The DOI matches its Crossref record; 56 of the 56 references it cites were found in a registry or an index.
Dynamic linkages between financial inclusion and carbon emissions: Evidence from selected OECD countries
Open accessAbstract
This study analyzes the dynamic linkages between financial inclusion, energy consumption, and carbon emissions taking corruption, infrastructure, and economic growth as control variables. The data of 23 OECD countries covering the period from 2004 to 2017 have been used. The study develops two indexes with the help of Principal Component Analysis; one for financial inclusion and the other for infrastructure. The study also adopts second generation tests for unit root and cross-sectional dependence. To check long-run linkages, this study uses (Dynamic) Common Correlated Effects Estimator technique, also called CS-ARDL, which provides more reliable results. The results indicate positive connections between financial inclusion, energy consumption and carbon emissions. Corruption, infrastructure and economic growth are highly sensitive to carbon emissions. The study provides important points for pollution control and attaining the targets of sustainable development. Efforts are needed on government level to align the financial inclusion targets with energy usage behavior and environmental policies.
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
A simple panel unit root test in the presence of cross‐section dependence
Pesaran, M. H. (2007) · Journal of Applied Econometrics · doi:10.1002/jae.951 · Cited by 12,787
Economic growth and the environment
Grossman, G. M., & Krueger, A. B. (1995) · The Quarterly Journal of Economics · doi:10.2307/2118443 · Cited by 9,901
Critical Values for Cointegration Tests in Heterogeneous Panels with Multiple Regressors
Pedroni, P. (1999) · Oxford Bulletin of Economics and Statistics · doi:10.1111/1468-0084.61.s1.14 · Cited by 6,726
Awais, A. (2015) · Data Archiving and Networked Services (DANS) · doi:10.17632/zcvgc6m58h.1 · Cited by 6,707
Pooled Mean Group Estimation of Dynamic Heterogeneous Panels
Pesaran, M. H., Shin, Y., & Smith, R. P. (1999) · Journal of the American Statistical Association · doi:10.1080/01621459.1999.10474156 · Cited by 6,683
Pedroni, P. (2004) · Econometric Theory · doi:10.1017/s0266466604203073 · Cited by 6,669
Testing for Error Correction in Panel Data*
Westerlund, J. (2007) · Oxford Bulletin of Economics and Statistics · doi:10.1111/j.1468-0084.2007.00477.x · Cited by 6,113
Spurious regression and residual-based tests for cointegration in panel data
Kao, C. (1999) · Journal of Econometrics · doi:10.1016/s0304-4076(98)00023-2 · Cited by 5,763
Estimating long-run relationships from dynamic heterogeneous panels
Pesaran, M. H., & Smith, R. (1995) · Journal of Econometrics · doi:10.1016/0304-4076(94)01644-f · Cited by 5,479
Frankel, J. A., & Romer, D. (1999) · American Economic Review · doi:10.1257/aer.89.3.379 · Cited by 5,384
Cited by
Ozturk, I., & Ullah, S. (2022) · Resources Conservation and Recycling · doi:10.1016/j.resconrec.2022.106489 · Cited by 480
Qin, L., Raheem, S., Murshed, M., Miao, X., Khan, Z., & Kirikkaleli, D. (2021) · Sustainable Development · doi:10.1002/sd.2208 · Cited by 346
Wang, X., Wang, X., Ren, X., & Wen, F. (2022) · Energy Economics · doi:10.1016/j.eneco.2022.105966 · Cited by 329
Metadata
- Authors
- Zaidi, S. A. H., Hussain, M., & Uz Zaman, Q.
- Venue
- Resources, Environment and Sustainability
- Publisher
- Elsevier BV
- Published
- 2021-06
- Volume
- 4
- Pages
- 100022
- ISSN
- 2666-9161 (ISSN-L)
- OpenAlex
- W3140413211
- Cited by
- 253
- References
- 56
- FWCI
- 36.86
- Type
- journal article
- Language
- en
- Open access
- gold
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
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Dynamic linkages between financial inclusion and carbon emissions: Evidence from selected OECD countries. https://app.cochat.ai/papers/10.1016/j.resenv.2021.100022
- The paper
- Zaidi, S. A. H., Hussain, M., & Uz Zaman, Q. (2021). Dynamic linkages between financial inclusion and carbon emissions: Evidence from selected OECD countries. Resources, Environment and Sustainability. https://doi.org/10.1016/j.resenv.2021.100022
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.