2017/13 | LEM Working Paper Series | ||||||||||||||||
Spatio-Temporal Patterns of the International Merger and Acquisition Network |
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Marcos Duenas, Rossana Mastrandrea, Matteo Barigozzi, Giorgio Fagiolo |
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Keywords | |||||||||||||||||
International Economics; Mergers and Acquisitions; Network Analysis; Geographical Distance
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JEL Classifications | |||||||||||||||||
C40; F21; F40
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Abstract | |||||||||||||||||
This paper analyzes the world web of mergers and acquisitions (M&As)
using a complex network approach. We use data of M&As to build a
temporal sequence of binary and weighted-directed networks, for the
period 1995-2010 and 224 countries. We study different geographical
and temporal aspects of the international M&As network (IMAN),
building sequences of filtered sub-networks whose links belong to
specific intervals of distance or time. Given that M&As and trade are
complementary ways of reaching foreign markets, we perform our
analysis using statistics employed for the study of the international
trade network (ITN), highlighting the similarities and differences
between the ITN and the IMAN. In contrast to the ITN, the IMAN is a
low density network characterized by a persistent giant component with
many external nodes and low reciprocity. Clustering patterns are very
heterogeneous and dynamic. High-income economies are the main
acquirers and are characterized by high connectivity, implying that
most countries are targets of a few acquirers. Like in the ITN,
geographical distance strongly impacts the structure of the IMAN:
link-weights and node degrees are strongly non-linear, and an
assortative pattern is present at short distances.
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