Cross-border takeovers, corruption, and related aspects of governance

Abstract

We use a panel of 4979 cross-border and domestic takeovers to test the relation between host country corruption and premiums paid for local targets. Host country corruption is negatively associated with target premiums, after correcting for other governance-related factors such as political stability, legal systems, and financial disclosure standards. We estimate that deterioration in the corruption index by one point (on a 10-point scale) is, on average, associated with a reduction of 21% of local targets' premiums. Our results do not support the notion that local corruption constitutes a significant market barrier to foreign investors; rather, it represents a discount on local takeover synergies, which affects foreign and domestic acquirers alike. However, we find that the major effects of corruption can alternatively be explained by government effectiveness, pointing towards an endogenous relationship between bribery and bureaucracy.

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Notes

  1. 1.

    We use the terms ‘merger’, ‘acquisition’, ‘takeover’, ‘transaction’, and ‘deal’ synonymously. M&A is used as the standard abbreviation for all of these terms.

  2. 2.

    Mauro (1995) found this relationship for a subjective index of corruption, as well as for bureaucratic efficiency, which he computed as the average of three indices from Business International (now The Economist Intelligence Unit): degree of corruption, amount of red tape, and efficiency and integrity of the judicial system.

  3. 3.

    As a simple illustrative example, consider merger synergies of $100 and an expected greenfield profit of $90, when there are no market barriers. In this case, the ‘net’ synergies (referred to as ‘gains of trade’ in the bargaining literature) that remain to be bargained over after considering the parties' outside options would be $10 ($100 total synergies minus $90 greenfield profit as outside option). In line with the Nash bargaining solution, we assume that the gains of trade are split evenly between both parties, generating a target premium of $5. For a corruption scenario, we lower greenfield profits to $40 owing to extra costs for outsiders (market barrier to entry). Now the gains of trade for the same takeover are $100−$40=$60, allowing ceteris paribus a target premium of $30 (evenly split).

  4. 4.

    See Harzing (2003) and Shimizu et al. (2004) for surveys on cultural distance studies focusing on entry mode decisions and cross-border M&As, respectively.

  5. 5.

    This includes the costs if agreements based on corrupt activities are not fulfilled (as they are unenforceable), and the costs if such agreements are rendered null and void, which is possible in many countries if convincing proof is presented (Council of Europe, 1995).

  6. 6.

    For a more detailed discussion, see Bardhan (1997) and also Kaufmann and Wei (1999).

  7. 7.

    All unreported regressions mentioned in this paper are available upon request from the authors.

  8. 8.

    For a similar procedure with the same database see, for example, Officer (2003) or Bates and Lemmon (2003).

  9. 9.

    For an overview and a detailed discussion of the index (including a comparison with other measures of corruption), see Wei (2000b), Husted (1999), and Lambsdorff (1999).

  10. 10.

    Where needed, monetary terms are deflated by the US CPI (1982–1984=100), and several control variables are lagged by 1 year to prevent possible endogeneity (especially in small countries).

  11. 11.

    As our model already includes several culture-related variables (e.g., legal systems, corruption, disclosure, ownership), we use the power distance index (PDI), being the strongest predictor within Hofstede's (1980) cultural index (Husted, 1999), as a simple proxy.

  12. 12.

    For 1990, SDC provides international coverage of 7144 transactions, including 396 transactions from non-OECD countries (5.5%). For 1999, 21,881 transactions are recorded, including 3300 from non-OECD countries (15%).

  13. 13.

    By this we want to exclude mixed cases where foreign (direct) acquirers may execute decisions of their domestic parents and vice versa (see Shimizu et al., 2004, 309).

  14. 14.

    The skewness of the distribution is similar to Gugler et al. (2003), who present a comprehensive international analysis of the SDC merger data.

  15. 15.

    Noteworthy exceptions are that the cross-border sample contains a politically more unstable environment (+81% compared with the domestic mean), a higher proportion of civil law legal systems (+73%), and more tender offers (+79%).

  16. 16.

    In support of this explanation, Table 3 reports a negative bivariate correlation between past GDP growth and GDP per capita.

  17. 17.

    In Models 3 and 4, a total of 547 takeovers with targets from the US, UK, or Japan are excluded.

  18. 18.

    The number of observations decreases slightly because some acquirer countries have no TI and/or WB corruption index, which is needed for computing an absolute difference.

  19. 19.

    We removed the acquirer's country dummy because it represents a host country fixed effect in the domestic panel.

  20. 20.

    We, inter alia, omitted Israel as an outlier, analysed several interaction effects, checked different samples, various time lags, absolute differences, and various fixed effects specifications.

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Acknowledgements

We thank Harry Garretsen, Gerrit Faber, Gerhard Kling, Peter Rodriguez, and four anonymous referees for insightful comments. We also thank Nico den Hartog for his help with the collection of the data. The usual disclaimers apply.

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Correspondence to Utz Weitzel.

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Accepted by Lorraine Eden, Amy Hillman, Peter Rodriguez and Donald Siegel, Guest Editors, 17 April 2006. This paper has been with the author for two revisions.

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Weitzel, U., Berns, S. Cross-border takeovers, corruption, and related aspects of governance. J Int Bus Stud 37, 786–806 (2006). https://doi.org/10.1057/palgrave.jibs.8400225

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Keywords

  • corruption
  • mergers and acquisitions
  • multinational enterprise
  • governance
  • foreign direct investment
  • institutions