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The Determinants of Mergers

Burcin Yurtoglu

University of Vienna

Department of Economics

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Empirical Regularities

1) Mergers come in waves USA: Late 1890s, 1920s, 1960s, 1980s, 1990s

2) Merger waves are correlated with increases in share prices and price/earnings ratios

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Mergers and Average P/E ratio

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5

10

15

20

25

30

35

40

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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

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Types of Mergers

• Horizontal– involve two firms operating in the same kind of

business activity, e.g. Daimler-Chrysler

• Vertical– occur between firms in different stages of production

operation

• Conglomerate– occur between firms engaged in unrelated types of

business activity– product-extension: broadens the product lines of firms– geographic market-extension: between firms whose

operations have been conducted in non-overlapping geographic areas

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Hypothesis about Mergers

There are a big number of hypothesis as to why mergers occur, these can be grouped into two broad categories:

1) Neoclassical theories

that assume that managers maximize profits or shareholder wealth and thus that mergers increase either market power or efficiency

2) Non-neoclassical or behavioral theories

that posit some other motivation for mergers and/or other consequences.

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1) Neoclassical Theoriesa) Market Power Increases

b) Efficiency Increases

2) Non-neoclassical or Behaviorala) Speculative Motives

b) The Adaptive Firm Hypothesis

c) The Market for Corporate Control

d) The Economic Disturbance Hypothesis

e) Financial Efficiencies

f) The Capital Redeployment Hypothesis

g) The Life-Cycle-Growth-Maximization Hypothesis

h) The Winner’s Curse- Hubris Hypothesis

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(1a) Market Power Increases

Horizontal Mergers– fewer firms in an industry have greater incentives to

cooperate and raise the price– In a symmetric Cournot equilibrium, with

homogeneous product and all firms having the same, constant unit cost c

– H :Herfindahl index– :price elasticity of demand for the industry

p c HL

p

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• Since a horizontal merger increases industry concentration, it increases H, it must also increase the industry price-cost margin and profits.

• Salant, Switzer and Reynolds (1983)– However, Salant et al. (1983) show that mergers in such a

setting are not privately profitable. When all firms have identical costs, they all must have the same size.

– The above equation must hold before and after the merger. Since the immediate effect of the merger is to make the merged firm twice as big as ist competitors, it needs to shrink following the merger to return to the new size of ist rivals.

– The loss of profits to the merging firms from having to shrink to rejoin the symmetric Cournot equilibrium more than offsets the gain in profits from the increase in price cost margin caused by the increase in H.

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• Vertical mergers– by increasing the barriers to entry at one or more links in

the vertical production chain– Example: a firm which wished to enter into aluminum

refining in the USA prior to the Second World War would have found that all known bauxite deposits were owned by ist main competitor ALCOA. ALCOA could easily foreclose the bauxite market to the entrant and thus created an entry barrier.

• Conglomerate mergers– multimarket contact (Scott, 1982, 1993)– An increase in concentration leads to a greater increase

in profits in a market in which the sellers also face one another in other markets than when such multimarket contact is not present. This motive may also be the cause of purposeful diversification mergers.

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(1b) Efficiency Increases

• Horizontal Mergers

AC

Output

A

B

C

DE

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• In such an industry, one would expect the merging firms to be smaller than non-merging firms, because the expected cost reductions are greter for pairs of small firms.

• Empirical Evidence:– In Belgium, Germany, USA, and UK merging firms were

significantly larger than non-merging firms– In France, the Netherlands, and Sweden merging pairs were in

significantly different in size from randomly selected nonmerging companies.

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• Vertical mergers

• Can increase the efficiency of the merging firms by eliminating steps in the production process, which reduces the transaction costs from bargaining due to asset specificity

• Asset Specificity refers to the relative lack of transferability of assets intended for use in a given transaction to other uses. Highly specific assets represent sunk costs that have relatively little value beyond their use in the context of a specific transaction. Williamson has suggested six main types of asset specificity: – Site, physical asset, human asset, brand names, dedicated assets,

temporal specificity

• High asset specificity requires strong contracts or internalization to combat the threat of opportunism.

• Small subcontractors locating and investing next to only customer who could potentially turn to alternative suppliers (site- and physical asset specificity).

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General Motors and Fisher Body 1919-1926

After a 10 year contractual agreement was signed in 1919, GM's demand for closed-body cars increased to extent that it became unhappy with the contractual price provisions and "urged Fisher to locate its body plants adjacent to GM assembly plants, thereby to realize transportation and inventory economies." [Williamson, AJS, p.561]

Finally, Fisher Body was merged into GM in 1926 after Fisher had resisted GM's locational demands.

As Coase recalls:

"I was told [by GM officials] that the main reason for the acquisition was to make sure that the body plants were located next to General Motors assembly plants." [Coase, "The Nature of the Firm: Origin", in: Williamson & Winter, eds., The Nature of the Firm. 1993, p.43.]

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• Conglomerate Mergers

– Economies of scope (ESC) arise when the production of two different products by the same firm leads to lower production costs for one or both products.

– Example: warehousing and delivery of products

– Formally, ESC is said to exist if the cost function is subadditive

C(x1, x2) < C(x1,0) + C(0, x2)

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(2a) Speculative Motives

• Studies of early merger waves often mention “promoters’ profits as a cause for mergers. During these waves men like J.P. Morgan often approached corporate managers and suggested a possible merger. They earned large fees for their advice and for other services they rendered to facilitate and finance the deals.

• Underwriters of the securities floated in the great merger that created the United States Steel Corp. In 1901, earned fees of $575.5 million – over $1 billion in today‘s dollars (The Economist, April 27, 1991, p. 11).

• Michael Milken

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Fee Revenue from underwriting and M&A transactions in 1998 (Saunders and Srinivasan, 2001 )

Investment BankFee Revenue from

Underwriting (equity & debt) (1)

Fee Revenue from Merger Advice (2)

(2) / (1)

Morgan Stanley 1253.8 302.9 19.50%

Goldman Sachs 1087.8 531.2 32.80%

Merrill Lynch 1496.9 321.3 17.70%

Credit Suisse First Boston 386 287.4 42.70%

DLJ 491.8 200 28.90%

Citibank 913.2 189.1 17.20%

Lehman 516.3 199.2 27.80%

J.P. Morgan 358.9 70.9 16.50%

Bankers Trust 252.2 56.9 18.40%

NationsBank Montgomery 132.7 26.2 16.50%

Average 688.9 218.5 23.80%

Total 6889.6 2185.1 31.72%

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(2b) The Adaptive (Failing Firm) Hypothesis

• Donald Dewey (1961):– mergers as a civilized alternative to bankruptcy

• John McGowan (1965):– An adaptive theory to account for why small firms are typically

the targets in mergers and why the much more competitive US and UK economies had more mergers than the less competitive ones.

• Two implications:– Mergers should follow a counter-cyclical pattern. Why don’t we

see merger waves during recessions?– Profit rates of acquirers should be higher than targets

• Empirical Evidence– Most studies of mergers in the USA have found that acquired

firms have the same average profit rates as similar non-acquired companies

– During the conglomerate merger wave acquiring companies had below average profit rates and also profit rates lower than the firms they acquired.

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Characteristics of Acquiring and Target Companies, 1980-1998

Gugler, Mueller, Yurtoglu, and Zulehner (2003)

Profit rate

Numberof Mergers

Acquirer Target

United States of America 1,967 0.029 0.019

United Kingdom 379 0.066 0.039

Continental Europe 172 0.035 0.033

Japan 16 0.011 0.030

Australia/N.Zealand/Canada 172 0.024 0.027

Rest of the World 47 0.052 0.013

All mergers 2,753 0.034 0.023

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(2c) The Market for Corporate Control

• Mt: market value of the firm in year t• Kt: the value of the assets of the firm in year t• If Mt > Kt: the assets bundled together as a firm are worth

more than their sum as measured by Kt.• Marris (1963, 1964) called Mt / Kt the valuation ratio, Vt • Tobin (1969) measured Kt as the replacement cost of the

firm’s asset and called qt = Mt / Kt.• Manne (1965):• Buyers in the market for corporate control would step in

whenever Vt falls short of its maximum value, and thus that this process ensures that corporate assets are managed by the most competent managers and those intend shareholder wealth maximization.

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• Smiley (1976):– Actual market values of acquired companies are

compared to a projected value (control group).– The market values of takeover targets began to fall

below their predicted values on average 10 years before the takeover, and that the cumulative decline was 50% of predicted values.

• Other Studies– have found the shares of acquiring firms to be

underperforming prior to their takeover (Mandelker, 1974; Langetieg, 1978; Asquith, 1983; Malatesta, 1983)

– Exception Dodd and Ruback (1977)

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(2d) The Economic Disturbance Hypothesis

• Gort (1969)– a group of non-holders suddenly raises its

expectations about firm B’s future profits. If these non-holders are managers of another firm, the transaction takes the form of a merger.

– Mergers under this hypothesis are more likely to happen in periods in which stock market experiences rapid changes in value.

– Consistent with the wave pattern– But also consistent with merger waves during sudden

drops in stock market values (even more intense merger activity!)

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(2e) Financial Efficiencies

Savings on Borrowing Costs

Riskpooling

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(2f) The Capital Redeployment Hypothesis

• Weston (1970)– Similar to financial efficiencies argument, but

goes beyond it by positing ongoing potential gains from a central management team’s ability to monitor the investment opportunities of each division and shift capital across them.

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(2g) The Life-Cycle Growth Maximization Hypothesis

• Mueller (1969)– Mergers are the quickest way to grow and

diversify and thus an attractive way for managers with limited time horizons to achieve growth.

– Predictions• diversification mergers by mature firms

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• Direct Evidence by Harford (1999):– Cash rich firms are more likely to acquire– Their acquisitions are more likely to be

diversifying– The abnormal price reaction is negative and

lower for bidders who are cash rich– Operating performance deteriorates after

mergers by cash rich companies

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(2h) The Winner’s Curse –Hubris hypothesis

• There are a number of bidders• The bidder with the highest valuation acquires

the target• With rational expectations, the expected true

value of the target should be at the mean of the distribution

• The winner will bid too much!• Why bid then?• Roll (1986):• Because managers of acquiring firms suffer from

hubris, excessive pride and arrogance.

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Testing Competing Hypotheses about the Determinants of Mergers

Three categories of hypotheses1) Synergy

• e.g., a horizontal merger that increases the market power of the two merging companies

• The ynergistic gains arise from specific characteristics of the two merging firms.

• It is reasonable to assume that both firms share these gains, since each firm‘s participation in the merger is required for there be any gains at all.

• A weaker assumption would be simply that the shareholders of both firms benefit from the merger.

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2) Market for Corporate Control• All of the gains from the merger are tied to the

target firm. In principle, any other firm could buy the target and replace its managers and obtain the wealth increase from its action.

• If the bidding for the target continues until the target‘s share price rises by enough to reflect all of the gains from replacing ist management, the bidder‘s shareholders will experience no gain from the merger.

• Target‘s shareholders receive positive welath increases

• Bidders‘ gains averge zero and are unrelated to the gains to the targets.

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2) Managerial Discretion• There are no net gains from the mergers• Each dollar paid to the target shareholders represents a dollar loss

to the acquirers‘ shareholders.• Thus, the gains to the target‘s and bidder‘s shareholders should

be inversely related.• It is not possible to distinguish a merger motivated by pure hubris

from one stemming from managerial empirebuilding. In both cases, the targets‘ gains are bidders‘ losses. It is also possible, however, that managerial hubris may arise with mergers that do generate positive net wealth gains. Out of overoptimism the bidder pays too much for the target.

• In such a mixed case, we would expect a net positive gain from the merger, but a loss to the bidder. Moreover, the bigger the gain to the target, the more likely it is that the bidder overbid, and the bigger ist expected loss.

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Tests: Mueller and Sirower (2002)

G: Gain to the bidder in dollars over a 24-month period beginning with the month of the merger

P: Premium paid to the target‘s shareholders in dollars

VT: Market value of the target firm

T T

G Pe f

V V

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The predicted coefficients

Hypothesis Prediction without

Hubris Hypothesis

Prediction with

Hubris Hypothesis

Synergy

(SH) e=0, f=1 e<>0, f<1

Market for Corporate Control

(MCCH)e=0, f=0 e<>0, f<0

Managerial discretion (MDH) e=0, f=-1 e=0, f=-1

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Relationship between gains to acquirers and premia paid to targets

e f N / R2 e f N / R2

Contested Uncontested

0.03 -0.21 44 / -0.023 0.26 -2.23 124 / 0.053

(0.06) (0.19) (0.97) (2.81)

Multiple Bidders Single Bidder

0.48 -1.94 45 / 0.051 0.09 -1.34 123 / 0.015

(1.13) (1.84) (0.32) (1.68)

Related (3 Digit) Unrelated (3 Digit)

0.20 -0.68 95 / -0.000 0.13 -2.54 73 / 0.052

(0.79) (1.00) (0.31) (2.23)

Cash Only Noncash (mixed)

0.49 -1.46 90 / 0.023 0.05 -2.48 78 / 0.057

(1.42) (1.75) (0.16) (2.38)

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• The mean gain to the bidders is -$50• The variance around this mean is $ 3,579,664 million• Are you willing to play in a game in which

– the expected winnings are -$50– you might lose as much as $10, 000,000– You might also win as much as $13,000,000

• These are summary statistics from the above sample, except that they are measured in millions.

• Why do managers of these firms undertake such gambles?– Hubris? Averages do not apply them– Managerial discretion? They are not gambling with other peoples

money!