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Spatio-temporal patterns of the international merger and acquisition network

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  • Dueñas, Marco
  • Mastrandrea, Rossana
  • Barigozzi, Matteo
  • Fagiolo, Giorgio

Abstract

This paper analyses 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 (nodes) connected according to their M&As flows (links). We study different geographical and temporal aspects of the international M&A 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 have a non-linear relation with distance, and an assortative pattern is present at short distances

Suggested Citation

  • Dueñas, Marco & Mastrandrea, Rossana & Barigozzi, Matteo & Fagiolo, Giorgio, 2017. "Spatio-temporal patterns of the international merger and acquisition network," LSE Research Online Documents on Economics 84092, London School of Economics and Political Science, LSE Library.
  • Handle: RePEc:ehl:lserod:84092
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    References listed on IDEAS

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    Cited by:

    1. A. Baronchelli & T.E. Uberti, 2018. "Exports and FDI: comparing networks in the new millennium," Working Paper CRENoS 201813, Centre for North South Economic Research, University of Cagliari and Sassari, Sardinia.
    2. Brózda-Wilamek Dominika, 2023. "The global cross-border mergers and acquisitions network between 1990 and 2021," International Journal of Management and Economics, Warsaw School of Economics, Collegium of World Economy, vol. 59(4), pages 333-348, December.
    3. Mercedes Campi & Marco Dueñas & Matteo Barigozzi & Giorgio Fagiolo, 2019. "Intellectual property rights, imitation, and development. The effect on cross-border mergers and acquisitions," The Journal of International Trade & Economic Development, Taylor & Francis Journals, vol. 28(2), pages 230-256, February.

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    JEL classification:

    • C1 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General
    • N0 - Economic History - - General

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