Evidence map›Paper›PMID 32143412›Full record

ArticleInternational journal of environmental research and public health2020

The Agglomeration of Manufacturing Industry, Innovation and Haze Pollution in China: Theory and Evidence.

Zhidong Liu, Yang Cai, Xiaojing Hao

Abstract read
In one paragraph

Article in International journal of environmental research and public health, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. The Impact of Low-Carbon City (LCC) on Elderly People's Health: Evidence from a Natural Experiment in China.International journal of environmental research and public health · 2022
    Article
  2. Article
  3. The Relationship between Environmental Regulation, Pollution and Corporate Environmental Responsibility.International journal of environmental research and public health · 2021
    Article
  4. 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

3 authors.

Zhidong LiuSchool of Management Science and Engineering, Central University of Finance and Economics, Beijing 100081, China.
Yang CaiSchool of Management Science and Engineering, Central University of Finance and Economics, Beijing 100081, China.
Xiaojing HaoSchool of Public Finance and Tax, Central University of Finance and Economics, Beijing 100081, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Haze pollution in China is a serious environmental issue, which does harm both to people's health and to economic development. Simultaneously, as an important industrial development law, agglomeration may result in the increased concentration of manufacturing firms and, consequently, an increase in haze pollution. However, the positive externalities of agglomeration can also improve the efficiency of regional innovation, which curbs haze pollution. In this paper, we construct both theoretical and empirical models to investigate the effects of industrial manufacturing agglomeration on haze pollution. The results reveal the following: (1) By incorporating the effect of agglomeration and haze pollution into a general endogenous growth model, we show an inverted-U relationship between agglomeration and haze pollution on the balance growth path. (2) Based on data concerning haze pollution (PM

Indexed as

Air PollutantsAir PollutionManufacturing IndustryChinaCitiesEconomic DevelopmentEnvironmental MonitoringEnvironmental PollutionParticulate MatterAir PollutantsParticulate Matterhaze pollutionindustrial agglomerationinnovationpollution prevention

Identifiers

PMID32143412
PMCPMC7084824

What OpenQuestion holds

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LicenceCC BY
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Registered trials

None linked

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.