The impact of global attention, reputation on foreign direct investment: Based on big data research in African countries

doi:10.3969/j.issn.1004-9479.2024.08.20222287

Abstract

Abstract:

Taking 35 African countries as examples, based on GDELT and using sentiment analysis, spatial analysis, visualization and dynamic panel econometric model, this paper constructs global attention and reputation indicators in African countries and explain foreign direct investment behavior (FDI). It is found that, in terms of time trends, there are four types of FDI curves in African countries,including high investment, rising investment, falling investment and low investment. Spatially, there are marked regional differences of FDI in Africa. The econometric model shows that FDI in African regions is influenced by global attention and reputation. Besides, the size of the influence effect of global attention is about 11.6% of the economic development level and equivalent to the influence effect of the policy superiority. The effect size of global reputation on FDI is about 7.54% of economic factors and about half of that of policy factors. This paper is a macro-quantitative analysis based on big data to expand and extend the theory of FDI from the perspective of socio-cultural communication, which is a useful combination of big data and computational social science methods with traditional quantitative research methods. This paper also provides data and theoretical support for enhancing national image development strategies.

Key words: African countries, foreign direct investment, global communication, GDELT database, dynamic panel model

摘要：

以非洲35个国家为例，基于GDELT新闻媒体数据库，构建非洲国家的全球关注度和美誉度指标，使用情感分析、空间分析、可视化和动态面板计量模型对外商直接投资（FDI）区位选择的影响因素进行研究。研究发现：从时间趋势上看，非洲的外商直接投资趋势曲线共有4种变动模式——高投资型、投资上升型、投资下降型和低投资型。从空间维度上看，非洲的外商直接投资和全球传播指标的地区差异明显，并形成以非洲南部、几内亚湾和部分北非地区为主的外商直接投资和全球传播高地。基准模型表明，非洲国家的外商直接投资除了取决于经济和制度等传统因素外，也受到其在全球传播中的关注度和美誉度的影响。其中，全球媒体关注度影响效应的大小约为投资国经济发展水平影响效应的11.6%，与投资国制度政策优越度影响效应相当。而媒体美誉度指数对外商直接投资的影响效应大小约为经济因素的7.54%，约为制度政策因素的二分之一。基于大数据的宏观定量分析，从社会文化传播角度对外商直接投资理论进行拓展延伸，是大数据和计算社会科学方法与传统定量研究方法的有益结合，也为提升国家形象发展战略提供了数据和理论支持。

关键词: 非洲国家, 外商直接投资, 全球传播, GDELT数据库, 动态面板模型

Boyang ZHANG, Zhihui FU, Yunsong CHEN, Ying LI. The impact of global attention, reputation on foreign direct investment: Based on big data research in African countries[J]. World Regional Studies, 2024, 33(8): 27-39.

张柏杨, 付志惠, 陈云松, 李颖. 媒体关注度、美誉度对外商直接投资的影响[J]. 世界地理研究, 2024, 33(8): 27-39.

Figures/Tables 5

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变量	均值	标准差	最小值	最大值	观测值
外商直接投资FDI/亿元	8.029	10.744	－8.836	44.170	N=175
全球关注指数Att（比值）	0.002	0.002	0.000	0.009	N=175
国家美誉度指数Img（比值）	－0.186	0.802	－2.694	1.637	N=175
经济发展水平GDP/亿元	320.220	710.500	3.161	4 868.030	N=175
对外开放度Open（比值）	0.668	0.447	0.211	3.072	N=165
财政政策优越度Fin（评分）	3.140	0.524	2.000	4.000	N=175
公共管理政策优越度Pub（评分）	3.037	0.422	2.000	4.000	N=175
防腐败政策优越度Cor（评分）	2.760	0.616	1.500	4.500	N=175
人力资源政策优越度HR（评分）	3.657	0.467	2.500	4.500	N=175
贸易政策优越度Tra（评分）	3.829	0.457	2.500	4.500	N=175
预算与金融管理政策优越度Bud（评分）	3.154	0.478	2.000	4.000	N=175
金融发展政策优越度Finsec（评分）	2.891	0.401	2.000	4.000	N=175
性别平等政策优越度Gend（评分）	3.266	0.535	2.000	4.500	N=175
环境可持续发展政策优越度Env（评分）	3.326	0.473	2.000	4.500	N=175
自然禀赋Nat/%	8.449	7.119	0.265	47.952	N=175
劳动力禀赋Lab/万人	992.130	1 297.010	6.641	6 322.672	N=175
移动互联网资源Cell/（部/百人）	80.947	26.683	32.129	145.341	N=166
城镇化水平Urb/%	40.857	16.166	12.078	77.915	N=175

变量	均值	标准差	最小值	最大值	观测值
外商直接投资FDI/亿元	8.029	10.744	－8.836	44.170	N=175
全球关注指数Att（比值）	0.002	0.002	0.000	0.009	N=175
国家美誉度指数Img（比值）	－0.186	0.802	－2.694	1.637	N=175
经济发展水平GDP/亿元	320.220	710.500	3.161	4 868.030	N=175
对外开放度Open（比值）	0.668	0.447	0.211	3.072	N=165
财政政策优越度Fin（评分）	3.140	0.524	2.000	4.000	N=175
公共管理政策优越度Pub（评分）	3.037	0.422	2.000	4.000	N=175
防腐败政策优越度Cor（评分）	2.760	0.616	1.500	4.500	N=175
人力资源政策优越度HR（评分）	3.657	0.467	2.500	4.500	N=175
贸易政策优越度Tra（评分）	3.829	0.457	2.500	4.500	N=175
预算与金融管理政策优越度Bud（评分）	3.154	0.478	2.000	4.000	N=175
金融发展政策优越度Finsec（评分）	2.891	0.401	2.000	4.000	N=175
性别平等政策优越度Gend（评分）	3.266	0.535	2.000	4.500	N=175
环境可持续发展政策优越度Env（评分）	3.326	0.473	2.000	4.500	N=175
自然禀赋Nat/%	8.449	7.119	0.265	47.952	N=175
劳动力禀赋Lab/万人	992.130	1 297.010	6.641	6 322.672	N=175
移动互联网资源Cell/（部/百人）	80.947	26.683	32.129	145.341	N=166
城镇化水平Urb/%	40.857	16.166	12.078	77.915	N=175

因素	变量	模型系数	聚类稳健标准误
路径依赖	FDI_(t-1)	0.337^***	0.084
文化传播因素	Att	0.134^*	0.062
文化传播因素	Img	0.087^*	0.042
经济因素	GDP	1.155^***	0.212
经济因素	Open	－0.013	0.039
制度因素	Fin	0.137^*	0.056
	Pub	－0.251	0.134
	Cor	0.156^**	0.054
	HR	－0.057	0.081
	Tra	－0.210	0.126
	Bud	0.131^*	0.066
	Finsec	0.026	0.061
	Gend	0.190	0.135
	Env	0.181^**	0.066
公共设施与资源因素	Nat	－0.136^*	0.062
	Lab	－0.839^***	0.252
	Cell	0.190	0.110
	Urb	－1.659^***	0.490
截距		－0.286^*	0.133

因素	变量	模型系数	聚类稳健标准误
路径依赖	FDI_(t-1)	0.337^***	0.084
文化传播因素	Att	0.134^*	0.062
文化传播因素	Img	0.087^*	0.042
经济因素	GDP	1.155^***	0.212
经济因素	Open	－0.013	0.039
制度因素	Fin	0.137^*	0.056
	Pub	－0.251	0.134
	Cor	0.156^**	0.054
	HR	－0.057	0.081
	Tra	－0.210	0.126
	Bud	0.131^*	0.066
	Finsec	0.026	0.061
	Gend	0.190	0.135
	Env	0.181^**	0.066
公共设施与资源因素	Nat	－0.136^*	0.062
	Lab	－0.839^***	0.252
	Cell	0.190	0.110
	Urb	－1.659^***	0.490
截距		－0.286^*	0.133

变量	第一阶段全球媒体关注度	第二阶段FDI	变量	第一阶段全球媒体美誉度	第二阶段FDI
Bartik IV	0.169^**		Bartik IV	0.605^***
	(0.048)			(0.063)
Att		0.701^*	Img		0.303^**
		(0.352)			(0.096)
控制变量	是	是	控制变量	是	是
观测数	160	160	观测数	160	160
R²	0.582	0.398	R²	0.728	0.484