Article
A Study on the Impact of China’s OFDI on Labor Export Using a Linear Regression Model
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Abstract
Chinese enterprises’ overseas investments have significantly facilitated China’s foreign labor export, but the international labor market is undergoing profound changes, posing new challenges. This study constructs an empirical model to examine the relationship between labor export and China’s OFDI, conducts a Pearson correlation test, and uses a simple linear regression model to verify the influence of OFDI on labor export flow. The study suggests that China’s OFDI has a significant impact on labor export, transitioning from pulling to crowding out effects after the Belt and Road Initiative, with policy recommendations for enhancing labor enterprise competitiveness and government oversight.
Keywords
OFDI, Labor export, Impact, 62J05
Citation
Gao, K. & Yang, L. (2024). A study on the impact of china’s OFDI on labor export using a linear regression model. Applied Mathematics and Nonlinear Sciences, 9(1). https://doi.org/10.2478/amns-2024-1492
K. Gao and L. Yang, “A study on the impact of china’s OFDI on labor export using a linear regression model,” Applied Mathematics and Nonlinear Sciences, vol. 9, no. 1, 2024, doi: 10.2478/amns-2024-1492.
Gao K, Yang L. A study on the impact of china’s OFDI on labor export using a linear regression model. Applied Mathematics and Nonlinear Sciences. 2024;9(1). doi:10.2478/amns-2024-1492.
Gao, K. and Yang, L. (2024), ‘A study on the impact of china’s OFDI on labor export using a linear regression model’, Applied Mathematics and Nonlinear Sciences, 9(1). Available at: https://doi.org/10.2478/amns-2024-1492.
Gao, Ke, and Liang Yang. “A Study on the Impact of China’s OFDI on Labor Export Using a Linear Regression Model.” Applied Mathematics and Nonlinear Sciences, vol. 9, no. 1, 2024. https://doi.org/10.2478/amns-2024-1492.
Gao, Ke, and Liang Yang. “A Study on the Impact of China’s OFDI on Labor Export Using a Linear Regression Model.” Applied Mathematics and Nonlinear Sciences 9, no. 1 (2024). https://doi.org/10.2478/amns-2024-1492.
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Published by: Engineering Journals


