Evidence map›Paper›PMID 39391477›Full record

ArticleHeliyon2024

The impact of public fiscal expenditure on industrial transformation and upgrading: An inverted U-shape evidence from China.

Junfeng Zhao, Jinling Yan

Abstract read
In one paragraph

Article in Heliyon, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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.

Junfeng ZhaoCollege of Economics, Xinjiang University of Finance and Economics, Urumqi, 830012, China.
Jinling YanChina (Xinjiang) and Central Asia Regional Economic Cooperation Research Center, Urumqi, 830012, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

High-quality economic development relies on industrial transformation and upgrading. To promote industrial transformation and upgrading, efficient fiscal expenditures are undoubtedly important as pillars of national governance. However, in the context of the market economy, the government's excessive intervention in industrial development will lead to the "promotion tournament" of officials and the "beggar-thy-neighbor" local protectionism, resulting in the convergence of regional industrial structure, which will bring uncertain impact on the upgrading of regional industrial structure. Thus, this study empirically assesses how public fiscal expenditure impacts industrial transformation and upgrading as well as the mechanism by developing a spatial econometric model using the panel data of 250 Chinese cities from 2007 to 2020 and further discusses the differential impact from the perspective of urban scale. The findings disclose that public fiscal expenditure serves a crucial role in facilitating industrial transformation and upgrading, but their relationship resembles an inverted U. Therefore, an optimal scale of public fiscal expenditure exists. Heterogeneity findings reveal that the promoting effect of public fiscal expenditure on industrial transformation and upgrading decreases with the expansion of the city scale. The role mechanism implies that public fiscal expenditure indirectly leverages industrial transformation and upgrading through promoting technological innovation, reducing resource dependence, and expanding scale economies. The conclusion provides a theoretical and practical framework for the government to optimize public fiscal expenditure, promote the transformation and upgrading of China's industrial structure, and ultimately attain high-quality development.

Indexed as

Industrial transformation and upgradingInverted U-ShapePublic fiscal expenditureSpatial Durbin model

Identifiers

PMID39391477
PMCPMC11466588

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

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.