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Determinants of partial versus full cross-border acquisitions for Sovereign Wealth Funds

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Abstract

In this paper, we investigate the determinants of equity shares purchased by Sovereign Wealth Funds (SWFs). Based on the literature of cross-border acquisitions and entry mode choice theory, we shed light on the real drivers of these state-owned funds when they buy small or large stakes in cross-border target firms. Using an original dataset of SWF acquisitions over the period 2000–2015, a Two-Part Fractional Regression Model is estimated to account for both the fractional nature of the dependent variable as well as the separation between the decision to invest and that concerning the share of equity invested. We find that the decision to invest and the decision on the share of equity to be acquired are two distinct processes. We also find that SWFs take the investment decision in cross-border target firms by trying to reduce transaction costs and information asymmetry according to the cross-border acquisition theory, and also by taking the legal and institutional environment of the host country into consideration. However, the fact that they do not hesitate to take large shares or to acquire targeted firms that are considered to be strategic and located in politically unstable countries suggests that their motives may go beyond financial consideration.

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Notes

  1. According to the SWF Institute, the assets managed by these funds were estimated to be USD 3.2 trillion in September 2007, which means that the size of these funds has more than tripled since the beginning of the financial crisis (source: www.swfinstitute.org).

  2. See the recent surveys of Megginson and Fotak (2015) and Megginson and Gao (2019).

  3. According to (Ferreira et al., 2014) there is no single theory dominant in M &A research, but only four theories that are predominantly used: agency theory, institutional theory, transaction cost theory and resource-based-view theory.

  4. In the same way, Boubakri et al. (2016) find that SWFs should less likely be attracted by large and liquid target firms than pension funds.

  5. For instance, French Decree No. 2014/079 specifies that foreign investments in transport, water, energy, electronic communications, public health and activities of vital importance as specified in the Defense Code will require authorization.

  6. Regulation (EU) 2017/1946 of 11 July 2017 supplementing Directives 2004/39/EC and 2014/65/EU.

  7. http://www.swfinstitute.org/.

  8. See Amar et al. (2019) for more details on the definition of SWF and the construction of the sample.

  9. Dewenter et al. (2010) collected a sample of 996 transactions covering the period 1997–2008. Kotter and Lel (2011) study 503 SWF investments over the period 1980 to 2009. Knill et al. (2012) use a sample of 900 acquisitions of public and private target firm’s stockholdings by SWFs, over the period 1984–2009. For the period 1980–2012, Bortolotti et al. (2015) use a sample of 1,018 investments while Murtinu and Scalera (2016) built a sample of 716 investments (474 cross-border) during 1997–2013. Another stream of work employs much larger datasets on SWF shareholdings rather than transactions, with some samples exceeding 20,000 companies (Avendano, 2012; ?; Dyck and Morse, 2011; Fernandes, 2014).

  10. The features of each transaction were gathered and include information on the target firms (firm name and country), information on the SWFs (name, subsidiary and country), date of the transaction, share acquired in the target firm and value of the deal. We dropped observations with missing data on the transaction share. We also dropped observations with missing/unavailable data for the variables of interest.

  11. According to Karolyi and Liao (2017), corporate deals fall by almost 90% because the unavailability of firm-specific variables in the Thomson Reuters database. Kotter and Lel (2011) have the same problem of availability of data but only mention the number of firms in which SWFs could invest (including their control sample).

  12. As the aim of the paper is to explain what are the drivers of SWFs when they buy small or large stakes in cross-border target firms, we exclude disinvestments because the determinants to explain the decision to partially or fully divest shares in cross-border firms are not the same.

  13. This is also called the World Market Index at level 1. These indices are composed of 7,138 firms from 53 countries and 170 sectors worldwide and covers for each market a minimum 75–80% of total market capitalization.

  14. Firm performance may also be proxied by net income by equity (ROE). We tested it in our estimates and find similar results which are available upon request.

  15. An alternative proxy is the total debt divided by the market value of equity (Debt/Equity). We testes it in our estimates and find similar results which are available upon request.

  16. We alternatively used the logarithm of total assets (Assets). We find similar results which are available upon request.

  17. We also tested two additional dummy variables. Strategic3 includes the following sectors: aerospace and defense; telecommunication service providers; telecommunications equipment; and chemicals. Strategic4 includes the following sectors: aerospace and defense; telecommunications equipment; oil, gas and coal; and chemicals.The results are not conclusive. They have not been included in the paper but are available on request.

  18. Contrary to logit and probit, which are symmetric functions around the point 0.5, the loglog and cloglog are asymmetric functions: the former (later) increasing more sharply (slowly) at small values of \(G(\cdot )\) and slowly (sharply) at values close to 1.

  19. We could also have estimated a Generalized Two-Part FRM (see Wulff (2019)) which models the correlation between the two decisions. However, this specification imposes very strong constraints on the second equation since it needs an exclusion restriction to be identified. Yet, the purpose of this paper is precisely to identify the determinants of the share acquired by SWFs. We have nevertheless tested the GTP-FRM which is not conclusive since the correlation coefficient is not significantly different from 0. In this case, the TP-FRM is the best choice. Results are not presented here in order not to alter the readability of the paper but are available on request.

  20. The results are clearly in favor of the probit specification (see Table 5).

  21. The tables give average effects, which may mask heterogeneity depending on the values taken by the explanatory variables. Their interpretation must therefore be completed by graphical analyses.

  22. SWFs target firms with high leverage with the aim of restructuring the management, adding value and potentially selling the firm once it has become profitable.

  23. According to Fernandez and Eschweiler (2008), by buying sizeable stakes in corporations, it is possible for SWFs to expropriate minority shareholders and pursue interests other than maximizing portfolio performance.

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Authors and Affiliations

  1. Université Côte d’Azur, CNRS, GREDEG, Nice, France

    J. Amar & M. Arouri

  2. Aix-Marseille University (Aix-Marseille School of Economics), CNRS, EHESS, Aix-en-Provence, France

    G. Dufrénot & C. Lecourt

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  1. J. Amar
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Amar, J., Arouri, M., Dufrénot, G. et al. Determinants of partial versus full cross-border acquisitions for Sovereign Wealth Funds. Rev World Econ (2023). https://doi.org/10.1007/s10290-023-00504-6

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