How Accounting Firms Compete for Financial Advisory Roles in the M&A Market

Pawel Bilinski, Cass Business School, City University London†

Andrew Yim, Cass Business School, City University London‡

25 November 2015

Abstract. Thomson Reuter’s quarterly rankings consistently place accounting firms among top ten financial advisors on mergers and acquisitions (M&A) in the mid- and low-end of the market. We propose that accounting firms lever their audit expertise to produce fairer target valuations, particularly in industries where the auditor specializes, and when the target has low reporting quality. These competitive strengths of accounting firms translate into tangible gains for bidders as transactions advised by accounting firms have (1) higher announcement day price reactions compared to deals with investment-bank financial advisors, (2) a lower likelihood the acquirer overpays for the target, and (3) a lower likelihood the deal will not complete. These acquirer benefits translate into more repeat business for accounting firms as they are more likely to advise on subsequent transactions. (JEL G34, M41, M49)

Key words: accounting firms, industry expertise, financial advisory, mergers and acquisitions, unlisted targets

† Corresponding author. Address: Faculty of Finance, Cass Business School, City University London, 106 Bunhill Row, London EC1Y 8TZ, UK. E-mail: [email protected]. ‡ E-mail: [email protected]. We thank Alexander Ljungqvist and Paolo Volpin and participants of the CeFARR M&A roundtable for their useful feedback. All remaining errors are ours.

1. Introduction

Accounting firms, besides audit, provide a variety of non-audit services including financial advisory services for mergers and acquisitions (M&As). In recent years, accounting firms have been repeatedly ranked among the top ten M&A financial advisors by Thomson Reuter’s quarterly rankings for the mid- and low-end market.1 Yet, it is unclear what competitive strengths allow accounting firms to compete with established investment banks for the M&A advisory role and what incremental benefits they offer to their clients. We propose that accounting firms lever their audit expertise to produce fairer target valuations, particularly in industries where the auditor specializes, and when the target has low reporting quality. These competitive strengths translate into tangible gains for bidders, such as lower offer premium, higher price reactions to deal announcements, and lower risk the deal will not complete, and a repeat M&A business for accounting firms.2 Valuation fairness is strengthened by the lack of pressure to cross-sell financing for the transaction, which generates bulk of profits for bulge bracket investment banks.3 These distinct benefits of accounting firms merger advice explain their active role in the global M&A market.

To address the research question, we collect a sample of global M&A transactions involving a public bidder domiciled in the US, Canada or one of 15 European markets. Over the period 1990–

2014, accounting firms advised on 1,582 transactions or around 7.6% of all the deals in the sample.

To put these numbers into context, accounting firms competed with 190 active advisors in the

1 Thomson Reuters Worldwide Rankings for the first quarter of 2015 are presented in Appendix A. 2 The Economist highlights that overpaying for the target is the second most common reason for a deal collapse after regulatory disapproval. On average 10–20% of proposed M&A deals fail leading to significant costs related to managerial time and credibility of the bidder that often lead to forced departures for the acquirer’s managers (The Economist 2014). 3 Saunders and Srinivasan (2001) document that revenues from underwriting public security issues to finance M&A transactions are on average 55% higher than merger advisory fees for bulge bracket investment banks.

market over the period and top bulge bracket investment banks Goldman Sachs and J.P. Morgan advised on 4.7% and 4.5% of all the deals, respectively. For the transactions advised by accounting firms, over 85% were advised by the largest four accounting firms (Big 4) with KPMG being the most active accounting firm advising 2.3% of all the transactions.

We document significant differences in accounting firms M&A advisory activity over time: less than 1% of the deals were advised by accounting firms over the period 1990–1992, with the proportion increasing to 9% in 2001, then standing at an average of 8% for the remaining period

(i.e., around 65 deals per year). The European volume of transactions for accounting firms is similar to that in the combined market of the US and Canada. But as a proportion of all M&A transactions, accounting firms are more active in Europe (18% of the European deals were advised by accounting firms vs. only 2% of the North American deals). These results point to substantial heterogeneity in accounting firms activity in the M&A market over time and across countries, which we investigate in detail in the study.

The first part of the study examines whether accounting firms’ competitive advantages, i.e. their expertise to produce fairer target valuations, explain why bidders choose them as M&A advisors. We classify a deal as advised by an accounting firm if the accounting firm is the sole advisor or part of the advisory team.4 We document that acquirers are more likely to choose accounting firms as advisors when the likelihood of overpaying for the target is high. These include deals where the target is in an industry characterized by low accounting accruals quality, for smaller targets, when the target is a private firm, is located outside the US, and for cross-country deals. Further, accounting firms are more likely to advise on deals where the target’s country

4 We repeat the analysis for deals with an accounting firm as the only advisor. All the conclusions remain unchanged.

aggregate earnings management score from Leuz, Nanda, and Wysocki (2003) is higher than that of the acquirer home country.5 Accounting firms should be better placed to value these transactions considering their expertise in evaluating financial statements and better understanding of unlisted entities’ operations in general. The latter comes from the privilege of accessing undisclosed information of many unlisted entities through their auditor role. The economic importance of valuation difficulty in predicting the advisor choice is high. For example, an accounting firm has

36% higher odds to advise on a deal where the target is in a low accruals quality industry. These results confirm that resolving valuation uncertainties is an important consideration of the bidders when selecting accounting firms as advisors.

In the second part of the study, we examine if the advantages accounting firms offer translate into better deal outcomes for the bidders. We first examine investor reactions to deal announcements and document more positive price reactions for deals advised by accounting firms.

The economic magnitude of this effect is significant: deals advised by accounting firms have close to two times higher price reactions compared to deals advised by investment banks (2.03% vs.

0.68%). This translates into a $148 million shareholder value gain for a mean-sized bidder. Price reactions are higher for deals where accounting firms have competitive advantages, such as deals where the target is in an industry with low accruals quality and the accounting firm is an audit- specialist for this industry. To address endogeneity inherent in advisor choice, we perform two tests. First, we repeat the analysis using propensity score matching (PSM) and find similar conclusions. Second, we take advantage of a quasi-natural experiment and repeat the analysis in the period after the introduction of the Sarbanes-Oxley Act (SOX) of 2002. Because the regulation

5 Leuz, Nanda, and Wysocki (2003) develop an aggregate earnings management score based on four measures: earnings smoothing, correlation between changes in accounting accruals and changes in operating cash flows, the magnitudes of accruals, and small loss avoidance.

excluded some auditors from advisory roles, our conclusions from this period should be less subject to endogeneity concerns. The results for the post-SOX period are qualitatively similar to the main results, corroborating our conclusion that, on average, investors perceive deals advised by accounting firms as more value-increasing than deals advised by investment banks.

In subsequent tests, we confirm that accounting firms’ competitive strengths lie in the valuation area. We document that the offer premium for M&As advised by accounting firms is on average 24.7% smaller than that for deals advised by investment banks. This translates into an average saving of $135 million for a mean-sized deal. The valuation benefit from hiring accounting firm as advisors is particularly strong when the target is in low accruals quality industry. The result that bidders are less likely to overpay for the target confirms that accounting firms help resolve valuation uncertainties, particularly when the target’s accounting information is of low quality.

Further, we examine and find consistent evidence that deals advised by accounting firms are less likely to fail. Bates and Lemmon (2003) report that 21% of M&A transactions fail, and that failed deals lead to reputational costs for the managerial team such as forced bidder firm CEO departure

(Lehn and Zhao 2006) and negative market returns (Davidson, Dutia, and Cheng 1989). We show that accounting firms help mitigate such costs.

Benefits from the advisory role of accounting firms should lead to reputational effects and repeat business. Consistent with this proposition, we document that the odds a bidder will choose an accounting firm as an advisor are 1.7 times higher when the firm advised on a previous M&A.

This result confirms that acquirers recognize the benefits from accounting firms’ advisory roles and reward them with repeat future business.

This paper makes three major contributions. To our knowledge, we are first to document the growing visibility of accounting firms in the global M&A financial advisory market. Thus, our

paper extends the literature on financial advisors in M&A transactions, which, to date, has focused solely on the roles played by investment banks (McLaughlin 1990, 1992; Servaes and Zenner

1996; Rau 2000; Kale, Kini, and Ryan Jr. 2003; Allen et al. 2004, Golubov, Petmezas, and Travlos

2012). The emergence of accounting firms as deal advisors and their consistent placement in top

Thomson Reuter’s quarterly rankings for the mid- and low-end market has evaded the accounting and finance literature. This is partly due to the US focus of the literature. We show that regulatory constraints in the US have limited accounting firms’ activity in that market.6 In addition to the US focus, seminal M&A papers use sample periods that end in early 1990s (see Schulz 2007,

DeYoung, Evanoff, and Molyneux 2009, and Faulkner, Teerikangas, and Joseph 2012 for the review of the M&A literature). We show that early 1990s had very few M&As advised by accounting firms. Even more recent studies, such as Kisgen, Qian, and Song (2009), who examine fairness of opinion advisors in the US, do not identify any accounting firms.

Importantly, our study identifies how accounting firms compete with established investment banks for advisory roles. Evidence in the literature suggests that on average acquiring firm shareholders do not seem to benefit from acquisitions (Fuller, Netter, and Stegemoller 2002,

Moeller, Schlingemann, and Stulz 2003, McNamara, Haleblain, and Dykes 2008). This observation often captures newspaper headlines and raises concerns about the high fees charged by investment banks. For example, Businessweek: “Mergers: Why Most Bid Deals Don’t Pay

Off” (Henry and Jespersen 2002); Fortune: “Merger fees that bend the mind” (Petre 1986); The

Telegraph: “Investors seek Government help to reduce advisers' bank charges” (Armitstead 2011).

According to Mauboussin (2010), “[o]ne important reason that so many M&A deals fail to create

6 The introduction of SOX limited some auditors from playing the advisory roles concurrently. We document that following the regulation, the likelihood of an accounting firm advising on an M&A transaction is drastically reduced. This explains the lower activity of accounting firms in the US market. Specifically, the odds of an accounting advising on an M&A transaction are 45% lower after the SOX regulation.

value for buyers is that acquirers tend to overpay for targets.” We show that accounting firm advisors are more preferred by acquirers for targets with higher target valuation uncertainties, particularly for targets with low accounting quality where bidders are more likely to overpay

(McNichols and Stubben 2015; Raman, Shivakumar, and Tamayo 2013; Marquardt and Zur 2015).

Our evidence is consistent with the perspective that accounting advisors help resolve target valuation uncertainty.

Finally, our finding on the active role of accounting firms in the M&A market enhances the literature on non-audit services of accounting firms. Advisory revenue is the fastest growing revenue segment for accounting firms. We provide evidence showing how accounting firms compete and gain foothold in the M&A market.7 We also highlight how the SOX regulation curbed the activity of accounting firms in the US, limiting the competition in the M&A market there.

2. M&A Financial Advisory Market: Prior Literature

Various measures have been used in the M&A literature to examine the outcomes to acquirers.

They include the acquirer’s announcement-period stock returns (e.g., Faccio, McConnell, and

Stolin 2006), the offer premium paid by the acquirer (e.g., Alexandridis et al. 2013), and the deal completion ratio (e.g., Mooney and Sibilkov 2012). Prior studies find that acquirers of listed targets earn, on average, a negative or zero abnormal announcement-period return, and their post-merger

7 PwC UK reported that advisory revenue was the fastest growing revenue segment (16%) contributing £571m compared to assurance (which includes audit) growing at 9% and contributing £1.1b (Agnew 2015b). Businessbecause highlights that Big4 audit firms are aggressively expanding their finance wings as growth in audit and tax stagnates away from audit roots (Murray 2015). This drive is supported by hiring several senior investment bankers as partners, e.g. EY hired Blaise Girard, Bank of America Merrill Lynch’s head of retail investment banking in Europe.

stock performance is poor (Faccio, McConnell, and Stolin 2006 and Loughran and Vijh 1997). 8

Overpaying for targets is believed to be an important reason for so many M&A deals failing to create value for buyers (Mauboussin 2010). Successful M&As require enormous investment of managerial time in evaluating targets and negotiating deals. This becomes a loss in case of uncompleted deals. Between 1979–2007, over 13% of the M&As are uncompleted. The expertise of M&A financial advisors contributes to the successful completion of deals (Mooney and Sibilkov

2012).

The market for M&A financial advisors is dominated by investment banks playing advisory roles (the certification hypothesis) and organizing financing for deals (Bowers and Miller 1990;

Puri 1996; Ang and Richardson 1994; DePamphilis 2010). Prior research, however, has difficulty finding empirical evidence on the benefits of hiring investment banks as M&A advisors. For example, Servaes and Zenner (1996) compare acquisitions conducted with and without the help of investment banks and find that neither the use of an advisor in general nor the use of a top-tier advisor affects announcement day returns. Porrini (2006) finds that firms that did not use investment banks paid lower offer premia. Rau (2000) documents no association between the quality of investment bank and acquirer announcement returns. In line with these, McLaughlin

(1992), Hunter and Jagtiani (2003) and Ismail (2010) report higher premia paid and lower announcement day returns for bidders using tier-one investment bank advisors, as opposed to the tier-two. For acquirers advised by tier-one advisors, the loss in the market value on the announcement day is more than $42 billion (Ismail 2010). Allen et al. (2004) find no evidence of the certification role of commercial banks, or similar M&A outcomes, for bidders advised by

8 The evidence on underperformance after M&As has been challenged by Bessembinder and Zhang (2013), Chang (2012) and Mortal and Schill (2013) which attribute previous evidence to misspecification of the normal returns benchmark.

commercial and investment banks. They attribute the findings to commercial banks suffering from similar conflicts of interest as bulge bracket investment banks. For example, the advice of commercial banks is likely to be affected by the loan financing they provide for the M&A transaction. Recently, Golubov, Petmezas, and Travlos (2012) report a positive association between investment bank quality and announcement-period return, but only for public targets – not for unlisted targets. Given the very limited evidence on positive benefits from hiring investment banks as M&A advisors, one would expect new entrants into this lucrative market. Our study focuses on how accounting firms compete for financial advisory roles in this market.

Accounting firms can offer distinct advantages compared to investment banks. Specifically, they can lever their audit expertise to produce fairer target valuation, particularly in industries where the firms are audit-specialists, and when the target has poor reporting quality. McNichols and Stubben (2015) document that acquisitions of targets with low accounting quality are less profitable, as measured by lower acquirer announcement returns. They attribute the lower returns to higher target valuation uncertainties. Marquardt and Zur (2015) also document negative associations between target accounting quality and acquisition costs, such as time to complete the transaction and the likelihood of deal completion. Raman, Shivakumar, and Tamayo (2013) document that targets’ low quality earnings are associated with higher offer premium. Cai et al.

(2015) document that deals with a common auditor for the bidder and the target have higher acquisition announcement returns than do non-common-auditor deals. They attribute the finding to the information intermediation role of common auditors. In contrast, Dhaliwal et al. (2015) emphasize the conflict of interest in deals with a common auditor shared by the target and the

acquirer.9

To our knowledge, no prior research has recognized the growing visibility of accounting firms in the global M&A financial advisory market, nor examined their competitive strength and the benefits they can provide to acquirer clients.

3. Data and Sample

We collect the sample of acquisitions from the SDC Platinum M&A database with the announcement date falling in the years between 1990 and 2014 inclusively. We place no restriction on the public status or nationality of the acquirer, nor on the industry of the acquirer or the target, to minimize the risk of sample bias (Netter, Stegemoller, and Wintoki 2011). As is standard in previous studies, we require deals with explicit change of control, i.e., the acquirer initially must own less than 50% of the target’s stock and seek to own more than 50% after the acquisition. We also require the availability of data on the announcement date, bidder cusip or sedol code, acquirer advisor and acquirer advisor parent name, Standard Industrial Classification (SIC) code and country of incorporation of the acquirer and the target, and deal value. To exclude ad-hoc advisors, we retain advisors with at least ten M&A transactions over the sample period. These criteria give rise to an initial sample of 22,494 acquisition transactions in the US, Canada, and 15 European countries. By definition, these transactions exclude in-house acquisitions where the acquirers do not employ a financial advisor (Golubov et al. 2012). SDC’s “Acquirer Financial Advisors

(Codes)” identifies the acquirer advisors and “Parent of Acquirer Advisors” the advisor’s parent

9 Cai et al. (2015) and Dhaliwal et al. (2015) restrict their samples to only public acquirers, public targets, and a deal value of at least $1 (or $10) million. Netter, Stegemoller, and Wintoki (2011) find that requiring public targets and a deal value of at least $1 million can drastically reduce the sample size, increasing the risk of sample bias. In contrast, our primary sample for the advisor choice analysis includes both unlisted and listed targets and acquirers.

company. We use the latter to identify accounting firms as advisors do not share the same name across markets. Appendix B1 illustrate the match between advisor and parent for PwC. We manually identify the list of accounting firms based on the list of auditors on Compustat and

Compustat Global and searches on advisors’ websites. The list of SDC parent advisor codes and names we use to identify accounting firms is included in Appendix B2. For multivariate tests that examine choice of advisor and price reactions to merger announcements, we collect accounting and market information from Compustat and CRPS for US stocks and from Compustat Global

Fundamentals and Compustat Global Security Daily files for non-US firms.

The dashed line in Figure 1 reports the frequency of M&As advised by accounting firms over the period 1990–2014. Less than 1% of deals were advised by accounting firms over the period

1990–1992, and the proportion increases to 9% in 2001. The average proportion of deals advised by accounting firms is stable over the period 2002–2014, at around 8% or 65 deals per year. To provide context for Figure 1, the solid line reports the total number of M&A transactions over the sample period. We observe that accounting firms were able to retain their market share during market downturns following the internet bubble crash and the recent financial crisis. This result suggests that accounting firms are not ad-hoc advisers that fill a gap in the market in periods of high M&A activity where existing investment banks are unable to cope with the volume of transactions.

[Figure 1]

Splitting the sample by bidder region, Figure 2a shows similar number of deals advised by accounting firms in Europe as in the North American market (i.e., the US and Canada combined).

The time-trends in the figure mirror that in Figure 1. However, the picture changes when we consider percentages in Figure 2b: the share of deals advised by accounting firms increases

gradually in Europe, reaching a peak of close to a third of all the deals in 2013. In contrast, their share of the North American market is small, at less than 5%, and declining after 2002, which coincides with the SOX regulation.10 This result suggests that differences in the market structure between the US and Europe can explain why past research failed to identify accounting firms’ increasing activity in the M&A market.

[Figure 2a,b]

To provide more insights into the accounting firm activities across individual markets, Figure

3 reports the percentage of deals advised by accounting firms and the ratio of mean value of M&As with accounting firm advisors to mean value of deals with investment bank advisors. Among

European countries, France has the lowest proportion of deals advised by accounting firms, but the average size of the deals is 16% higher than that for investment banks. Over 15% of deals in the UK, Austria and Spain are advised by accounting firms, though the average deals size is less than half of that for investment banks. These results suggest that within Europe, there are significant differences in the market activity of accounting firms. They more often advise on smaller deals, which is consistent with their listing in Thomson Reuter’s rankings for medium and small capitalization M&As.

[Figure 3]

4. The choice of accounting firm as M&A advisor

Our first test examines the likelihood an accounting firm will advise on a merger transaction.

We argue that accounting firms are more likely to advise on deals with high valuation uncertainty.

10 These trends may reflect higher volume of deals in the US than in Europe and lower head-count of corporate finance departments in accounting firms than in established investment banks.

We use serval proxies to capture valuation uncertainty. Our first measures capture target’s accounting quality because Raman, Shivakumar, and Tamayo (2013), Marquardt and Zur (2015) and McNichols and Stubben (2015) document that target’s low accounting quality increases valuation difficulties. Specifically, we consider firms with low accounting quality as those belonging to an industry characterized by low accruals quality. We construct the measure at the industry level because this allows us to retain private targets in the sample. We measure accrual quality using the absolute value of total accruals for all listed firms in each market we examine and then rank industries in ascending order. We then construct an indicator variable, Target in high

|Total Accruals| industry, which equals 1 if the target belongs to the top two industries with the highest values of the equal-weighted average of the absolute total accruals of all the firms in the industry and 0 otherwise.11

Our other valuation proxies include an indicator variable, Unlisted target, for whether the target is an unlisted entity. Compared to listed companies, information about unlisted entities is not as easily available owing to the lack of restrictions by stock exchange listing requirements or the lack of incentives for voluntary disclosure (Singhvi and Desai 1971). We argue that unlisted targets are more difficult to value given the limited information available and high information search costs.

We consider the size of the target an important proxy for valuation difficulty. Smaller firms are associated with lower quality information environments (Lang and Lundholm 1993). This is likely to result in higher valuation difficulties. We measure target size by the log value of Deal

Value, which is the value of the M&A deal in concern.

11 In robustness tests, we also use variation in discretionary accruals from the Jones model (Jones 1991) to capture accrual quality. Our conclusions are unchanged using this measure, though our sample reduces because of higher data requirements.

Prior research has documented higher financial reporting quality under US GAAP than other national GAAPs (Lang, Smith Raedy, and Wilson 2006). Significant differences remain despite enhanced financial reporting comparability with US firms after adopting IFRS (Barth et al. 2012).

Thus, we expect a target located in the US to associate with low valuation uncertainties. To capture this effect, we include a dummy variable, US target, for whether the target is located in the US.

Acquiring a target located outside the bidder’s home country is more challenging as the information may be prepared in a different language and with different accounting practices

(Jeanjean et al. 2015). We expect cross-country deals to involve more valuation uncertainty.

Hence, we include an indicator variable, Cross-border, which equals 1 if the home country of the target is different from that of the acquirer and 0 otherwise.

4.1 Control variables: deal financing and method of payment

We expect that bidders will be less likely to choose an accounting firm for deals that require external equity or debt financing. This is because investment and commercial banks are better suited to organize deal financing. A dummy variable Financing required captures the need for external financing for the M&A transaction. The variable equals 1 if the source of funding for the transaction is either borrowing, bridge loan, common stock issue, debt issue, junk bond issue, mezzanine financing, rights issue, staple offering, or preferred stock, and 0 otherwise. We also control for deal structure as firms are more likely to hire investment banks for more complex transactions where the payment involves a mix of cash, equity or hybrid financing. The variable, Number of considerations offered, counts the number of securities used in the payment for target stock.

As is standard in the literature, we control for the method of payment. We construct an indicator variable, Cash offering, which takes the value of 1 if the transaction payment method is

cash and 0 otherwise. Cash offerings are more risky to the bidder since any cost related to offer mispricing is born by the bidder after the transaction.

4.2 Control variables: past relation with the advisor

Sibilkov and McConnell (2014) document that past bidder relation with the advisor plays an important role in predicting the choice of the advisor. Prior experience with an advisor builds trust and allows the bidder to be sure on the strength of the advisor. To capture the effect, we include an indicator variable, Returning acquirer advisor, which takes the value of 1 if the acquirer advisor advised the bidder in a prior M&A deal and 0 otherwise.

4.3 Control variables: other deal characteristics

Other controls include deal characteristics such as the percentage of shares sought. Acquiring a larger stake in the target is more costly as potential misvaluation has larger effect on bidder shareholders. The variable Percentage of shares sought captures the percentage of target shares the bidder seeks to acquire.

We control for the number of advisors on a deal. Because bidders may be skeptical about the ability of accounting firms to advise on a transaction, they may want to pair them with investment banks. Number of acquirer advisors counts the number of financial advisors advising the acquirer in an M&A deal.

Bulge bracket and top-tier boutique investment banks dominate the M&A market in the US

(Wachtel 2015). This oligopolistic setting increases the barriers of entry for new competitors, thus reducing the chances an accounting firm will advise on a deal. The indicator variable US acquirer captures deals where the bidder is located in the US.

Acquirers may prefer to choose an investment bank with active presence in the target market, which can facilitate information acquisition. However, not all countries have strong investment banking presence, particularly by large investment banks. IB presence in target country is an indicator variable for countries listed in Thomson Reuters M&A global rankings, which indicates strong presence and competition among investment banks.12

We control for significant family ownership of the target as substantial family ownership may increase negotiation difficulties and chances of deal collapse (Bena and Li 2014). This effect is particularly important in Europe, which are characterized by greater ownership concentration in the hands of families (Peterson-Withorn 2015 and Park, Li, and Lien 2015). The indicator variable

Family owned target captures significant family ownership of the target. It takes the value of 1 where a family or group of families controls at least 20% of the target and 0 otherwise.

We include a dummy variable, SOX, to capture the fixed effect arising from the regulatory change in the US due to the SOX regulation. Section 201 of the SOX prohibits auditors from providing a number of non-audit services, including investment banking services, to audit clients.

Soon after the SOX was enacted, three of the big four divested their advisory and consulting practices in the US (Harris 2014). Thus, we expect a lower likelihood of an accounting firm advising on a merger following the regulation as accounting firms acting as auditors were banned from providing financial advisory services to their audit clients.13

12 The countries are Argentina, Australia, Belgium, Brazil, Canada, China, Denmark, Finland, France, Germany, Hong Kong, India, Italy, Mexico, Netherlands, New Zealand, Norway, Spain, Sweden, United Kingdom, and United States. 13 “As part of [the] divestitures, the accounting firms signed non-compete agreements with their former consulting divisions. By the mid-2000s, these agreements had expired, paving the way for the firms to rebuild in consulting — under the guise of ‘advisory’ work — through a series of acquisitions. ... Non-audit work now makes up some 60 per cent of the Big Four’s total global revenues, compared with under half in 2004.” (Agnew 2015a)

4.4 Control variables: acquirer characteristics

We control for Acquirer size, measured by the acquirer’s market capitalization, as larger firms may prefer to use reputable investment banks rather than accounting firms. For comparison between countries, we express firm market capitalization in USD using the exchange rate from end of January 2005.

The acquirer’s book-to-market ratio, Acquirer B/M, and stock return momentum, Acquirer stock momentum, capture the overpricing of the bidder’s stock. Stock overvaluation increases the chances of opportunistic acquisitions (Akbulut 2013). We expect that the bidder may prefer an investment bank advisor to add credibility to such transactions. Similarly, we expect firms with higher diversity of opinion about firm prospects to choose investment banks to certify the prospects of the transaction. We use the acquirer’s share price volatility to capture diversity of opinion,

Acquirer stock volatility.

4.5 Control variables: country characteristics

The shareholder governance model in countries with a UK common law legal origin makes managers more accountable (Ball, Kothari, and Robin 2000), increasing the risk that negative deal outcomes may lead to the dismissal of the managerial team (Lehn and Zhao 2006). To reduce this risk, bidders may choose accounting firm advisors if this choice leads to fairer target valuation.

We include an indicator variable, Common Law, for acquirers located in common law countries to capture this effect.

We control for differences in average ownership structures between bidder countries using the variable Ownership concentration. This is the ownership concentration index from La Porta et al.

(1998). It is defined as the median proportion of common shares owned by the three largest

shareholders in the ten largest privately owned non-financial firms. Previous research shows that more concentrated ownership increases the monitoring of managers (Jensen and Meckling 1976 and Schleifer and Vishny 1986). Given the greater monitoring in countries with more concentrated ownership, we expect bidders in these countries to have a stronger incentive to hire accounting firm advisors to reduce target valuation uncertainty.

Lower-quality disclosure increases information search and acquisition costs and thus valuation uncertainty. We expect bidders to have a stronger incentive to hire accounting firm advisors if the target country has lower-quality disclosure regulation. We include an indicator variable, Lower-quality disclosure regulation, which equals 1 if the target country’s disclosure regulation is weakly lower in quality than that of the bidder country. The quality of disclosure regulation is measured by the country disclosure scores from Hope (2003).

We control for differences in the extent of earnings management across countries. Previous studies suggest that more earnings management increases valuation uncertainty as accounting information is less reliable. This may increase the need for accounting firms’ expert opinions.

More aggregate earnings management is an indicator variable for cases where the target country’s aggregate earnings management score is higher than that of the bidder country. The score is from

Leuz, Nanda, and Wysocki (2003). For completeness, we also include the bidder’s country disclosure score, Disclosure regulation, and aggregate earnings management score, Aggregate earnings management, in the regressions of the advisor choice analysis.

All regressions control for the industry and year effects. The statistical tests on the estimated coefficients of the regressions are based on clustered standard errors robust to within-acquirer and year correlation (Rogers 1993) and heteroskedasticity-adjusted (White 1980). All continuous explanatory variables used in the regressions are winsorized at the 1st and 99th percentiles.

The specification of the logit model predicting the adviser choice is as follows:

Pr(Accounting firm acquirer advisor) = f(variables for valuation uncertainty,

deal financing and method of payment,

past relation with the advisor,

other deal characteristics,

acquirer characteristics,

country characteristics), (1) where f is the cumulative distribution function of the standard normal distribution. Table 1 summarizes the definitions of the variables used in the advisor choice model and other analyses of the paper.

[Table 1]

Table 2 shows the descriptive statistics of the variables used in the advisor choice analysis.

They are partitioned into the M&A deals advised by accounting firms and by investment banks.

The t-tests for differences in the means of the variables across the two groups are reported in the last column. Deals advised by accounting firms tend to be for targets in industries with lower accruals quality, that are unlisted and outside the US, and in cross-border transactions. These univariate results provide preliminary evidence that accounting firms advise on deals difficult to value. We also observe a large difference in the mean size of the deals advised by accounting firms and by investment banks. Despite the statistically insignificant t test on the means, the medians reveal that deals advised by accounting firms are much smaller. Finally, we document that accounting firms are more likely to advise on deals where the target’s country has a higher aggregate earnings management score than the bidder’s. Together, these results suggest that bidders are more likely to hire accounting firm advisors when target valuation uncertainty is high.

[Table 2]

Looking at the control variables in Table 2, we observe that deals advised by accounting firms infrequently require external financing, involve multiple payment forms, or use non-cash payment method. Investment banks have competitive advantages in those areas. Because acquirers advised by investment banks tend to be larger, these acquirers are likely to have more M&A activities in the past and establish a relation with a specific investment banks. This explains why these bidders are more likely to choose an investment banks that advised on a previous transaction.

Accounting firms more often advise on deals where the bidder is located outside the US and in countries without a strong presence of investment banking. Smaller bidders, who are located in non-common-law countries, with lower ownership concentration, lower-quality disclosure regulation, lower B/M ratio and higher share price volatility are more likely to hire accounting firm advisors for their M&A transactions.

4.5 Regression results for the advisor choice model

Table 3 presents regression results for the advisor choice model. We confirm the univariate evidence that accounting firms more frequently advise on deals with higher valuation uncertainty.

These include deals with the targets from the industries characterized by low accruals quality, unlisted targets, non-US targets, targets of cross-border deals, and smaller targets as measured by deal value. These results hold when we control for proxies for deal financing and payment method, and past bidder relation with the advisor. Further, auditors are more likely to advise on deals where the target country’s aggregate earnings management score is higher than the acquirer’s country, which corroborates our conclusion.

The valuation uncertainty proxies are economically important predictors of the advisor choice.

The odds an accounting firm will advise on an M&A transaction are 36% higher when the target is in a low accruals quality industry, 1.85 times higher for unlisted targets, 60% lower for non-US targets, 26% higher for cross-border deals, and 31% higher when the aggregate earnings management score in the target country is higher than in the bidder country. These results suggest that bidders consider accounting firms better set to resolve valuation uncertainties than investment banks.

[Table 3]

In unreported results, we repeat the analysis using the variation in discretionary accruals from the Jones model (Jones 1991) to capture target’s industry accruals quality and find consistent results. Thus, our conclusion is not changed with this alternative measure of accounting quality.

We also repeat the analysis confined to big four accounting firms (Big4) and still find that the proxies for valuation uncertainty are strong predictors of the choice of Big4 as M&A financial advisors.14

The signs for control variables are similar to the univariate results. Importantly, we document that accounting firms were less likely to win advisory roles after the passage of the SOX. This effect is economically significant: the odds a bidder hires an accounting firm are 45% lower after the regulation. This suggests the regulation imposed a significant barrier for accounting firms to compete with investment banks in the US market. This result helps explain Figure 2 evidence, which shows much higher relative activity of accounting firms in Europe than in the US. From

14 We recognize that because of familiarity, bidders may choose the same accounting firm as their auditor. We can identify bidder auditors for 6.1% of all deals and for those cases, in 34% of transactions the auditor is also the advisor on the deal (for obvious reason, we cannot include this control in the advisor choice analysis). This result likely reflects that accounting firms avoid joint roles of auditor and M&A advisor because of potential regulatory scrutiny. We also check instances where the bidder chooses an accounting firm that audits the target. We find that in only two cases bidders had accounting advisors who were also auditors for the target. This likely reflects that accounting firms try to avoid potential conflicts of interest arising from these dual roles (Dhaliwal et al. 2015).

other noteworthy results, we find that accounting firms are more likely to advise as part of a team rather than as single advisors. This result suggests that accounting firms may be chosen to certify the transaction quality to bidder shareholders, e.g., reliability of synergy gain estimates. Further, accounting firms are more likely to be hired as advisors when the acquirer country has poorer disclosure regulation and a higher aggregate earnings management score. This result further reinforces the conclusion that target valuation uncertainties play an important role in the choice of the accounting firm as a deal advisor.

6. Acquirer announcement return

Next, we examine whether investors perceive transactions advised by accounting firms more favourably compared to deals advised by investment banks. If investors perceive that accounting firms can resolve information uncertainty and reduce the risk of deal failure, we would expect a more positive price reactions to deal announcements. For this test, we calculate a five-day announcement period cumulative abnormal return, CAR, where the normal return benchmark is the stock market index of the acquirer's listing exchange.

Our main variable of interest is the indicator variable for accounting firm advisor. We expect this variable to load positively when regressed on announcement day returns. To test the prediction that accounting firms bring valuable accounting knowledge, we also create an indicator variable that captures the industry specialization of the parent audit firm, AF advisor with industry expertise on accounting. This variable takes the value of 1 if the acquirer advisor is an accounting firm whose parent firm has expertise as an audit-specialist of the target’s industry and 0 otherwise. An industry audit-specialist is defined analogously according to the dominant player definition in

Reichelt and Wang (2010), with the market shares by audit clients’ total assets substituting for the

market shares by audit fee in the original definition.

Because industry-knowledge should be particularly valuable for targets in industries with low accounting quality, we interact the industry specialization variable with the indicator variable

Target in high |Total Accruals| industry. We expect that investors will react more favorably when the bidders hire an accounting firm to advise on deals where the target is in a low accounting quality industry and the accounting firm can lever on the parent’s audit expertise in evaluating accounting information for this industry.

The regression controls are standard. We control for the method of payment as cash-financed acquisitions elicit more favorable price reactions (Travlos 1987). We control for the previous relation between the bidder and the advisor as acquirers are more likely to retain better performing advisors. We also control for the size of the advisory team as larger teams may benefit from the synergy of expertise between partners in the team and can ensure better risk sharing and monitoring, which can produce better outcomes (Hunter and Jagtiani 2003). Previous research documents higher price reaction for larger transactions (Golubov et al. 2012), so we control for size of the deal. We also include controls for cross-border deals and for whether the target has significant family ownership as these transactions tend to have disappointing outcomes (Eckbo and Thorburn 2000; Basu, Dimitrova, and Paeglis 2009) Finally, we also control for deals made after the passage of the SOX and include acquirer firm and country controls from the advisor choice model, as well as dummy variables for the year and industry fixed effects.15

The specification of the regression model for the acquirer announcement return analysis is as follows (with deal subscripts omitted for brevity):

15 We do not include the offer premium in the regression because (i) previous studies show an insignificant relation between the offer premium and price reactions (e.g. Golubov et al. 2012), and (ii) the offer premium is only available for public targets, which would substantially reduce the sample size.

CAR = α0 + α1 AF advisor + α2 AF advisor with industry expertise on accounting

+ α3 (AF advisor with industry expertise on accounting

× Target in high |Total Accruals| industry)

+ α4 Target in high |Total Accruals| industry

+ Λ5 Controls + Λ6 Year effects + Λ7 Industry Effects + ε (2)

The indicator variable AF advisor takes the value of 1 if an accounting firm is hired to advise on an M&A deal and 0 otherwise.

Because the advisor choice is unlikely to be random, we also estimate equation (2) for a restricted sample with deals advised by accounting firms matched with deals advised by investment banks. The matching is based on propensity scores estimated from equation (1). This approach generates a sample of 1,660 deals advised by accounting firms and by investment banks with non-missing information on announcement-period returns. Results from the matched sample should not be subject to endogeneity concerns.

Panel A of table 4 reports average CARs for deals split by the type of acquirer advisor. For the full sample, price reactions for deals advised by accounting firms are on average nearly three times higher than those advised by investment banks (2.03% vs. 0.68%). This difference translates into a $148 million shareholder value gain for a mean-sized bidder. For the PSM sample, the difference in CARs is similarly large (2.03% vs. 1.10%), which generates $102 million gain in shareholder wealth at the announcement for a mean-sized bidder. These results suggest substantial gains to bidders when they hire accounting firms to advise on M&As.

[Table 4]

We confirm higher price reactions to M&As advised by accounting firms in panel B of table

4, which shows estimates for equation (2). The coefficient on AF advisor is positive for the full

sample as well as the PSM sample. Further, we show that price reactions are higher for deals where accounting firms have competitive advantages, namely for deals where the target is in an industry with low accruals quality and the accounting firm is an audit-specialist for this industry. These results indicate that investors recognize that accounting firms may use their audit expertise to produce fairer target valuations.

The coefficient estimates for the controls are consistent with past evidence. Importantly, the

PSM sample regression indicates that deals with a target from a low accounting quality industry are received less favorably by investors. This result is consistent with the higher valuation uncertainty of these targets and a higher likelihood of overpayment (McNichols and Stubben

2015). As we show in the next section, bidders are less likely to overpay for targets with low accounting quality when they hire accounting firm as advisors.

In unreported results, we also estimated equation (2) for deals with sole advisors and find similar results to Table 4. This suggests that our conclusions are not driven by deals where accounting firms are paired with investment banks. Further, the results remain qualitatively the same when we use the variation in discretionary accruals from the Jones model (Jones 1991) to capture accruals quality. This is the case despite a smaller sample size due to higher data requirements. Hence, our conclusion remains unchanged for this alternative measure of accounting quality.

5. Target valuation: offer premium

Previous studies document that valuation uncertainty increases the likelihood the bidder will overpay for the target. Laamanen (2007) finds that the acquisition premium tends to be higher when it is more difficult to value a target’s resources (e.g., R&D-related assets) and reports an

average premium in the US ranging between 30–50% between 1970s–2000s. McNichols and

Stubben (2015) document that bidders pay less to acquire a target with high-quality accounting information, which they attribute to better accounting quality mitigating the risk of overpaying for the target. We argue that the competitive advantage of accounting firms as M&A advisors stems from their expertise in target valuation. Specifically, accounting acquirer advisor help reduce the uncertainty in target valuation and reduced valuation uncertainty allows the acquirer to estimate more accurately the target’s reservation price and thereby lower the offer premium. We test this prediction next.

We define the variable Offer premium as (the ratio of the bid price per share to the target’s closing stock price 1 day prior to announcement – 1) × 100. Like Dimopoulos and Sacchetto

(2014), we consider only the premium corresponding to the final offer. This is the winning bid in a successfully completed takeover or otherwise the last withdrawn bid in an unsuccessful takeover.

As is standard in the literature, we winsorize offer premium at the 1% level.

The specification of the regression model for the offer premium analysis is as follows:

Offer premium = β0 + β1 AF advisor + β2 AF advisor with industry expertise on accounting

+ β3 (AF advisor with industry expertise on accounting

× Target in high |Total Accruals| industry)

+ β4 Target in high |Total Accruals| industry

+ Β5 Controls + Β6 Year effects + Β7 Industry Effects + ε (3)

As in the acquirer announcement return analysis, the coefficients of interest are β1–β3. We expect accounting firms to help negotiate lower average premia, particularly for firms with low accruals quality.

The set of controls includes Unlisted target as information search costs are higher for these

targets, which can increase offer premium. We include Returning acquirer advisor to control for past bidder relation with the advisor as previous advisors may be better able to assess expected synergy gains, which affect the offer premium (Sibilkov and McConnell 2014). The certification hypothesis suggests that more reputable advisors should be better at negotiating more favorable deal conditions (Chemmanur and Fulghieri 1994). To capture this effect, we include a measure of advisor reputation, Last year's total deal value of acquirer advisors, which is the total value of all the M&A deals advised by the acquirer advisors in the year prior to the M&A deal. We also include the Number of acquirer advisors as larger advisory teams might be better negotiating down the offer price. Financing required is included to control for whether the deal will be financed by external financing as premia financed by internal cash tend to be higher (Huang and Walkling

1987 and Savor and Lu 2009). Prior studies find that significant family ownership has a negative association with takeover premia (Villalonga and Amit 2006; Holmen and Nivorozhkin 2005), which is attributed to lower bargaining power and higher willingness to accept lower offer price by family owned targets. Thus, we include the control Family owned target. Lastly, we control for

Deal value as a proxy for the target firm size because Alexandridis et al. (2013) find a negative relationship between target firm size and offer premium.

Panel A of Table 5 reports average premia for the sample split by the type of advisor. M&As with accounting firm advisors have on average 24.7% lower premia compared to deals advised by investment banks (22.3% vs. 29.7%). This translates into average savings of $135 million for a mean-sized deal. This univariate result provides preliminary evidence suggesting accounting firms may be better set to value M&A targets.16

16 We do not report PSM results because of a very small sample size in this case (168 observations), which leaves few degrees of freedom for estimation.

[Table 5]

Panel B of the table reports estimates for model (3). We confirm univariate results of lower premia for deals advised by accounting firms. Further, the valuation strength of accounting firms seems particularly strong in cases where the target is in a lower accounting quality industry and the accounting firm is an audit-specialist of the industry. The positive coefficient of Target in high

|Total Accruals| industry is consistent with prior research suggesting that investors tend to overpay for targets with poor accounting quality (McNichols and Stubben 2015). The results of Table 5 help explain our price reaction results—investors recognize the competitive skill of accounting firms in valuation and anticipate the relatively lower premium the bidder will pay for the target.

Because the offer premium requires target share price, our sample is limited only to public targets. To control for endogeneity related to the choice of advisor for public deals, we use instrumental variables. As an instrument, we use an indicator variable, IB presence in target country, for whether the target country has strong investment banking presence as the likelihood of choosing an investment bank may reduce if there is no subsidiary in the target country. The second instrument is an indicator variable, Acquirer has prior experience using AF advisor, for whether the firm hired an accounting firm for an M&A transaction in the previous five years.

Bidders are more likely to hire an accounting firm if a previous relation exists. The final instrument is the indicator variable, AF advisor has acquirer industry expertise on accounting, for whether the parent audit firm is a specialist of the acquirer industry. The acquirer may be more aware that an accounting firm is also involved in M&A advisory services if the accounting firm is the audit- specialist of the acquirer’s industry. We do not expect any of the instruments to correlate with the offer premium and the test of overidentifying restrictions comfortably rejects the hypothesis the instruments are not valid. Last columns of Table 5 report results from 2SLS regressions, and we

confirm that accounting firms negotiate lower offer premia. Together, the results in Table 5 confirm superior valuation skills of accounting firms that translate into more competitively priced transactions for the bidder.

6. Deal completion rate

Our results reveal that accounting firms help mitigate valuation uncertainty inherent in M&As, but managers may be also concerned about the deal completion. Failed transactions increase the turnover risk for the managerial team (Jacobsen 2014) and associate with negative price reactions

(Jacobsen 2014; Davidson, Dutia, and Cheng 1989). Merger failure can occur for a variety of reasons, which include the occurrence of “material adverse effect” events, problems discovered during the due diligence process or a receipt of a higher bid (Luo 2005).17 Broadly, the likelihood a deal will be terminated increases with the probability new information becomes available to the bidder after the deal announcement regarding the true value of the target (Marquardt and Zur

2015). Because accounting firms should be better at analyzing target information before the announcement, collected from public sources and via the parent audit firm, the risk material information will emerge after the announcement should be lower.

To test the prediction that accounting firms help resolve the uncertainty new information on target true value will lead to deal termination, we identify all deals with SDC withdrawn status.

There are 962 transactions falling into this category or 6.6% of the sample. We create an indicator variable, Withdrawn, taking the value of 1 for withdrawn deals and 0 otherwise. We then regress this variable on AF advisor and other variables using the following specification of a logit model:

17 Material adverse effect (MAE) clauses allow the bidder to terminate the deal if specific events are triggered, which include economic or industry shocks, financial misreporting, and regulatory changes (Denis and Macias 2013).

Pr(Withdrawn = 1) = f(AF advisor, Controls, Year effects, Industry Effects), (4) where f is the cumulative distribution function of the standard normal distribution. The controls are the variables predicting effort and difficulty in collecting information about the target: prior bidder relation with the advisor (Returning acquirer advisor), reputation of the advisor (Last year's total deal value of acquirer advisors), size of the advisory team (Number of acquirer advisors), whether target is in a low accounting quality industry (Target in high |Total Accruals| industry), unlisted target (Unlisted target), significant family ownership (Family owned target), and target size proxy (Deal value).

Panel A of table 6 reports the average frequency of withdrawn transactions split by the advisor type for the full sample and the PSM sample. M&As advised by investment banks have 61 times higher chances of withdrawal compared to deals advised by accounting firms (7.01% vs. 0.11%).

For the PSM sample we observe a similar result: deals with investment bank advisors have 12 times higher chance of failure (1.48% vs. 0.11%). This result confirms the lower risk of withdrawal for deals with accounting firm advisors.

[Table 6]

Panel B reports the results of the logit regression for the deal withdrawal analysis. The significant coefficient on the AF advisor variable confirms that accounting firms reduce the likelihood of deal withdrawal. This result is present for the full sample and the PSM sample.18 The results in this table corroborate the conclusion that accounting firms are better able to analyze and gather information about the target before the transactions, which reduces the risk new information will lead to deal withdrawal.

18 For the PSM sample regression, we had to exclude Target in high |Total Accruals| industry and Family owned target as none of the M&As withdrawn has a value of 1 for these indicator variables. For similar reason, we do not control for year and industry effects for this sample.

7. Accounting firms’ future advisory role

Our results thus far document significant benefits, in terms of fairer valuation and a lower risk of deal withdrawal, to acquirers hiring accounting firm advisors. Our final test shows that bidders recognize these benefits and re-hire accounting firms to advise on future M&A transactions. For this test, we create an indicator variable, Prior experience using AF advisor, for whether the bidder hired an accounting firm advisor in the previous five years. We expect that previous positive experience from hiring an accounting firm will translate into future business for the whole category of accounting firm advisors.

Panel A of table 7 reports the frequency of deals advised by accounting firms and by investment banks, conditional on the bidder using an accounting firm advisor previously. We observe that acquirers are two times more likely to hire an accounting firm advisor if they already had an experience with accounting firm advisors. This supports the prediction that bidders reward accounting firms with future business.

[Table 7]

Next, we examine our prediction in a regression setting. Specifically, we expand the logit regression for the advisor choice analysis, equation (1), to include Prior experience using AF advisor. Panel B reports abbreviated regression results confirming that bidders are more likely to hire an accounting firm advisor if they had used accounting firm advisors before. Specifically, the odds a bidder will choose an accounting firm advisor are 1.7 times higher if the bidder used an accounting firm advisor in a previous M&A. This result confirms that acquirers recognize the benefits from accounting firm advisory roles and seek to capture similar benefits in future business.

8. Conclusion

The superior accounting knowledge of accounting firm advisors allows them to better assess a target’s value. Analyzing accounting information is no doubt the central expertise of accounting firms. They are stronger in understanding how different accounting manipulation techniques could have distorted the reported information and are less likely to be misled. They also have stronger expertise in judging the competence of the target’s accounting personnel, the quality of its accounting information system, and the effectiveness of the internal control and corporate governance mechanisms in place, on top of the independent evaluation by the accountant assisting the due diligence process. Therefore, accounting firm advisors are more likely to reach at a more precise valuation of the target, mitigating the valuation uncertainty that otherwise might give rise to an overpaid offer premium or reduce the deal completion likelihood. In sum, accounting firm advisors have a distinct edge over investment bank advisors in every aspect where accounting matters.

To our knowledge, we are the first to document the growing visibility of accounting firms in the global M&A financial advisory market. We obtain evidence showing that accounting firm advisors are more preferred by acquirers interested in targets from an industry characterized by low accounting accruals quality, in smaller targets, when the target is a private firm, is located outside the US, and for cross-country deals. Further, accounting firms are more likely to advise on deals where the target’s country aggregate earnings management score from Leuz, Nanda, and

Wysocki (2003) is higher than that of the acquirer home country. This evidence is consistent with the perspective that the superior accounting knowledge of accounting firm advisors is particularly useful in resolving target valuation uncertainty in those circumstances.

Most importantly, we find evidence confirming various benefits to acquirers choosing accounting firm advisors: higher announcement returns to acquirers reflecting net gains anticipated from the acquisitions, lower offer premiums to targets, and higher deal completion rates. These benefits explain why accounting firms have a growing visibility in the global M&A financial advisory market.

Appendix A. Thomson Reuters Worldwide Mid-Market Rankings for the first quarter of 2015.

The graph reports Thomson Reuters Worldwide Rankings of M&A advisors for the mid-capitalization and small-capitalization M&As.

Appendix B1. Names of M&A advisors associated with PwC

The table shows names of advisors on SDC and their codes where the parent is PwC.

Advisor name SDC advisor code Parent Name Price Waterhouse Corporate Fin PRICE-CORP-FIN PricewaterhouseCoopers Pricewaterhouse Coopers Secur PWC-SECURITIES PricewaterhouseCoopers PricewaterhouseCoopers PWC PricewaterhouseCoopers PricewaterhouseCoopers (Aus) PWC-AUS PricewaterhouseCoopers PricewaterhouseCoopers (JP) PWC-JAPAN PricewaterhouseCoopers PricewaterhouseCoopers (SG) PWC-SG PricewaterhouseCoopers Pricewaterhousecoopers Corpora PWC-CF-SAS PricewaterhouseCoopers PricewaterhouseCoopers Secur PWC-SEC PricewaterhouseCoopers PwC Advisory Co Ltd (JP) PWC-ADV-JAPAN PricewaterhouseCoopers PwC Transaction Services Inc PWC-TRANS-SVCS PricewaterhouseCoopers PricewaterhouseCoopers (UK) PWC-UK PricewaterhouseCoopers

Appendix B2. SDC parent advisor codes and names

The table reports parent advisor codes and names of accounting firms on SDC.

SDC parent advisor codes SDC parent advisor names ARTHUR-ANDERSEN Arthur Andersen BAKER-TILLY-INT Baker Tilly BDO BDO CROWECLARK Crowe Clark Whitehill DELOITTE Deloitte ERNST-YOUNG Ernst & Young GRANT-INTL Grant Thornton HMT-CORP-FIN Hurst Morrison Thomson KPMG KPMG MCGLADREY-CM McGladrey Capital Markets PANNELL-KERR Pannell Kerr Forster PKF-INTL PKF International PKFITALIA PKF Italia PWC PricewaterhouseCoopers RSM-BENTJEN RSM Bentley Jennison RSM-TENON RSM Tenon Group RSMROB RSM Robson Rhodes SMITH-W Smith & Williamson Securities TENON-GROUP Tenon Group

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Figure 1. Percentage of M&As advised by accounting firms (N=22494)

12% Total number of M&A transactions 2000

1800 10% % of M&As advised by accounting firms 1600

1400 8% 1200

6% 1000

800 4% 600

400 2% 200

0% 0 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014

Figure 2a. Number of M&As advised by accounting firms: US&Canada vs. Europe 1000 900 US&Canada 800

700 Europe 600 500 400 300 200 100 0

Figure 2b. Proportion of M&As advised by accounting firms: US&Canada vs. Europe 30%

US&Canada 25%

Europe 20%

15%

10%

Figure 3. Percentge and mean-value ratio of accounting-firm-advised deals across countries (N=22494)

25% 1.4 Percentage of deals advised by accounting firms

1.2 Ratio of mean value of deals advised by accounting firms to that by 20% investment banks 1.0

15% 0.8

0.6 10%

0.4

5% 0.2

0% 0.0

Table 1 Variable definitions This table presents the definitions of the main variables used in the study. An industry is defined based on the two- digit SIC code. Variable Definition Deal characteristics Deal value The market value of the shares sought in the M&A deal Percentage of shares sought The percentage of target shares the bidder seeks to acquire (1 = 100%) Offer premium (the ratio of the bid price per share to the target’s closing stock price 4 weeks prior to announcement – 1) × 100 Number of acquirer advisors The number of financial advisors advising the acquirer in the M&A deal Last year's total deal value of The total value of all the M&A deals advised by the acquirer advisors in the year prior acquirer advisors to the M&A deal Financing required An indicator variable equal to 1 if the source of funding for the transaction is either borrowing, bridge loan, common stock issue, debt issue, junk bond issue, mezzanine financing, rights issue, staple offering, or preferred stock, and 0 otherwise. Number of considerations The number of securities used in the payment for target stock. offered Cash offering An indicator variable equal to 1 if the transaction payment method is cash and 0 otherwise. Withdrawn An indicator variable equal to 1 if the deal offer is withdrawn by the acquirer and 0 otherwise. Returning acquirer advisor An indicator variable equal to 1 if the acquirer advisors advised the acquirer in a prior M&A deal and 0 otherwise AF advisor An indicator variable equal to 1 if the acquirer advisor is an accounting firm and 0 otherwise AF advisor with industry An indicator variable equal to 1 if the acquirer advisor is an accounting firm whose expertise on accounting parent audit firm has expertise as an audit-specialist of the target’s industry and 0 otherwise. An industry audit-specialist is defined analogously according to the dominant player definition in Reichelt and Wang (2010, p. 656), with the market shares by audit clients' total assets substituting for the market shares by audit fee in the original definition. SOX An indicator variable equal to 1 if the M&A deal is in the era after the Sarbanes-Oxley Act was enacted on 30 July 2002 and 0 otherwise Year effects Year dummy variables for the M&A deal announcement year. Acquirer characteristics Acquirer size [MV (USD)] Acquirer's market capitalization measured at the end of the fiscal year before the M&A deal date and expressed in USD millions. Acquirer B/M Acquirer's book value of equity to market value of equity ratio at the fiscal year end prior to the M&A deal Acquirer stock momentum Acquirer's buy-and-hold stock returns for 90-days prior to the previous fiscal year- end. Acquirer stock volatility Stock price standard deviation measured over 90-days before the previous fiscal year- end, scaled by the mean price level over this period.

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Table 1 (continued) Variable Definition Acquirer characteristics (continued) Prior experience using AF An indicator variable equal to 1 if the acquirer has chosen an AF advisor in an M&A advisor deal in the previous five years, and 0 otherwise. US acquirer An indicator variable equal to 1 if the acquirer is incorporated in the US and 0 otherwise. Industry effects Acquirer's industry dummy variables. Target characteristics Target in high |Total An indicator variable equal to 1 if the target belongs to the top two industries with the Accruals| industry highest values of the equal-weighted average of the absolute values of the total accruals of all the firms in the industry and 0 otherwise Unlisted target An indicator variable equal to 1 if the target is not a firm listed on an exchange and 0 otherwise Cross-border An indicator variable equal to 1 if the target is incorporated in a country different from the acquirer's country of incorporation and 0 otherwise. US target An indicator variable equal to 1 if the target is incorporated in the US and 0 otherwise IB presence in target country An indicator variable equal to 1 if the target country is listed in the Thomson Reuters M&A global rankings (i.e., Argentina, Australia, Belgium, Brazil, Canada, China, Denmark, Finland, France, Germany, Hong Kong, India, Italy, Mexico, Netherlands, New Zealand, Norway, Spain, Sweden, United Kingdom, and United States) and 0 otherwise. Family owned target An indicator variable equal to 1 if a family or group of families controls at least 20% of the target and 0 otherwise. Sourced from SDC Platinum. Country characteristics (Acquirer) Common law An indicator variable equal to 1 if the legal system of the bidder country originates from the UK common law system and 0 otherwise. Sourced from La Porta et al. (2006) Ownership concentration Ownership concentration index of the acquirer's country of incorporation, which is the median proportion of common shares owned by the three largest shareholders in the ten largest privately owned nonfinancial firms. Sourced from La Porta et al. (2006) Disclosure regulation A measure for the bidder country based on the country disclosure score from Hope (2003). The higher the score, the higher the quality of the disclosure regulation in the country. Aggregate earnings An aggregate score of the earnings management activities of the nonfinancial firms in management the acquirer's country of incorporation. Sourced from Leuz et al. (2003) Country characteristics (Target) Lower-quality disclosure An indicator variable equal to 1 if the target country’s disclosure regulation is lower regulation in quality than that of the bidder country. The quality of disclosure regulation is measured by the country disclosure scores from Hope (2003). The higher the score, the higher the quality of the disclosure regulation in the country. More aggregate earnings An indicator variable equal to 1 if the target country’s aggregate earnings management management score is higher than that of the bidder country and 0 otherwise. The score is from Leuz et al. (2003).

Table 2 Descriptive statistics This table presents the descriptive statistics of the variables used for analysis. All variables are defined in table 1. (1) (2) (1) - (2) Accounting firm acquirer advisor Investment bank acquirer advisor Difference in mean (N = 880) (N = 13,716) Variable Mean Median S.D. Mean Median S.D. % diff. t A. Valuation uncertainty Target in high |Total Accruals| industry 0.043 0.000 0.203 0.040 0.000 0.197 7.3% 10.34 Unlisted target 0.867 1.000 0.340 0.560 1.000 0.496 54.8% 44.87 US target 0.164 0.000 0.370 0.543 1.000 0.498 −69.9% −52.99 Cross-border 0.539 1.000 0.499 0.344 0.000 0.475 56.5% 32.64 Deal value 353 48 2,211 1,835 304 6,359 −80.7% −0.01 Deal value / Acquirer size 0.624 0.066 4.308 13.027 0.203 562.069 −95.2% −0.20 B. Deal financing and method of payment Financing required 0.140 0.000 0.347 0.196 0.000 0.397 −28.5% −23.42 Cash offering 0.420 0.000 0.494 0.393 0.000 0.488 6.9% 4.04 Number of considerations offered 1.407 1.000 0.675 1.598 1.000 0.892 −12.0% −4.98 C. Past relation with the advisor Returning acquirer advisor 0.297 0.000 0.457 0.391 0.000 0.488 −24.1% −15.08 D. Other deal characteristics Percentage of shares sought 91.4 100.0 20.9 91.4 100.0 21.4 −0.1% 0.00 Number of acquirer advisors 1.481 1.000 0.846 1.590 1.000 1.015 −6.9% −2.30 US acquirer 0.183 0.000 0.387 0.558 1.000 0.497 −67.2% −49.01 IB presence in target country 0.870 1.000 0.336 0.933 1.000 0.250 −6.7% −5.82 Family owned target 0.002 0.000 0.048 0.002 0.000 0.049 −5.5% −33.36 SOX 0.652 1.000 0.477 0.583 1.000 0.493 11.9% 7.14

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Table 2 (continued) (1) (2) (1) - (2) Accounting firm acquirer advisor Investment bank acquirer advisor Difference in mean (N = 880) (N = 13,716) Variable Mean Median S.D. Mean Median S.D. % diff. t E. Acquirer characteristics Acquirer size [USD] 6,452 824 53,048 11,228 1,790 367,866 −42.5% 0.00 Acquirer B/M 0.688 0.482 0.740 0.618 0.461 0.855 11.4% 4.38 Acquirer stock momentum 0.105 0.050 0.377 0.105 0.057 0.426 −0.7% −0.54 Acquirer stock volatility 0.115 0.061 0.187 0.104 0.061 0.156 10.3% 15.98 F. Country characteristics (Acquirer) Common law 0.601 1.000 0.490 0.752 1.000 0.432 −20.1% −11.89 Ownership concentration 0.257 0.150 0.163 0.197 0.120 0.134 30.3% 53.97 Disclosure regulation 0.753 0.833 0.184 0.870 1.000 0.181 −13.3% −20.84 Aggregate earnings management 10.211 7.000 7.168 6.589 2.000 6.767 55.0% 2.21 (N = 880) (N = 13,716) Variable Mean Median S.D. Mean Median S.D. % diff. t G. Country characteristics (Target) Lower-quality disclosure regulation 0.793 1.000 0.405 0.862 1.000 0.344 −8.0% 36.02 More aggregate earnings management 0.260 0.000 0.439 0.152 0.000 0.359 71.8% 47.49

Table 3 Type of financial advisor chosen by the acquirer: audit-frim vs. investment-bank advisor The table shows the results of the logit regression analysis of advisor choice by the acquirer. The dependent variable AF advisor takes the value of 1 if the acquirer has chosen an accounting firm advisor in the M&A deal, and 0 otherwise. The explanatory variables are defined in table 1. ln denotes the logarithm value of a variable and N is the number of observations. p(Wald Χ2) is the p-value of the Wald Χ2-test for model specification. Pseudo R2 is the pseudo R-squared. All the models are pooled cross-sectional models with clustered standard errors robust to within acquirer and year correlation (Rogers 1993) and heteroskedasticity-adjusted (White 1980). (1) (2) (3) (4) Baseline Deal financing Past relation Country characteristics Estimate p Estimate p Estimate p Estimate p Intercept −1.470 0.000 −1.460 0.000 −1.446 0.000 −0.737 0.198 Target in high |Total Accruals| 0.276 0.031 0.279 0.029 0.282 0.033 0.310 0.025 industry Unlisted target 1.067 0.000 1.073 0.000 1.075 0.000 1.047 0.000 US target −0.955 0.000 −0.952 0.000 −0.937 0.000 −0.910 0.000 Cross-border 0.434 0.000 0.433 0.000 0.425 0.000 0.232 0.166 ln Deal value −0.530 0.000 −0.523 0.000 −0.524 0.000 −0.533 0.000 Financing required −0.141 0.190 −0.124 0.244 −0.109 0.309 Cash offering 0.007 0.948 0.017 0.877 0.023 0.789 Number of considerations offered 0.005 0.946 0.008 0.920 0.002 0.972 Returning acquirer advisor −0.282 0.030 −0.281 0.034 Percentage of shares sought 0.011 0.005 0.011 0.005 0.011 0.006 0.011 0.003 Number of acquirer advisors 0.265 0.001 0.271 0.000 0.282 0.000 0.280 0.000 US acquirer −0.988 0.000 −0.999 0.000 −1.016 0.000 −0.486 0.008 IB presence in target country −0.047 0.758 −0.043 0.780 −0.061 0.700 −0.046 0.799 Family owned target −0.158 0.810 −0.176 0.789 −0.195 0.772 −0.170 0.801 SOX −0.595 0.000 −0.593 0.000 −0.598 0.000 −0.600 0.000 ln Acquirer size (USD) 0.028 0.401 0.022 0.521 0.033 0.332 0.032 0.395 ln Acquirer B/M −0.054 0.346 −0.061 0.289 −0.060 0.314 −0.059 0.333 Acquirer stock momentum 0.102 0.196 0.103 0.189 0.108 0.146 0.117 0.109 Acquirer stock volatility 0.005 0.988 0.001 0.997 0.007 0.984 −0.059 0.854 Country characteristics (Acquirer): Common law 0.832 0.000 Ownership concentration −0.567 0.475 Disclosure regulation -2.068 0.001 Aggregate earnings management 0.048 0.012 Country characteristics (Target): Lower-quality disclosure regulation -0.171 0.236 More aggregate earnings management 0.268 0.075 Year and industry effects Yes Yes Yes Yes N 14,596 14,596 14,596 14,596 p(Wald X2) 0.000 0.000 0.000 0.000 Pseudo R2 23.66% 23.69% 23.86% 24.49%

Table 4 Acquirer announcement-period CAR Panel A of this table reports the average acquirer CARs partitioned by the accounting firm and investment bank advised deals. Panel B shows the regression analysis of acquirer announcement returns. The dependent variable is the acquirer CAR calculated for the five days (-2, 2) around the announcement (day 0) of an acquisition deal, adjusted for the market return based on the stock market index of the acquirer's country of incorporation. Acquirer firm controls are the log values of the acquirer size and B/M, the acquirer stock momentum and volatility, and the US acquirer dummy. Acquirer country controls are the country characteristics for the acquirer defined in table 1. The other explanatory variables are also defined in table 1. ln denotes the logarithm value of a variable and N is the number of observations. F is the F-statistic for the model specification and p(F) is the corresponding p-value. R2 is the R- squared. Model 3 is based on the paired sample matched by the propensity score estimated with Model 3 in table 3. All the models are pooled cross-sectional models with clustered standard errors robust to within acquirer and year correlation (Rogers 1993) and heteroskedasticity-adjusted (White 1980). Panel A: Descriptive statistics N Mean S.D. t Full sample: Accounting firm advisor 830 2.03% 0.28% 7.220 Investment bank advisor 13,087 0.68% 0.08% 8.880 % diff. 198.1% 0.29% 678.2 Propensity score matched sample: Accounting firm advisor 830 2.03% 0.28% 7.220 Investment bank advisor 830 1.10% 0.25% 4.340 % diff. 84.9% 0.38% 223.8 Panel B: Regression results (1) (2) (3) Baseline Full model Propensity score

matched sample Estimate p Estimate p Estimate p Intercept 0.053 0.000 0.072 0.000 0.103 0.001 AF advisor 0.007 0.025 0.006 0.075 0.010 0.012 AF advisor with industry expertise on −0.002 0.811 accounting −0.004 0.519 AF advisor with industry expertise on accounting × Target in high |Total Accruals| industry 0.019 0.085 0.032 0.022 Target in high |Total Accruals| industry −0.004 0.306 −0.015 0.056 Cash offering 0.009 0.000 0.010 0.000 −0.004 0.437 Returning acquirer advisor −0.002 0.267 −0.002 0.328 0.004 0.419 ln Deal value 0.000 0.829 0.000 0.650 0.005 0.018 Number of acquirer advisors −0.001 0.627 −0.001 0.453 −0.004 0.267 Cross-border 0.004 0.031 0.004 0.205 −0.002 0.650 Family owned target −0.011 0.296 −0.012 0.246 −0.020 0.223 SOX 0.000 0.990 0.000 0.954 −0.040 0.068 Acquirer firm controls Yes Yes Yes Acquirer country controls Yes Yes Yes Year effects Yes Yes Yes Industry effects Yes Yes Yes N 13,917 13,917 1,660 p(F) 0.000 0.000 0.000 R2 2.96% 3.10% 6.96%

Table 5 Offer premium Panel A of this table reports the average offer premium partitioned by the type of advisor. Panel B shows the regression analysis of offer premium. The dependent variable is the offer premium defined as (the ratio of the bid price per share to the target’s closing stock price 4 weeks prior to announcement – 1) × 100. The bid price is the winning bid in a successfully completed takeover or otherwise the last withdrawn bid in an unsuccessful takeover. Acquirer firm controls are the log values of the acquirer size and B/M, the acquirer stock momentum and volatility, and the US acquirer dummy. Acquirer country controls are the country characteristics for the acquirer defined in table 1. The other explanatory variables are also defined in table 1. ln denotes the logarithm value of a variable and N is the number of observations. F is the F-statistic for the model specification and p(F) is the corresponding p-value. R2 is the R-squared. Model 3 uses IV estimation to control for the endogeneity of the AF acquirer advisor variable. All the models are pooled cross-sectional models with clustered standard errors robust to within acquirer and year correlation (Rogers 1993) and heteroskedasticity-adjusted (White 1980). Panel A: Descriptive N Mean S.D. t statistics Full sample: Accounting firm advisor 84 22.3% 2.8% 8.1 Investment bank advisor 5,316 29.7% 0.4% 72.8 % diff. −24.7% 2.8% −8.9 Panel B: Regression results (1) (2) (3) Industry expertise Baseline 2SLS on accounting Estimate p Estimate p Estimate p Intercept 0.306 0.000 0.304 0.000 0.310 0.000 AF advisor −0.053 0.066 −0.046 0.162 −0.087 0.088 AF advisor with industry expertise on −0.023 0.696 accounting AF advisor with industry expertise on accounting −0.113 0.057 × Target in high |Total Accruals| industry Target in high |Total Accruals| industry 0.061 0.039 0.062 0.036 0.062 0.006 Unlisted target −0.157 0.000 −0.156 0.000 −0.157 0.000 Returning acquirer advisor 0.007 0.514 0.007 0.514 0.007 0.408 ln Last year's total deal value of acquirer −0.004 −0.004 −0.004 advisors 0.033 0.033 0.028 Financing required 0.028 0.029 0.028 0.028 0.028 0.003 Family owned target −0.032 0.759 −0.032 0.760 −0.033 0.633 ln Deal value 0.000 0.988 0.000 0.987 0.000 0.946 Number of acquirer advisors −0.023 0.000 −0.023 0.000 −0.023 0.000 Acquirer firm controls Yes Yes Yes Acquirer country controls Yes Yes Yes Year effects Yes Yes Yes Industry effects Yes Yes Yes N 5,400 5,400 5,400 p(F) 0.000 0.000 0.000 R2 7.57% 7.57% 7.55%

Table 6 Deal completion rate Panel A of this table reports the frequency of withdrawn deals partitioned by the advisor type for the full sample and the PSM sample. Panel B shows the logit regression analysis of deal withdrawal. The dependent variable Withdrawn takes the value of 1 if the deal offer is withdrawn by the acquirer and 0 otherwise. Acquirer firm controls are the log values of the acquirer size and B/M, the acquirer stock momentum and volatility, and the US acquirer dummy. Acquirer country controls are the country characteristics for the acquirer defined in table 1. The other explanatory variables are also defined in table 1. ln denotes the logarithm value of a variable and N is the number of observations. p(Wald Χ2) is the p-value of the Wald Χ2-test for model specification. Pseudo R2 is the pseudo R-squared. Model 2 is based on the paired sample matched by the propensity score estimated with Model 3 in table 3. All the models are pooled cross-sectional models with clustered standard errors robust to within acquirer and year correlation (Rogers 1993) and heteroskedasticity-adjusted (White 1980). Panel A: Descriptive N Mean S.D. t statistics Full sample: Accounting firm advisor 880 0.11% 0.11% 1.0 Investment bank advisor 13,716 7.01% 0.22% 32.2 % diff. −98.4% 0.25% −400.2 Propensity score matched sample: Accounting firm advisor 880 0.11% 0.11% 1.0 Investment bank advisor 880 1.48% 0.41% 3.6 % diff. −92.3% 0.42% −218.5 Panel B: Regression results (1) (2) Full sample Propensity score matched sample Estimate p Estimate p Intercept −1.802 0.023 −3.510 0.280 AF advisor −3.234 0.001 −2.731 0.000 Target in high |Total Accruals| industry −0.327 0.321 Unlisted target −1.413 0.000 −1.647 0.000 Returning acquirer advisor −0.051 0.657 −0.279 0.672 ln Last year's total deal value of 0.016 0.297 0.044 0.677 acquirer advisors Family owned target −0.490 0.467 ln Deal value 0.418 0.000 0.738 0.004 Number of acquirer advisors 0.043 0.378 −1.151 0.286 Acquirer firm controls Yes Yes Acquirer country controls Yes Yes Year effects Yes No Industry effects Yes No N 14,596 1,760 p(Wald X2) 0.000 0.000 Pseudo R2 15.83% 24.53%

Table 7 Repeated use of accounting firm advisors by acquirers Panel A of this table reports the frequency of deals advised by accounting firms and by investment banks, conditional on the bidder using an accounting firm advisor previously. Panel B shows the results of the logit regression for the expanded advisor choice analysis. The dependent variable AF advisor takes the value of 1 if the acquirer has chosen an accounting firm advisor in the M&A deal, and 0 otherwise. Deal controls are all the deal- related variables included in table 3. Acquirer firm controls are the log values of the acquirer size and B/M, the acquirer stock momentum and volatility, and the US acquirer dummy. Acquirer country controls are the country characteristics for the acquirer defined in table 1. The other explanatory variables are also defined in table 1. ln denotes the logarithm value of a variable and N is the number of observations. p(Wald Χ2) is the p-value of the Wald Χ2-test for model specification. Pseudo R2 is the pseudo R-squared. All the models are pooled cross-sectional models with clustered standard errors robust to within acquirer and year correlation (Rogers 1993) and heteroskedasticity-adjusted (White 1980). Panel A: Descriptive statistics N Mean S.D. t Conditional on Prior experience using

AF advisor = 1: Accounting firm advisor 880 31.3% 1.56% 20.0 Investment bank advisor 13,716 10.0% 0.26% 39.1 % diff. 211.5% 1.58% 133.5 Panel B: Regression results (1) (2) Baseline Returning acquirer advisor Estimate p Estimate p Intercept −0.628 0.259 −0.723 0.205 Prior experience using AF advisor 0.880 0.000 0.997 0.000 Returning acquirer advisor −0.475 0.000 Deal controls Yes Yes Acquirer firm controls Yes Yes Acquirer country controls Yes Yes Year effects Yes Yes Industry effects Yes Yes N 14,596 14,596 0.000 0.000 p(Wald X2) Pseudo R2 25.61% 25.50%