Global Ownership and Corporate Control Networks

Abstract

In this contribution, at …rst, we introduce a basic network framework to study pyramidal structures and wedges between ownership and control of companies. Then, we apply it to a dataset of 53.5 million of companies operating in 208 countries. Among others, we detect a strong concentration of corporate power, as less than 1% of parent companies collect more than 100 subsidiaries, but they are responsible for more than 50% of global sales. Therefore, we show that the role of indirect control, i.e., through middlemen subsidiaries, is relevant in 15% of domestic and 54% of foreign subsidiaries. Among foreign companies, cases emerge of blurring nationality, when control paths cross more than one national border, in the presence of multiple passports (19.1%), indirectly foreign (24.5%), and round-tripping subsidiaries (1.33%). Finally, we relate indirect control strategies to country indicators of the institutional environment. We …nd that pyramidal structures arise less likely in the presence of good …nancial and contractual institutions in the parent's country, as these foster more transparent forms of corporate governance. Instead, parent companies choose indirect control through countries of subsidiaries that have better …nancial institutions, possibly because it is easier to coordinate decisions from remote. Finally, we …nd that o¤shore …nancial centers are preferred jurisdictions for middlemen subsidiaries, probably due to a lower taxation and a lack of …nancial disclosure.

Raising Arab Capital: Experirnces of Russian Regions

“…The perimeter of 320,000 MNEs is a globally representative universe resulting from a massive extraction of firm-level information from Orbis (based on an initial sample of 22 million firms reporting ownership information) after several computational and cleaning steps. The identification of the MNE corporate boundaries, and the computational effort of mapping a total of nearly 40 million ownership links, uses the algorithmic approach developed in Rungi et al (2016). …”

“…6 The first set of affiliates can be identified directly in Orbis by setting ownership thresholds at 50 per cent. The second set of affiliates cannot be derived directly in Orbis but has been generated here following the aggregation methodology developed in Rungi et al (2016). 7 The number of this group varies depending on an exogenously determined "probability threshold".…”

“…This set has been excluded from the analyses in this section. The control-probabilities method for the calculation of corporate boundaries is developed in Rungi et al (2016). 8 Lewellen and Robinson (2013) find that historical coincidence is a statistically significant determinant of ownership complexity.…”

“…Source: ©UNCTAD analysis based on Orbis data (November 2015). Note: The identification of the corporate boundaries of the 100 MNEs, and the computational effort, uses the algorithmic approach developed in Rungi et al (2016). The perimeter of jurisdictions qualifying as OFCs includes tax havens and major offshore investment hubs (see WIR15 on OFCs and offshore investment hubs).…”

The multilayer structure of corporate networks

“…These networks have revealed a small corporate world; a large concentration of ultimate ownership in a small group of core companies in this network [11]. In [12], ownership networks are studied to find the role of subsidiaries in control of large parent companies.…”