State capital in a geoeconomic world: mapping state-led foreign investment in the global political economy

Figures & data

Table 1. Comparing the geopolitical and geoeconomic approaches to foreign state investment.

Approach	Motivation of investment senders (states)	Conceptualization of targets	Status of global political economy	Nature of potential international competition/conflict/cooperation
Geopolitical	Projection of state power: Economic means for geopolitical goals	Other states	International: Space of dyadic inter-state relations	Direct: States vs./with other states
Geoeconomic	Exploitation of global investment opportunities: State capital is used to acquire assets and gain returns on investment	Industries, sectors, companies or regions	Transnational: Multiple network structures as part of a complex system	Indirect: States as owners compete for/collaborate on same or similar targets as/with other states and private actors and host governments

Figure 1. Illustration of the geopolitical (A) and geoeconomic (B) perspective. Each node is a state as owner, each tie represents total investment into another state (A) or cluster (B). Node size approximates total investment by a state, tie thickness approximates amount of the respective investment into a state (A) or cluster (B). (B) contains only states as owners (and not other actors) for representational reasons.

Table 2. Top 10 sectors of total transnational state capital.

Sector	Inflow state capital (in $)	Percentage of total
Manufacturing	414 bn.	23.9
Wholesale and retail trade	375 bn.	21.6
Financial and insurance activities	233 bn.	13.4
Electricity and gas	213 bn.	12.3
Transportation and storage	132 bn.	7.6
Mining and quarrying	148 bn.	6.6
Information and communication	88 bn.	5.1
Professional, scientific and technical activities	63 bn.	3.6
Administrative and support service activities	37 bn.	2.2
Construction	25 bn.	1.5

Note: Full table in the appendix, Supplemental Material tab online.

Figure 2. The range and frequency of the Gini-coefficients of the top 31 clusters analyzed in this paper.

Figure 3. Top 20 owners and their investment of transnational state capital in different regions. The left numbers are the total investment by each state, the right the total inflows in each region (in US Dollars). The node size reflects outflows (states) and inflows (regions). The color of the edges reflects the destination (region) of the investment.

Figure 4. Concentration of transnational state capital in different geo-industrial clusters, in percent. The percentages are to be read row-wise. Darker color indicates a higher percentage of absolute investment in the respective cluster. Each cell represents one geo-industrial cluster.

Figure 5. Southern European manufacturing cluster.

Figure 6. Southern European electricity and gas cluster.

Figure 7. Northern European transportation and storage cluster.

Figure 8. Northern American mining and quarrying cluster.

Figure 9. Western European manufacturing cluster.

Figure 10. Western European electricity and gas cluster.

Figure 11. Western European transportation and storage cluster.

Table 3. Control-portfolio ratios and Gini coefficients for all geographical areas. Sorted descending by total state investment.

Area	Control-portfolio ratio	Gini coefficient
Western Europe	5.1	0.51
Northern America	0.1	0.76
Northern Europe	2.4	0.68
South-Eastern Asia	33.7	0.82
Southern Europe	13.7	0.68
Eastern Asia	0.2	0.73
Australia and New Zealand	10.6	0.71
Latin America and the Caribbean	2.9	0.75
Eastern Europe	3.2	0.68
Southern Asia	1.6	0.74
Western Asia	4.1	0.76
Sub-Saharan Africa	0.4	0.73
Northern Africa	13.5	0.77
Central Asia	1254.8	0.78

Data availability statement

The data that support the findings of this study are available from Bureau van Dijk’s ORBIS database (https://www.bvdinfo.com/). Restrictions apply to the availability of these data, which were used under license for this study. Data are available from the author with the permission of Bureau van Dijk. The nationally aggregated and processed data as well as more supplementary material and the Python script are freely available at the Open Science Framework at https://osf.io/rkx7e/?view_only=2759b4b447204420b1353c62e7a6febe.