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Do hubris and the information environment explain the effect of acquirers’ size on their gains from acquisitions?

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Abstract

We examine the negative relation between abnormal returns at acquisition announcements and the size of acquiring firms. This so-called size effect was first documented and investigated by Moeller et al. (J Financ Econ 73:201–228, 2004), who conclude that hubris on the part of large acquirers most likely explains the size effect. Our study is a further investigation of this size effect and makes the following contributions. First, we document that the effect exists monotonically across firm size deciles, not just in a comparison of “small” and “large” firms. Second, using a different methodology than Moeller et al. (J Financ Econ 73:201–228, 2004), we corroborate their finding that acquisitions made by large firms reflect more hubris than those made by small firms, but we also document that acquisitions made by small firms create more synergies than those made by large firms. In addition, we find that the size effect is significantly stronger for the smallest acquirers—who make value-creating acquisitions, on average—than it is for the largest acquirers. Taken together, therefore, our evidence indicates that the size effect is at least as much driven by small firms making superior, synergistic acquisitions as it is driven by large firms making inferior, hubristic acquisitions. Finally, we document that differences in the information environment between small and large firms do not explain the size effect.

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Notes

  1. Premiums are potentially available only for public targets. MSS use 1,761 observations to test for hubris using premium data (MSS Table 6, 221–222) and state that they lose “almost 600 acquisitions” (MSS, 220).

  2. Offenberg (2009), in his Table 3, shows that the size effect obtains in quintile partitions, but does not focus on this result.

  3. This argument is based on the theoretical correlations. Because the hubris motive can co-exist with the synergy and agency motives, however, total dollar returns are rarely zero, and target and total dollar gains could be significantly correlated even in the presence of hubris. Instead of examining correlations, we therefore estimate regressions and focus on the intercept as the test for hubris—as do Berkovitch and Narayanan (1993)—because the intercept captures the wealth transfer between the acquirer and target.

  4. Minimum tick size on the NYSE prior to 1997 was 1/8th. Thus, a share of stock with a value of $2.00 or less would have a minimum movement of +/− 6.25 %.

  5. If we winsorize CARs instead (at the 1st and 99th percentiles), our sample size increases from 18,872 to 19,716 for the univariate analyses, and from 15,007 to 15,746 for the multivariate analyses. Our results are qualitatively unchanged.

  6. We replicate the full analysis in MSS’s Table 2 (p.207) for our sample and find consistent results for the abnormal dollar returns for each acquisition as well. These results are available upon request.

  7. We replicate these analyses using size portfolios formed using rankings based on the population of NYSE-AMEX-NASDAQ firms and draw similar conclusions, indicating that our results are not specific to our portfolio formation process. These results are available upon request.

  8. We conduct all significance tests using heteroskedasticity-consistent standard errors (White 1980).

  9. We conduct all significance tests using heteroskedasticity-consistent standard errors (White 1980).

  10. A statistical test, not reported in the table, shows that the slope coefficient in the first four quintiles is also significantly larger than in the fifth quintile.

  11. A statistical test, not reported in the table, shows that the slope coefficient in the fifth quintile is also significantly lower than that in the first four quintiles.

  12. These results are identical to those presented in Table 2. We do not discuss them further here.

  13. In this partition, correlations between ln(size) and the CARs are −0.06 for the (−10, −2) window, −0.12 for the (−1, +1) window, 0.00 for the (+2, +10) window, and −0.10 for the (−10, +10) window. The three nonzero correlations are significant at p < 0.01.

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Acknowledgements

We thank the anonymous reviewers, the participants at the 2010 SFA conference and the 2010 Front Range Finance Seminar, and Steve Huffman, Steve Makar, Cliff Moll, Sherrill Shaffer, Hilla Skiba, Fred Sterbenz, and Marc Umber for their helpful comments and suggestions.

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Authors and Affiliations

  1. School of Business—Camden, Rutgers University, 227 Penn Street, Camden, NJ, 08102, USA

    Ivo Ph. Jansen

  2. Department of Economics, Whitman College, 345 Boyer Avenue, Walla Walla, WA, 99362, USA

    Lee W. Sanning

  3. Department of Accounting, College of Business, University of Wisconsin Oshkosh, 800 Algoma Boulevard, Oshkosh, WI, 54904, USA

    Nathan V. Stuart

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  1. Ivo Ph. Jansen
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  2. Lee W. Sanning
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  3. Nathan V. Stuart
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Correspondence to Ivo Ph. Jansen.

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Table 8 Variable definitions
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Jansen, I.P., Sanning, L.W. & Stuart, N.V. Do hubris and the information environment explain the effect of acquirers’ size on their gains from acquisitions?. J Econ Finan 39, 211–234 (2015). https://doi.org/10.1007/s12197-012-9240-0

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