The Determinants of Merger Waves - univie.ac.at

The Determinants of Merger Waves - univie.ac.at

The Determinants of Merger Waves Klaus Gugler Dennis C. Mueller B. Burcin Yurtoglu University of Vienna Department of Economics Vienna, Austria 1 Stylized facts on mergers Mergers come in waves Waves are positively correlated with share prices and price/earnings ratios 2 Mergers and Average P/E ratio 45 40 35 30 25 20 15 10 5 0 1895 1900 1905 1910 1915 1920 1925 1930 1935 1940 1945 1950 1955 1960 1965 1970 1975 1980 1985 1990 1995 2000 Year Average P/E Mergers/Population 3 An enormous number of hypotheses have been advanced to explain why mergers take place. Most of the hypotheses have been advanced to explain specific kinds of

mergers. Many of them are plausible explanations for some mergers, but they do not offer convincing explanations for waves in aggregate merger activity. 4 Example: Vertical mergers to increase market power by increasing barriers to entry (Comanor, 1967) to increase efficiency by reducing transaction costs (Williamson, 1975). However, it is difficult to imagine why the conditions necessary to make such mergers profitable would appear across a sufficient number of industries at a particular point in time to generate a wave in aggregate merger activity, and why this point in time should correspond to a stock market rally. 5 For a merger wave to occur some sorts of mergers must greatly increase in frequency at particular points in time. We want to determine which hypotheses are likely to predict such variations in the frequency of mergers over time. We examine four hypotheses that have been put forward specifically as explanations of merger waves 1) 2) 3) 4) the q-theory the industry shocks hypothesis the overvaluation hypothesis The managerial discretion hypothesis 6

The first two are neoclassical in that they assume that (1) managers maximize shareholders wealth (2) mergers are wealth creating (3) capital market efficiency The other two may be classified as behavioral, because they drop the assumption of capital market efficiency and/or that managers maximize their shareholders wealth. 7 Neoclassical hypotheses The q-theory of mergers Jovanovic and Rousseau (2002) The industry shocks hypothesis Mitchell and Mulherin (1996) Harford (2004) 8 Behavioral hypotheses The overvaluation hypothesis of mergers Shleifer and Vishny (2003) Rhodes-Kropf and Viswanathan (2003) Rhodes-Kropf, Robinson and Viswanathan (2003) The managerial discretion hypothesis of mergers Marris (1964) Mueller (1969) 9 The theories differ with respect to their predictions about the determinants of mergers, (DM) the determinants of tender offers versus friendly mergers, (TO vs. FM) the characteristics of target firms the post-merger share performance of acquiring firms (SP) 10

The q-Theory of Mergers Underlying logic: Firms with qs > 1 can profitably expand by acquiring assets Critique: If managers are maximizing shareholders wealth, and they have just become more talented, then the mergers must benefit the acquirers shareholders. Three options: new plant and equipment, used plant and equipment, purchase another company. Why only latter two? (Jovanovic and Rousseau, 2002); Premia rise in wave! 11 Table 1: Number of Acquirers and Targets in Friendly Mergers (FM) and Tender Offers (TO) and Mean Tobins qs Acquirers Year FM TO %TO Targets FM TO FM FM TO TO MV / TA MV / TA MV / TA

DV / TA MV / TA DV / TA 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 205 311 486 478 166 156 177 181 273 318 346 513 607 726 817 960 1001

599 588 550 453 339 14 23 23 29 41 56 47 60 55 26 19 16 25 33 57 55 73 72 63 63 47 37 6.39% 6.89% 4.52% 5.72% 19.81% 26.42% 20.98% 24.90% 16.77% 7.56% 5.21% 3.02% 3.96% 4.35% 6.52% 5.42% 6.80%

10.73% 9.68% 10.28% 9.40% 9.84% 1.275 1.216 1.377 1.411 1.154 1.245 1.380 1.298 1.327 1.532 1.459 1.873 1.681 1.644 1.623 1.803 1.902 2.004 2.218 2.708 1.962 1.705 0.664 0.906 0.781 0.921 0.902 1.001 1.118 1.316 0.998 1.356 1.282 2.034 1.557 1.732 1.570 1.581 1.652

1.732 1.860 1.646 2.416 2.006 1.011 0.846 1.052 1.218 1.085 1.234 1.204 1.384 1.306 1.341 1.397 1.343 1.384 1.238 1.147 1.490 1.213 1.590 1.687 2.012 1.490 0.862 0.756 0.829 1.018 1.097 1.465 1.654 1.564 2.048 1.588 1.435 1.857 2.123 2.096 2.060 2.292 2.819 2.295

3.095 3.109 2.340 2.281 1.000 1.066 0.758 0.797 1.073 1.075 1.232 1.140 1.046 1.266 1.253 1.274 1.133 1.706 1.259 1.503 1.200 1.057 1.274 1.498 1.886 1.091 1.017 0.787 0.711 0.804 0.897 1.754 1.815 1.662 1.757 2.008 1.694 2.144 1.720 2.548 2.556 2.951 2.525 2.340

2.602 2.216 2.076 1.865 1.468 Total 10250 934 8.35% 1.742 1.489 1.298 1.976 1.118 1.854 Wave 4515 383 7.82% 1.988 1.683 1.433 2.611 1.358 2.471

Nonwave 5735 551 8.77% 1.548 1.347 1.216 1.589 1.117 1.618 12 The Industry Shocks Hypothesis Underlying logic: Shocks to industry (e.g., technological innovations and deregulation) make mergers profitable and lead to industry merger waves several industries must enter a wave at the same time However, these shocks are not enough. There must be sufficient capital liquidity to accommodate the asset reallocation. (macroeconomic liquidity) Critique: Ignores association of wave and stock market boom (Harford, 2004) Given its neoclassical nature, the role of liquidity is problematic 13 Implications of the ISH Why does liquidity play an important role? This can be reconciled with the efficient capital market assumption, if one assumes that the firms making acquisitions are undervalued, and thus cannot profitably finance an acquisition by issuing shares.

This interpretation of the ISH leads to a testable prediction: firms undertaking acquisitions during a merger wave will be undervalued. 14 A second implication of the ISH There should be a relative expansion of the amount of assets acquired by issuing debt during a merger wave, because it is the fall in borrowing costs that precipitates mergers in industries experiencing shocks. Table 2 presents the sources of finance for mergers over our sample period. During the merger wave years (1995-2000), the relative importance of debt actually fell. 15 Table 2: Sources of Finance for Acquisitions: Total Amounts of Assets Financed by the Various Sources Year 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 Non-Wave Wave (1995-2000) All years Equity 14.54 22.18

16.57 18.25 16.85 22.33 25.69 14.62 22.23 29.88 31.00 27.97 30.45 35.33 35.86 29.52 18.40 20.11 31.75 24.22 Cash 78.06 73.38 78.70 74.89 76.36 68.79 63.88 73.97 68.17 63.63 62.89 65.55 63.19 59.49 60.00 63.96 74.28 72.22 62.46 68.77 Other 7.45 4.73 5.12 7.09

6.96 9.30 10.81 10.21 9.64 7.04 6.57 7.00 6.85 5.72 4.53 7.21 7.77 7.85 6.29 7.30 16 A third implication of the ISH is that acquirers shareholders benefit from the mergers. An industry shock creates profitable merger opportunities, and shareholder-wealth-maximizing managers seize these opportunities. The assumption of capital market efficiency implies that all wealth gains from mergers are registered in share price movements at their announcements, and thus that the shares of acquirers exhibit positive abnormal returns at the announcements. Over longer time spans following the mergers share performance should be indistinguishable from nonmerging firms. These predictions also differ from those of both the managerial discretion and overvaluation hypotheses and thus constitute tests to discriminate between the two sets of hypotheses. 17 Summary Both the q - and industry shocks theories suffer as explanations of merger waves, because important implications of them are not supported by the data. Target firms do not become relatively inexpensive during a merger wave as predicted by the q-theory, they become relatively more expensive than capital equipment. Debt-financed mergers do not become relatively more important, as predicted by the industry shocks hypothesis, they become less

important. An additional reason for rejecting these two theories is that they fail to incorporate the most salient characteristic of a merger wave into their explanation for it -the markets over-optimism. Since this over-optimism plays a central role in both behavioral theories of merger waves, we now discuss the psychology of stock market booms. 18 The Psychology of Stock Markets Todays share price should have a definite relationship to a firms future earnings and dividends. Shiller (1981): swings in stock prices in the USA over the 20th century were far greater than could be accounted for by subsequent swings in earnings and dividend payments. 1920s optimistic 1930s pessimistic it t (1 k ) t 0 i Vi 0 io (1 gi )t io Vi 0 t (1 k ) ki g i t 0

i (1) Assuming an average rate of growth of gi from now to infinity, (1) becomes (2) 19 if ki > gi, which implies that the price/earnings ratio of firm i should equal 1/(ki - gi). In the 1990s stock market boom, the S&P price/earnings ratio topped 40. Assuming an average ki of 0.12, roughly the average return on stocks over the period 1928-2004, then a P/E of 40 implies an expected, perpetual growth rate of 0.095, which is more than four times the average growth rate over the same period. Why should share prices rise to unprecedented levels? a new era ? 1920s, mergers in the steel industry, railroads community of interest: mergers will avoid much economic waste and effect various economies coincident to consolidation. 1960s conglomerate merger wave, conglomerate mergers P/E magic

1990s, Harford (2005) industry shocks 20 Industry Reason / Shock The insurance industry 1998 big is safer, leading to consolidation, especially in reinsurers. The medical equipment industry - 1998 (1) acquisitions in core areas to grow (2) acquisitions outside core areas to offer broad products to increasingly consolidated customers (hospitals). 21 The Managerial-Discretion Hypothesis Underlying logic: Managers sacrifice profits for size and growth; constraints less binding in waves due to increased optimism, high share prices, and cash flows Critique: The MDH departs from most neoclassical economics by assuming that managers pursue growth and not shareholder wealth, and that stock market psychology influences managers decisions 22 managers utility can be expressed as a function of the growth of their firms, g, and the threat of takeover, which is inversely related to q U U g , q

U g 0 2 2 U g 0 U q 0 2 U 0 q 2 g g (M ) (U / g )(g / M ) (U / q )(q / M ) 23 Figure2:TheM anagerial Trade-off (A) (B) u q qMN u g , gM u q qM u q qMB q

B 1.0 N u g g M M N M B M M 24 Tests: Degree of speculation, Shiller (2000): (P/Et) MDH-DM: M t M t M t M t M t 0, 0, 0, 0, 0 CFt 1 ( P / E )t qt 1 (qt 1 CFt 1 ) St 1 MDH-TO: The MDH-DM receives less support for tender offers, TOit, than for friendly mergers, FMit.

25 MDH-SP1: The shares of acquiring firms earn large negative abnormal returns over long time spans following the mergers, but not immediately when they are announced. MDH-SP2: The post-merger performance of acquirers shares is worse for mergers undertaken during merger waves. 26 The Overvalued Shares Hypothesis Underlying logic: Shleifer and Vishny (2003); managers exchange their overvalued shares for real assets of another company Critique: managers of overvalued firm maximize welfare of current shareholders at the expense of new ones; why pay high premia? (Any other asset would work) 27 How to measure the overvaluation Logically difficult Others (Verter, 2002; Ang and Cheng, 2003; Dong, Hirshleifer, Richardson and Teoh, 2005; and RKRV, 2005) measures typically involve the ratio of market to book value of equity or its reciprocal. all firms in an industry have the same costs of capital and expected growth rates and use equation 2 to estimate 1/( ki - gi) for a typical firm by regressing the market values of all firms in the industry on their profits for a period of time when, based on the aggregate P/E ratio for the S&P index, shares in aggregate do not appear to be overpriced. Call this estimate of 1/( ki - gi), .

V it it Oit Vit V it (4) (5) 28 Tests: OVH-DM1: The assets acquired through mergers are positively related to Oit. OVH-DM2: The assets acquired through mergers are positively related to dOit and Ot, and both variables have identical coefficients (dOit = Oit - Ot) 29 OVH-TO: The OVH is better supported for friendly mergers than for tender offers. OVH-TC: The probability that firm i is acquired in t is a positive function of VSit and Oit. OVH-SP1: The shares of acquiring firms earn large negative abnormal returns over long time spans following the mergers, but not immediately when they are announced. OVH-SP2: The post-merger performance of acquirers shares is worse for mergers undertaken during merger waves. 30 Previous Tests of the Two Hypotheses MDH Schwartz (1984) Harford (1999) (1) cash rich companies are more likely to undertake acquisitions,

(2) their acquisitions are more likely to be diversifying acquisitions, (3) the abnormal share price reaction of bidders is negative and lower than for bidders which are not cash rich, and (4) operating performance deteriorates after acquisitions by cash rich companies. 31 OVH Dong et al. (2002) focus mainly on the choice of payment in mergers, and the pattern of post merger returns. Both Ang and Cheng and RKRV find a positive relationship between the likelihood that a firm becomes an acquirer and measures of overvaluation. Ang and Cheng (2003, Table 3) include size in their logit regression to predict the identities of acquirers. It picks up a positive coefficient and is by far the most significant variable in the equation. 32 Returns to acquiring and target firm shareholders Three categories: 1) 2) 3) very short windows, acquirers experience zero or slightly positive returns very short windows, acquirers experience negative returns, and conclude that some non-neoclassical hypothesis must explain mergers event windows spanning two, three or more years, none estimated positive returns to acquirers over long windows 33 Table 2a: Summary statistics, mean values All Acquisitions

Tender Offers Friendly Mergers Acquirer characteristics: Tobin's q Overvaluation (% of Total assets) Cash flow/Total assets Total assets (Mn 1985 USD) 1.71 69.7 0.064 4828.1 1.48 55.3 0.094 8296.6 1.74 71.6 0.060 4461.0 Target characteristics: Tobin's q Overvaluation (% of Total assets) Cash flow/Total assets Deal Value (Mn 1985 USD) 1.28 43.7 0.037 307.32 1.18 34.6 0.079 474.76 1.33 48.6

0.021 283.91 Mit 0.121 Tobin's q Overvaluation (% of Total assets) Cash flow/Total assets Total assets (Mn 1985 USD) 0.168 Non-merging firms: 1.50 37.6 0.014 503.6 0.116 34 Table 4 Eq. Hypothesis Type qit-1 Explaining the Amounts of Assets Acquired 1 MDH FM 0.027 16.69 2 MDH TO 0.0058 1.13 Oit 3 OVH

FM 4 OVH TO 0.078 23.56 0.031 3.66 dOit 0.062 18.82 0.42 29.79 Ot P/Et CFit-1 qit CF,it-1 Kt-1 Kt-12 Kt-13 Industry dummies N R2 Consistent with Hypothesis 5 OVH FM 0.012 40.53 0.21 7.89 0.022 3.7 9.3*10-6 17.83 -5.5*10-11

13.39 0.012 14.62 1.05 9.21 -0.078 3.81 2.0*10-5 14.60 -1.2*10-10 10.62 7.1*10-17 1.6*10-16 11.22 9.52 Yes No Yes No Yes 89182 0.137 82724 0.102 50238 0.073 45974 0.002 50238 0.11

Yes Yes Yes Yes No 35 Discriminating between the MDH and OVH Predicting the Probability of Being Acquired (PAQt) NW: PAQt = 3.99*10-7 Oit - 0.00115 VSit, n=20,378, R2=0.0009 0.14 1.22 W: PAQt = -8.10*10-6 Oit - 0.00191 VSit, 1.22 n=7,826, R2=0.0005 0.63 36 Predicting the Means of Finance SFt = 63.82 + 5.19 O/MVt 141.33CF/MVt 2.87FFt +10.58TMV/MVt 28.51 4.49 10.72 9.46 4.17 N = 3840, R2= 0.071 SFt, the fraction of assets acquired by a firm in year t through the issuance of new shares O/MVt, the ratio of the dollar amount by which an acquiring firm is overvalued to its market value in year t, CF/MVt, the ratio of the acquiring firms cash flow to its market value in year t,

FFt, the federal funds rate in year t, and TMV/MVt, the ratio of the targets market value to the acquirers market value in year t 37 Abnormal Returns We measure the ARs of acquiring companies (A) using AR A t n R A t n R NA t n The benchmark is the mean return on a portfolio of non-acquiring (NA) companies, which are in the same size decile as the acquiring company. Datastream, using the changes in the total return index, which is adjusted for dividend payments and share splits. 38 Table 5: The Returns to Acquiring Firms Window Month of Acquisition Period of Acquisition Friendly Mergers N Non-Wave

1624 Wave 1396 Difference One Year after Acquisition N -0.32 180 0.37 (1.42) 0.00 165 -0.35 (1.00) -0.32 Mean 0.92 (1.39) Median N -0.00 1804 2.23 (2.56) 1.01 1561

-1.31 (1.09) -1.01 Mean 0.11 (0.21) Median -0.29 0.56 (0.25) 0.13 -0.45 (0.33) -0.42 1645 -5.21 (5.85) -8.43 184 -2.78 (2.61) -6.09 1829 -4.97 (0.84) -8.31 Wave

1524 -7.95 (7.36) -10.83 171 -10.88 (3.05) -12.43 1695 -8.24 (1.02) -10.97 2.73b (1.95) 2.40a 8.09b (4.00) 6.34b 3.27b (1.32) 2.66a Non-Wave 1636 -15.37 (10.18) -22.17 183

-2.63 (4.73) -13.98 1819 -14.09 (1.44) -21.18 Wave 1513 -20.75 (12.35) -27.11 169 -31.19 (4.42) -37.36 1682 -21.80 (1.58) -28.35 5.37b (2.39) 4.94a 28.55a (6.50) 23.38a

7.70a (2.13) 7.17a Difference Three Years after Acquisition Median All Acquisitions Non-Wave Difference Two Years after Acquisition Mean 0.021 (0.09) Tender Offers Non-Wave 1625 -23.38 (11.24) -34.63 183 -12.09 (6.37) -23.82 1808 -22.23 (1.98)

-33.47 Wave 1480 -31.20 (13.93) -42.62 167 -45.85 (6.14) -58.55 1647 -32.68 (2.11) -44.58 7.81a (2.55) 7.99a 33.75a (8.89) 34.73a 10.45a (2.89) 11.11a Difference 39 Table 6: Predicting the Post-merger Returns of Acquirers Window

Period 1 Month 2 Constant Tt Ot dOit Tt*Oit N R Whole 0.016 27.98 -0.031 -8.82 -0.020 18.46 0.001 2.32 0.007 4.92 17015 0.021 1 Month Wave

0.011 6.25 -0.046 -8.81 -0.012 -5.18 0.001 0.45 0.009 5.16 12462 0.018 1 Month NW 0.018 23.11 -0.017 -3.77 -0.025 -13.81 -0.001 -4.07 0.005 1.87 4553 0.019 1 Year Whole

0.268 29.78 -0.467 -8.65 -0.247 -14.28 0.002 0.77 0.112 5.38 16682 0.017 1 Year Wave 0.188 6.42 -0.695 -8.29 -0.115 -2.78 0.006 1.55 0.136 4.91 4464 0.017 1 Year NW

0.311 25.85 -0.303 -4.19 -0.366 -12.83 -0.002 -0.47 0.106 2.82 12218 0.014 2 Years Whole 0.491 32.16 -0.823 -9.16 -0.437 -14.75 -0.010 -2.4 0.171 4.99 14891 0.021 2 Years Wave

0.221 4.99 -0.958 -7.18 -0.104 -1.75 0.004 0.68 0.144 3.49 3619 0.014 2 Years NW 0.508 24.16 -0.705 -5.81 -0.456 -9.11 -0.029 -4.14 0.260 4.15 11272 0.011 3 Years Whole

0.767 31.18 -1.209 -9.78 -0.743 -14.51 -0.032 -4.23 0.214 4.33 13372 0.026 3 Years Wave 0.408 4.84 -0.988 -5.64 -0.419 -3.28 0.006 0.5 0.154 2.66 2943 0.017 3 Years NW

0.644 21.23 -1.186 -7.03 -0.333 -4.6 -0.057 -5.77 0.205 2.36 10429 0.010 Tt: The size of the target at the announcement, Ot : The average overvaluation in the market at the time of the acquisition dOit : The acquirers deviation from the average overvaluation in the market at the time of the acquisition 40 Conclusions Support for Behavioral Theories stronger than for Neoclassical Some evidence against overvaluation hypothesis Overvaluation hypothesis cannot explain increase in mergers financed by debt or cash flows Managerial discretion hypothesis first decide whether to make an acquisition or not, second how to finance it. 41 Based on our empirical results we offer the following account of merger waves: At some points in time, shareholder optimism begins to rise. This optimism in the market allows managers to undertake wealthdestroying acquisitions, and not have their announcements met by immediate declines in their companies share prices. The number of wealth-destroying mergers increases dramatically during a stock market boom creating a merger wave. As the market learns about the mergers, it realizes that they will not

produce synergies, and that the theories behind them were false. The markets optimism disappears and the share prices of acquiring firms fall relative to those of other companies. Because of the premia paid for the targets and the transaction costs of integrating separate companies, the losses to shareholders of companies making acquisitions are greater than one expects, simply because the 42 acquiring companies were overvalued.

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