Evidence map›Paper›PMID 38236569›Full record

ArticleEnvironmental science and pollution research international2024

The impact of clean energy demonstration province policies on carbon intensity in Chinese counties based on the multi-phase PSM-DID method.

Lei Chen, Cunjing Liu, Zhezhou Li, Difan Wu

Open access · hybridAbstract read
In one paragraph

Article in Environmental science and pollution research international, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
10.2field-weighted citation impact, top 3% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed, 9 citations in OpenAlex.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors at 3 institutions in 1 country.

Lei ChenRural Development Institute, Yan'an University, Yan'an, 716000, China.
Cunjing LiuSchool of Economics and Management, Yan'an University, Yan'an, 716000, China. liucunjing@yau.edu.cn.ORCID http://orcid.org/0009-0003-7294-5724
Zhezhou LiSchool of Economics and Management, Fuzhou University of International Studies and Trade, Fuzhou, 350202, China.
Difan WuState Grid Shanghai Electric Power Company Shibei Power Supply Company, Shanghai, 200070, China.
Yan'an University · CNFuzhou University · CNShanghai Electric (China) · CN

Funding

Fujian Provincial Federation of Social Sciences FJ2022BF076Yan'an University YAU202303805
6 · The paper itself

Abstract

Based on China's empirical data from 2000 to 2020 of 1875 county-level administrative units, combined with the multi-phase by the propensity score matching and difference-in-difference (PSM-DID) model, this paper studies the impact of clean energy demonstration province policies on the carbon intensity of pilot counties, and its further impact on carbon emissions and economic development level. The results showed that 1. from a county-level perspective, although the economic development level of the pilot areas of clean energy demonstration provinces has improved as the carbon emissions have also increased, what is more, the carbon intensity has also significantly improved in this process; 2. there is no time lag in the impact of policies on the carbon intensity of counties, and the impact effects gradually increase over time along with strong regional heterogeneity; 3. the clean energy demonstration policy has weakened the technological level of the county and reduced the proportion of industrial-added value to GDP, thereby increasing the carbon intensity of the county through these intermediaries.

Indexed as

Public PolicyCarbonCarbon DioxideChinaEconomic DevelopmentPropensity ScoreCarbonCarbon DioxideCarbon emissionsCarbon intensityCounty-level of ChinaEconomic development levelPSM-DID

Identifiers

PMID38236569
PMCPMC10881742
OpenAlexW4390985289

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.