“一带一路”沿线国家来华留学生与中国对外直接投资关系的实证研究

蔡文伯; 闫佳丽

doi:10.16382/j.cnki.1000-5560.2020.04.003

“一带一路”沿线国家来华留学生与中国对外直接投资关系的实证研究

doi: 10.16382/j.cnki.1000-5560.2020.04.003

蔡文伯^1,2,
闫佳丽²

1.
塔里木大学人文学院，新疆阿拉尔 843300
2.
石河子大学师范学院，新疆石河子 832003

基金项目: 国家自然科学基金项目“深度贫困地区教育精准扶贫政策绩效的测度与评价研究”（71864032）

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出版历程
- 刊出日期: 2020-04-01

An Empirical Study on the Relationship between International Students from Countries along The Belt and Road and China’s Foreign Direct Investment

Cai Wenno^1,2,
Yan Jiali²

1.
Faculty of Humanities, Tarim University, Alear 843300, Xinjiang China
2.
School of Teacher Education, University of Shihezi, Shihezi 832003, Xinjiang China

摘要

摘要: 本研究以2006—2017年为考察期，利用PVAR模型对“一带一路”沿线44个样本国家的来华留学生规模和中国对其直接投资量之间的动态影响关系进行分析，发现二者存在显著的相互依存关系。研究结果显示：OFDI规模增长在短期内对沿线国留学生流入有明显的正向冲击作用，它是二者关系进一步发展的强烈动因，且具有一定的引导性；沿线国来华留学规模增长是推动OFDI发展的基本源动力之一，并存在较强的正效应，但整体质量不高、经济贡献率偏低；OFDI规模扩张对其本身进一步的发展具有一定的拉动作用，但后期动力不足；受我国高等教育国际化水平、国际价值链地位等因素的影响，双边人才存量对留学生来华促进作用有限。基于此，政府应合理评估沿线国家投资环境，集约化经营OFDI发展模式，以推动区位资源结构优化和提高全球化价值链的地位；同时，还应搭建国际化人才交流体系、健全留学教育质量保障制度和拓宽留学生学科专业招生范围，发展我国人力资源的核心竞争力。
- “一带一路” /
- 来华留学生 /
- 对外直接投资（OFDI）
Abstract: Based on the 2006—2017 study period, the PVAR model used the study to empirically analyze the number of international students from 44 sample countries along the Belt and Road route and the ongoing impact of China's direct investment in China. On the whole, there is a significant interdependence between the two. The results show that the growth of OFDI scale has a significantly positive impact on the inflow of international students in the countries along the route in the short term, which is a strong driving force for the further development of the relationship between the two countries and has a certain guiding effect. The overall quality is not high and its economic contribution rate is low . While OFDI expansion has a certain pull for its own further development, the motivation is not enough,Influenced by the internationalization level of higher education in China, and the status of the international value chain and other factors, the contribution of bilateral talent stock to attracting international students to come to China is limited. Therefore, the study holds that the government should reasonably evaluate the investment environment of the countries along the route and intensively operate the OFDI development model for the optimization of the location resource structure and improve the global value chain. At the same time, it’s important to set up an international talent exchange system and improve the quality assurance system of study international education for, the development of China's core competitiveness of human resources.
- “The Belt and Road” /
- International students studying in China /
- OFDI

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图 1 特征多项式的根在单位圆中的位置图

下载: 全尺寸图片幻灯片

图 2 “一带一路”来华留学生数与中国对沿线国家直接投资间的脉冲响应图

注：图中的横坐标表示脉冲响应函数的追踪滞后期数，纵坐标表示响应程度，中间曲线为脉冲响应函数曲线。

下载: 全尺寸图片幻灯片

图 3 lns与lnin影响关系的方差分解图

下载: 全尺寸图片幻灯片

表 1 ADF单位根检验结果

变量	P值	结论
lnin	0.0230**	平稳
lns	0.2858	非平稳
△lnin	0.0000***	平稳
△lns	0.0033***	平稳
注：表示在5%水平上显著，*表示在1%水平上显著。

下载: 导出CSV

表 2 协整检验结果

统计量	value	Z-value	P值
Gt	−2.909	−4.568	0.000
Ga	−18.658	−6.742	0.000
Pa	−13.070	1.100	0.864
Pt	−11.782	−3.141	0.001
注：Gt和Pt统计量不考虑序列相关，Ga和Pa考虑了序列相关。

下载: 导出CSV

表 3 PVAR模型最佳滞后期的确定结果

滞后阶数	MBIC	MAIC	MQIC
1	−47.62748***	−19.44828***	−29.8399***
2	−38.10893	−16.97453	−24.76825
3	−26.79385	−12.70425	−17.90006
4	−11.19061	−4.145873	−6.743718

下载: 导出CSV

表 4 Granger因果检验结果

原假设	F统计量	P值	结论
lnin→lns	5.354	0.021	拒绝
lns→lnin	2.905	0.088	拒绝

下载: 导出CSV

表 5 PVAR模型GMM估计结果

统计量依赖变量	Lns	Lnin
L.lns	0.62516***	0.31430
	（0.05847）	（0.02537）
	[10.69]	[0.91]
L2.lns	0.24325	0.52181**
	（0.03884）	（0.11544）
	[1.66]	[2.16]
L.lnin	0.51955***	0.56127***
	（0.02172）	（0.04657）
	[5.80]	[2.63]
L2.lnin	0.15259	0.14939
	（0.19711）	（0.04226）
	[0.77]	[1.17]
R-sq	0.9817	0.9261
注：表中不带括号的数字为VAR模型的参数估计值，“（）”中的数字为参数估计的标准差，“［］”中的数字为参数估计值的t统计量

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参考文献(9)

[1]	邹玉娟, 陈漓高. (2008). 我国对外直接投资与技术提升的实证研究. 世界经济研究,(05),70−77+89.
[2]	钟优慧, 杨志江. (2016). 人力资本、国际技术溢出与技术效率. 科技与经济,29(02),77−80. doi: 10.3969/j.issn.1003-7691.2016.02.016
[3]	Bitzer, J., & Kerekes, M (2008). Does foreign direct investment transfer technology across borders? New evidence. Economics Letters, (100), 355−358.
[4]	Borensztein, E., & Lee, G (1998). How does foreign direct investment affect economic growth?. Journal of International Economics, (45), 115−135.
[5]	Coe, D. T., Helpman, E., Alexander, W., & Hoffmaister, A. W (2009). International R&D spillovers and institutions. European Economic Review, 53(7), 45−52.
[6]	Denzer, A. (2011). The effects of outward FDI on economic growth: A theoretical and empirical analysis. BadenWürttemberg: Eberhard Karls Universit Tübingen, 35(3), 1−30.
[7]	Holtz-Eakin, D., Newey, W., & Rosen, H.S (1988). Estimating vector auto regressions with panel data. Journal of the Econometric Society, 56(6), 1371−1395. doi: 10.2307/1913103
[8]	Kogut, B., Chang, S.J (1991). Technological capabilities and Japanese direct investment in the United States. Review of Economic sand Statistics, 73(3), 401−413. doi: 10.2307/2109564
[9]	Levin, A., Lin, C. F., & Chu, C.S.J (2002). Unit root tests in panel data: Asymptotic and finite-sample properties. Journal of Econometrics, (108), 335−341.