Evidence map›Paper›PMID 35886634›Full record

ArticleInternational journal of environmental research and public health2022

Spatial Distribution and Convergence of Agricultural Green Total Factor Productivity in China.

Liping Zhu, Rui Shi, Lincheng Mi, Pu Liu, Guofeng Wang

Abstract read
In one paragraph

Article in International journal of environmental research and public health, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing 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

7 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. How Does Agricultural Mechanization Service Affect Agricultural Green Transformation in China?International journal of environmental research and public health · 2023
    Article
  6. Article
  7. Article
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

5 authors.

Liping ZhuFaculty of International Trade, Shanxi University of Finance and Economics, Taiyuan 030006, China.
Rui ShiFaculty of International Trade, Shanxi University of Finance and Economics, Taiyuan 030006, China.ORCID 0000-0003-4245-4337
Lincheng MiFaculty of International Trade, Shanxi University of Finance and Economics, Taiyuan 030006, China.
Pu LiuFaculty of International Trade, Shanxi University of Finance and Economics, Taiyuan 030006, China.
Guofeng WangFaculty of International Trade, Shanxi University of Finance and Economics, Taiyuan 030006, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The power source, spatial-temporal differentiation and convergence of the growth rate of green total factor productivity in China's agriculture were analyzed. The Malmquist index was used to measure the growth rate, and the spatial-temporal convergence was tested by σ convergence, absolute β convergence, conditional β convergence and dynamic spatial convergence. The study drew conclusions that the impetus for the intensive growth of green agriculture was insufficient, and the driving force for the growth of agricultural green total factor productivity (AGTFP) in the eastern, western and central region was green technology progress. In addition, AGTFP did not have an absolute σ convergence trend. Dynamic spatial absolute β and conditional β convergence indicated that regional differences were not completely related to regional endowment conditions, and regional green agricultural production was unbalanced. This study provides an important support for regional green development in China's agriculture.

Indexed as

AgricultureEfficiencyChinaEconomic DevelopmentTechnologyabsolute convergenceagricultureconditional convergencedynamic spatial convergencegreen total factor productivityspatial distribution

Identifiers

PMID35886634
PMCPMC9318734

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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.