Envy‐Motivated Merger Waves

Author:Wenjia Zhang, John A. Doukas
Publication Date:01 Jan 2016
Introduction

A stylised fact about mergers is that they often occur in waves (e. g., Weston et al., ; Gaughan, 1999). During the past 100 years, the USA experienced five complete merger waves: those of the early 1900s, the 1920s, the 1960s, the 1980s, and the 1990s. The question of why mergers come in waves has been listed as one of the ten unsolved problems in finance (Brealey and Myers, )’.

While the academic literature offers a number of explanations for merger waves such as operational efficiency (Banerjee and Eckard, ), product market demand increases (Maksimovic and Phillips, 2001), industry‐specific shocks (Mitchell and Mulherin, ), stock market overvaluation (Rhodes‐Kropf and Viswanathan, ;Shleifer and Vishny, ; Gort, ), scale economies during economic expansions (Lambrecht, ) and regime shifts (Gorton et al., ), they are grounded on conflicting theoretical assumptions and have difficulties reconciling merger waves in industries with questionable scale economies such as the banking industry in the USA in the 1990s.

Surprisingly, merger waves in the banking industry, in contrast to industrial merger waves, have not been the focus of academic research. This study is the first attempt in the finance literature to examine bank merger waves and, in particular, whether they are motivated by managerial envy considerations. Envy can be viewed as the blend of feelings characterised by admiration and longing caused by a comparison with a person who possesses something that another person desires. In this study, we focus on the role of top managerial executive envy in making merger decisions. Envy is defined in terms of relative payoffs between acquiring top executives and their highest paid peers and we refer to it as the CEO envy‐pay hypothesis (i. e., pay gap between the highest paid bank top executives and their acquiring peers). While bank merger waves are likely to have occurred as a result of the removal of interstate branching restrictions, which facilitate the pursuit of scale economies (Lambrecht, ), empirical evidence (Berger and Hannan, , ; Berger, ) contradicts this efficiency‐based view. As Table illustrates, the annual US bank merger activity, based on completed transactions, increased tremendously in 1993, from 96 to 161 deals, and remained high till 2000. Hence, the merger wave began before the Riegle–Neal Interstate Banking and Branching Efficiency Act, passed by the Congress on 29 September 1994, which is often cited as important evidence of deregulation (Cho, ; Jones and Critchfield, ) that may have played a vital role in bank consolidation. Furthermore, the empirical evidence of DeLong () negates the role of scale economies as a possible source of merger waves.

Descriptive statistics for US bank merger bids <note numbered="no" xml:id="eufm12045-note-0001">This table reports descriptive statistics for the entire sample, including all 2,148 US banking bids during 1985–2006. Panel A reports the number of bank merger bids, number using stock payment, number of bids aiming at public targets, cross‐state bids, nominal and inflation‐adjusted average deal value, nominal and inflation‐adjusted average market value of bidders/targets, by calendar year. US Inflation adjusted US means that the deal value and the market prices have been adjusted to the Gross Domestic Product: Implicit Price Deflator composed by the US Department of Commerce: Bureau of Economic Analysis*, 2005 as the base year. *(<url href="http://www.bea.gov/national/nipaweb">http://www.bea.gov/national/nipaweb</url>). Panel B reports the number of bank mergers and median deal size for each type of merger, classified by method of payment, type of target bank, geographic diversification (cross‐state), and activity diversification.</note> Panel A: Frequency description Year Bank Mergers Stock Payment Public Targets Private Targets Cross‐state Bids Average Deal Size ($mil) Average Market Value of Bidders ($mil) Average Market Value of Targets ($mil) Nominal Inflation Adjusted Nominal Inflation Adjusted Nominal Inflation Adjusted 1985 18 12 11 7 9 96.17 155.91 NA NA NA NA 1986 93 48 23 70 29 110.25 174.75 860.89 1364.56 307.57 487.52 1987 53 31 22 31 23 54.34 83.63 656.99 1011.11 176.42 271.51 1988 39 17 25 14 16 51.93 77.07 1084.10 1608.84 144.59 214.58 1989 65 39 34 31 21 62.38 89.38 1286.72 1843.57 201.62 288.87 1990 60 19 40 20 9 17.24 23.75 242.62 334.22 295.54 407.12 1991 66 39 39 27 22 197.61 263.24 1566.45 2086.68 269.80 359.40 1992 96 61 57 39 37 99.01 129.07 1866.97 2433.71 413.16 538.58 1993 161 95 85 76 51 91.43 116.62 2209.89 2818.77 310.21 395.68 1994 195 106 102 93 71 45.68 57.03 1624.04 2027.67 445.90 556.72 1995 205 88 137 68 57 238.34 291.69 2289.86 2802.42 496.44 607.56 1996 207 69 175 32 43 46.77 56.23 2215.41 2663.42 460.75 553.93 1997 190 122 122 68 71 408.17 482.08 2962.03 3498.36 799.88 944.71 1998 205 125 126 79 56 696.83 813.52 2713.81 3168.27 942.03 1099.78 1999 152 71 117 35 38 242.58 279.07 5907.92 6796.65 1410.62 1622.82 2000 130 45 114 16 34 398.27 447.98 7796.45 8769.61 1179.89 1327.17 2001 71 22 58 13 16 414.86 456.52 3916.51 4309.82 2994.44 3295.16 2002 22 6 13 9 6 31.97 34.64 3326.41 3604.54 95.38 103.35 2003 37 12 22 15 11 1466.5 1555.08 4120.34 4369.21 769.22 815.68 2004 40 16 22 18 12 306.26 315.31 4816.64 4958.91 1371.37 1411.88 2005 28 12 10 18 13 195.23 194.33 5732.18 5705.88 424.17 422.22 2006 25 8 15 10 16 170.54 164.37 12164.84 11724.47 264.16 254.60 Total 2148 1063 1369 779 661 Average 247.38 284.6 3302.91 3709.56 655.86 760.9 Panel B: Median Size of Mergers, by Type Merger Type Number of Mergers Median Deal Value ($mil) Median Market Value of Bidders ($mil) Relative Deal Size (Deal Value/Bidder MV) All Mergers 2148 19.40 650.70 2.98% Mergers with Stock Payment 1063 44.90 768.40 5.84% Mergers with Cash Payment 1085 6.89 308.80 2.23% Mergers with Public Targets 1369 22.01 1,261.91 1.74% Mergers with Private Targets 779 17.95 395.33 4.54% Geographic and Activity Diversification 143 65.00 1617.50 4.02% Geographic and Activity Focus 1286 9.85 302.38 3.26% Geographic Focus and Activity Diversification 199 31.78 249.30 12.75% Geographic Diversification and Activity Focus 520 50.4 1,786.79 2.82%

The market overvaluation theory of merger waves implies that mispricing is more likely during bull markets than in bear markets. However, Goel and Thakor () argue that mispricing is equally likely to occur during bull and bear market states and one would expect merger waves during bear markets when acquirers are searching for undervalued targets. In addition, the stock market overvaluation explanation is rooted in correlated values of mergers or perceptions of value gains rather than cross‐sectional causality between mergers. Consequently, in contrast to the managerial envy‐pay hypothesis, it does not put forward any prediction about the timing of mergers in a merger wave in terms of target size or bidder returns. Finally, Harford () shows that merger waves are not associated with market timing. All this, then, raises the question of what might be the source of a merger wave in an industry in which the wave‐propagating shock is not linked to market mispricing. These issues motivate the question addressed in this study: does managerial envy‐pay affect US bank merger waves?

Despite the fact that research on envy‐related issues in social sciences, including economics, has gained significant attention, finance research on envy is only at its early stages. Goel and Thakor () develop a theoretical framework, where agents exhibit envy‐based preferences. and show that envy leads to corporate socialism when capital is centrally allocated, whereas decentralised capital budgeting leads to overinvestment. Thus, they conclude that envy decreases firm value. More recently, Goel and Thakor () theorise and provide empirical evidence showing that envy among chief executive officers (CEOs) of industrialised (non‐financial) firms can generate merger waves, even when the shocks that precipitated the initial mergers are purely idiosyncratic for the first firm in the wave. Their model assumes that the preferences of CEOs depend on both absolute and relative consumption – with relative consumption preferences characterised by envy – and shows that merger waves can arise even when the shocks that trigger the initial mergers in the wave are idiosyncratic. Namely, CEO envy ‘induces a correlation in merger activities by making other CEOs in the same cohort envious of the larger firm size and compensation now linked with the CEO of the firm that acquired first’ (Goel and Thakor, , p. 490). The authors' analysis predicts and shows that earlier acquisitions produce higher bidder returns, involve smaller targets, and result in higher compensation gains for the bidder's top managers than late acquisitions in the merger wave. Consequently, they view envy as the key driving force behind corporate merger waves. In a different context, Bouwman () examines whether geography affects executive compensation and finds that envy is the most plausible explanation for the geographic clustering of CEO pay. Shue () uses envy among peers to explain corporate policies.

Although Goel and Thakor () show that envy leads managers to engage in merger activities that enable them to manage larger corporations and attain higher compensation which, in turn, lead to more industrial mergers, the question of whether bank merger waves are associated with envy‐pay remains unanswered. Additionally, focusing on bank mergers allow us to make inferences about the role of top managerial executive envy on a data set that has not been used before and, hence, overcome the standard criticism that observed empirical regularities arise from data mining. Additionally, to understand the effects of top executive envy on merger waves, it is instructive to rely on one industry rather than rely entirely on cross‐industry evidence that can be contaminated by unobserved heterogeneity. Moreover, the US banking...

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