Evidence map›Paper›PMID 42787791›Full record

ArticleFrontiers in public health2026

Does the environmental protection tax improve population health? Evidence from China's quasi-natural experiment.

Junyao Tong, Bingnan Guo

Abstract read
In one paragraph

Article in Frontiers in public health, 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
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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

2 authors.

Junyao TongSchool of Humanities and Social Sciences, Jiangsu University of Science and Technology, Zhenjiang, China.
Bingnan GuoSchool of Humanities and Social Sciences, Jiangsu University of Science and Technology, Zhenjiang, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Health constitutes a fundamental component of human capital for high-quality economic development and an important indicator of social well-being. Using panel data for 31 Chinese provinces from 2010 to 2023, this study treats the implementation of the Environmental Protection Tax Law of the People's Republic of China in 2018 as a quasi-natural experiment and employs a difference-in-differences model to systematically identify the effect of the environmental protection tax policy on population health. The results show that, first, the environmental protection tax policy significantly improves population health, and this finding remains robust after controlling for province fixed effects, year fixed effects, and a set of relevant covariates. Second, the baseline results are consistently supported by the parallel-trends test, placebo test, control for concurrent policies, replacement of the dependent variable, and propensity score matching difference-in-differences estimation. Third, the mechanism analysis indicates that pollution reduction and investment in environmental pollution control are important channels through which the environmental protection tax improves population health. Fourth, the regional heterogeneity analysis shows that the policy significantly improves population health in eastern and western China, whereas its effect in central China is positive but statistically insignificant, suggesting a certain degree of regional variation in policy effectiveness. This study extends the literature on the effects of environmental protection taxation from the perspective of population health and provides empirical evidence for improving the green taxation system and promoting coordination between ecological governance and the Healthy China initiative.

Indexed as

Conservation of Natural ResourcesEnvironmental PolicyPopulation HealthTaxesChinaEnvironmental PollutionHumansdifference-in-differencesenvironmental protection taxinvestment in environmental pollution controlpollution reductionpopulation health

Identifiers

PMID42787791
PMCPMC13602210

What OpenQuestion holds

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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.