10.1016/j.jenvman.2019.03.112 · Cited by 605
Testing for an unstable root in conditional and structural error correction models
Peter Boswijk, H. (1994) · Journal of Econometrics · doi:10.1016/0304-4076(93)01560-9 · Cited by 592
Baloch, M. A., Zhang, J., Iqbal, K., & Iqbal, Z. (2019) · Environmental Science and Pollution Research · doi:10.1007/s11356-018-3992-9 · Cited by 559
Chang, C.-C. (2010) · Applied Energy · doi:10.1016/j.apenergy.2010.05.004 · Cited by 547
Sirunyan, A., Tumasyan, A., Adam, W., Asilar, E., Bergauer, T., Brandstetter, J., Brondolin, E., Dragicevic, M., Erö, J., Flechl, M., et al. (2017) · NOT FOUND REPOSITORY (Indian Institute of Science Bangalore) · doi:10.1140/epjc/s10052-017-4912-8.pdf · Cited by 511
Environmental Kuznets Curve in China: New evidence from dynamic panel analysis
Li, T., Wang, Y., & Zhao, D. (2016) · Energy Policy · doi:10.1016/j.enpol.2016.01.002 · Cited by 436
Socioeconomic impact assessment of China's CO2 emissions peak prior to 2030
Mi, Z., Wei, Y.-M., Wang, B., Meng, J., Liu, Z., Shan, Y., Liu, J., & Guan, D. (2017) · Journal of Cleaner Production · doi:10.1016/j.jclepro.2016.11.055 · Cited by 423
Environmental Kuznets curve for CO2 emissions in China: A spatial panel data approach
Kang, Y.-Q., Zhao, T., & Yang, Y.-Y. (2016) · Ecological Indicators · doi:10.1016/j.ecolind.2015.12.011 · Cited by 413
Environmental Kuznets curve in an open economy: A bounds testing and causality analysis for Tunisia
Shahbaz, M., Khraief, N., Uddin, G. S., & Ozturk, I. (2014) · Renewable and Sustainable Energy Reviews · doi:10.1016/j.rser.2014.03.022 · Cited by 347
Self-citationTHE IMPACT OF GLOBALIZATION ON CO2 EMISSIONS IN CHINA
SHAHBAZ, M., KHAN, S., ALI, A., & BHATTACHARYA, M. (2017) · The Singapore Economic Review · doi:10.1142/s0217590817400331 · Cited by 340
Self-citationGROWTH, FOREIGN DIRECT INVESTMENT, AND THE ENVIRONMENT: EVIDENCE FROM CHINESE CITIES
Cole, M. A., Elliott, R. J. R., & Zhang, J. (2011) · Journal of Regional Science · doi:10.1111/j.1467-9787.2010.00674.x · Cited by 313
Asongu, S. A., Agboola, M. O., Alola, A. A., & Bekun, F. V. (2020) · Science of The Total Environment · doi:10.1016/j.scitotenv.2019.136376 · Cited by 307
Xu, Z., Baloch, M. A., Danish, Meng, F., Zhang, J., & Mahmood, Z. (2018) · Environmental Science and Pollution Research · doi:10.1007/s11356-018-2876-3 · Cited by 262
Modelling carbon emission intensity: Application of artificial neural network
Acheampong, A. O., & Boateng, E. B. (2019) · Journal of Cleaner Production · doi:10.1016/j.jclepro.2019.03.352 · Cited by 256
Ulucak, R., Danish, & Khan, S. U. (2020) · Sustainable Development · doi:10.1002/sd.2041 · Cited by 250
Danish, Saud, S., Baloch, M. A., & Lodhi, R. N. (2018) · Environmental Science and Pollution Research · doi:10.1007/s11356-018-2069-0 · Cited by 181
Using LMDI to analyze the decoupling of carbon dioxide emissions by China's manufacturing industry
Ren, S., Yin, H., & Chen, X. (2014) · Environmental Development · doi:10.1016/j.envdev.2013.11.003 · Cited by 180
Energy consumption and economic growth in China: A multivariate causality test
Wang, Y., Wang, Y., Zhou, J., Zhu, X., & Lu, G. (2011) · Energy Policy · doi:10.1016/j.enpol.2011.04.063 · Cited by 169
Baloch, M. A., Danish, & Meng, F. (2019) · Environmental Science and Pollution Research · doi:10.1007/s11356-019-04317-9 · Cited by 159
Globalization, Macroeconomic Performance, and Monetary Policy
Mishkin, F. S. (2009) · Journal of money credit and banking · doi:10.1111/j.1538-4616.2008.00204.x · Cited by 151
Jian, J., Fan, X., He, P., Xiong, H., & Shen, H. (2019) · Sustainability · doi:10.3390/su11184850 · Cited by 128
Lahiani, A. (2019) · Environmental Science and Pollution Research · doi:10.1007/s11356-019-07467-y · Cited by 114
Financial instability and CO2 emissions: the case of Saudi Arabia
Baloch, M. A., Danish, Meng, F., et al. (2018) · Environmental Science and Pollution Research · doi:10.1007/s11356-018-2654-2 · Cited by 83
Alola, A. A., & Kırıkkaleli, D. (2019) · Environmental Science and Pollution Research · doi:10.1007/s11356-019-06522-y · Cited by 73
Akadırı, S. S., Alola, A. A., Bekun, F. V., & Etokakpan, M. U. (2020) · Environmental Science and Pollution Research · doi:10.1007/s11356-020-08784-3 · Cited by 61
Bekun, F. V., Yalçıner, K., Etokakpan, M. U., & Alola, A. A. (2020) · Environmental Science and Pollution Research · doi:10.1007/s11356-020-08866-2 · Cited by 49
CO 2 EMISSIONS AND REGIONAL INCOME DISPARITY: EVIDENCE FROM CHINA
Guo, L. (2014) · The Singapore Economic Review · doi:10.1142/s0217590814500076 · Cited by 33
The globaliser dragon: how is China changing economic globalisation?
Magalhães, D. T. D. (2018) · Third World Quarterly · doi:10.1080/01436597.2018.1432352 · Cited by 17
Analysis of Nonstationary Change of Annual Maximum Level Records in the Yangtze River Estuary
Li, G., Xiang, X., & Guo, C. (2015) · Advances in Meteorology · doi:10.1155/2016/7205723 · Cited by 12
Cited by
Hao, L.-N., Umar, M., Khan, Z., & Ali, W. (2021) · Science of The Total Environment · doi:10.1016/j.scitotenv.2020.141853 · Cited by 785
Self-citationShen, Y., Su, Z.-W., Malik, M. Y., Umar, M., Khan, Z., & Khan, M. (2021) · Science of The Total Environment · doi:10.1016/j.scitotenv.2020.142538 · Cited by 698
Self-citationShan, S., Genç, S. Y., Kamran, H. W., & Dinca, G. (2021) · Journal of Environmental Management · doi:10.1016/j.jenvman.2021.113004 · Cited by 622
Shao, X., Zhong, Y., Liu, W., & Li, R. Y. M. (2021) · Journal of Environmental Management · doi:10.1016/j.jenvman.2021.113189 · Cited by 429
Cheng, Y., Awan, U., Ahmad, S., & Tan, Z. (2021) · Technological Forecasting and Social Change · doi:10.1016/j.techfore.2020.120398 · Cited by 401
Metadata
- Authors
- Umar, M., Ji, X., Kirikkaleli, D., Shahbaz, M., & Zhou, X.
- Venue
- Sustainable Development
- Publisher
- Wiley
- Published
- 2020-08-19
- Volume
- 28
- Issue
- 6
- Pages
- 1678-1688
- ISSN
- 0968-0802 (ISSN-L)
- 1099-1719
- OpenAlex
- W3068395678
- Cited by
- 386
- References
- 49
- FWCI
- 55.81
- Type
- journal article
- Language
- en
- Open access
- closed
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
