The DOI matches its Crossref record; 3 of the 3 references it cites were found in a registry or an index.
How does energy consumption affect China's urbanization? New evidence from dynamic threshold panel models
Open accessAbstract
Energy consumption may play different roles at different stages of urbanization and economic growth. Given China's rapid economic development and urbanization process, this study tries to explore the possible nonlinear relationship between energy consumption and urbanization in China. Against the background of promoting new-type urbanization, the level of China's urbanization is evaluated comprehensively using the entropy method. A newly-developed dynamic threshold panel model is employed to examine the nexus of energy consumption and comprehensive urbanization with full consideration of heterogeneous characteristics. The Panel Data Vector Autoregression, or PVAR, model is also used to estimate the direct effects of various energy consumption patterns on the urbanization. The empirical results indicate that the nexus of energy consumption and urbanization is indeed nonlinear and that energy consumption is conducive to promote China's urbanization at the current stage of development. However, the positive effect decreases when there is an increase in energy consumption intensity and energy consumption scale, whereas the effect increases with the promotion of energy consumption structure.
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
Initial conditions and moment restrictions in dynamic panel data models
Blundell, R., & Bond, S. (1998) · Journal of Econometrics · doi:10.1016/s0304-4076(98)00009-8 · Cited by 22,571
Another look at the instrumental variable estimation of error-components models
Arellano, M., & Bover, O. (1995) · Journal of Econometrics · doi:10.1016/0304-4076(94)01642-d · Cited by 19,880
Biases in dynamic models with fixed effects
Nickell, S. (1981) · Econometrica · doi:10.2307/1911408 · Cited by 8,735
Cited by
Fang, Z., Razzaq, A., Mohsin, M., & Irfan, M. (2022) · Technology in Society · doi:10.1016/j.techsoc.2021.101844 · Cited by 380
Yang, X., Zhang, J., Ren, S., & Ran, Q. (2021) · Journal of Cleaner Production · doi:10.1016/j.jclepro.2020.125015 · Cited by 264
Metadata
- Authors
- Wu, H., Hao, Y., & Weng, J.-H.
- Venue
- Energy Policy
- Publisher
- Elsevier BV
- Published
- 2019-04
- Volume
- 127
- Pages
- 24-38
- ISSN
- 0301-4215 (ISSN-L)
- OpenAlex
- W2904643362
- Cited by
- 280
- References
- 3
- FWCI
- 36.86
- Type
- journal article
- Language
- en
- Open access
- green
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: How does energy consumption affect China's urbanization? New evidence from dynamic threshold panel models. https://app.cochat.ai/papers/10.1016/j.enpol.2018.11.057
- The paper
- Wu, H., Hao, Y., & Weng, J.-H. (2019). How does energy consumption affect China's urbanization? New evidence from dynamic threshold panel models. Energy Policy. https://doi.org/10.1016/j.enpol.2018.11.057
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.