Evidence map›Paper›PMID 40788883›Full record

ArticlePloS one2025

Population aging and corporate tax avoidance: Suppression or promotion?

Luzhuang Qi, Peng Liang

Abstract read
In one paragraph

Article in PloS one, 2025. 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

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.

Luzhuang QiSchool of Economics and Management, Shihezi University, Shihezi, China.
Peng LiangSchool of Accounting, Capital University of Economics and Business, Beijing, China.ORCID https://orcid.org/0009-0006-2229-0485

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Addressing population aging has emerged as a paramount national strategic priority. Against the backdrop of a continual rise in population aging and considerable escalation in labor costs within China, this study aims to investigate whether firms, confronted with the burden of labor costs, intensify their tax avoidance motives to generate a "stimulating effect" or whether they are compelled to adapt traditional factors, thereby reducing tax avoidance and exerting a "restraining effect". To address this inquiry, we empirically examine the impact of population aging on corporate tax avoidance and its underlying mechanisms utilizing a sample of non-financial listed companies in China's A-share market spanning from 2008 to 2023. Our findings substantiate that the level of population aging significantly diminishes firms' tax avoidance motives, confirming the presence of a "restraining effect". Mechanism tests unveil that population aging, through capital-labor substitution, fosters research and development innovation and improves production efficiency, thus curbing firms' tax avoidance behavior and affirming the existence of the "factor substitution effect" "innovation capacity effect" and "resource allocation effect". Heterogeneity analysis reveals that the inhibitory impact of population aging on corporate tax avoidance is more pronounced in labor-intensive industries, entities with limited financing capacity, weak financial conditions, and adverse external financial conditions. By examining the economic ramifications of population aging from a micro-level perspective on corporate financial decision-making and enriching the existing literature on corporate tax avoidance through a population economics lens, this study provides valuable insights for firms undergoing transformation and informs policy formulation in response to the challenges posed by population aging.

Indexed as

Population DynamicsTaxesAgingChinaHumans

Identifiers

PMID40788883
PMCPMC12338803

What OpenQuestion holds

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LicenceCC BY
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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.