Evidence map›Paper›PMID 42151307›Full record

ArticleScientific reports2026

Spatiotemporal patterns and underlying drivers of provincial agricultural green total factor productivity in China.

Guifan Rong

Abstract read
In one paragraph

Article in Scientific reports, 2026. 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

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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

1 author.

Guifan RongGuangzhou Institute of Technology, Guangzhou, 510075, China. guifan.rong@cqu-edu.cn.

Funding

the Teaching Reform Project No. XJL202570
6 · The paper itself

Abstract

Under tightening resource and environmental constraints, understanding the evolution and determinants of agricultural green total factor productivity (AGTFP) is essential for evaluating sustainable agricultural development. Using balanced panel data for 31 Chinese provinces from 2005 to 2024, this study measures AGTFP through a super-efficiency global SBM-Malmquist framework incorporating undesirable outputs. The geographic detector method is further employed to examine stage-specific spatial explanatory patterns across seven dimensions, including factor endowments, technological progress, rural governance, production organization, market environment, affluence, and ecological pressure. Results indicate that AGTFP exhibits a fluctuating but overall upward trajectory over the study period, with a noticeable acceleration after 2018. Persistent spatial disparities are observed, as eastern provinces maintain higher productivity levels, while central and western regions demonstrate gradual convergence in recent years. Decomposition analysis reveals that technological progress constitutes the principal source of long-term growth, whereas technical efficiency improvements contribute increasingly in the later stages. Spatial dependence remains relatively weak and varies across periods. The determinant structure shows a dynamic transition from early-stage dominance of ecological and factor constraints toward strengthened roles of efficiency, organizational restructuring, and market-related factors. Accordingly, to accelerate agricultural green transformation, policy efforts should prioritize optimizing the structure of agricultural factor supply, incentivizing green technological progress, enhancing the effectiveness of environmental regulation, and improving agricultural governance systems, with greater emphasis on region-specific and stage-differentiated policy coordination.

Indexed as

Agricultural green total factor productivityEnvironmental regulationFactor allocation efficiencyGreen developmentInstitutional policiesTechnological progress

Identifiers

PMID42151307
PMCPMC13376895

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.