Evidence map›Paper›PMID 38841491›Full record

ArticleHeliyon2024

Spatial spillover effects of skilled migration on innovation in China.

Xing Gao, Jin Zhu, He Zhu, Xingman Zhang

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. 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

4 authors.

Xing GaoSchool of Economics, Beijing Institute of Technology, Beijing, China.
Jin ZhuDepartment of Real Estate and Construction & Department of Urban Planning and Design & Urban Systems Institute, Faculty of Architecture, The University of Hong Kong, Hong Kong SAR, China.
He ZhuSchool of Architecture and Urban Planning, Beijing University of Civil Engineering and Architecture, Beijing, China.
Xingman ZhangSchool of Economics, Beijing Institute of Technology, Beijing, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Despite the importance of interregional skilled migration to regional development, few studies have explored its spatial spillover effects and their changes over time. Thus, employing the Spatial Durbin Model, we investigate the presence of regional spillovers of skilled migration at both national and sub-national levels in China. Especially, we focus on the regional difference and change in the spatial spillover. Although our results confirm positive spillover effects at the national level due to the strong mobility characteristic of skilled migrants, developed regions benefit more from spillovers of skilled migration than developing regions, and such effects are divergent in different regions over time. Our findings also indicate that changes in spatial spillovers among regions are closely associated with the mobility of economic factors in geography. Theoretically, by considering the spatial effects of skilled migration on the innovation output of recipient regions, we extend the labour economics literature into geographical economic agglomeration, especially innovation economic geography. Methodologically, we examine the spatial effects at both national and sub-national levels, and capture the spatial externalities; we also apply Maximum Likelihood estimation to assess the endogeneity issues to understand the mechanisms of spillover change over time. The study can be of significance for municipalities in the policy-making of attracting talents and promoting regional innovation.

Indexed as

ChangeChinaInnovationSkilled migrationSpatial spillover

Identifiers

PMID38841491
PMCPMC11152691

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

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.