A New Measure for Shareholder Value Creation and the Performance of Mergers and Acquisitions

Transcription

1 A New Measure for Shareholder Value Creation and the Performance of Mergers and Acquisitions Last Revised: November 2011 Julie Lei Zhu Boston University School of Management Abstract This paper develops a new measure for shareholder value creation to assess the efficiency of acquiring firms in utilizing capital before mergers and acquisitions (M&As) and links this measure to acquirers post-acquisition performance. Based on the concept of residual earnings, I define the measure as the residual from regressions of firms excess earnings earnings in excess of cost of capital on invested capital and other firm characteristics for each industry and year. A positive (negative) residual indicates a firm is able to generate excess return on invested capital at a higher (lower) rate than its industry peers in a given year. The announcement returns for acquirers with low residuals are lower than those for acquirers with high residuals. Moreover, this measure, constructed before the M&A transaction, (a) predicts both the operating and long-run abnormal stock performance of merged firms after the acquisitions and (b) hedge portfolios based on the measure generate substantial abnormal returns. Overall, the results indicate that investors do not fully recognize how efficient acquirers have been in utilizing capital before M&As and that incorporating the new value creation measure into the decision process of large-scale M&As can help protect shareholder wealth. Keywords: Merger and acquisition, earnings, residual earnings, invested capital, stock returns. JEL Classifications: G14, G34, M41. I appreciate useful comments from Bjorn Jorgensen, Sanjai Bhagat (WFA discussant), Brian Bolton (WFA codiscussant), Patricia Dechow, Kenneth French, Amy Hutton, Wei Jiang, Sharon Katz, Duane Kennedy (AAA discussant), Partha Mohanram, Doron Nissim, Derek Oler, Stephen Penman, Lakshmanan Shivakumar, Doug Skinner, Philip Strahan, Kent Womack, and seminar/session participants at Boston College, Boston University, Columbia Business School, Dartmouth College, New York University, Western Finance Association (WFA) Meetings in Hawaii and AAA meetings in San Francisco. Financial support from Boston University is gratefully acknowledged. All errors are my own. 0

2 1. Introduction Large-scale mergers and acquisitions (M&As) require substantial investment capital. While good M&As can lead to significant growth and value creation, bad M&As can generate massive losses for acquiring firms shareholders (e.g., Moeller, Schlingemann, and Stulz, 2005). Before approving an M&A transaction that is, before allowing managers to deploy resources and capital to a large acquisition what should the board of directors and shareholders of the acquiring firm be concerned about? In this paper, I propose that one factor should be the firm s efficiency in utilizing capital. If capital has been directed to productive projects and has created positive (net) returns for shareholders in the past a strong indicator of overall effective management then the board and investors should have confidence in management to continue the process of value creation. If, however, capital was misallocated to negative-npv projects, then shareholders should be cautious in approving the new M&A deal to avoid further losses. What should be the proper measure(s) to evaluate shareholder value creation, given invested capital? Both anecdotal and large-sample evidence suggest that investors and the market can be fixated on earnings when valuing firms (e.g., Sloan and Skinner, 2002). 1 However, accounting scholars have long criticized earnings as an imperfect measure for a firm s economic profitability because earnings do not reflect the cost of equity capital raised (e.g., Solomons, 1965; Morse and Zimmerman, 1997). Hence, a firm can grow earnings, at least temporarily, by investing in projects that generate sufficient profits to cover the cost of debt but not the cost of equity capital (i.e., negative-npv projects). If these firms are allowed to launch large-scale acquisitions, it is possible that these new M&A deals can lead to more wealth destruction. 1 Also see, for example, La Porta, Lakonishok, Shleifer, and Vishny (1997), Bernard, Thomas, and Wahlen (1997), La Porta (1996), and Dechow and Sloan (1997). 1

3 In this regard, I develop a new measure of value creation from investment capital, based on the concept of residual earnings, which takes into account the cost of capital. Specifically, I compare the rate at which an acquiring firm s invested capital generates excess earnings earnings in excess of cost of capital in comparison to industry peers in a given year. Acquirers that generate higher net returns than their peers are expected to continue to deliver superior returns to their shareholders in the new M&A transaction, whereas acquirers that underperform their peers are likely to repeat the subpar performance. I test this hypothesis by examining whether my value added measure for an acquiring firm, constructed before the M&A deal announcement date, can predict the firm s post-acquisition operating and stock performance. If better ex-ante value creation is associated with better postacquisition performance, then this positive link would validate both my measure and the hypothesis of the persistence of management effectiveness in value creation. This link would also imply that investors and the market do not fully recognize how efficiently acquirers have been utilizing capital before the acquisition. My M&A sample includes more than 1,900 completed deals over the period I define the measure of shareholder value creation as the residual from regressing excess earnings earnings in excess of the cost of capital on current and lagged total invested capital, controlling for firm size, financing constraints, and other factors. Cost of capital is calculated as weighted average of cost of debt and equity. I first run the regressions by industry and year, using all Compustat firms, and then I obtain residual estimates for each of the acquirers and their matching non-acquirers as of the fiscal year-end before the M&A deal announcement date. A positive (negative) residual indicates that a firm is able to generate excess return on invested capital at a higher (lower) rate than do its industry peers in a given year. I include matching non-acquirers in my analyses so as to rule out mean reversion as the reason for the possible reversal in acquirers operating performance. 2

4 With the value added measures for each acquirer and its matching non-acquirer in hand, I examine whether, at the time of the M&A deal announcement, investors and the market differentiate acquirers with high levels of shareholder value creation from those with low value creation. I also test whether the value creation measure can predict postacquisition performance of the merged firms. Specifically, I run regressions with the postacquisition return on assets (defined as net operating profits, or NOPAT, scaled by average assets), and with the merged firm s short-run and long-run abnormal stock returns as the dependent variable, while controlling for firm and M&A deal characteristics and other factors that have been shown to affect performance. To measure long-run abnormal stock returns, I use the Buy-and-Hold Abnormal Return, or BHAR, commonly used in the long-run event study literature, and subtract a benchmark return from the raw buy-and-hold returns. The benchmark return is the return on the characteristic-based benchmark portfolios constructed by Daniel, Grinblatt, Titman, and Wermers (1997) and Wermers (2004) (hereafter DGTW). 2 The main explanatory variable in these regressions is the firm-specific residual estimates from the excess earnings-invested capital regressions, constructed at the fiscal year-end before the M&A deal announcement date. I find that acquirers with low residuals have lower announcement period returns than acquirers with high residuals. This result suggests that, triggered by the M&A deal announcement, the market adjusts its valuation of acquirers with different levels of shareholder value creation. While the direction of the adjustment is correct, the magnitude is too small, in that the residuals also strongly predict both the operating performance and the long-run abnormal stock returns of post-merger firms. For example, during the first year after acquisition, the return on assets (ROA) for merged firms with residuals in the lowest 20% of the sample is 6.7% lower than the ROA for those in the top 20%. The comparative 2 The DGTW benchmarks are available via 3

5 underperformance of ROA persists in two-year and three-year post-acquisition windows. Moreover, in the first year post-acquisition, the abnormal stock returns for merged firms with their residuals in the lowest 20% of the sample is 10.8% lower than those in the top 20%. The underperformance of the abnormal returns for the low residual firms is 29.2% during the first two years and 25.7% during the first three years post acquisition. Taken together, the results confirm the validity of my ex-ante value creation measure in assessing management effectiveness prior to M&A deals and support my hypothesis that such management effectiveness persists and is manifested in the quality of the new M&A transactions. The results also imply that investors and the market do not fully understand how acquirers have differed in their capacity for value creation before M&As. To the best of my knowledge, this paper is the first to document a link between the ex-ante value creation measure, based on the concept of residual earnings, and the ex-post performance of acquiring firms. 3 For practical purposes, this measure can be used by the board of directors and/or shareholders of acquiring firms to make prudent decisions before approving M&A deals. This measure can also be used to investigate management effectiveness in other significant corporate events. In addition, my measure sheds new light on the underperformance anomaly of high- M/B glamour acquirers relative to low-m/b value acquirers post acquisition. Specifically, Loughran and Vijh (1997) and Rau and Vermaelen (1998) first document that glamour acquirers earn negative abnormal stock returns after M&As and postulate that this underperformance is due to naïve investors over-extrapolating glamour acquirers past earnings performance in assessing the value of the acquisition. 4 Consistent with this 3 Balachandran and Mohanram (2010) decompose the earnings growth of a general firm sample into components including growth in residual income and growth in invested capital, and then use this decomposition to explain the cross-sectional relation between earnings and stock returns. 4 Motivated by this finding, Shleifer and Vishny (2003) argue that firms managers take advantage of market misvaluations when making M&A decisions and that such decisions in turn affect post-acquisition performance. 4

6 interpretation, I find that glamour acquirers, defined as acquirers with M/B in the top 20% during the fiscal year-end before the M&A deal announcement, show much higher earnings than value acquirers (M/B in the lowest 20%) and matching non-acquirers during the threeyear period before an acquisition. However, the positive earnings momentum of glamour acquirers reverses sharply after the acquisition, relative to that of value acquirers and matching glamour non-acquirers, suggesting that the decline cannot be explained by mean reversion alone. Moreover, the mean residual (value creation) estimate of glamour acquirers is 1.9% (below the predicted value/rate), significantly lower than that of the medium-m/b group (3.2%) and matching glamour non-acquirers (5.0%); and not statistically different from that of the value acquirer group ( 0.2%). Finally, the positive link between the value creation measure and ex-post performance is robust to controlling for acquirers M/B ratios before M&As. These results indicate a new interpretation of the glamour-versus-value phenomenon: Investors may have been focusing on bottom-line earnings, rather than on the acquirers true economic profitability, in assessing the value of an acquisition. The reversal in earnings experienced by glamour acquirers is not due to mean reversion of earnings after acquisitions, but possibly to these acquirers inferior ability to create value, which was not recognized by investors until after the M&As. To demonstrate the economic significance of the measure, I use it to calculate hedge returns and compare them to returns from a strategy based on the M/B of acquirers before M&As. A strategy of shorting low-residual acquirers and going long on high-residual acquirers yields abnormal returns of 8.0% in the first year, 28.3% in two years, and 20.1% in three years post acquisition. These returns are higher than those from hedging portfolios of long low-m/b acquirers and short high-m/b acquirers, a strategy that prior literature has shown to consistently generate abnormal returns. A combined strategy of shorting lowresidual and high-m/b acquirers and going long on high-residual and low-m/b acquirers 5

7 yields significant abnormal returns that are greater than the sum of those yielded by the two strategies that are based on M/B or residuals alone. This suggests that the strategy based on my value creation measure adds to the returns of the previously known glamour-versus-value strategy and that the abnormal returns are economically significant. A few papers link cross-sectional variations in post-merger performance to certain firm characteristics. For example, Erickson and Wang (1999) and Louis (2004) find that stock acquirers underperform cash acquirers because stock acquirers inflate accruals in the quarter immediately prior to the acquisition. Gong, Louis, and Sun (2008) show that the post-merger underperformance can be explained by lawsuits aimed at pre-acquisition earnings management. Harford (1999) and Oler (2008) find that higher levels of acquirers cash holdings before acquisitions are associated with worse announcement returns and postmerger performance. The main result of my paper, the impact of ex-ante shareholder value creation on post-merger performance, is robust to the inclusion of acquirers accruals and cash holdings and of other factors that have been shown to influence performance. There is also a strand of literature examining firms operating performance around corporate events. For example, Bouwman, Fuller, and Nain (2009) find that post-merger operating performance is negatively related to the valuation level of the entire market, so that merged firms perform worse during high-valuation periods. 5 My paper extends this literature by developing a new measure of shareholder value creation and linking it to post-merger stock and operating performance and by showing the persistence of management effectiveness in value creation after M&A transactions. Section 2 of the paper defines the measure of value creation for shareholders and describes the empirical methodologies. Section 3 describes the M&A sample and presents 5 In addition, Loughran and Ritter (1997) find, using a sample of seasoned equity offerings (SEOs) in the 1980s, that the operating performance of issuing firms peaks around the time of the offering but deteriorates afterwards. They conjecture that the issuers are investing in what the market views as positive-npv projects, but in fact these projects have negative NPVs. The authors do not, however, provide evidence to support this conjecture. 6

8 results on the impact of the ex-ante value creation measure on the announcement period returns and post-acquisition performance of merged firms. Section 4 presents robustness tests. Section 5 concludes. 2. Empirical Methodologies I first define a new measure of shareholder value creation for acquiring firms. I then describe the empirical procedures in examining the relation between the pre-merger value creation measure and post-acquisitions performance. I also provide explanations of the key variables measuring the short-run and long-run stock performance and long-run operating performance of acquiring firms. 2.1 Measure of Shareholder Value Creation I construct a value added measure for acquiring firms based on the concept of residual earnings. As discussed earlier, it has been established in prior literature that residual earnings is a better measure of a firm s economic profitability than earnings, because residual earnings includes a charge for capital employed. A firm can temporarily grow earnings by investing in projects that generate enough profits to cover the cost of debt, but not the cost of equity capital. The resulting earnings growth does not create values for shareholders. By contrast, residual earnings growth can be generated only if the invested capital earns a return above the return required by investors, thereby creating shareholder value. Theory work has used residual earnings to develop structural models to value firms (Ohlson, 1995; Feltham and Ohlson, 1995). The residual-income valuation models have also been used empirically to estimate the intrinsic value of the firm (Frankel and Lee, 1997). Residual earnings is therefore a natural starting point for measuring value added to shareholders. Following prior literature, I define a firm s excess earnings or abnormal return on assets as a firm s gross return on assets less its weighted average cost of capital (WACC). To 7

9 assess how much value has been created from the firm s available resources, I estimate a firm-specific model of abnormal return on assets as a linear function of the firm s invested capital over the previous three years and the firm s size, age, and financing constraint (leverage), as follows: where is the abnormal returns on assets for firm i in year t. I define normal return on assets (ROA) as NOPAT (net operating profits) scaled by the average assets of the current and previous years. NOPAT is defined as earnings adding back net financing expenses, where earnings is equal to net income minus preferred dividends and after-tax special items and net financing expense is equal to after-tax net interest expense plus preferred dividends. Abnormal ROA ( ) is then calculated as ROA minus WACC. 6 The main independent variables in Eq. (1) are one-, two-, and three-year lagged invested capital ( ). Invested capital is defined as the sum of long-term debt, short-term debt, minority interests, and common equity, scaled by average assets. I also control for firm size (, firm age, and leverage at the beginning of the year, all of which can affect firms ROA. I estimate the model for each industry-year, based on 2-digit SIC codes for all industries with at least 20 observations in a given year. The predicted value from this regression is the estimate of the average industry-year abnormal rate of return on capital; the residual estimate from the 6 WACC is calculated by (1) estimating a CAPM cost of equity using the past 60 monthly returns, (2) inferring after-tax cost of debt from interest expenses, total interest-bearing debt, and the tax rate, and (3) using the market value of equity and book value of total debt as weights in the WACC formula. I estimate stock βs using at least 24 months and up to 60 months of lagged returns; βs below 0.4 are set to 0.4 and those above 3 are set to 3. 8

10 regression is the firm-specific measure of value added in a given year. As discussed earlier, the interpretation of the residual is intuitive: A positive residual indicates that a firm earns a higher abnormal return on all the capital used than do its industry peers in a given year, while a negative residual indicates that the firm earns a lower abnormal return from its capital than do its industry peers in a given year. 2.2 Performance Measures of Merged Firms Announcement Period Returns and Long-run Abnormal Returns Following Brown and Warner (1985), I use the modified market model to estimate abnormal announcement period returns. I calculate daily abnormal returns for an acquirer by deducting the equally-weighted index return from the acquirer s raw return (results are similar when using value-weighted index return): where is firm i s daily stock return on date t and is the return for the equallyweighted CRSP index on date t. I calculate cumulative abnormal returns (CARs) by summing the abnormal daily returns over a three-day event window around the M&A deal announcement date. To measure the long-run stock performance of merged firms, I follow the literature on long-run event studies and use the buy-and-hold returns of a sample firm less the buy-andhold return of a properly chosen benchmark portfolio. The buy and hold abnormal return, or BHAR, is calculated as: where is the month t return for firm i, is the benchmark portfolio return, and T is the time horizon over which returns are calculated. I use the characteristic-based portfolio constructed in Daniel, Grinblatt, Titman, and Wermers (1997) and Wermers (2004) as my 9

11 benchmark portfolio. The DGTW benchmark portfolio for a given stock during a given month is constructed to directly match that stock s three main characteristics: size, (industryadjusted) book-to-market (B/M) ratio, and past momentum. Therefore, DGTW form benchmarks that directly match the characteristics of the stocks being evaluated. This approach can be contrasted with the alternative factor-based approach that forms factor portfolios based on characteristic-sorted stocks; returns on these factor portfolios are then used as regressors in a traditional three- or four-factor model. There are several advantages of using the DGTW benchmark portfolios. First, empirical evidence suggests that the characteristics of stocks provide better ex-ante forecasts of the cross-sectional patterns of future stock returns (see, for example, Daniel and Titman, 1997). Second, characteristic matching also does a better job of matching future realized returns; that is, the average fraction of the variance of the stock returns explained by the benchmark is higher and the standard error of the estimates of the stock s abnormal performance is lower. Therefore, characteristic matching should have more statistical power than factor-based models do to detect abnormal performance (Wermers (2004)). Post-acquisition Operating Performance As discussed above, in constructing the measure of shareholder value creation, I use NOPAT scaled by average assets minus WACC as the abnormal returns ROA, then regress this variable on invested capital and firm controls. To be consistent, I also use NOPAT scaled by average assets as ROA to measure the post-acquisition operating performance. It is useful to discuss the implications that the differences in accounting and payment methods in M&As have for using NOPAT as a measure of post-acquisition operating performance. Since NOPAT is defined as earnings adding back net financing expenses, it is not affected by the methods of payment in acquisitions. As discussed in Healy, Palepu, and Ruback (1992), if an acquisition is financed by debt and cash, its post-acquisition income will be lower than 10

12 if it is financed by stock, because income is computed after deducting interest expenses. I also exclude the period between the M&A deal announcement and the completion date from the post-acquisition period to account for the differences in the timing of consolidating targets under the purchase or pooling method. Under purchase accounting, earnings are usually lower in the year of M&A deal completion because the target s financial statements are consolidated with those of the acquirer from the date of deal completion. Under pooling accounting, however, financial statements are consolidated from the beginning of the year, which can be much earlier than the M&A deal completion date. NOPAT, in contrast, is not immune to the differences in depreciation and amortization expenses, which are generally higher under purchase accounting than under the pooling method. The purchase method restates the assets and liabilities of the target firm at their market values and records any difference between the purchase price and the market value of the target s identifiable assets and liabilities as goodwill. No such re-valuation (and no goodwill) is recorded under the pooling method. To ensure that my results are not driven by differences in accounting and payment methods, I include, as controls in regressions, an indicator for the pooling method and another indicator that equals one if more than 50% of the consideration for acquisition is paid for with the acquirer s stock. 2.3 Regression Framework To examine the link between the ex-ante measure of value creation and the ex-post performance of the merged firms, I run multivariate regressions to control for factors that may impact a firm s (abnormal) performance. The dependent variables are the three-day CARs, the one-, two-, and three-year post-acquisition BHARs, and ROA. For stock performance, I estimate the following model: 11

13 (2) In Eq. (2), AR is the three-day CARs or the one-, two-, and three-year post-acquisition BHARs of acquirers. ( ) is an indicator that equals one if an acquirer s residual falls in the bottom quintile (middle three quintiles) of all the acquirers residual estimates from Eq. (1) and equals zero otherwise. ( ) is an indicator that equals one if the acquirer s M/B ratio, calculated one quarter before the M&A announcement date, is in the top quintile (middle three quintiles) of the M/B ratios of all the acquirers that announced acquisitions in the same year and equals zero otherwise. These indicators are included because prior literature (e.g., Rau and Vermaelen, 1998) find that high-m/b glamour acquirers tend to underperform low-m/b value acquirers post acquisition. Moeller, Schlingemann, and Stulz (2004) show that smaller acquirers tend to have higher announcement period returns. Therefore, I include as a control variable, defined as an acquiring firm with market capitalization below the 25th percentile of NYSE firms as of the fiscal year-end immediately before the M&A announcement date. Prior literature finds that acquirers in stock acquisitions show higher abnormal accruals before the acquisition announcement relative to cash acquirers; and that the high abnormal accruals are related to lower post-acquisition returns (Erickson and Wang (1999) and Louis (2004)). Accordingly, I control for and net operating assets (, which are the balance sheet representation of the cumulative accruals. I also control for acquirers preannouncement cash levels ( ), since Harford (1999) finds that cash-rich acquirers have lower announcement returns and Oler (2008) finds that an acquirer s cash 12

14 level is associated with worse long-term post-acquisition stock returns. Previous research has demonstrated that the relative size of an acquisition to the size of the acquirer affects the acquirer s post-acquisition returns (Asquith, Bruner, and Mullins, 1983). Therefore, I include, defined as the transaction value divided by the acquirer s market capitalization at the end of fiscal year immediately before the deal announcement date. 7 I also include an indicator,, which equals one if the target and acquirer have different two-digit SIC codes and zero otherwise. As discussed above, I include a indicator that equals one if the acquirer uses the pooling method. is an indicator that equals one if more than 50% of the deal is paid for with the acquirer s stock. This is included because Bhagat et al. (2005) find that stock-based deals experience a negative announcement period return; and, Loughran and Vijh (1997) show that stock deals have worse long run post-acquisition returns. is a dummy variable that equals one if the acquisition is a tender offer and zero otherwise. Jagadeesh and Titman (1993) documents that the pre M&A announcement price run-up leads to short-term price momentum and DeBondt and Thaler (1985) documents that price reverses in the long run. Therefore, I include, the mean pre-announcement return of acquirers from 200 days to 31 days prior to the deal announcement date to account for short-run price momentum. In the regression model for long-run operating performance, in addition to including all the variables in Eq. (2), I also control for matching non-acquirers post-acquisition operating performance to ensure that the results are not driven by the (possible) mean reversion properties of long-run operating performance. Freeman, Ohlson, and Penman (1982) and Nissim and Penman (2001) both show that extreme values of operating performance, such as sales growth or return on assets, are strongly mean-reverting in subsequent periods. To find matching non-acquirers, I follow the procedure used in the long- 7 I also use the sizes of the acquirer and target separately, as in Schwert (2000); results are very similar. 13

15 run stock performance literature and match each acquirer with a non-acquirer, chosen on the basis of firm (asset) size, industry, and M/B (Barber and Lyon, 1997; Kothari and Warner, 1997). Specifically, the candidate matching firms for an acquirer are those listed on the AMEX, NYSE, or Nasdaq with the same 2-digit SIC codes and with asset size at the end of fiscal year before the deal announcement date that is 50% to 200% of the asset size of the acquirer. From this set of firms, those that have not made an acquisition during the three years prior to and three years after the deal announcement year are ranked based on their M/B. The firm with the closest M/B is chosen as the matching non-acquirer. 2.4 Hedge Returns I also conduct a non-parametric test to gauge the magnitude of the long-run postacquisition abnormal returns in economic terms. Specifically, I calculate the return on an implementable trading strategy that takes a long position on acquirers with high residuals from the excess earnings-invested capital regressions and a short position on acquirers with low residuals. An acquirer falls into the low-residual (high-residual) group if its residual from the regression in Equation (1) is in the bottom (top) quintile of all acquirer residuals one year before the acquisition announcement. The positions are taken on the day of M&A deal completion and closed out 12 months, 24 months, and 36 months after that. As discussed above, I calculate abnormal returns using the DGTW benchmark portfolio that matches acquirers on size, M/B, and momentum. The combined returns are the total returns on both long and short positions for one year, two years, and three years post acquisition. 3. Data and Empirical Results From the Securities Data Company s (SDC) U.S. M&A database, I identify all completed corporate acquisitions during the period of , based on standard sample 14

16 selection criteria. 8 As is common practice, I exclude financial institutions and regulated utility firms. In addition, if an acquirer announces multiple M&A deals in the same year, I only keep the deal with the largest transaction value. Finally, I only include deals in which sufficient Compustat data is available to calculate the summary statistics shown in Table 1. 9 This procedure generates a sample of 1,938 acquisitions, for which I analyze the value added measure, operating performance, and stock returns. [Insert Table 1 here.] Table 1 reports summary statistics of all the acquirers during the sample period of and in three sub-periods. Panel A reports deal characteristics and Panel B reports firm characteristics. Panel A shows that there were significantly more acquisitions during the 1990s than in the other two periods (1,012 deals in the 1990s, 376 in the 1980s, and 637 in the 2000s). The period from 2000 to 2005 had the highest average deal value and the 1980s had the lowest. About 50% of the deals in the 1980s were tender offers, while 60% of the deals in the 1990s were paid for with the acquirer s stock. About 37% of the deals in the 1990s used the pooling method to account for the acquisitions, compared to only 2% in the 1980s and 6% in the 2000s. 10 Panel B shows that the average M/B ratio of acquirers was highest in the 2000s (3.38) and lowest in the 1980s (1.59). Most of the acquirers accounting ratios increased over time (e.g., accrual, NOA, acquirer cash, invested capital, and size), but leverage decreased over time, from 0.24 in the 1980s to 0.18 in the 2000s, and average acquirers age also decreased from 24.9 years in the 1980s to 18.2 in the 2000s. 8 My sample selection criteria include the following: The deal value is at least $10 million; both acquirer and target are public firms and the acquirer is listed on NYSE, AMEX or Nasdaq; the acquisition is announced during the sample period of ; all partial acquisitions (i.e., acquiring less than 100% of the target assets) are excluded. 9 These include NOA, accruals, and the acquirer s cash, invested capital, size, leverage, M/B, and age at the fiscal year-end prior to the M&A deal announcement date. 10 SFAS 141 requires all firms to use the purchase method for acquisitions initiated after June 30,

17 3.1 Univariate Analyses As indicated in Panel A of Table 2, the average announcement period return for all acquisitions is negative (-1.0%), as is the post-acquisition long-run abnormal return, with the average one-year return being -1.0%, the two-year return -2.8%, and the three-year return - 2.7%. These patterns are consistent with the findings in prior work (e.g., Bouwman, Fuller, and Nain, 2007; Oler, 2008). 11 [Insert Table 2 here.] I next examine the announcement and long-run abnormal returns for the low-residual and high-residual groups versus the other acquirers. Once again, an acquirer falls into the low-residual (high-residual) group if its residual from the excess earnings-invested capital regression (in Eq. 1) is in the bottom (top) quintile of all acquirer residuals at the fiscal yearend before the deal announcement date. The low-residual group has a lower average announcement return than do the rest of the acquirers (non-low-residual), but the difference is not statistically significant. By contrast, the low-residual group has significantly lower postacquisition returns than the other acquirers in all three years. The average return for the lowresidual group is 4.8% lower in the first year after acquisition, 11.5% lower in the first two years, and 9.8% lower in the first three years after acquisition than that of other acquirers; all the differences are statistically significant. Not surprisingly, when I compare the highresidual group to all the other acquirers, I obtain the opposite results, which suggest that the low-residual (high-residual) group underperforms (outperforms) relative to the other acquirers in terms of abnormal stock returns post acquisition. Panel B of Table 2 provides the same comparisons for operating performance (ROA). Again, the low-residual group has significantly worse post-acquisition operating performance than the others. The gaps in ROA during the one-year, two-year, and three-year post-acquisition periods are 6.1%, 4.8%, and 11 See Brunner (2002) for a comprehensive survey of the studies examining shareholder returns for M&A. 16

18 4.0%, respectively; all the differences are highly significant. By contrast, the high-residual group has significantly higher post-acquisition ROAs in the same periods after acquisition. In summary, while there is no difference in the announcement period return between the low-residual groups and other acquirers, the low-residual acquirers significantly underperform other acquirers in both operating and stock performance post acquisition. These results support the notion that, prior to the acquisitions, the market and investors do not fully differentiate the acquirers ability to create value for their shareholders and are subsequently disappointed by the poor post-acquisition performance of low-residual acquirers Multivariate Analyses In this subsection, I present the multivariate results from the announcement period (event) study and long-run stock and operating performance analyses. Announcement Period Returns and Long-run Abnormal Returns I test whether univariate evidence of the underperformance of low-residual acquirers in the post-acquisition period holds in a multivariate setting. Table 3 shows that the announcement period return is 1.4% lower for low-residual acquirers than for high-residual acquirers (the default group in the regressions) after controlling for firm and deal characteristics; the result is significant at 5% (Column 1). As has been found in prior research (e.g., Servaes, 1991; Rau and Vermaelen, 1998), the market responds negatively to stock acquisitions and when the target is large relative to the acquirer. The announcement period return is higher if the acquirer experiences larger pre-announcement stock returns, consistent with the short-term stock price persistence documented in Jagadeesh and Titman (1993). On the other hand, the announcement returns are lower in a tender offer or when the acquirer uses pooling accounting, but these results are not statistically significant. Announcement returns do not seem to be affected by the acquirer s M/B ratio at the time of 17

19 the acquisition announcement. I also find that the announcement returns decrease in the level of the acquirer s cash holdings, consistent with Harford (1999), who interprets this result as the market taking cash-rich acquirers to have more severe agency problems, as indicated by Jensen (1986). Finally, the announcement returns also decrease in the acquirers NOA (scaled by lagged total assets), which Hirshleifer, Hou, Teoh, and Zhang (2004) propose as an indicator of weak earnings quality. The next three columns of Table 3 show the regression results for the buy-and-hold abnormal returns (BHAR) calculated over the one-year, two-year, and three-year windows post acquisition. The long-run abnormal returns are lower for acquirers with high M/B ratios (low-m/b acquirers are the default group) and for acquirers with greater pre-announcement price run-ups, both findings are consistent with prior studies (Rau and Vamaelen, 1998; Jagadeesh and Titman, 1993). Controlling for firm and deal characteristics, I find that lowresidual acquirers have significantly lower post-acquisition returns over all three windows after the deal completion date; the return gap between low-residual acquirers and highresidual acquirers (the default group) over the one-, two-, and three-year windows is 10.8%, 29.2%, and 25.7%, respectively; all the results are significant at the 5% level. The size and significance of the coefficients of the Low Residual indicator suggest that the pre-acquisition value creation measure is an important determinant for long-run post-acquisition stock performance. Combining the announcement period results with the long-run abnormal returns, I conclude that the market, triggered by an M&A deal announcement, partially recognizes low-residual acquirers poor performance in creating value for shareholders. While the adjustment s direction (during the announcement period) is correct, its magnitude is too small, in that low-residual acquirers continue to underperform the high-residual acquirers during the first three years after an acquisition. 18

20 [Insert Table 3 here.] Post-acquisition Operating Performance Table 4 reports results from regressions for long-run operating performance (ROA). Operating performance is worse if the acquirer is small, has large (pre-announcement) cash holdings, and uses stock as the main method of payment. The relation between cash level and long-run post-acquisition operating performance is consistent with the findings in Oler (2008). The ROA of matching non-acquirers in the post-acquisition period is positively and significantly related to the acquirers post-acquisition ROA, which illustrates the success of the matching procedure. Operating performance is also better if the acquirer has high preacquisition M/B and uses the pooling method. The result for the pooling method is consistent with earlier discussions of the differences between the pooling and purchase accounting methods; in particular, acquirers generally have higher post-acquisition earnings if they use the pooling rather than the purchase method. More importantly, as in the stock return regressions (Table 3), operating performance is significantly worse if the acquirer belongs to the low-residual group: The gap in ROA between the high- and low-residual groups is 6.7% for the first year, 2.7% for the first two years, and 3.4% for the first three years post acquisition; all the results are significant at 5%. In summary, the results from Tables 3 and 4 show that the ex-ante value creation measure strongly predicts the post-acquisition stock and operating performance of acquiring firms, validating both the measure itself as an assessment of management effectiveness and the hypothesis on which the measure is based the persistence of management s effectiveness (or lack of it) in creating value. Acquirers that generated higher net returns than their peers before acquisitions are expected to continue to deliver superior returns to their shareholders after the M&A transaction, while acquirers that underperformed their peers are likely to repeat the subpar performance. 19

21 [Insert Table 4 here.] 3.3. Hedge Returns To further gauge the economic significance of the positive link between the ex-ante shareholder value creation and the ex-post performance of merged firms, I calculate the returns to an implementable trading strategy and report the results in Table 5. The strategy calls for taking a long position on high-residual acquirers and a short position on low-residual acquirers. The positions are formed on the day of M&A deal completion and closed 12 months (Column 1), 24 months (Column 2), and 36 months (Column 3) after the completion date. Panel A shows that this investment strategy produces significant abnormal returns in all three post-acquisition windows, with an abnormal return of 8.0% during the first year, 28.3% in the first two years, and 20.1% in the first three years after M&A deal completion. I also compare the hedge returns based on the ex-ante value creation measure to the returns on a previous known investment strategy based on acquirers M/B ratios. This strategy involves going short on high-m/b acquirers and long on low-m/b acquirers. An acquirer falls in the high-m/b (low-m/b) group if its M/B ratio at the time of the acquisition announcement is in the top (bottom) quintile of M/B ratios of all the acquirers that announced acquisitions in the same year. Panel B shows that the mean abnormal return from this strategy is 10.1% in the first year, 21.9% in the first two years, and 7.3% in the first three years post acquisition. These results are consistent with the findings in Rau and Vermaelen (1998), which show that the high-m/b glamour acquirers tend to underperform the low-m/b value acquirers post acquisitions. Comparing the results from Panels A and B, it is clear that the strategy of going long on high-residual and short on low-residual acquirers generates significantly higher returns than the M/B-based strategy over the two- and three-year postacquisition windows. While strategies based on the value added residual generate higher hedge returns than 20

22 the M/B-based strategies, it is unclear whether the hedge returns based on the residuals subsume or add to the returns based on M/B. To test this, I examine the hedge returns for a combined strategy, in which I go long on high-residual and low-m/b acquirers and short on low-residual and high-m/b acquirers. To have a reasonable number of stocks in each portfolio, I group acquirers value added residuals and M/B ratios into terciles (rather than quintiles); thus the long (short) portfolio contains acquirers with residuals in the top (bottom) tercile and M/B in the lowest (highest) tercile. Panel C of Table 5 shows that this combined strategy generates substantial abnormal returns, which are greater than the sum of the abnormal returns generated by the two strategies separately in all three post-acquisition windows. Interestingly, the larger abnormal returns seem mainly to come from the stocks in the long portfolio. The results suggest that the hedge returns based on acquirers ex-ante ability to create shareholder value add to the previously known glamour-versus-value strategy and are both economically and statistically significant. [Insert Table 5 here.] 3.4. Implications of the Comparison of Glamour versus Value Acquirers The new shareholder value added measure also provides new insight on the postacquisition underperformance of high-m/b glamour acquirers relative to low-m/b value acquirers. Loughran and Vijh (1997) and Rau and Vermaelen (1998) first document this underperformance anomaly and Rau and Vermaelen interpret the result as naïve investors over-extrapolating glamour acquirers past earnings performance in assessing the value of the acquisition. In this section, I provide a new interpretation of the finding based on the shareholder value added measure: Investors and the market may be focusing on the acquirer s bottom-line earnings, rather than on its true economic profitability before acquisitions. Thus, the glamour acquirer s reversal in earnings is not due to mean reversion of earnings, but rather to the glamour acquirer s inferior ability to create value for shareholders, which is not 21

23 recognized by the market until after the M&A. Operating Performance of Glamour versus Value Acquirers I first examine the time-series patterns of operating performance for the high- and low-m/b acquirers and their matching non-acquirers before and after the M&As. As discussed above, in defining high- and low-m/b acquirers, I sort the acquirers, for each announcement year, into quintiles by their M/B ratios at the fiscal quarter-end immediately preceding the acquisition announcement date. As has been done in prior work, I define the quintile with the lowest M/B as value acquirers, the quintile with the highest M/B as glamour acquirers, and the rest (60% of the sample) as medium-m/b acquirers. [Insert Table 6 and Figure 1 here.] Table 6 presents the mean ROAs of acquirers and matching non-acquirers for the three fiscal years before the M&A deal announcement date and the three fiscal years after the deal completion date. Figure 1 plots the mean ROA of glamour and value acquirers and their matching non-acquirers during the same period around M&As. Both the table and figure show that the operating performance of glamour acquirers evolves quite differently around M&As than does that of other groups. For glamour acquirers, ROA rises during the three years prior to the acquisition date, peaking at 26.7% of assets in the year before deal announcement (Year 1), only to fall sharply to 17.2% one year after deal completion (Year +1) and 13.7% two years later. Other measures of operating performance (sales growth and EBITDA) all go through the same rise-and-fall pattern (results not reported in tables). In fact, almost all the accounting ratios of glamour acquirers peak one year before acquisitions, only to rapidly decline one year after deal completion and continue their slide in the following years. While ROAs (and other operating ratios) for matching high-m/b nonacquirers also show an overall downward trend from Year 3 to Year+3, the drop is not as pronounced as that of glamour acquirers. Finally, the operating performance of value 22

24 acquirers is much more stable during the same period and not much different from that of their matching non-acquirers. The observed time-series patterns of operating performance suggest that glamour acquirers launch acquisitions at the peak of their performance. This finding is consistent with the stock-market-driven acquisition theory of Shleifer and Vishny (2003), who posit that fully rational managers can take advantage of market misvaluations by timing acquisitions and choosing the means of payment. 12 The comparisons with matching non-acquirers rule out mean reversion in operating performance as the only reason for the sharp decline in the ROA of glamour acquirers. I next examine whether the inferior ability of glamour acquirers to create value for shareholders before acquisitions is a possible source of these acquirers subsequent drop in ROA. Value Added Residuals of Glamour and Value Acquirers Table 7 reports the univariate comparisons of the value added residuals across different M/B groups and Figure 2 plots the residuals for different groups. I find that both glamour acquirers and value acquirers have negative average residuals (-1.9% and -0.2%, respectively), indicating that both groups earn returns on invested capital at a lower rate than their industry peers. Both groups residuals are also lower than that of their matching nonacquirer group, with the residuals of glamour acquirers considerably lower than that of their matching firms (+5.0%). On the other hand, the medium-m/b acquirers earn a rate on invested capital that is 3.2% higher than that of their industry peers and their matching firms and much higher than that of the glamour acquirers. Overall, glamour acquirers have the lowest average residuals among all the acquirer groups and matching groups (the difference between glamour and value acquirers is not statistically significant), yet their average ROA and M/B are the highest among all the groups. In addition, the positive relationship between 12 Market timing is also documented in other corporate events, such as initial public offerings (IPOs) and seasoned equity offerings (SEOs); see, for example, Graham and Harvey (2001), Baker and Wurgler (2002), and Loughran and Ritter (1997). 23