The Role of Deal‐Level Compensation in Leveraged Buyout Performance

Sven Fürth1 | Christian Rauch2| Marc Umber3

September 2013

Abstract

This paper analyzes the influence of deal‐level compensation structures for buyout fund managers on the performance of Leveraged Buyouts. We use a unique and hand‐collected data set of 93 LBO deals in the United States over the period 1999‐2008 for which we can distinguish between different fund‐ and deal‐level compensation components that fund managers receive. Our results show that higher deal‐level compensation is negatively related to deal‐level performance. A one percent increase in the fees‐to‐proceeds ratio lowers the return to LPs by 127 percentage points. We also document that the occurrence of deal‐level fees does not depend on the structure of the fund‐level compensation structures, but instead on the profitability of the LBO target company and the historic performance of the buyout firm. These results are robust to changing market environments, characteristics of the LBO and restructuring activities in the target company, terms of the partnership agreements between investors and fund managers, fund structure and –profitability and different performance measures.

JEL classification: G23, G24, G34, G12, G15 Keywords: Private Equity, IPO, Insider Trading, Buyout

1 Goethe University Frankfurt, Finance Department, House of Finance, Grueneburgplatz 1, 60323 Frankfurt am Main, Germany. Phone: +49‐(0)69‐798‐33727. E‐mail: [email protected]‐frankfurt.de. 2 (Corresponding Author) Goethe University Frankfurt, Finance Department, House of Finance, Grueneburgplatz 1, 60323 Frankfurt am Main, Germany. Phone: +49‐(0)69‐798‐33731. E‐mail [email protected]. 3 Frankfurt School of Finance & Management, Sonnemannstrasse 9‐11, D‐60314 Frankfurt am Main, Germany. Email: [email protected]

For valuable comments and suggestions we would like to thank Michael Grote, Günter Strobl, as well as participants at the 2012 Southern Finance Association Annual Meeting, the 2012 Financial Management Association Europe Annual Meeting, the Frankfurt School of Finance Brown Bag Seminar, the Goethe‐University Brown Bag Seminar, and the UniCredit Research Workshop. Sven Fürth gratefully acknowledges the financial support of “Vereinigung der Freunde und Förderer der Goethe Universität Frankfurt” and of “Commerzbank Stiftung Frankfurt”. All remaining errors are our own. 1

Which incentive structures should principals choose for agents to maximize their returns? This question is at the core of many agency problems and has therefore been tackled in many different settings. Classic agency theory states that more performance‐linked compensation leads to better performing agents, ultimately resulting in a higher return to the principal

(Jensen and Meckling, 1976; Fama, 1980; Fama and Jensen, 1983a and 1983b; Jensen and

Ruback, 1983; Jensen, 1986). Empirically, this finding has been documented in various settings

(e.g. Agarwal, Daniel and Naik, 2009). This paper adds to this body of literature by analyzing an under‐researched compensation structure which unique for one specific asset class: deal‐ level compensation for General Partners (GPs) in Leveraged Buyouts (LBO). What makes this compensation structure unique and why would analyzing it help expand the knowledge about the link between compensation and performance?

In LBO funds, GPs are commonly paid based on the overall performance of the fund, and for their general fund management services. The former is usually referred to as “Carried

Interest” or “Carry”, the latter is known as the “management fee”. The carry is a fixed percentage of the return that GPs generate for the fund investors (known as Limited Partners,

LPs), whereas the management fee is a percentage of the fund volume, paid out annually to the GPs. In addition to these fund‐level fees, some LBO deals exhibit an additional compensation component for the GPs on deal level, i.e., Termination Fees, Transaction Fees, as well as deal‐level Management Fees. Deal‐level management fees are paid for monitoring and general advisory services the buyout firm provides for the portfolio company. Transaction fees are paid specifically for advisory on corporate transactions as part of the LBO restructuring process in the portfolio companies, e.g., recapitalizations or Mergers and Acquisitions (M&A).

Termination fees are paid in connection with the exit of the buyout fund.

These deal‐level fees exhibit a set of very interesting features, making them suitable to obtain a better understanding of the relationship between incentivization and performance. First, the

GPs as agents choose the magnitude and structure of the deal‐level fees without explicit acknowledgment. The LPs as principals have little say in whether or not these fees are being paid out to the GPs and/or in which magnitude they are being paid out. This feature is unique in the sense that agents rarely may choose their own compensation without approval or oversight by the principal. Second, deal fees are paid to the GP by the portfolio companies. 2

Even though deal‐level fees are linked to certain services rendered by the GP, the portfolio companies compensate their owners for advising them. Third, deal‐level fees are not linked to the adequate performance measure. The payment of the fees depends on actions taken by the

GP regardless of the return these actions yield for the LPs. This is especially interesting since

GPs are already compensated for general management services through the fund‐level management fee. An additional fee for non‐performance related actions comes as a surprise.

Given these unique features, we believe there are three major reasons why these fees should influence the performance of the LBOs. First, the fact that the portfolio companies’ cash is used to fund the fees has a direct influence on the performance of the LBO: instead of compensating the GPs with this cash, it could have been distributed to the LPs as a cash payout, directly boosting their rate of return. Second, deal‐level fees could be justified by the creation of additional incentives for the GP to perform well in the restructuring activities and value creation in their LBOs. After all, being paid money for a task increases the willingness to perform well (Holmstrom and Ricard I Costa, 1986). For example, a GP who is being paid for monitoring will do so more closely and diligently than a GP who is not compensated for her monitoring activities. In that sense, deal‐level fees should create strong positive incentives for the GPs to perform well, ultimately boosting the performance for the buyout deals. Third, deal‐level fees might also create an adverse effect: by receiving lump‐sum payments from their portfolio companies the incentives of GPs and LPs become misaligned. As explained above,

GPs receive a major component of their compensation through Carry. By receiving deal‐level fees independently of their fund’s performance, GPs might be able to disentangle their income from the income generated for the LPs. The resulting agency costs could lead to lower LBO performance especially, since GPs receive the deal‐level fees without necessarily having to create value in the deals. For example, transaction fees are not tied to the success of a certain

M&A performance, rather they are tied to whether or not M&A transactions are completed.

This also applies to monitoring fees. They are paid out regardless of whether or not the GPs diligently fulfill their board member duties.

We believe that the fees’ unique structure and their interesting implications make them most suitable to advance the knowledge about the link between incentivization in principal‐agency relationships and performance. Consequently, it is the main goal of this paper to answer the 3 questions: how do deal‐level fees in LBOs influence the performance of these deals? To find an answer to this research question we use a data set of 93 leveraged buyout deals over the period 1996 to 2008 in the United States. Although this number represents only a fraction of the total U.S. leveraged buyout market in this period, our sample is highly homogenous and contains all necessary information needed for the purposes of our analysis. For every LBO, we have the full GP compensation, both on fund‐ as well as on deal‐level. On fund‐level, this includes the management fees, preferred returns, and performance‐linked Carried Interest. On deal‐level, we obtain all portfolio company‐specific management fees, transaction fees, and termination fees. To measure the relationship between compensation and performance, we also obtain the main performance metrics on fund‐ and deal‐level. These are the Internal Rate of Return (IRR) and Cash Multiple on fund level (annually throughout the duration of the funds, as well as ex‐post numbers after the fund closings), as well as deal‐level IRR and cash multiple for each LBO. We choose these performance measures based on a broad body of literature in this field which has established the IRR and the Cash Multiple as the most widely used and relevant performance metrics in Private Equity.

We tackle our main research questions by running a simple and clear‐cut two‐step analytical framework. In a first step, we analyze the different fee structures in a univariate setting. We analyze when the fees are being paid, what their magnitudes are and who receives them. Most importantly, we question whether deal‐level fees follow a certain pattern, i.e. whether or not the occurrence of deal‐levels depends on certain factors. Since LBO returns can be driven by a plethora of influence factors other than the fund manager’s compensation, we have to carefully craft a set of variables controlling for these factors. We do so by compiling proxy variables for three different groups of possible influence factors, in line with the findings of prior literature. The first group contains all restructuring activities that buyout firms engage in after they acquire a portfolio company and start to increase the enterprise value. The second group contains all buyout fund‐ and firm characteristics that can influence the overall performance. Finally, the third group contains all portfolio company‐specifics variables which might drive the LBO performance. These variables allow us to run a detailed multivariate analysis and to perform a number of robustness tests that support the importance of our results.

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We find a strong heterogeneity in deal‐level fees across LBOs despite a surprising homogeneity of fund‐level terms across GPs. Ex ante, we find no clear pattern in deal‐level fees based on deal characteristics at the time of the LBO. However, we document a significantly negative impact of deal‐level fees on LBO performance – supporting the hypothesis of an adverse effect of deal‐level fees. Surprisingly, the univariate descriptive statistics suggest that LBOs with deal‐level fees are more profitable. However, after controlling for fund terms and other deal characteristics a persistently negative relationship appears. This adverse effect neither is compensated by preferred return on fund level nor by a transaction fee rebate.

We test a multitude of variations in our analysis both for measurement and for the regression method. Our findings are not driven by the type of performance measure, i.e., IRR and cash multiple, and they persist in an ordinary regression setup as well as in a two‐stage regression where we take endogeneity into account. Our results also hold when we measure deal‐level fees as a percentage, in gross payments or through a binary variable.

The paper is structured as follows. Part 1 contains a detailed explanation of the literature and our four value creation hypotheses. Part 2 describes the data set, followed by a description of the methodology and the results are presented in Part 3. All robustness tests are discussed in

Part 4 concludes, Part 5 concludes.

1 Background on Private Equity Fees

1.A Compensation Structures – Fund Level Fees

There are two different layers of fees in Private Equity: deal‐level and fund‐level fees. The standard compensation package for the fund managers (the “General Partners”, or GPs) in almost all types of Private Equity is comprised of an annual fund‐level Management Fee and a performance‐based fee called “Carried Interest”. The fee conditions are written down in the

Partnership Agreement, which is the contract governing the structure of a Private Equity fund, along with all duties and obligations of the GPs and fund investors (the “Limited Partners”, or

LPs).1 Management Fees are paid by the LPs to the GPs for general fund management

1 The broadest and most general overviews of partnership term structures and compensation schemes are provided by Fleischer (2008) and Litvak (2009). Fleischer (2008) provides a very general overview of the Private Equity fund terms, especially from a 5 services. Their magnitude is measured as a percentage of the Dollar‐volume of the money invested in the fund. A 2012 Preqin survey shows2 that the Management Fee of U.S. buyout funds is set at 1.5‐2.5 percent of the fund volume. The fees are usually calculated on an annual basis and paid out pro rata on a quarterly or annual basis. The GPs receive the Management

Fee over the whole fund lifecycle3, disregarding the actual performance of the fund. At times, the Management Fee is only paid out during the period in which the fund can draw down on committed capital. This stands in contrast to the performance fee, the Carried Interest (or short

“Carry”). It is meant to reward GPs for financially successful transactions by letting them participate in the profits. Consequently, the Carried Interest is measured as a percentage (as

Preqin shows almost always 20 percent)4 of the generated profits. A most simple example of a

Carried Interest payment would be to pay out 20 of the profits from a single transaction to the

GPs. The profits (net, disregarding costs) are calculated as the sale price of a portfolio company minus all outstanding debt used to finance the transaction minus the drawn capital from the fund investors to purchase the company. However, in reality the Carried Interest payments are usually structured in a more complex manner. As graphically shown in Panel A of Figure 1, the payment depends on the profitability of the fund. Instead of splitting all deal‐ level distributions beyond the investor capital repayment on a 80/20 basis, the Carried Interest is usually only distributed to the GPs after the fund as a whole has reached a certain profitability, measured as the fund‐level Internal Rate of Return (IRR). This threshold level of profitability is referred to as “Hurdle Rate” or “Preferred Return”. Beyond this rate, the GPs begin receiving a share of their Carried Interest, which is only fully reached until the so called

“Catch‐Up Zone” has been cleared. It is only after the IRR has cleared this threshold that the

GPs receive their full share of the profit split.

(Figure 1)

Structuring fund manager compensation in this way is meant to alleviate agency costs by aligning the interests between LPs and GPs. GPs are strongly incentivized to create performance early on in a fund’s lifetime. Also with regard to our hypothesis development regulatory perspective and in the light of tax considerations; Litvak (2009) provides a very in‐depth overview of venture capital fund terms, also regarding the distribution waterfall. 2 See Preqin 2012 Private Equity Fund Terms Advisor, Preqin Ltd., London, U.K. 3 Sometimes this is paid only over the period in which the fund actually makes investments. 4 As also shown in the Preqin 2012 Private Equity Fund Terms Advisor, Preqin Ltd., London, U.K. 6 described below in section 2.C, it should be noted that these fund‐level compensation structures are also featured in many other alternative investment asset classes, especially hedge funds. The hedge fund managers are also paid a fixed annual management fee and a performance‐based fee, which is only paid out on the condition of the fund’s profitability.

1.B Compensation Structures – Deal Level Fees

Next to the fund‐level fees, GPs of buyout funds also receive so called deal‐level fees. Whereas the aforementioned fund‐level fees are employed by every Private Equity type (Venture,

Mezzanine etc.), the deal‐level fees are a special occurrence in buyout funds. There are three kinds of deal‐level fees: Transaction Fees, Advisory Fees and Termination Fees. The two major differences between deal‐level and fund‐level fees are that first, the volume and payoff structure of fund‐level fees is based on the features of the fund, especially the fund volume and its profitability. In contrast, deal‐level fees solely depend on each single buyout deal a fund engages in and are almost totally unrelated to the features of the fund. Second, whereas fund‐level fees are paid from the LPs to the GPs, the deal‐level fees are paid by the portfolio companies to the GPs.

Transaction Fees are paid to compensate GPs for their services in any kind of corporate transaction a portfolio company of their fund engages in. These transactions could be the acquisition of the portfolio company along with its recapitalization and/or possible other corporate restructuring activities upon the entry of the buyout fund. Any subsequent transactions, such as further recapitalizations, debt or equity issuances and all M&A transactions are rewarded with the payment of a designated Transaction Fee. This means that

Transaction Fees are always paid out in connection with covered corporate transactions.

Advisory Fees are paid to compensate the buyout fund managers for their general advisory and monitoring functions they perform while invested in a portfolio company. To create value in their investments, GPs actively restructure the operating business, financing structure, and strategic direction of their portfolio companies. Next to advising the management board of the companies, they also have board seats and actively monitor the implementation and success of their restructuring activities. Since the GPs constantly advise and monitor their portfolio companies throughout the duration of the investment, the Advisory Fees are paid on an annual or quarterly basis. The advisory and monitoring relationship between GPs and the 7 portfolio companies are governed by advisory contracts, in which the Advisory Fee compensations are also set forth. Finally, when the portfolio company is exited and the buyout fund sells the shares and gives up the board seats, the advisory contract is also terminated. In case these contracts are terminated before their actual end dates, a contract Termination Fee has to be paid to the GPs. So, whereas the Advisory Fee is paid on an annual or quarterly basis over the whole duration of the investment, and the Transaction Fees are paid when certain corporate transactions occur, the Termination Fee is always paid out at the end of the investment period when the portfolio company is exited. A typical payoff structure is graphically shown in Panel B of Figure 1. The Figure shows the chronology of a typical buyout deal, from start (t0) to exit (t3). Fund‐level Management Fees are paid independently of the deal, which is why they continue to be paid after the exit of the deal. The Carried Interest is only paid out in connection with distributions being made from the investments to the LPs

(assuming here that the fund has already cleared the preferred return and the catch‐up zone).

The Advisory Fee is paid constantly over the duration of the deal. The Transaction Fee is paid out in connection with transactions (here, the deal itself and one subsequent hypothetical refinancing). The Termination Fee is paid out upon the termination of the advisory contract, which always happens at the end of a deal.

These three deal‐level fees allow the GPs to substantially increase their compensation from buyout deals. Since GPs receive these fees regardless of the performance of the deals, and because they are paid for by the portfolio companies and might therefore financially constrain the companies, we believe these fees hold interesting implications for the performance of buyout deals. We will further elaborate on these implications and our thoughts on the influence they have on the performance in section 2.C below.

1.C Literature Review and Hypothesis Development

The main research question of this paper is: how do deal‐level fees influence the performance of LBO deals? As described in sections 2.A and 2.B, deal‐level fees are only one component of the total pay GPs receive in buyouts, next to fund‐level fees. So, in order to derive a hypothetical assumption about the direction of influence deal‐level fees might have on deal performance, we should consider both types of compensations. The question of what influence fund manager compensation schemes have on the performance of their investment funds is 8 not entirely new to academic research. For Private Equity, Gompers and Lerner (1999) provide the first and very general overview of compensation schemes and their implications, by focusing on the U.S. venture capital sector. They document that the compensation structure is set out in the partnership agreement at the inception of the fund, does not get changed or adjusted during the fund’s lifecycle, and usually includes fixed and performance‐linked fees.

Empirically, they do not find any relationship between a fund’s performance and the compensation structure; however, they do find that funds of younger and more inexperienced

GPs tend to have lower performance‐linked fees and higher fixed management fees. Covitz and Liang (2002) focus on the Private Equity asset class as a whole. They are the first to analyze preferred returns as an important extension to classic GP compensation based solely on Carry and the management fee. They find that even though preferred returns have some contractual benefits by facilitating monitoring and solving liquidity problems by forcing GPs to exit investments more quickly, they might also enhance the risk taking of GPs to get to higher returns sooner. Even though they do not focus on actual returns, their result regarding risk‐taking can lead us to believe that preferred returns might also lead to higher returns in these funds. Conner (2004) tests the effects that different contractual terms in the partnership agreements might have on a Private Equity fund’s profitability. Predominantly, he focuses on management fees versus Carry. Using a hypothetical example, he shows that preferred returns do not impact the return, whereas a higher Carry might actually hurt the return of the fund.

Robinson and Sensoy (2013) perform a long‐term study of the relationship certain fund terms have on absolute and relative fund performance in the Private Equity industry. As compensation, they analyze management fees and Carry. Their study finds that both components do not influence net‐of‐fees fund performance. Their interpretation of the finding is that GPs which receive higher compensation also earn higher returns for their investors. The only two papers which focus on deal‐level fees in addition to fund‐level fees are Metrick and

Yasuda (2010) and Choi, Metrick and Yasuda (2013). Next to providing an extensive analysis of Private Equity compensation structures, both papers analyze the determinants of compensation revenue streams for GPs. The papers distinguish between performance and non‐performance linked compensation components and show that the broad majority of compensation for GPs stems from performance‐insensitive components and that buyout managers use past success to increase the size of their future funds, which in turn leads to higher compensation revenues. So even though they make an indirect connection between 9 performance and compensation, they do not necessarily explain how compensation affects the

GPs in their performance.

So, even though there is a wide body of literature dealing with compensation schemes in

Private Equity deals, it seems interesting that there is no clear‐cut result regarding the influence compensation schemes – especially performance‐ and non‐performance‐linked components – have on fund manager performance. This is especially interesting since the interpretation of the fund level fees might seem straightforward: although the management fee provides the GPs with some cash inflow, the major component of their total compensation is represented by the Carry. In order to boost their income, GPs therefore have to generate returns for LPs through profitable investments. Generating Carry is also important for another reason: GPs use their historic fund performance as the main argument in fundraising processes with investors in future funds. Stronger performance‐based compensation should therefore be responsible for a better performance, a result in line with general agency cost theory (Jensen and Meckling, 1976; Fama, 1980; Fama and Jensen, 1983a and 1983b; Jensen and

Ruback, 1983; Jensen, 1986). For alternative investment funds, this result is supported by

Agarwal, Daniel and Naik (2009) who link managerial incentives in Hedge Funds to the funds’ performance. They develop a special proxy for fund managers’ compensation sensitivity in relation to the funds’ NAV. Specifically, they measure the change in Dollar‐value of total fund manager compensation induced by a 1% change in the fund’s NAV. Their results show that this “delta measure” of performance is positively linked to fund performance. The paper therefore suggests that a higher alignment of investor and fund manager incentives should lead to higher performance. However, as discussed above, this result is not clearly supported by the body of literature on Private Equity.

Additionally, the existing body of literature does not offer a direct indication of how deal‐level fees might affect the LBO performance. We believe that two effects might be contradictory in their effect on performance. First, it might be suspected that deal‐level fees create additional incentives for GPs to perform well in the restructuring activities and value creation in their deals. After all, being paid money for a task increases the willingness to perform well

(Holmstrom and Ricard I Costa, 1986; Agarwal and Ben‐David, 2012). For example, a GP who is being paid for monitoring will do so more closely and diligently than a GP who is not 10 compensated for her monitoring activities. In that sense, deal‐level fees should create strong positive incentives for the GPs to perform well, ultimately boosting the performance for the buyout deals. However, deal‐level fees might also create a contradictory effect: by receiving lump‐sum payments from their portfolio companies which are not – or only in a limited way – passed on to the LPs, there is a misalignment between the incentives of GPs and LPs. As explained above, GPs receive a major component of their compensation through Carry. By receiving deal‐level fees independently of their fund’s performance, GPs might be able to disentangle their income from the income generated for the LPs. The resulting agency costs should lead to a lower performance. Especially, since GPs receive the deal‐level fees without necessarily having to create value in the deals. For example, transaction fees are not tied to the success of a given M&A performance, they are only tide to whether or not there is a M&A transaction. The same goes for the monitoring fees: these sums are paid out regardless of whether or not the GPs diligently fulfill their board member duties. In other words: deal‐level fees represent a significant component of GP compensation which is neither tied to any deal performance, nor to the returns generated for the LPs. Consequently, it might be suspected that the existence of deal‐level fees decreases performance, as opposed to boosting it. These effects, jointly with the effects of the fund‐level fees, will be investigated in more detail in section 3 as described below.

2 Data and Methodology

2.A Data Collection

Our data collection is based on four steps. First, we identify the buyout transactions along with the buyout investors. Second, we identify all fund‐ and deal‐level fees used as compensation in these deals. Third, we collect the data used to calculate our LBO performance proxies. And fourth, we add information to control for any other potential influence factor on

LBO performance. Our core sample of buyout transactions contains 224 buyout deals that went public in an Initial Public Offering (IPO) at the New York Stock Exchange (NYSE) or the

NASDAQ between 1999 and 2008. We restrict our sample to IPO companies for information disclosure and transparency reasons. The data necessary for our analyses is obtained from filings with the Securities and Exchange Commission (SEC) during the course of the IPO. Since this information is made publicly available by the SEC, we are able to collect and use otherwise proprietary and classified data about the portfolio companies and the structures of 11 the buyout deals. We are well aware that this rigid data collection might induce a sample selection and survivorship bias. As a consequence, our results might not be representative for the entire asset class of private equity. Schmidt, Steffen and Szabó (2010), for example, show that only the most successfully buyouts are taken public. However, given that the IPO filings are the only conduit for this level of detail used in our analyses, we do not see a possibility to either adequately control for this bias or to use different sources. Given this trade‐off between representativeness and unprecedented buyout insight, we opt for the latter.

All IPO data is taken from the Thomson Reuters SDC database. To identify buyout deals, we use the “buyout flag”‐indicator provided by Thomson Reuters. This variable shows which company had a non‐venture Private Equity investor at the time of the IPO. Out of roughly

3500 IPOs in the U.S. during our observation period, we obtain 450 buyout‐backed IPOs in our observation period. To validate our data, we manually analyze the shareholder structures of all buyout‐backed companies based on the information given in the firms’ stock offering prospectuses (S‐1 and 424‐B) filed with the SEC and available through the EDGAR website.

All buyout investors are identified on a case‐by‐case basis. We manually analyze every institutional shareholder listed in the filings to identify buyout firms and their funds to obtain a homogeneous and valid data set.

In a second step, we complement the buyout deal data with our main explanatory variables, i.e., the fees. We use two different sources for this data. The Preqin Fund Term and

Compensation database provides fee information on fund level. And, we use publicly available SEC filings by the portfolio companies to retrieve deal‐level information. All deal‐ level fees are taken from S‐1 filings of the portfolio companies prior to the IPO. These prospectuses discuss the investment of the buyout firm, and which transactions took place between the portfolio company and the buyout firms prior to the IPO. The SEC considers this to be material information for any future shareholder of the post‐IPO corporate entity, and it is therefore to be disclosed in the S‐1 filing. We identify the fee information by going through each S‐1 filing (as well as through the amended 424B updates of the S‐1 filings) to determine transaction advisory, management advisory and termination fees on deal‐level. Usually, the management and transaction fees are mentioned in the “Certain Transactions” sections of the prospectuses, whereas the termination fee is usually mentioned in the “Use of Proceeds” 12 section. Fortunately, the prospectuses also explicitly mention if the portfolio company does not pay any fees (or not pay a specific fee) to the buyout investors. We therefore do not run the risk of having biased data through misreporting. There are only 14 companies for which we cannot explicitly identify the deal‐level fees, which is why we reduce our initial sample of 224 portfolio companies to 210.

All fund‐level fee information is taken from Preqin. It contains detailed data on all GP compensation used in all funds invested in the portfolio companies in our data sample. Preqin provides the volume of Carried Interest, Management Fees, Preferred Returns, as well as transaction fee rebates. Additionally, the data contains the absolute volumes of all fees paid by the LPs to the GPs in any given year during the fund duration. Preqin generates this data through the Freedom of Information Act. Among other things, the Act states that the usage of public funds must be made available to the general public. Since many buyout funds have public pension funds as investors, the fund terms must be made publicly available. However, the consequence of retrieving data through the FIA means that the terms for some of the funds in our data set are not disclosed. Our sample of 210 buyout deals, for which we have deal‐level fee information, is further reduced to 134 deals, for which we have both fund‐ and deal‐level data. We match the data on the buyout fund level. In case several funds are invested in a portfolio company, we use the data of the lead fund, i.e., the fund owning the largest ownership stake.

In the third step we collect all data information necessary to calculate the performance of the deals. As explained in more detail later in the paper, we use the cash flow‐based performance measures Internal Rate of Return (IRR) and Cash Multiple (CM). Both are commonly used in the buyout industry to measure deal‐ and fund‐level performance. IRR and CM are based on cash in‐ and outflows of the investments. We manually collect these cash flows from the S‐1

IPO prospectuses (all cash outflows, i.e., the investments in the IPO companies, as well as the cash inflows through sales at the IPO), and from mandatory S‐4 post‐IPO insider share sale filings made with the SEC and available through SEC EDGAR (for all cash inflows through post‐IPO share sales). Matching all cash in‐ and outflows on deal level allows us to determine the exact cash flow‐based performance of each deal.

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These previous steps leaves us with a set of 134 LBO transactions that went public on NYSE or

NASDAQ in the period between 1999 and2008. For these 134 deals, we have all fund‐ and deal‐level fees that the GPs received as part of their compensation. We are also document all relevant fund‐level terms governing the payoff distributions, hurdle rates, fee rebates, management fees, and carried interest. In a final step, we complement our sample with a number of additional databases to obtain control variables for our multivariate analyses and to run robustness tests to validate our results. First, we use the Thomson ONE Banker data for all

Mergers and Acquisitions (M&A) transactions that the IPO companies were engaged in during the pre‐ and post‐IPO period (while the buyout funds was invested). Second, we use

Standard & Poor’s COMPUSTAT data for all balance sheet and P&L information on the IPO companies. Third, we use the U.S. GAO (Government Accounting Office) Financial

Restatement Database for information on financial restatements. Fourth, we use information on the companies’ liabilities structure given in the Standard & Poor’s LPC Dealscan data base on syndicated loans. Information on the IPOs themselves, such as date, volume, and pricing details are taken from the Thomson Reuters SDC data base. Also, we use the aforementioned

S‐1 IPO prospectuses (and the 424B amendments) to collect additional variables which are not available in other databases, such as shareholder, management and board structures, details on the structure of the buyout investment (investment periods etc.), and pre‐IPO financial and accounting information on the firm which might not be available in COMPUSTAT. This information is manually extracted from the prospectus and merged on the IPO‐firm‐level to the aforementioned data sets.

2.B Summary Statistics

Table 1 gives an overview of deal‐level fees in our sample. Overall, 57 percent of all portfolio companies pay deal‐level fees to the GP. The most prominent type of fee is the management advisory fee with almost 55 percent of all LBOs. 39 percent of all firms pay transaction fees and only 24.7 percent pay termination fees. The volume of fee payments differs even more drastically. On average, $ 10.8 mil. is paid out in deal level fees across our sample. The median and standard deviation indicate that the distribution is heavily skewed with few, large cases.

As deal‐level fees are payments that could be transferred to the fund (and ultimately to the

LP) but instead are paid out to the GP, we calculate the ratio of deal‐level fees to the total proceeds that actually are paid to the fund. Economically, this measure reflects how much fee‐ 14 based compensation GPs extract for themselves in relation to what they generate for their principal. The statistics show an overall average of 2.41 percent of total proceeds. Considering that 43 percent of all portfolio firms do not pay deal‐level fees, 2.41 seems a substantial fraction – which is paid in addition to the fund‐level fees. Again, median and standard deviation indicate that there are few large observations. GPs in the top 10 percentile even demand a fee‐to‐proceeds ratio of more than 6.9 precent (figure not reported). Table 1 also shows that the total deal‐level fees are mainly driven by the management fees which comprise

1.36 percent on average and has a standard deviation of 5.94 precent. The table also reports the ratio of deal‐level fees to total enterprise value (TEV) of the portfolio company and the estimated carried interest. Especially the latter documents the economic significance of deal‐ level compensation.

(Table 1)

Additional summary statistics are shown in Table 2. In contrast to the very heterogenous deal‐ level fees, the fund level terms are rather homogenous. The average fund management fees are

1.83 and the deviation of its distribution is very low with 0.24%. Also, the preferred return is distributed very narrowly. Either funds have no preferred return or they have a rate around 8 percent. Little more variation is shown in the transaction rebate. Roughly 23 percent of all funds have a zero rebate and the rest of them shows rebates between 50 and 100 percent. The strongest conformity can be seen in the carried interest which is literally the same in all fund of our sample. This is a surprising results with regards to GP compensation: We find very strong heterogeneity on deal‐level, yet. almost all funds show very similar fund‐level terms.

Table 3 contains selected summary statistics on our sample of 224 buyout‐backed IPOs.

Starting in Panel A, the average portfolio company had total assets in the amount of 608 million US‐Dollars at the time of the IPO, revenues of 445 million US‐Dollars, a slightly negative net income of ‐10.6 million US‐Dollars and, consequently, a negative return on assets of ‐17.9 percent. Based on these numbers, the average portfolio company of a buyout fund seems to be of medium size with a slightly negative profitability at the time of going public.

However, comparing mean and median numbers shows that there is a degree of heterogeneity in the data set. Median asset and revenue numbers are smaller and profitability is higher as compared to average numbers. Apparently, the mean is driven by few large and more 15 unprofitable companies, a finding also supported by the large standard deviations of the numbers. Although this result is not surprising, given that buyout firms are known to engage in single large transactions, we will thoroughly control for this heterogeneity in all further analyses.

(Table 2)

Looking at the characteristics of the buyout deals itself, we see that the average deal is syndicated with 1.7 private equity investors, it has more than one investment round, all buyout investors jointly purchase the majority of the ownership rights in the portfolio companies (71 percent), and already divest parts of their shareholdings before going public

(48.1 percent shareholdings at the time of the IPO). We also see that the management of the portfolio company receives parts of the shares upon the buyout (10.3 percent) and that the buyout funds exercise control in the portfolio companies through the board of directors by holding roughly a third (2.9 of 8.8 seats overall) of the board seats. Overall, these numbers are in line with “typical” buyout deals found in practice: A syndicate of buyout funds purchases controlling stakes in a portfolio company, reduces agency costs by awarding the portfolio company’s management shareholdings, divests parts of their ownership before the actual exit through the IPO and controls the company through the board.

Finally, Panel B of Table 2 reports summary statistics of the buyout investments and IPOs over time and across industries. First, we can see that the investments in the portfolio companies which went public between 1999 and 2008 date back to as early as 1993/1994. Again, our data is in line with prior research, showing that buyout companies tend to be invested for an average of 5‐6 years before an IPO (e.g., Kaplan, 1991; Strömberg, 2007). The numbers furthermore suggest that the investments and IPOs depend on economic boom and bust cycles, showing slight peaks in boom periods, such as 1999‐2000 and 2004‐2006, and slight troughs in bust periods, such as 1993‐1995, 2001 and 2008. This might be a first indication that buyout firms try to time the market to some degree, which will be further investigated in section 3 of the paper. Regarding the industries, we see that although the manufacturing and service sectors are dominant, buyout investments span across a wide variety of different sectors. 16

2.C Methodology

There are three pivotal methodological steps which have to be discussed here. First: how we calculate our main fee proxies and performance measures. Second: how we run our statistical analysis and specify our regression models. And third: how we perform the additional analysis.

In the first step we calculate our main proxy variables for compensation and performance measurement. As stated above, we use the total US‐Dollar volume figures for transaction, management, and termination fees on buyout deal level, as stated in the portfolio companies’

S‐1 filings. We use the absolute Dollar‐volumes of the fees in relation to the total proceeds generated by the deal. We classify all cash flows to the buyout fund (and, therefore, ultimately to the GPs and LPs) generated through each investment as a “proceed”. The cash flows are taken from two sources: the S‐1 filings (for e.g. dividends and pre‐IPO share transactions), and post‐IPO share sale data, such as Thomson M&A data (for share sales through one‐time M&A transactions), and SEC S‐4 insider trading data (for gradual exits with many smaller share sales). All proceeds are aggregated on deal level. We scale the fees by the proceeds for two major reasons: first, to obtain a comparable figure of the relative fee volume paid to the GPs across different deals of different size. Second, because the fees could hypothetically – if they were not paid out to the GPs as part of their compensation – also be paid as deal proceeds to the LPs. Comparing the fees to the remaining proceeds therefore shows what relative volume of cash is used as GP compensation as opposed to LP proceeds.

In the second step we run multivariate regression models to analyze the nature of deal‐level fees and to try identify whether certain drivers are able to explain the strong heterogeneity among them. We use OLS regression and test the impact of deal and fund characteristics at the time of the LBO. We use characteristics of the funds, the portfolio firms and the GP directly.

In the third step, we analyze deal‐level return measures to test the impact of deal‐level fees on the performance of LBOs. We run one model specification in three different settings. Using the identical set of explanatory variables, we try and explain three separate dependent variables: the IRR, the cash multiple, and the unlevered IRR following Acharya et al. (2012) to adjust for 17 the impact of leverage on the return. Next to our main explanatory variable, the ratio of deal‐ level fees to total proceeds, we use additional sets of explanatory variables to control for other possible influence factors on deal performance. To identify these explanatory variables, we rely on prior research which has established a variety of different drivers for buyout performance.

The arguably most important group of control variables is the buyout fund‐specific compensation structure. As discussed in part 2 of the paper, GPs are to a large degree compensated on fund‐level through management fees and performance‐based Carried

Interest. These factors therefore have to be controlled for when analyzing the deal‐specific compensation of GPs. Unfortunately, the carried interest for all funds in our sample is the same 20 percent, which is why we have to exclude carry from the regression. Next to the fund‐ level annual management fee, we also include the Preferred Return (or Hurdle Rate), as well as the Transaction Fee Rebate. These four factors are the most important aspects of the overall compensation structure in a buyout fund, which is why we include all four of them in our regression. All four variables are expressed in percentage values. The management fee is the percentage of the total fund volume, paid annually from the LPs to the GPs. The preferred return is measured as the percentage of fund‐level IRR which has to be reached before the

Carry is being paid out. Finally, the transaction fee rebate is measured as the percentage of deal‐specific transaction fees ‐ which are actually paid to the GPs by the portfolio companies ‐ which are paid out to the LPs to allow them to participate in this deal‐specific fee. Including these four variables allows us to fully account for all fund‐specific compensation structures which might influence the performance of the deals.

Of the six remaining groups of control variables, four groups directly control for the active value creation strategies employed by buyout funds in their portfolio companies, whereas the last two groups control for additional factors which have also proven to have an influence on buyout deal performance. It is of utmost importance that we control for all reasons which could impact deal performance other than the compensation structure to rule out that our results are biased by unobserved factors. The first four groups of control variables for active value creation are: (1) fundamental restructuring activities of buyout firms in their portfolio companies, (2) financial restructuring activities of buyout firms in their portfolio companies, 18

(3) cash draining of the portfolio companies through the buyout funds, and (4) market timing of the deals’ entry and exit times. As show in detail in Table 4, we employ a number of proxy variables for each of these groups. We base the selection of these proxy variables, just as the identification of the four value creation groups, on the existing literature. Based on Muscarella and Vetsuypens (1990), a large of body of literature has developed focusing on the kinds of fundamental restructuring activities buyout funds use to create performance through their investments. Based on Jensen’s and Meckling’s (1976) idea of the separation of ownership and control and Jensen’s (1989) idea of buyouts as a combination of financial restructuring and high‐powered incentives, Denis (1994), Phan and Hill (1995), Berger, Ofak and Yermak (1997) as well as Cotter and Peck (2001) show the influence buyout investments can have on the governance structure and agency costs of the portfolio companies. To control for these factors, we include a number of proxy variables for the portfolio companies’ governance structures, incentive schemes, and agency costs, as can be seen in Table 4. Fundamental restructuring activities in buyout deals beyond governance interventions are documented by Muscarella and Vetsuypens (1990) and Edgerton (2012) for M&A transactions and/or asset sales, as well as by Holthausen and Larcker (1996) and Degeorge and Zeckhauser (2003) for increases in firm profitability. All of these factors are controlled for in our model. The importance of financial engineering in the form of re‐ or leveraging of the portfolio companies dates back to

Jensen (1989), and is well documented by Acharya et al. (2012) and Axelson et al. (2013). Next to changes in the portfolio companies’ leverage structure, Teoh, Welch and Wong (1998) and

Chou, Gombola and Liu (2006) show that earnings management can be another important financial engineering process employed by GPs in buyout transactions. Consequently, we control for this as well. The market timing aspect of buyout deals, i.e. when portfolio companies are bought out and exited, is most impressively shown by Cao (2011). His findings suggest that the market environment plays a critical role in GPs’ decision to enter and exit investments. Consequently, we control for different (stock‐) market environments at the time of the LBO and IPO in our regression setup.

Finally, a large body of literature shows that specific features of buyout funds and firms can also significantly impact the performance of their investments. The most striking features which impact performance the most are (1) reputation, as represented by the average historic profitability (shown by Kaserer and Diller, 2005; Demiroglu and James, 2010; Chung, Sensoy, 19

Stern and Weisbach, 2012) and the age of the buyout firm (as shown by Covitz and Liang,

2002), (2) size, represented by the total historic fundraising of each respective buyout firm

(shown by Gompers, 1996; Gompers and Lerner, 2000; Strömberg, 2007), (3) the total funding inflow into the buyout industry as a whole (Ljungqvist and Richardson, 2003), and whether or not a buyout deal is syndicated (Hochberg, Ljungqvist and Lu, 2007). All these factors are controlled for in our model. And, finally, the last two groups are: (5) portfolio company‐ specific control variables, and (6) buyout fund‐ and firm‐specific control variables. For transparency reasons, we only report our central exogenous variables in the main regression tables. The full list of coefficients can be found in the appendix tables.

3 Results

3.A The Influence of Deal Characteristics on Deal‐Level Fees

Table 4 gives a descriptive overview on the average investments, proceeds and returns. The top line shows the overall averages and the lower part splits the sample according to the type of deal‐level fees. Overall, the mean initial investment amounts to $ 203 mil.. The average LBO pays a dividend of $ 116.7 mil., generates IPO proceeds of $ 51.1 mil., and returns a total of $

693.6 mil. back to the private equity fund. The average IRR is 92.3 percent and the Cash

Multiple is 5.12 (median IRR is 47.2 percent, and median Cash Multiple is 3.54), clearly reflecting some of the most successful LBO transactions. Once we split the sample according to deal‐level fee types, a strong difference is can be seen: LBOs with deal‐level fees are significantly larger, and they are significantly more profitable than LBOs without deal‐level fees. Given any type of deal‐level fee, the initial investments are $ 80 mil. larger and generate an IRR that was 28.4 percentage points higher than those without fees. This pattern is most pronounced for Transaction Fees and Termination Fees. The latter shows a size difference of more than $ 200 mil. initial investment and a significant 48 percentage points higher an IRR in

LBOs with Termination Fees. This seems to support the hypothesis that deal‐level fees help stimulate the profitability of LBOs to limited partners dramatically.

(Table 4)

The split between paying versus not‐paying deal‐level fees seems too crude a measure which is why we express all deal‐level fee payments as a percentage of total proceeds that were paid 20 out during the LBO transaction. This measure contrasts every dollar that is paid out by the portfolio company to the fund where LPs participate (i.e., the denominator of our measure) against every dollar that was instead paid out to the GP (i.e., the numerator of our measure).

Of all LBOs with deal‐level fees, 4.1 percent of total proceeds are paid directly to the GPs. The top 10 percentile even pays out more than 8.8 percent of all proceeds through deal‐level fees.

Since deal‐level fees are agreed upon at the time of LBO, certain deal and fund characteristics could cause and motivate their necessity. To better understand what determines deal‐level fees, we regress deal‐level fees on fund and portfolio firm characteristics. Table 5 shows the

OLS regression results. The dependent variables comprise the total‐, transaction‐, management‐, and termination deal‐level fees as a percentage of total deal proceeds in separate regression models. All dependent variables are expressed by their natural logarithm of the percentage of total proceeds.

(Table 5)

Table 5 shows that deal‐level fees are hardly related to fund‐level fee characteristics. Fund management fee, preferred return and fee rebate mostly show negative signs but the t‐ statistics do not support a significant relationship to deal‐level fees. More impact can be found for portfolio firm characteristics. Cash‐rich portfolio companies seem to pay significantly less deal‐level fees. And, return‐on‐assets has a negative relationship to deal‐level management and termination fees. Firms with weaker operating performance might need more attention and they are more demanding to the GP. This could explain why GPs pay themselves an additional deal‐level fee for management advisory. Also, a termination fee might set the right incentive for rapid restructuring to allow for a proper exit instead of a lengthy process. On firm level, debt ratios seem to play a role for management fees, i.e., higher leverage correlates with higher fees. All remaining fund and GP characteristics show few impact if any. Neither size, age, nor syndication shows any convincing pattern. There is some weak negative relationship for past profitability. Model 4 shows a significant impact on termination fees. In other words, GPs with lower average fund performance tend to receive higher termination fees. Transaction fees also have a negative coefficient with a mentionable t‐statistic reflecting an error of below 11 percent. Yet, the overall significance of model 2 is too low as can be seen in the R² and F‐statistic which is why do not consider this finding to be robust. The four 21 regression models in table 5 are only a small fraction of models we actually tested to analyze deal‐level fees. In our set of available deal and fund characteristics, we tested every relationship that was economically plausible. Two problems are dominant in finding adequate regression models: First, fund characteristics show considerable correlation with other fund specifics. For example, fund management fees correlate with fund preferred returns at a level of ρ=0.20. The transaction rebate even shows a correlation of ρ=‐0.34. To see whether multicolinearity is an issue in explaining deal‐level fees we analyze variance inflation and correlations, and we run a large amount of sub‐set regression models. The second problem in model identification is the surprising homogeneity of fund terms as opposed to very heterogeneous deal‐level fees across funds. Over all, it seems that there is no strong, persistent pattern in explaining deal‐level fees.

3.B The Influence of Deal‐Level Fees on Performance

Our main focus is the impact of deal‐level fees on fund profitability, i.e., the impact on LP investments. If deal‐level fees improve the determination and motivation of the GP then this should have a positive impact on LBO performance. Deal‐level fees are agreed upon at the time of the LBO and, therefore, they are somewhat endogenous. We use an instrumental variable approach to take this endogeneity into account.5 Table 6 shows IV Tobit regression6 results of our IRR, cash multiple, and unlevered IRR on LBO characteristics. Due to high correlation between our three deal‐level fees we distinguish four different models: First, we use the ratio of total deal‐level fees to total proceeds (models 1, 5 and 9). Then, we regress each deal‐level fee separately on the same set of control variables (remaining models). To improve readability we only report fund‐level control variables. For a complete list of coefficients including portfolio company and other LBO characteristics please see appendix table A4.

Overall, deal‐level fees show a significantly negative impact on the IRR as can be seen in model 1. This highly negative relationship persists although controlling for fund‐level terms like the preferred return or the transaction fee rebate that should reduce agency costs between

LP and GP considerably. This negative pattern is robust against a variation in performance measures, such as the cash multiple in model 5 or the unlevered IRR in model 9. For the latter,

5 In the first stage regression we use the following LBO characteristics total assets, cash to assets ratio, RoA, debt to assets, called up capital at LBO, DPI at LBO and industry fixed effects as exogenous variables. 6 We use a Tobit approach because both IRR and cash multiple have truncated distributions. 22 the statistical significance even is highest with a z‐value of 3.09. To disaggregate and to see whether different deal‐level fees might show different impact on LBO performance, we report each deal‐level fee in separate regressions. Possibly, transaction fees for restructuring activities, e.g., M&A, could have a positive impact on LBO profitability. Also, termination fees could set the right incentive for a rapid and profitable exit instead of procrastination and waiting for the “right” moment. Models 2, 6 and 10, reveal that transaction fees show the same negative relationship throughout all performance measures. In similar fashion, management fees have large negative coefficients as reported in models 3, 7 and 11. It vaguely appears that management fees have the largest economic significance of all three deal‐level fees.

Termination fees turn out to be insignificant although z‐values of 1.53 and 1.58 in model 4 and

8 suggest an error probability of below 13 percent. Vague significance is also supported by model 12 where terminations fees show a significant coefficient of ‐0.79.

(Table 6)

On fund‐level, fund management fees impact persistently negative on LBO performance across all performance measures. Neither the preferred return nor the transaction rebate alleviates this undesirable impact of fees. The preferred return turns out to be negatively related to the IRR and unrelated to the cash multiple and the unlevered IRR. The latter suggests that the preferred return is somewhat related to leverage. Two possible explanations would be consistent with our findings: First, if GPs increase LBO leverage attempting to realize the hurdle rate more rapidly, yet, file to boost return on equity, then this would be consistent with our findings. Second, if funds without preferred returns generate a higher fraction of their return through leverage. An unreported regression of leverage on IRR, rebate and controls weakly supports the hypothesis of higher leverage in LBOs by funds with higher preferred return. However, this analysis is not within scope of our study and is left to further research. Although transaction rebates should lower agency costs between GP and LP in terms of deal‐level fees, it turns out to be a weak instrument. If the rebate was able to perfectly compensate the loss in distributions to the LP, we would expect to find a strong positive coefficient. Including a control variable for rebates should also have a strong impact on the coefficient of deal‐level fees as the loss in distributions due to deal‐level fees is offset by the rebate. However, inclusion of the rebate variable lowers the coefficient of the total deal‐level 23 fees by only 0.048 and its z‐value by 0.13 (results not reported). Given that half of all LBOs have a substantial rebate we would expect the impact to be much higher. Overall, our results show that all deal‐level fees have a significantly negative impact on LBO performance, even after controlling for preferred return and transaction rebate.

4 Robustness Tests

4.A Endogeneity and estimation issues

The IV Tobit regressions in table 6 display that the exogeneity of deal‐level fees cannot be rejected for all fee types. We cannot entirely rule out whether weak endogeneity or bad instruments is the cause, but the Chi²‐values of the Wald test for exogeneity in all IV models for transaction fees and termination fees are very low. Appendix table 3 shows the results of regular Tobit regressions without instrumenting for deal‐level fees. Our results are robust and even become more pronounced, both statistically and economically. Especially for termination fees, models 4 and 8 with instrumental variables have Wald tests indicating very low endogeneity with an error probability of 56 and 24 percent. These two models show insignificant coefficients for termination fees in the IV regression, but, given the Wald statistic, a regular Tobit can be applied which yields a strong negative impact of deal‐level termination fees.

(Appendix Table A3)

We use Tobit regression analysis as the dependent variables are truncated at ‐1 for the IRR and zero for the cash multiple, respectively. For robustness reasons we also run OLS and IV OLS regressions both leaving our findings unchanged (tables not reported, available upon request).

The OLS regressions show a weaker overall significance in the F‐test than our Tobit regressions which underscores the adequacy of our model. In addition, we also run our analysis on winsorized IRR and cash multiple performance measures as, e.g., in Acharya et al.

(2012), which does not alter our findings.

4.B Measure of deal‐level fees 24

To this point, we use the ratio of fees to proceeds as a measure for deal‐level fees to measure its impact on LBO performance. Although we strongly believe that this is the most adequate way in terms of its economic character, we also run our analysis based on fee dummies. We find a significantly negative impact of deal‐level management fees on IRR and unlevered IRR yet all other deal‐level fee coefficients are insignificant (tables not reported, available upon request). However, the drawback with dummy variables is the absence of magnitude which plays a critical role in our analysis. As an alternative measure we also run our analysis with gross dollar deal‐level fees. Since we include a control variable for the size of the portfolio firm this should somewhat take size effects into account. The results show that all IRR and unlevered IRR regressions generate qualitatively the same results as in table 6. Only the cash multiple regressions do not show any significant impact of deal‐level fees (tables not reported, available upon request). After all, the above robustness checks support our findings and we strongly believe that the ratio of fees to total proceeds precisely reflects the economic nature of deal‐level fees – the amount of dollars that could have been distributed to the LPs as a percentage of the total amount that actually was distributed to the LP.

5 Conclusion

This paper analyzes the influence deal‐level compensation structures have on the performance of Leveraged Buyout (LBO) deals. To do so, we observe transaction fees, management fees, and termination fees paid out to fund managers in 93 LBO deals in the United States over the period 1999‐2008. These deal‐level fees are paid in addition to the fund‐level compensation the buyout fund managers receive in form of the non‐performance‐linked management fee and the performance‐linked Carried Interest. We analyze deal‐level fees in buyout transactions because they possess unique characteristics which make them most suitable to help advance the knowledge about incentive structures and their implications for performance in principal‐ agency relationships. The fees are chosen by agents, i.e. the buyout fund managers, themselves, they are funded by the portfolio companies’ cash, and they are not performance‐ linked but connected to restructuring actions taken by the buyout fund managers.

Our analysis yields two major findings: first, that higher deal‐level fee compensation significantly worsens the performance of the LBO deals, as measured by the deal‐level Internal 25

Rate of Return (IRR) and the Cash Multiple. Second, we find that the occurrence of deal‐level fees does not depend on the structure of the fund‐level compensation structures, but instead on the profitability of the LBO target company and the historic performance of the buyout firm. Our results are robust to changing market environments, characteristics of the LBO and restructuring activities in the target company, terms of the partnership agreements between investors and fund managers, fund structure and –profitability and different performance measures.

Our paper offers three major contributions. First, this is the first paper to analyze the structure of all deal‐level fees in buyout transactions and their implications for the performance of the affected buyout deals. Second, the results of our paper have major implications for the buyout fund investors. The investors are interested in maximizing the return their invested funds yield. All contract terms between them and the fund managers should consequently be directed at reaching this goal. Based on our results, deal‐level compensation should not be part of the overall compensation package fund managers receive since they lower the overall performance of the transactions these managers engage in. Deal‐level fees are therefore not in the best interest of the fund investors and should therefore be disallowed in the partnership agreement. And third, our paper adds valuable insight into a very specific compensation structure in a principal‐agency relationship and can thereby help advance the knowledge in this area. Although the existing body of literature has established that more performance‐ linked compensation increases the agents’ overall performance for the principals, no paper has shown this with the unique compensation structure that deal‐level fees in buyout funds are.

26

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30

Figure 1 Fund‐ and Deal‐Level Compensation Structures in Leveraged Buyouts

The presented figures show exemplary compensation schemes in buyout investments. Panel A shows the payoff structure of compensations on buyout fund‐levels, Panel B shows the typical compensation structure of GPs on buyout deal levels. Panel A shows: on the primary y‐axis the total volume of carried interest paid out to the GPs, on the secondary y‐axis the share of the total distributions paid out to the LPs. The x‐axis shows the development of the fund‐level IRR. The figure depicts how the GPs do not receive any Carry until a hurdle rate is cleared, at which point the LPs cease to receive 100 percent of the distributions. If the IRR moves past the catch‐up zone, the GPs receive the full Carry (assumed to be 20 percent), making each distribution split in 80 percent for the LPs and 20 percent for the GPs. Panel B shows: the chronology of a typical buyout deal from the investment (t0) to the exit (t3). The bottom of the graph shows deal‐ and fund‐level fees received by the GPs at any stage during the investment. The GPs receive fund‐level management fees throughout the duration of the fund. Carry is paid out only if distributions are generated. Deal‐specific advisory fees are paid from the portfolio company to the GPs from t0 to t3. Transaction fees are paid out whenever the GPs advise the portfolio company on a refinancing or M&A acquisition. Finally, termination fees are paid upon exit.

Panel A:

Panel B: 31

Table 1 Summary Statistics of Deal‐Level Fees

The displayed table contains summary statistics for the deal‐level variables. For each variable we report the number and percentage, as well as absolute and relative volumes. For each value we report mean, median and standard deviation, respectively measured in million US‐Dollars.

Total Transaction Management Termination

Fees Fees Fees Fees Number of Deals with Fees Number 53 36 51 23 Percent 57.0% 38.7% 54.8% 24.7%

Fee Volumes Mean (mn. USD) 10.79 5.22 2.83 2.75 Median (mn. USD) 1.35 0.00 0.51 0.00 St. Dev. (mn. USD) 24.59 13.50 9.10 9.08

Fees as Percent of Deal Proceeds Mean 2.41% 0.69% 1.36% 0.36% Median 0.59% 0.00% 0.07% 0.00% St. Dev. 6.36% 1.38% 5.94% 0.95%

Fees as Percent of TEV Mean 2.32% 0.87% 1.02% 0.42% Median 0.21% 0.00% 0.08% 0.00% St. Dev. 5.48% 2.14% 4.64% 1.15%

Fees as Percent of (Estimated) Carried Interest Mean 11.59% 4.37% 5.10% 2.11% Median 1.05% 0.00% 0.38% 0.00% St. Dev. 27.40% 10.69% 23.20% 5.75%

Percentage of Fee Combinations in Deals Transaction Fees 39% 37% 24% Management Fees 55% 25% Termination Fees 25% 32

Table 2 Summary Statistics

The following table displays summary statistics for the 93 buyout‐backed IPO firms in our sample. Panel A reports statistics on the portfolio company and on characteristics of the buyout deal at LBO. “At LBO” refers to items based on the first financial statements of the successor entity post LBO. All variables are defined as in Table 3. Panel B reports the number of buyouts over time and the industry distribution of the deals based on the 1 digit Standard Industrial Classification (SIC). The expression “pre” LBO/IPO refers to items based on the last financial statements of the portfolio company before LBO or IPO; the expression “at” LBO/IPO refers to the first financial statement after the LBO/IPO.

PANEL A: Portfolio Company and Buyout Deal Characteristics Mean Median St.Dev. Fund‐level Characteristics Fund Management Fee 1.83% 1.83% 0.24% Fund Preferred Return 6.82% 8.0% 2.90% Fund Transaction Rebate 57.6% 75.0% 37.1% Fund Carried Interest 20.0% 20.0% 0.0%

Buyout Deal Characteristics Number of Buyout Firms invested at IPO 1.69 2.00 0.79 Number of Investment Rounds 1.43 1.00 1.19 Joined Ownership by all Buyout Firms – pre IPO 74.3% 77.1% 23.9% Joined Ownership by all Buyout Firms – at IPO 49.8% 51.6% 17.8% Management Ownership – pre IPO 10.6% 4.0% 19.2% Management Ownership – at IPO 7.7% 2.5% 14.1% Board Size 8.1 7.0 3.0 Number of Directors from Buyout Firm 3.2 3.0 1.9

Portfolio Company (at LBO) Total Assets 923.2 341.2 1504.6 Net Income 562.4 218.1 1072.8

PANEL B: Buyout Deals over Time and Industry Distribution Avg. Avg. # of IPO # of IPO Year # of Buyouts Amount Industry Amount IPOs Proceeds Buyouts Proceeds Invested Invested 1996 1 568.2 Mining 9 87.9 246.5

1997 Manufacturing 34 248.2 236.8 Transportation, 1998 17 413.6 234.3 Communications 1999 2 50.0 Wholesale Trade 5 105.9 169.8

2000 6 254.8 Retail Trade 4 107.5 56.4

2001 8 259.2 1 108.6 Services 24 142.0 131.3

2002 17 138.9 2 156.9

2003 16 248.7 9 197.4

2004 26 270.9 12 161.4

2005 12 168.3 25 296.3

2006 4 175.8 20 154.9

2007 1 250.0 21 161.4

2008 3 148.9 Total 93 221.8 93 198.7 Total 93 221.8 198.7 33

Table 3 Variable Overview

The following table contains variable descriptions for our main dependent and explanatory variables. For all variables, we list the name, the unit in which it is measured, as well as a brief description of how it is calculated.

Variable Name Unit Description Deal‐Level Fees The absolute U.S.‐Dollar denominated volume of total deal‐level fees Deal‐Level Fees over (management, transaction and termination) paid out to GPs in relation to the % Distributions absolute U.S.‐Dollar denominated volume of all distributions made from LBO investments to the LPs of the invested fund. Fund‐Level Fees The annual fund‐level management fee paid from the LPs to the GPs based on Management Fee % the total U.S.‐Dollar denominated fund volume (usually 1.5‐2%)

The performance‐linked profit share the GPs receive from all distributions Carried Interest % made to the LPs from their investments, on fund‐level.

The preferred return (also called “hurdle rate”) the GPs have to generate on Preferred Return % fund‐level before they receive Carried Interest.

The percent of all deal‐level transaction fees which have to be passed on to the Transaction Fee Rebate % LPs. Return Measures Internal Rate of Return on LBO deal‐level. Calculated using all cash in‐ and IRR % outflows of an LBO deal. Internal Rate of Return component attributed to the leverage used in the buyout deals. Calculated as the difference between the levered and unlevered IRR – Leverage Effect % IRR. It is calculated in line with the methodology provided by Acharya et al. (2012)

Internal Rate of Return component attributed to dividend payments made in IRR – Dividend Effect % the buyout deals. Calculated by leaving out all dividend distributions from the IRR calculation.

Calculated as the net IRR we obtain after unlevering the deal‐level IRR and IRR – Economic Effect % subtracting all dividend payments.

Calculated as the ratio between all cash inflows (all investments, i.e. Cash Multiple Metric contributions) and cash outflows (all divestments, i.e. distributions) of a single LBO transaction. Additional Explanatory Variables Ratio of total cash to total assets, as recorded on the balance sheet of the Cash over Assets at LBO % portfolio company in the LBO year

Return on Assets of the portfolio company in the LBO year, measured RoA at LBO % through the ratio of net income (as recorded on the P&L statement) to total assets (as recorded on the balance sheet) Ratio of total debt to total assets, as recorded on the balance sheet of the Debt to Assets at LBO % portfolio company in the LBO year.

GP Average Past Mean fund IRR of all past funds of each invested buyout firm in the respective % Profitability LBO deals. Dummy variable indicating whether or not a buyout deal in our sample is Syndicated Deal Dummy syndicated (i.e. has more than one buyout fund investor, also known as a “club deal”) or not. Dummy takes the value of 1 if the deal is syndicated. 34

Buyout fund‐level performance multiple indicating the ratio of distributions to paid‐in capital (measured on fund‐level with all distributions and Fund DPI in LBO Year % contributions made to and from LPs). Measured in the year in which the LBO took place. Total GP Past U.S.‐Dollar denominated volume of the total fundraising in all prior funds of Metric Fundraising each buyout investor in our sample. Age of each invested buyout fund in our sample at the time of the LBO, Fund Age at LBO Metric measured as the number of years between the fund’s inception year and the LBO year. Buyout Industry Total U.S.‐Dollar denominated fundraising in the whole buyout industry in Metric Fundraising Deal Year the United States in each respective year of our observation period.

Percent of the total capital drawn down by the GPs in the year of the LBO Called‐up Capital % (measured on fund‐level). Buyout fund‐level performance multiple indicating the ratio of distributions DPI % to paid‐in capital (measured on fund‐level with all distributions and contributions made to and from LPs). 35

Table 4 Proceeds and Returns The table presents the investments, proceeds, and returns of buyout deals. We report the numbers for our full sample of buyouts, and split the sample in accordance with whether or not the deal have deal‐level fees or not. Test statistics base on a two‐sample t‐test with unequal variances. ***,**,* denote significance at 1%, 5%, and 10% respectively.

Investments Proceeds Return Measures

Initial Overall Share Cash Cash Cash Dividends IPO Sale Total IRR Unlev. IRR Sale Multiple Investment Investment

All 203 221.8 116.7 51.1 525.8 693.6 0.929 0.408 5.115 Firms Any Fee(s)

No 157.3 176.2 69.5 43.2 417.5 530.3 0.768 0.389 4.163

Yes 237.5 256.2 152.4 57 607.5 816.8 1.052 0.422 5.834

Diff. 80.1** 80.1*** 82.9** 13.7** 190* 286.6* 0.284** 0.033** 1.671**

Transaction Fees

No 153.8 180.7 93 38.1 484.8 615.8 0.728 0.361 4.581

Yes 280.9 286.9 154.3 71.6 590.7 816.7 1.249 0.481 5.959

Diff. 127.1* 106.3*** 61.3** 33.6* 106* 200.9* 0.521** 0.120** 1.378**

Management Fees

No 153.6 171.6 71.8 45.6 423.2 540.6 0.819 0.404 4.733

Yes 243.6 263.2 153.7 55.6 610.3 819.6 1.02 0.410 5.429

Diff. 90* 91.6*** 81.9* 10* 187.1* 279* 0.201** 0.006** 0.696**

Termination Fees

No 146.6 172 92.1 45.9 449.4 587.4 0.81 0.383 4.845

Yes 374.5 373.3 191.8 66.7 758.3 1016.8 1.293 0.484 5.935

Diff. 227.9*** 201.3** 99.7** 20.7* 308.9* 429.3** 0.483** 0.101** 1.09**

36

Table 5 Deal‐level Fee Determinants The table present results of OLS regression models to determine factors influencing deal‐ level fees. All dependent deal‐level fees are measured by their natural logarithm of the percentage of total proceeds. All variables are defined in Table 3. ***,**,* denote significance at 1%, 5%, and 10% respectively. t‐values are in the parentheses based on robust standard errors. (1) (2) (3) (4) Total Transaction Management Termination Dependent: log(x) Fees to Fees to Fees to Fees to Proceeds Proceeds Proceeds Proceeds

Fund Management Fee ‐0.751 0.476 ‐0.538 0.076 (‐1.48) (1.36) (‐1.16) (0.26) Fund Preferred Return ‐0.040 ‐0.038 ‐0.016 ‐0.033 (‐1.14) (‐1.38) (‐0.62) (‐1.51) Fund Transaction Fee Rebate ‐0.002 ‐0.001 ‐0.003 ‐0.001 (‐0.91) (‐0.75) (‐1.40) (‐0.58) Cash over Assets at LBO ‐0.638** ‐0.214** ‐0.212* ‐0.086 (‐2.32) (‐2.02) (‐1.78) (‐0.95) RoA at LBO 0.005 ‐0.104 ‐0.183*** ‐0.277*** (0.07) (‐1.46) (‐2.91) (‐3.49) Debt to Assets at LBO ‐0.005 ‐0.021 0.147*** ‐0.023 (‐0.14) (‐0.54) (3.86) (‐1.61) GP Average Past Profitability ‐1.326 ‐0.887 ‐0.613 ‐0.621* (‐1.51) (‐1.67) (‐1.18) (‐1.74) Syndicated Deal ‐0.110 ‐0.083 ‐0.078 ‐0.041 (‐0.53) (‐0.61) (‐0.52) (‐0.42) Fund DPI in LBO year ‐0.385 ‐0.035 ‐0.125 ‐0.102 (‐1.57) (‐0.18) (‐0.71) (‐1.17) Total GP Past Fundraising ‐0.015 0.054 ‐0.061 0.009 (‐0.15) (0.61) (‐0.70) (0.16) Fund Age at LBO ‐0.021 0.026 ‐0.058 0.006 (‐0.26) (0.54) (‐1.11) (0.16)

FE year‐ and industry level Yes Yes Yes Yes

Adj. R2 0.135 ‐0.034 0.146 0.09 N 93 93 93 93 Prob(p>F) 0.000 0.273 0.000 0.079

37 Table 6 Main Regression Model The table present results of IV Tobit regression models to determine factors influencing various return measures. All variables are defined in Tables 3. We use a cross‐sectional left‐censored Tobit regression because of the truncated underlying distribution of IRRs and all of is components. ***,**,* denote significance at 1%, 5%, and 10% respectively. z‐values are in the parentheses and standard errors are clustered at industry level using two‐digit SIC codes. Additional controls on firm and deal level are included which can be found in appendix table 8. (1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) IRR IRR IRR IRR CM CM CM CM Unlev. IRR Unlev. IRR Unlev. IRR Unlev. IRR log(Total Deal‐Level Fees to Proceeds) ‐1.27*** ‐3.67** ‐0.48*** (‐2.77) (‐2.56) (‐3.09) log(Transaction Fees to Proceeds) ‐1.40** ‐4.98** ‐0.53** (‐2.20) (‐2.28) (‐2.47) log(Management Fees to Proceeds) ‐2.20*** ‐5.33** ‐0.80*** (‐2.72) (‐2.50) (‐2.85) log(Termination Fees to Proceeds) ‐1.76 ‐7.31 ‐0.79* (‐1.53) (‐1.58) (‐1.89) Fund Management Fee ‐2.79*** ‐2.21*** ‐2.86*** ‐2.62*** ‐5.35** ‐3.90 ‐5.11* ‐5.76* ‐1.00*** ‐0.79*** ‐1.02*** ‐0.99*** (‐3.30) (‐3.16) (‐2.87) (‐3.48) (‐2.03) (‐1.61) (‐1.95) (‐1.91) (‐3.53) (‐3.33) (‐2.95) (‐3.62) Fund Preferred Return ‐0.15** ‐0.14** ‐0.14* ‐0.12** ‐0.30 ‐0.28 ‐0.24 ‐0.19 ‐0.03 ‐0.03 ‐0.03 ‐0.02 (‐2.24) (‐2.35) (‐1.72) (‐2.29) (‐1.39) (‐1.35) (‐1.14) (‐0.95) (‐1.36) (‐1.32) (‐0.91) (‐0.95) Fund Transaction Fee Rebate 0.00 0.00 0.00 0.01 ‐0.05*** ‐0.05*** ‐0.05*** ‐0.04*** 0.00 0.00 0.00 0.00 (0.53) (1.07) (0.55) (1.46) (‐3.20) (‐3.04) (‐3.02) (‐2.88) (0.17) (0.69) (0.27) (0.94) Total Past Fundraising 0.02 ‐0.00 0.04 ‐0.01 ‐0.02 ‐0.09 ‐0.00 ‐0.10 0.01 0.00 0.01 ‐0.00 (0.98) (‐0.11) (1.21) (‐0.41) (‐0.22) (‐1.33) (‐0.00) (‐1.56) (1.31) (0.15) (1.43) (‐0.09) GP Average Past Profitability ‐3.25** ‐2.33* ‐3.42* ‐3.39** ‐0.44 2.05 ‐0.34 ‐2.46 ‐1.23** ‐0.89* ‐1.28* ‐1.38*** (‐1.97) (‐1.67) (‐1.75) (‐2.33) (‐0.09) (0.42) (‐0.07) (‐0.42) (‐2.23) (‐1.88) (‐1.89) (‐2.60) Fund Age at LBO ‐0.40** ‐0.30** ‐0.51*** ‐0.36*** ‐0.27 0.05 ‐0.55 ‐0.13 ‐0.14*** ‐0.11** ‐0.18*** ‐0.13*** (‐2.56) (‐2.16) (‐2.71) (‐3.04) (‐0.56) (0.11) (‐1.11) (‐0.27) (‐2.74) (‐2.25) (‐2.82) (‐2.93) Syndicated Deal 0.80** 1.01*** 0.51 1.20*** 1.89 2.51** 1.27 3.27** 0.37*** 0.45*** 0.26 0.53*** (2.02) (2.96) (1.02) (3.71) (1.53) (2.12) (0.97) (2.53) (2.76) (3.86) (1.53) (4.52) Buyout Industry Fundraising Deal Year 0.02*** 0.02*** 0.02*** 0.02*** 0.03* 0.03* 0.03 0.03 0.01*** 0.01*** 0.01*** 0.01*** (3.33) (3.80) (2.79) (4.03) (1.65) (1.84) (1.57) (1.47) (3.38) (3.85) (2.74) (3.77) Called‐up Capital ‐0.04* ‐0.03* ‐0.04 ‐0.04** ‐0.17** ‐0.15** ‐0.17** ‐0.19** ‐0.02** ‐0.01** ‐0.02* ‐0.02** (‐1.85) (‐1.76) (‐1.62) (‐2.34) (‐2.42) (‐2.23) (‐2.39) (‐2.54) (‐2.08) (‐1.97) (‐1.75) (‐2.54) DPI 0.01** 0.01** 0.01*** 0.01*** ‐0.00 ‐0.00 0.01 0.00 0.00** 0.00** 0.00** 0.00*** (2.21) (2.27) (2.63) (3.46) (‐0.02) (‐0.29) (0.73) (0.22) (2.07) (2.08) (2.51) (2.95)

Additional Controls* Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes FE year‐level Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Observations 93 93 93 93 93 93 93 93 93 93 93 93 Chi² 84.09 104.40 61.27 136.30 78.33 81.16 76.91 77.96 83.77 101.30 57.51 114.00 Prob (p>Chi²) 0.000 0.000 0.001 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.002 0.000 Endogeneity Chi² 6.69 2.59 13.42 0.34 4.15 2.89 4.27 1.36 4.78 1.53 11.06 0.48 Endogeneity Prob. 0.010 0.108 0.000 0.562 0.042 0.089 0.039 0.244 0.029 0.216 0.001 0.489 Overidentification Chi² 12.05 20.85 6.52 32.23 13.16 15.72 13.17 18.25 10.54 19.61 5.21 26.27 Overidentification Prob. 0.211 0.013 0.687 0.000 0.155 0.073 0.155 0.032 0.309 0.021 0.816 0.002 38

Appendix Table A1: Overview of Restructuring Activities

The table presents summary statistics for different types of value creation measures of buyout firms in their portfolio companies. All variables are reported as defined in Table 2. We classify four different groups of value creation: fundamental engineering, financial engineering, cash draining, and market timing. By group, we report several types of those value creation measures. In the third column, we show the actual instruments which are used to implement the corresponding type of value creation measures. For each instrument, we report the number of portfolio companies in which the instruments are used, their mean, median and standard deviation, if applicable.

# of Hypothesis Subtype Instrument Mean Median SD Companies Fundamental Monitoring Board Seat 216 96.4% Engineering Chairman from Buyout Firm 49 21.9% Ownership by Buyout Firms 224 71.0% 76.60% 24.13% Percent of Buyout Firm Directors 224 34.4% 31.01% 17.43% Management Ownership 210 10.3% 4.45% 17.26% Governance CEO Change 77 34.4% Intervention CFO Change 60 26.8% Any Management Change 105 46.9% Operational M&A Deals 78 34.8% Financial Debt Long‐term Debt pre LBO 161 183.49 21 555.82 Engineering Long‐term Debt at LBO 224 346.7 140.43 649.17 Long‐term Debt at IPO 224 369.5 172.56 623.36 Leverage Leverage pre LBO 161 0.71 0.15 2.34 Leverage at LBO 224 1.49 1.08 1.46 Leverage at IPO 224 1.44 0.99 1.75 Fin. Reporting Earnings Management 47 21.0% Financial Restatement 33 14.8% Cash Draining Dividends Firms with Dividends 115 51.3% Dividend to Revenues at IPO 115 25.0% 14.36% 42.89% Dividend to Proceeds 115 26.2% 19.92% 23.71% Market Timing Initial Timing Bear Market Investment 60 26.8% Exit Timing Bull Market IPO 165 73.7% Time Invested 224 6.21 5.89 2.96 Time from Investment to IPO 224 3.19 2.59 2.31

39

Appendix Table A2: List of Funds and Total Deal‐level Fees The table present summary statistics of the ratio of total deal‐level fees to total proceeds (as defined in Table 3) by each buyout fund in our sample. We report both the number of LBOs in which each buyout fund was invested in our sample as well as the ratio of fees to proceeds.

Average Ratio Number Fund Name Total Deal‐Level of LBOs Fees to Proceeds Carlyle Partners IV 0.427 1 Atlantic Equity Partners III 0.140 1 Providence Equity Partners IV 0.127 1 Thomas H Lee V 0.095 2 Green Equity Investors IV 0.088 1 Kelso Investment Associates VII 0.085 3 Ripplewood Partners II 0.082 1 Quadrangle Capital Partners II 0.069 1 Genstar Capital Partners III 0.058 1 Bain Capital Fund VIII 0.055 1 Trivest Fund III 0.053 1 Francisco Partners 0.053 3 TPG Partners IV 0.051 1 Castle Harlan Partners IV 0.048 1 Apollo Overseas Partners 0.040 1 Blackstone Capital Partners IV 0.039 2 Jordan Resolute Fund 0.026 1 KKR Millennium Fund 0.024 2 Aurora Equity Partners III 0.019 1 Apollo Investment Fund V 0.019 2 Charlesbank Equity Partners VI 0.019 1 Lake Capital Partners 0.018 1 Golder Thoma Cressey Rauner VIII 0.011 2 New Mountain Partners II 0.011 1 Wexford Partners VI 0.010 1 Parthenon Investors II 0.009 3 WLR Recovery Fund II 0.008 1 Ares Corporate Opportunities Fund 0.007 2 Charlesbank Equity Partners V 0.007 1 Endeavour Capital Fund IV 0.006 1 First Reserve Fund X 0.005 3 Silver Lake Partners 0.005 2 Berkshire Fund VI 0.004 1 Golder Thoma Cressey Rauner VII 0.003 4 Fortress Investment Fund II 0.002 1 Lindsay Goldberg ‐ Fund II 0.002 1 Oak Hill Special Opportunities Fund 0.002 1 Wellspring Capital Partners III 0.002 1 Onex Partners 0.001 1 Quantum Energy Partners II 0.001 1 TA IX 0.001 3 TPG Partners III 0.001 1 ABRY IV 0 1 ABS Capital IV 0 1 Austin Ventures VIII 0 1 Carlyle Partners III 0 1 Cerberus (America) 0 2 Clarity Partners 0 1 Cross Atlantic Technology Fund I 0 1 Crosspoint Venture Partners 2000 0 1 DLJ Merchant Banking Partners III 0 2 Fund Name Average Ratio Number 40

Total Deal‐Level of LBOs Fees to Proceeds EnCap Energy Capital Fund V 0 1 First Reserve Fund IX 0 1 Forstmann Little Debt & Equity Buyout VIII 0 1 Fortress Investment Fund III 0 1 ING Furman Selz Investors III 0 1 Lime Rock Partners III 0 1 Lindsay Goldberg ‐ Fund I 0 1 Madison Dearborn Capital Partners IV 0 1 MatlinPatterson Global Opportunities 0 1 SCF Fund V 0 1 Spectrum Equity Investors IV 0 1 Summit Ventures VI 0 2 TA Atlantic & Pacific V 0 2 Technology Crossover Ventures IV 0 1 Veritas Capital Fund II 0 1 Warburg Pincus International Partners 0 1 Warburg Pincus Private Equity VIII 0 1 Yorktown Energy Partners V 0 1 0.024 93 41

Appendix Table A3: Regular Tobit Regressions with Full Set of Control Variables The table present results of OLS and tobit regression models to determine factors influencing various return measures. All variables are as defined in Table 3. We use a cross‐sectional left‐censored tobit regression in models 2 to 5 because of the truncated underlying distribution of IRRs and all of is components. ***,**,* denote significance at 1%, 5%, and 10% respectively. z‐values are in the parentheses and standard errors are clustered at industry level using two‐digit SIC codes. (1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) IRR IRR IRR IRR CM CM CM CM Unlev. IRR Unlev. IRR Unlev. IRR Unlev. IRR log(Total Fees to Proceeds) ‐0.42*** ‐1.41** ‐0.22*** (‐3.31) (‐2.45) (‐4.46) log(Transaction Fees to Proceeds) ‐0.55*** ‐1.98** ‐0.30*** (‐3.05) (‐2.38) (‐3.90) log(Management Fees to Proceeds) ‐0.40** ‐1.89** ‐0.20*** (‐2.25) (‐2.29) (‐2.97) log(Termination Fees to Proceeds) ‐1.04*** ‐2.47** ‐0.49*** (‐3.63) (‐2.04) (‐4.42) Management Fee ‐2.25*** ‐2.08** ‐2.12** ‐2.37*** ‐3.76 ‐3.22 ‐3.60 ‐3.79 ‐0.84*** ‐0.75** ‐0.77** ‐0.88*** (‐2.82) (‐2.63) (‐2.59) (‐2.94) (‐1.38) (‐1.19) (‐1.29) (‐1.43) (‐2.90) (‐2.65) (‐2.55) (‐3.15) Preferred Return ‐0.12* ‐0.12* ‐0.11* ‐0.11* ‐0.22 ‐0.21 ‐0.19 ‐0.18 ‐0.02 ‐0.02 ‐0.02 ‐0.02 (‐1.99) (‐1.91) (‐1.78) (‐1.85) (‐1.19) (‐1.15) (‐1.03) (‐0.97) (‐0.98) (‐0.91) (‐0.73) (‐0.75) Transaction Fee Rebate 0.01 0.01 0.01 0.01 ‐0.05** ‐0.04* ‐0.05* ‐0.04* 0.00 0.00 0.00 0.00 (1.09) (1.21) (1.22) (1.30) (‐2.03) (‐1.97) (‐1.99) (‐1.91) (0.63) (0.81) (0.82) (0.91) Total Past Fundraising 0.00 ‐0.01 ‐0.00 ‐0.01 ‐0.08 ‐0.11** ‐0.08 ‐0.11** 0.00 ‐0.00 0.00 ‐0.00 (0.14) (‐0.48) (‐0.05) (‐0.59) (‐1.50) (‐2.14) (‐1.41) (‐2.28) (0.77) (‐0.03) (0.48) (‐0.21) Average Past Profitability ‐2.32** ‐2.03** ‐2.21** ‐2.75** 0.77 1.67 0.94 0.37 ‐0.97** ‐0.81** ‐0.90** ‐1.14*** (‐2.41) (‐2.07) (‐2.19) (‐2.57) (0.17) (0.35) (0.20) (0.08) (‐2.58) (‐2.11) (‐2.16) (‐2.75) Fund Age at LBO ‐0.42** ‐0.39** ‐0.44*** ‐0.39** ‐0.24 ‐0.11 ‐0.34 ‐0.20 ‐0.15*** ‐0.13** ‐0.16*** ‐0.14*** (‐2.63) (‐2.40) (‐2.72) (‐2.53) (‐0.61) (‐0.28) (‐0.88) (‐0.51) (‐2.94) (‐2.59) (‐2.99) (‐2.69) Syndicated Deal 0.99** 1.06** 0.96** 1.16*** 2.32* 2.57** 2.11* 2.80** 0.42*** 0.46*** 0.41*** 0.51*** (2.38) (2.61) (2.29) (2.84) (1.95) (2.19) (1.77) (2.38) (3.30) (3.63) (3.11) (3.94) Buyout Industry Fundraising Deal Year 0.02*** 0.02*** 0.02** 0.02** 0.02* 0.02* 0.02* 0.02 0.01*** 0.01*** 0.01*** 0.01*** (2.66) (2.72) (2.58) (2.64) (1.78) (1.83) (1.78) (1.65) (3.09) (3.15) (2.92) (3.06) Called‐up Capital ‐0.03** ‐0.03* ‐0.03** ‐0.04** ‐0.15** ‐0.15** ‐0.15** ‐0.16** ‐0.01** ‐0.01** ‐0.01** ‐0.01** (‐2.09) (‐1.94) (‐2.00) (‐2.12) (‐2.59) (‐2.48) (‐2.53) (‐2.53) (‐2.28) (‐2.06) (‐2.13) (‐2.30) DPI 0.01*** 0.01*** 0.01*** 0.01*** 0.01 0.01 0.01 0.01 0.00*** 0.00** 0.00*** 0.00*** (2.87) (2.74) (3.20) (3.03) (0.69) (0.57) (1.06) (0.85) (2.78) (2.56) (3.24) (2.97) Chairman from GP 0.48 0.46 0.52* 0.54* 1.87* 1.79* 2.04* 2.08* 0.22** 0.21** 0.24** 0.25** (1.58) (1.51) (1.70) (1.82) (1.80) (1.71) (1.89) (1.94) (2.14) (2.03) (2.17) (2.48) Any Mgmt Change 360 days around LBO 0.75*** 0.82*** 0.62** 0.84*** 2.68*** 2.96*** 2.26** 2.82*** 0.38*** 0.42*** 0.31*** 0.42*** (2.79) (3.01) (2.28) (3.12) (2.88) (3.03) (2.40) (3.02) (3.47) (3.68) (2.83) (3.79) Mgmt Holdings pre IPO ‐0.97 ‐0.75 ‐0.85 ‐1.12* ‐4.51* ‐3.85 ‐4.17 ‐4.45 0.01 0.12 0.07 ‐0.05 (‐1.64) (‐1.32) (‐1.48) (‐1.80) (‐1.71) (‐1.45) (‐1.58) (‐1.67) (0.02) (0.50) (0.28) (‐0.21) M&A ‐0.62 ‐0.57 ‐0.62 ‐0.77* ‐0.24 ‐0.05 ‐0.18 ‐0.62 ‐0.18 ‐0.15 ‐0.18 ‐0.26** (‐1.55) (‐1.40) (‐1.55) (‐1.88) (‐0.26) (‐0.05) (‐0.19) (‐0.64) (‐1.54) (‐1.28) (‐1.55) (‐2.07) RoA Growth 0.01 0.02 0.01 0.01 0.09 0.11* 0.09 0.08 0.01* 0.01** 0.01 0.00 (1.16) (1.54) (0.91) (0.62) (1.65) (1.87) (1.54) (1.37) (1.97) (2.50) (1.52) (1.06) Change D/E Ratio LBO to IPO 0.27*** 0.28*** 0.27*** 0.28*** 0.39 0.42* 0.38 0.42 0.08** 0.09** 0.08** 0.09*** (2.84) (2.86) (2.68) (3.21) (1.60) (1.72) (1.64) (1.59) (2.64) (2.64) (2.37) (3.15) 42

Debt to Assets at LBO ‐0.11 ‐0.14* ‐0.13* ‐0.11 0.23 0.16 0.20 0.20 ‐0.06** ‐0.07** ‐0.07** ‐0.06** (‐1.52) (‐1.88) (‐1.81) (‐1.53) (0.79) (0.57) (0.68) (0.70) (‐2.15) (‐2.62) (‐2.57) (‐2.20) Earnings Mgmt 0.05 0.07 0.10 0.05 0.45 0.49 0.55 0.50 ‐0.10 ‐0.09 ‐0.08 ‐0.10 (0.20) (0.24) (0.36) (0.16) (0.36) (0.38) (0.43) (0.40) (‐0.94) (‐0.83) (‐0.73) (‐0.86) Firm paid Dividend ‐0.08 ‐0.12 ‐0.04 ‐0.15 0.97 0.81 1.10 0.84 ‐0.07 ‐0.09 ‐0.05 ‐0.10 (‐0.32) (‐0.48) (‐0.14) (‐0.57) (0.83) (0.70) (0.90) (0.68) (‐0.68) (‐0.90) (‐0.42) (‐0.95) Dividend Recap 0.07 0.03 ‐0.09 0.42 1.94 1.82 1.47 2.59 0.23 0.21 0.15 0.39** (0.16) (0.06) (‐0.20) (0.99) (1.31) (1.25) (1.01) (1.61) (1.35) (1.24) (0.88) (2.24) Entry Bear Market, Exit Bull Market ‐0.05 ‐0.22 0.01 ‐0.14 5.05*** 4.43** 5.51*** 4.78** ‐0.07 ‐0.17 ‐0.04 ‐0.12 (‐0.11) (‐0.49) (0.03) (‐0.31) (2.73) (2.37) (2.91) (2.58) (‐0.44) (‐1.00) (‐0.23) (‐0.72) Days Invested ‐0.00*** ‐0.00** ‐0.00*** ‐0.00* ‐0.00 0.00 ‐0.00 0.00 ‐0.00** ‐0.00* ‐0.00** ‐0.00 (‐2.70) (‐2.26) (‐2.68) (‐1.92) (‐0.04) (0.25) (‐0.20) (0.31) (‐2.39) (‐1.90) (‐2.32) (‐1.60) log(Total Assets) 0.04 0.07 0.00 0.09 ‐1.14*** ‐1.04*** ‐1.31*** ‐1.04*** ‐0.07* ‐0.06 ‐0.09** ‐0.05 (0.38) (0.66) (0.00) (0.84) (‐3.16) (‐3.04) (‐3.38) (‐3.00) (‐1.80) (‐1.48) (‐2.18) (‐1.23) N 93 93 93 93 93 93 93 93 93 93 93 93 F 1.936 1.950 1.965 2.060 2.337 2.238 2.432 2.491 2.487 2.374 2.071 2.243 Prob(p >F) 0.0140 0.0132 0.0123 0.00807 0.00234 0.00365 0.00153 0.00117 0.00119 0.00198 0.00770 0.00356

43

Appendix Table A4: IV Tobit Regressions with Full Set of Control Variables The table present results of OLS and tobit regression models to determine factors influencing various return measures. All variables are as defined in Tables 1 and 2. We use a cross‐sectional left‐censored tobit regression in models 2 to 5 because of the truncated underlying distribution of IRRs and all of is components. ***,**,* denote significance at 1%, 5%, and 10% respectively. z‐values are in the parentheses and standard errors are clustered at industry level using two‐digit SIC codes. (1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) IRR IRR IRR IRR CM CM CM CM Unlev. IRR Unlev. IRR Unlev. IRR Unlev. IRR log(Total Fees to Proceeds) ‐1.27*** ‐3.67** ‐0.48*** (‐2.77) (‐2.56) (‐3.09) log(Transaction Fees to Proceeds) ‐1.40** ‐4.98** ‐0.53** (‐2.20) (‐2.28) (‐2.47) log(Management Fees to Proceeds) ‐2.20*** ‐5.33** ‐0.80*** (‐2.72) (‐2.50) (‐2.85) log(Termination Fees to Proceeds) ‐1.76 ‐7.31 ‐0.79* (‐1.53) (‐1.58) (‐1.89) Management Fee ‐2.79*** ‐2.21*** ‐2.86*** ‐2.62*** ‐5.35** ‐3.90 ‐5.11* ‐5.76* ‐1.00*** ‐0.79*** ‐1.02*** ‐0.99*** (‐3.30) (‐3.16) (‐2.87) (‐3.48) (‐2.03) (‐1.61) (‐1.95) (‐1.91) (‐3.53) (‐3.33) (‐2.95) (‐3.62) Preferred Return ‐0.15** ‐0.14** ‐0.14* ‐0.12** ‐0.30 ‐0.28 ‐0.24 ‐0.19 ‐0.03 ‐0.03 ‐0.03 ‐0.02 (‐2.24) (‐2.35) (‐1.72) (‐2.29) (‐1.39) (‐1.35) (‐1.14) (‐0.95) (‐1.36) (‐1.32) (‐0.91) (‐0.95) Transaction Fee Rebate 0.00 0.00 0.00 0.01 ‐0.05*** ‐0.05*** ‐0.05*** ‐0.04*** 0.00 0.00 0.00 0.00 (0.53) (1.07) (0.55) (1.46) (‐3.20) (‐3.04) (‐3.02) (‐2.88) (0.17) (0.69) (0.27) (0.94) Total Past Fundraising 0.02 ‐0.00 0.04 ‐0.01 ‐0.02 ‐0.09 ‐0.00 ‐0.10 0.01 0.00 0.01 ‐0.00 (0.98) (‐0.11) (1.21) (‐0.41) (‐0.22) (‐1.33) (‐0.00) (‐1.56) (1.31) (0.15) (1.43) (‐0.09) Average Past Profitability ‐3.25** ‐2.33* ‐3.42* ‐3.39** ‐0.44 2.05 ‐0.34 ‐2.46 ‐1.23** ‐0.89* ‐1.28* ‐1.38*** (‐1.97) (‐1.67) (‐1.75) (‐2.33) (‐0.09) (0.42) (‐0.07) (‐0.42) (‐2.23) (‐1.88) (‐1.89) (‐2.60) Fund Age at LBO ‐0.40** ‐0.30** ‐0.51*** ‐0.36*** ‐0.27 0.05 ‐0.55 ‐0.13 ‐0.14*** ‐0.11** ‐0.18*** ‐0.13*** (‐2.56) (‐2.16) (‐2.71) (‐3.04) (‐0.56) (0.11) (‐1.11) (‐0.27) (‐2.74) (‐2.25) (‐2.82) (‐2.93) Syndicated Deal 0.80** 1.01*** 0.51 1.20*** 1.89 2.51** 1.27 3.27** 0.37*** 0.45*** 0.26 0.53*** (2.02) (2.96) (1.02) (3.71) (1.53) (2.12) (0.97) (2.53) (2.76) (3.86) (1.53) (4.52) Buyout Industry Fundraising Deal Year 0.02*** 0.02*** 0.02*** 0.02*** 0.03* 0.03* 0.03 0.03 0.01*** 0.01*** 0.01*** 0.01*** (3.33) (3.80) (2.79) (4.03) (1.65) (1.84) (1.57) (1.47) (3.38) (3.85) (2.74) (3.77) Called‐up Capital ‐0.04* ‐0.03* ‐0.04 ‐0.04** ‐0.17** ‐0.15** ‐0.17** ‐0.19** ‐0.02** ‐0.01** ‐0.02* ‐0.02** (‐1.85) (‐1.76) (‐1.62) (‐2.34) (‐2.42) (‐2.23) (‐2.39) (‐2.54) (‐2.08) (‐1.97) (‐1.75) (‐2.54) DPI 0.01** 0.01** 0.01*** 0.01*** ‐0.00 ‐0.00 0.01 0.00 0.00** 0.00** 0.00** 0.00*** (2.21) (2.27) (2.63) (3.46) (‐0.02) (‐0.29) (0.73) (0.22) (2.07) (2.08) (2.51) (2.95) Chairman from GP 0.40 0.37 0.56 0.56* 1.71 1.52 2.15* 2.24* 0.19 0.18 0.25 0.26** (1.04) (1.09) (1.24) (1.96) (1.44) (1.30) (1.81) (1.94) (1.50) (1.58) (1.62) (2.46) Any Mgmt Change 360 days around LBO 0.98** 1.11*** 0.59 0.98*** 3.58*** 4.28*** 2.46** 4.04*** 0.45*** 0.50*** 0.31** 0.48*** (2.54) (2.82) (1.37) (2.66) (2.97) (3.17) (2.16) (2.74) (3.49) (3.79) (2.06) (3.58) Mgmt Holdings pre IPO ‐1.46 ‐0.80 ‐1.33 ‐1.40* ‐4.77 ‐2.88 ‐4.14 ‐5.38 ‐0.14 0.11 ‐0.09 ‐0.17 (‐1.45) (‐0.93) (‐1.13) (‐1.66) (‐1.52) (‐0.98) (‐1.34) (‐1.59) (‐0.42) (0.37) (‐0.22) (‐0.54) M&A ‐0.53 ‐0.41 ‐0.44 ‐0.84*** 0.14 0.64 0.30 ‐1.02 ‐0.16 ‐0.11 ‐0.13 ‐0.29** (‐1.37) (‐1.17) (‐0.96) (‐2.68) (0.12) (0.53) (0.25) (‐0.81) (‐1.21) (‐0.94) (‐0.79) (‐2.52) RoA Growth 0.02 0.03 0.01 0.01 0.12* 0.16** 0.09 0.08 0.01 0.01* 0.00 0.00 (0.88) (1.46) (0.37) (0.36) (1.95) (2.48) (1.56) (1.31) (1.26) (1.93) (0.64) (0.65) Change D/E Ratio LBO to IPO 0.25*** 0.28*** 0.24** 0.28*** 0.36 0.44 0.34 0.43 0.08*** 0.09*** 0.08** 0.09*** (2.87) (3.58) (2.28) (4.12) (1.31) (1.64) (1.21) (1.61) (2.69) (3.39) (2.06) (3.63) 44

Debt to Assets at LBO ‐0.05 ‐0.12 ‐0.06 ‐0.09 0.35 0.15 0.27 0.31 ‐0.04 ‐0.07* ‐0.05 ‐0.05 (‐0.34) (‐1.02) (‐0.39) (‐0.78) (0.80) (0.36) (0.62) (0.71) (‐0.89) (‐1.71) (‐0.85) (‐1.29) Earnings Mgmt ‐0.10 ‐0.03 ‐0.06 ‐0.01 ‐0.05 0.07 0.18 0.04 ‐0.15 ‐0.12 ‐0.13 ‐0.12 (‐0.23) (‐0.06) (‐0.11) (‐0.03) (‐0.03) (0.05) (0.12) (0.03) (‐0.96) (‐0.87) (‐0.68) (‐0.96) Firm paid Dividend ‐0.15 ‐0.22 ‐0.03 ‐0.22 0.78 0.41 1.12 0.30 ‐0.09 ‐0.12 ‐0.05 ‐0.13 (‐0.35) (‐0.59) (‐0.07) (‐0.64) (0.59) (0.31) (0.85) (0.22) (‐0.64) (‐0.93) (‐0.27) (‐1.05) Dividend Recap 0.43 0.22 0.05 0.78 2.93* 2.56 1.75 5.09* 0.34* 0.27 0.20 0.54** (0.76) (0.44) (0.08) (1.08) (1.67) (1.52) (1.06) (1.76) (1.81) (1.61) (0.92) (2.07) Entry Bear Market, Exit Bull Market 0.08 ‐0.42 0.70 ‐0.17 5.53*** 3.95** 6.92*** 4.86*** ‐0.03 ‐0.22 0.19 ‐0.12 (0.14) (‐0.88) (0.97) (‐0.42) (3.23) (2.37) (3.62) (2.96) (‐0.17) (‐1.35) (0.76) (‐0.82) Days Invested ‐0.00* ‐0.00 ‐0.00* ‐0.00 ‐0.00 0.00 ‐0.00 0.00 ‐0.00* ‐0.00 ‐0.00* ‐0.00 (‐1.67) (‐1.27) (‐1.80) (‐1.26) (‐0.08) (0.51) (‐0.46) (0.67) (‐1.84) (‐1.38) (‐1.92) (‐1.16) log(Total Assets) 0.07 0.13 ‐0.11 0.14 ‐1.06** ‐0.80* ‐1.52*** ‐0.72 ‐0.07 ‐0.04 ‐0.13** ‐0.03 (0.46) (0.95) (‐0.61) (1.01) (‐2.31) (‐1.68) (‐3.18) (‐1.33) (‐1.32) (‐0.88) (‐2.09) (‐0.64)

FE year‐level Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Observations 93 93 93 93 93 93 93 93 93 93 93 93 Chi² 84.09 104.4 61.27 136.3 78.33 81.16 76.91 77.96 83.77 101.3 57.51 114.0 Prob (p>Chi²) 0.000 0.000 0.000644 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.00182 0.000 Endogeneity Chi² 6.691 2.585 13.42 0.336 4.146 2.893 4.268 1.356 4.784 1.533 11.06 0.479 Endogeneity Prob. 0.00969 0.108 0.000249 0.562 0.0417 0.0889 0.0388 0.244 0.0287 0.216 0.000884 0.489 Overidentification Chi² 12.05 20.85 6.515 32.23 13.16 15.72 13.17 18.25 10.54 19.61 5.208 26.27 Overidentification Prob. 0.211 0.0134 0.687 0.000181 0.155 0.0731 0.155 0.0324 0.309 0.0205 0.816 0.00185