Evidence map›Paper›PMID 39183826›Full record

ArticleHeliyon2024

The impact of human capital misallocation on green economy efficiency: Empirical analysis of Chinese urban agglomerations.

Wen Lu, Liang Peng, Ning Fang

Abstract read
In one paragraph

Article in Heliyon, 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
–field-weighted citation impact
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.

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

3 authors.

Wen LuSchool of Marxism, Sanjiang University, Nanjing, China.
Liang PengSchool of Economics, Nanjing Audit University, Nanjing, China.
Ning FangSchool of Continuing Education, Nanjing University of Finance and Economics, Nanjing, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This paper uses panel data of 260 prefecture-level cities from 2000 to 2019 to explore spatial characteristics such as spatiotemporal divergence and dynamic convergence based on measuring the level of human capital misallocation in Chinese cities and empirically tests the green development effect of human capital misallocation. The study finds that: ① the human capital misallocation levels of the country and the eight major urban agglomerations show a fluctuating downward trend. ② Divergences in human capital misallocation continue to narrow across the country and urban agglomerations, and the difference between inter-urban agglomerations is the primary source of regional difference. ③ The YRD, PRD, MYR, HC, and CP have significant σ-convergence characteristics of human capital misallocation. Meanwhile, the country and each urban agglomeration show significant spatial absolute β-convergence and conditional β-convergence trends. ④ Human capital misallocation significantly negatively affects green economic efficiency, inhibiting green economy efficiency. Therefore, in the future, it is necessary to improve the match between regional industrial structure and human capital allocation through a combination of targeted policy guidance and market mechanisms tailored to local conditions to enhance the efficiency of the green economy. The significance of the study lies in accelerating the accumulation of human capital while realizing the appropriate matching of human capital, releasing the human capital dividend to the maximum extent, and boosting the structural reform of the labor market to realize the transformation of the green economy.

Indexed as

Dynamic convergenceGreen economy efficiencyHuman capital misallocationUrban agglomerations

Identifiers

PMID39183826
PMCPMC11341303

What OpenQuestion holds

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LicenceCC BY-NC-ND
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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.