Can outward direct investment and openness to the outside world reduce regional labor misallocation?

Using provincial panel data(Excludes Taiwan, Hong Kong and Macau) from China spanning 2009 to 2023, this paper systematically examines the relationships among openness to the outside world, outward direct investment, and regional labor misallocation. The research findings indicate a significant negative correlation between openness and the level of labor misallocation, suggesting that expanding openness is conducive to improving the efficiency of regional labor allocation. Meanwhile, outward direct investment also demonstrates a notable negative effect, implying its positive role in optimizing resource allocation and reducing labor misallocation. In addition, the empirical results reveal a significant synergistic effect between openness and outward direct investment, with their combined effect being more pronounced in reducing labor misallocation. Further mechanism analysis shows that outward direct investment plays a mediating role in the impact of openness on labor misallocation. It is noteworthy that this mediating effect exhibits marked heterogeneity across regions with differing degrees of marketization: in regions with low marketization, openness significantly reduces labor misallocation by promoting outward direct investment, while in regions with high marketization, this mediating role is not evident.

Authors

Institutions

Publication Details

Journal
International Review of Economics & Finance
Published
2025-11-03
DOI
https://doi.org/10.1016/j.iref.2025.104721
Primary Topic
Regional Economics and Spatial Analysis
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Can outward direct investment and openness to the outside world reduce regional labor misallocation?

Genhong Zhao, J.L. Lu
International Review of Economics & Finance
Regional Economics and Spatial Analysis
article

Can outward direct investment and openness to the outside world reduce regional labor misallocation?

Genhong Zhao, J.L. Lu
article en

Abstract

Using provincial panel data(Excludes Taiwan, Hong Kong and Macau) from China spanning 2009 to 2023, this paper systematically examines the relationships among openness to the outside world, outward direct investment, and regional labor misallocation. The research findings indicate a significant negative correlation between openness and the level of labor misallocation, suggesting that expanding openness is conducive to improving the efficiency of regional labor allocation. Meanwhile, outward direct investment also demonstrates a notable negative effect, implying its positive role in optimizing resource allocation and reducing labor misallocation. In addition, the empirical results reveal a significant synergistic effect between openness and outward direct investment, with their combined effect being more pronounced in reducing labor misallocation. Further mechanism analysis shows that outward direct investment plays a mediating role in the impact of openness on labor misallocation. It is noteworthy that this mediating effect exhibits marked heterogeneity across regions with differing degrees of marketization: in regions with low marketization, openness significantly reduces labor misallocation by promoting outward direct investment, while in regions with high marketization, this mediating role is not evident.

International Review of Economics & FinanceVol. 104
Liaoning University (CN), Shenzhen Institute of Information Technology (CN)
Openalex Percentile: Top 59%
Regional Economics and Spatial Analysis
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.