Evidence map›Paper›PMID 33907959›Full record

ArticleEnvironmental science and pollution research international2021

The heterogeneous impact of environmental regulation on urban green scale economy: an empirical analysis based on city-level panel data in China.

Ying Tian, Chao Feng

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Article in Environmental science and pollution research international, 2021. 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

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3 · Its place in the literature

Who cites it

4 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Do Environmental Regulations Facilitate a Low-Carbon Transformation in China's Resource-Based Cities?International journal of environmental research and public health · 2023
    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

2 authors.

Ying TianSchool of Economics and Business Administration, Chongqing University, Chongqing, 400030, China.
Chao FengSchool of Economics and Business Administration, Chongqing University, Chongqing, 400030, China. littlefc@126.com.

Funding

National Natural Science Foundation of China 72003017
6 · The paper itself

Abstract

With continued expansions of scale, the Chinese cities are facing unprecedented economic, environmental, and energy sustainability challenges. The aim of this paper is to examine the heterogeneous impact of environmental regulation (ER) on urban green scale economy (GSEC), by combining the global Malmquist index approach, spatial econometric model, panel quantile regression model (QRPD), and the city-level panel data from 2004 to 2018. The estimation results show that (1) from 2004 to 2018, the growth rate of GSEC fluctuates sharply, and the values of GSEC are less than 1 in many years. This indicates that GSEC is far from efficient and needs to be improved in the future; (2) the results of the spatial econometric model show that GSEC has a U-shaped relationship with the level of ER. Furthermore, the estimation results of QRPD verify the above conclusions and show that there is distinct heterogeneity of ER on GSEC at different quantiles and regional cities; (3) the results further indicate that other vital control variables have a significant and heterogeneous effect on GSEC. Therefore, the focus of future work should be adapted to local conditions. Specifically, in the cities with lower-level GSEC, the policymakers should give top priority to break through the U-shaped inflection point as soon as possible and help enterprises to achieve pollution reduction by technical and financial subsidies. While in the cities with higher-level GSEC, the government should further strengthen its ER and encourage competition among enterprises by internal technological innovation. In addition, the government should try to avoid the negative effect of the "resource curse" trap, excessive financial leverage, and "race-to-the-bottom" phenomenon.

Indexed as

Economic DevelopmentInventionsChinaCitiesEnvironmental PollutionChinese urban green scale economyEnvironmental regulation heterogeneitiesGlobal Malmquist indexPanel quantile regression modelSpatial econometric model

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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.