Buyout Groups’ Reputational Concerns and Costs of Debt Financing:
Evidence from Bond Offerings by IPO Firms
Rongbing Huang, Jay R. Ritter, and Donghang Zhang* May 31, 2012
Abstract
A popular view is that buyout groups are focused on short-term improvements in operations and wealth redistribution at the expense of long-term value creation. Using bonds offered during 1983-2009 by firms after their initial public offerings (IPOs), we examine the effects of buyout groups (private equity firms) on bond yield spreads, credit ratings, and bond issuers’ dividend and investment decisions. We find that yield spreads on bonds offered after the IPO by buyout-backed IPO firms are on average 67 basis points lower than those on bonds by other IPO firms, after controlling for other issuer and issue risk attributes, in spite of the fact that bond ratings by both Standard & Poor’s and Moody’s are unrelated to whether the issuer’s IPO was buyout-backed. We also provide evidence that buyout-backed IPO firms are less likely to pay dividends and that they invest less than other IPO firms in the fiscal years of bond offerings. Our findings suggest that the reputational concerns of buyout groups help their portfolio firms reduce the agency costs of debt.
Key Words: IPOs, Buyout Groups, Private Equity, Reputation, Agency Costs, Bond Offering
*
Huang is from the Coles College of Business, Kennesaw State University, Kennesaw, GA 30144, Ritter is from the Warrington College of Business Administration, University of Florida, Gainesville, FL 32611, and Zhang is from the Moore School of Business, University of South Carolina, Columbia, SC 29208. Huang can be reached at (678)
797-2081 or rhuang1@kennesaw.edu, Ritter can be reached at (352) 846-2837 or jay.ritter@warrington.ufl.edu, and
Zhang can be reached at (803) 777-0242 or zhang@moore.sc.edu. We thank Daniel Bradley and seminar
participants at the University of South Florida and Peking University for helpful comments. Kris Newcamp and Jenifer Snape provided excellent research assistance.
1 1. Introduction
Buyout groups (private equity firms) have been playing a more and more important role in initial public offerings (IPOs). From 1990 to 2000, buyout groups sponsored 11% of all IPOs in the U.S. For 2001 to 2011, the percentage has increased to 32%. The extant literature suggests that reverse leveraged buyouts (RLBOs) tend to have better financial performance than other IPOs (Degeorge and Zeckhauser (1993), Holthausen and Larcker (1996), Cao and Lerner (2009), and Guo, Hotchkiss, and Song (2011)). Buyout groups potentially play an important role in the firms that they sponsor not only before but also after the IPO. Cao and Lerner (2009) and Cao (2011) report that buyout groups continue to own a large percentage of shares of their portfolio firms and serve on the board of directors during at least the first several years after RLBOs.
Reverse leveraged buyouts, or RLBOs, are IPOs of buyout-backed private firms that were publicly traded and went through public-to-private leveraged buyout transactions. RLBOs are not the only type of IPOs backed by buyout groups. Private equity firms also engage in leveraged buyouts of private firms or divisions of public and private firms and then bring some of them public through IPOs. Jensen (1989) argues that buyout groups bring strong investor monitoring and managerial discipline to their portfolio firms. He suggests that firms that go through leveraged buyouts have a long-term optimal corporate governance structure.1 In contrast, many commentators have argued that the financial
promoters gain at the expense of other stakeholders, including the government through lower taxes due to the tax deductibility of interest payments, rather than creating social value (Shleifer and Summers (1988)).
An unanswered question is whether investor monitoring and improved managerial discipline, which apparently benefit equity holders, come at the expense of other stakeholders. For IPOs, does the superior financial performance of buyout-backed IPOs documented in the literature simply come from the legacy operating improvements due to the leveraged buyout? Or is it at least partly related to the presence of buyout groups after the IPO and their interactions with other stakeholders? In this paper, we shed light
1
Almost all buyout partnerships are structured with a clause that cash or shares must be distributed to the limited partners within 10-12 years of investing. Jensen (1989) does not discuss this mandatory exit feature of the standard partnership contract.
2 on the importance of the long-term presence of private equity firms and the importance of their
interactions with other stakeholders. More particularly, we examine this issue by studying bond offerings after IPOs by firms that are sponsored by buyout groups.
Bondholders are important stakeholders for buyout-backed firms, and the conflicts of interest between bondholders and shareholders are well documented. Warga and Welch (1993) provide evidence that the existing bondholders of a firm are harmed when it is acquired through a leveraged buyout. More generally, buyout groups, as shareholders, have an incentive to push their portfolio firms to make
investment decisions to the detriment of the firms’ bondholders. Equity can be viewed as a call option on the firm, and the option’s value increases when the volatility of the underlying assets increases. Therefore, shareholders of a levered firm have an incentive to take risky projects to transfer wealth from bondholders (Jensen and Meckling (1976)). This risk-shifting problem is more severe when a firm’s managers are incentivized to pursue short-term gains in their firm’s stock price. In addition to investment decisions, buyout groups could also adopt an aggressive payout policy that could potentially harm bondholders. There is anecdotal evidence that buyout groups sometimes pay themselves big dividends shortly before the IPOs of their portfolio firms.
Buyout groups play an important role in our sample firms that conducted bond offerings during the first five years after the IPO. We use hand-collected data on post-IPO ownership and directorship from EDGAR on the Securities and Exchange Commission (SEC) website. Consistent with Cao and Lerner (2009) and Cao (2011), for a firm in our sample, buyout groups on average own more than 20% of the firm’s equity at the end of the first five years after the IPO. For more than 90% of the firms after the first two years since the IPO, and for more than 60% of the firms after the first five years, buyout groups still have at least one director on the board of a sponsored firm. Our evidence is consistent with the notion that buyout groups are powerful shareholders of their portfolio firms, and they are potentially able to pursue their own interests at the expense of bond holders. If bond investors are concerned about such power and the incentive of buyout groups to expropriate them, they will “price protect” themselves. We thus have the wealth expropriation hypothesis: Because buyout groups have the incentive and possible
3 power to expropriate the bondholders of their portfolio firms, such possibilities increase the ex ante cost of public debt financing of the buyout-backed IPO firms.
The reputational concerns of buyout groups can help to alleviate their incentives to expropriate bondholders. Buyout groups often deal with bond investors repeatedly. If one firm owned by a buyout group exploits its bondholders, all firms owned and to be owned by the buyout group will likely face a higher risk premium on their bonds and more restrictive covenants (see, e.g., Diamond (1989), Klein and Leffler (1981), Shapiro (1983), Fang (2005), and Massa and Zaldokas (2011)). Buyout groups’
reputation capital can be viewed as the present values of buyout groups’ (significant) share of the savings due to lower borrowing costs for their portfolio firms. To protect their reputation capital, buyout groups are likely to avoid opportunistic behavior that hurts bondholders. Buyout groups’ reputational concern would also motivate them to help their portfolio firms adopt corporate governance and managerial compensation structures that are friendly to bondholders. Buyout groups are even likely to use their own resources to help their portfolio firms avoid costly bankruptcies (see Moody’s (2009, 2010)). Since all these arguments are rooted in buyout groups’ protection and/or acquisition of reputation capital, we call them the reputation acquisition hypothesis.
We first test the wealth expropriation hypothesis and the reputation acquisition hypothesis by examining the determination of credit ratings and yield spreads of bond offerings by IPO firms. We study bond offerings after IPOs because information on the involvement of buyout groups in IPO firms is publicly available.
Unlike bank loans, publicly issued bonds are almost always rated by both Standard & Poor’s (S&P), Moody’s and, increasingly, Fitch. We can thus study rating agencies’ view of the credit risk of bonds offered by buyout groups’ portfolio firms. Under the reputation acquisition hypothesis, buyout sponsorship of bond-issuing IPO firms will result in higher ratings, everything else being equal. Under the wealth expropriation hypothesis, the predictions would be the opposite.
It is important to note that even if either of the hypotheses is true, we will not necessarily find a statistically significant relation between buyout sponsorship and credit ratings. First, credit ratings can be
4 biased because of imperfections in the rating process (e.g., John, Lynch, and Puri (2003)). The recent controversies over ratings given to mortgage-backed securities have amply demonstrated this. Second, since rating agencies do not buy the bonds with their own funds, they do not always have an incentive to do adequate due diligence and provide unbiased ratings (e.g., Griffin and Tang (2011)). Third, if rating agencies believe that buyout groups’ reputational concern largely offsets their wealth expropriation incentive, then we would find an insignificant relation between buyout sponsorship and credit ratings.
Bond investors have their vote through determining the required yields on bond offerings. Besides the major credit rating agencies, fixed income analysts at many financial research firms,
including investment banks, provide advice to bond investors. Bond investors, such as bond mutual funds and hedge funds, also often do their own research. If the wealth expropriation hypothesis dominates and investors view bonds offered by buyout groups’ portfolio firms as being riskier, they will require a higher promised return on the bonds. On the other hand, if the reputation acquisition hypothesis dominates and bond investors recognize the value of the buyout groups’ reputational concerns, buyout sponsorship will be associated with lower bond yield spreads, everything else being equal.
We use bonds offered during 1983-2009 by IPO firms to study the effect of buyout sponsorship on credit ratings and yield spreads. Since buyout groups often continue to play an important role in their portfolio firms in the first several years after the firms’ IPOs, we focus on bonds offered no more than five years after IPOs. Because we require bond issuers’ stock returns during the one year period prior to bond offerings, we also exclude bonds offered during the first year after the IPO. We thus focus on a sample of 431 bonds issued at least one year but no more than five years after IPOs.
We estimate ordered logit models for the determination of S&P and Moody’s ratings of these bonds at the time of issuance. After controlling for borrower and issue characteristics, we find that bonds offered by buyout-backed IPO firms and those by other IPO firms receive similar credit ratings. This finding suggests that the rating agencies view bonds offered after buyout-backed IPOs and other IPOs as having similar credit risk.
5 We estimate Ordinary Least Squares (OLS) regressions for the determination of offering yield spreads of these bonds. We find that yield spreads on bonds issued by buyout-backed IPO firms are on average 67 basis points lower than those on bonds issued by other IPO firms after controlling for
observed issuer and issue characteristics and unobserved characteristics as captured by credit ratings. For an average bond offering of $350 million by our sample IPO firms, the 67 basis point lower yield spread represents a saving of $2.35 million per year on interest payments. For an average maturity of ten years of the bond offerings in our sample, this can be translated into a $23.5 million savings if the bond is not retired early. This statistically and economically significant effect of buyout sponsorship on bond yield spreads suggests that investors view bonds issued after buyout-backed IPOs as being less risky than those issued after other IPOs. This provides strong support for the reputation acquisition hypothesis.
An issuing firm can use bond covenants to lower the yield on its bond. As a robustness test, we analyze whether buyout-backed firms and other firms use bond covenants differently, and if there is a difference, whether the difference explains the lower cost of debt for buyout-backed firms. We follow Billett, King, and Mauer (2007), Chava, Kumar, and Warga (2010), and Mansi, Qi, and Wald (2011) and construct an index for the use of bond covenants. We find that buyout-backed IPO firms do not use more covenants in their bond contracts, and that the use of bond covenants does not affect the relations between bond yields and buyout sponsorship that we have identified.
The bond yield regression results are consistent with the reputation acquisition hypothesis, suggesting that, due to their reputational concerns, buyout groups adopt corporate governance structures and policies that are friendly to bondholders. To corroborate the results on bond yields and to shed further light on the importance of the presence of buyout groups after IPOs, we test two more hypotheses. The over-investment hypothesis argues that buyout-backed IPO firms invest more and take on riskier projects around bond offerings. The excessive dividend hypothesis suggests that buyout-backed IPO firms are more likely to pay dividends. The rationale for these two hypotheses is simple. With the significant infusion of capital through bond offerings, buyout groups as powerful shareholders could take
6 on more and riskier projects or pay dividends if their only goal is to maximize their short-term gains.2 We find that buyout-backed IPO firms are less likely to pay dividends and invest less than other IPO firms during the fiscal years of the bond offerings. These findings, taken together with our earlier findings of the effects of buyout sponsorship on yield spreads of bonds, suggest that buyout groups do not engage in wealth expropriation via their portfolio firms. Buyout groups’ reputational concerns help their portfolio firms even after the firms’ IPOs.
The contribution of the paper is three fold. First, the increasing importance of private equity in IPOs has drawn researchers’ attention to the influence of private equity firms on the stock and operating performances of a firm after its IPO (Cao and Lerner (2009), Cao (2011), and Guo, Hotchkiss, and Song (2011)). External debt financing shortly after the IPO provides an important way to shed light on how private equity firms can influence a firm after the IPO. Our paper thus provides important evidence on the interactions between private equity firms and bond investors and the effects of such interactions on external financing.
Second, this paper is related to the literature on the cost of debt and corporate governance. Empirically, several papers find supportive evidence that shareholder type, corporate governance, and managerial compensation are significantly related to the cost of debt. Anderson, Mansi, and Reeb (2003) find that founding family ownership is negatively related to the cost of debt. Ashbaugh-Skaife, Collins, and LaFond (2006) present evidence that firms with stronger corporate governance receive higher credit ratings from Standard and Poor’s. Both papers suggest that firms with founding families are less likely to be motivated by short-term gains in their stock prices and are therefore more likely to avoid costly bankruptcies. Oritz-Molina (2006) provides evidence that managerial ownership is positively related to at-issue yield spreads on corporate bonds, and that bond investors anticipate higher risk-taking incentives from managerial stock options than from equity ownership. Francis, Hasan, John, and Waisman (2010)
2
We assume that the underinvestment problem is not a concern around bond offerings since the issuing firm has or is expected to have a significant amount of fresh capital infusion through the public bond offering. Existing empirical studies generally document a tendency of security issuers to over-invest rather than under-invest (e.g., Titman, Wei, and Xie, 2004) and Billett, Flannery, and Garfinkel (2011)).
7 find that state antitakeover laws tend to reduce the cost of debt. They suggest that state antitakeover laws help to align the interest of managers with that of bondholders and thus reduce the risk-shifting and under-investment problems. In a study of 3,468 firms in 22 countries, Lin, Ma, Malatesta, and Xuan (2011) provide evidence that firms in which a major blockholder has more voting rights than cash flow rights pay a higher interest rate on bank loans. We provide evidence on whether the reputational concerns of increasingly important private equity firms can alleviate their expropriation incentives and lower the cost of debt for their portfolio firms.
Finally, this paper adds to our understanding of private equity firms, especially their reputational concerns and external financing costs. In a closely related paper, Demiroglu and James (2010) present evidence that the reputational concerns of buyout groups help to reduce the agency conflicts between shareholders and banks. Using a sample of 180 public-to-private LBOs in the US from January 1, 1997 to August 15, 2007, they find that borrowing costs are lower for LBO loans sponsored by high reputation buyout groups.
Our paper is also related to two concurrent papers. Hotchkiss, Smith, and Strömberg (2011) show that private equity-backed firms are not more likely to default on their loans, everything else being equal. Furthermore, a buyout-sponsored firm that is in bankruptcy is more likely to survive due to the financial and reputational capital of the sponsoring firm. Cain, Davidoff, and Macias (2011) provide evidence that some private equity firms do have to incur higher contract termination costs when they fail to execute an agreed buyout contract and suffer a reputational loss. Our paper adds to this growing literature in at least two important regards. First, the existing literature largely focuses on bank loans, while we study publicly issued bonds and shed light on how bondholders and credit rating agencies view the presence of buyout groups. Second, the literature examines buyout groups’ target firms in their private status, while we examine these firms after IPOs and help to understand whether and how buyout groups have long-lasting influence on their portfolio firms.
The rest of this paper is organized as follows. Section 2 describes the data. In Sections 3, we report the regression results on the effect of buyout sponsorship on credit ratings and yield spreads. We
8 discuss the influence of buyout groups on investment and dividend policies of their portfolio firms in Section 4. Robustness checks are in Section 5, and Section 6 concludes.
2. Data and Descriptive Statistics
2.1. Sample Construction and Distribution
We use Thomson Reuters’s SDC Global New Issues database to identify all public and 144A straight bond offerings of U.S. domestic non-financial firms from 1983-2009. Our sample of bond offerings starts from 1983 because Moody’s began issuing notch ratings after April 1982, instead of just letter ratings (see, e.g., Livingston and Zhou (2010)). We identify 12,287 public and 144A straight bond offerings that can be linked to the Center for Research in Security Prices (CRSP) database. Excluding floating rate, putable, exchangeable, perpetual, unit, and subordinated issues reduces the sample to 9,409 issues. Key issue characteristics (ratings by both Moody’s and S&P, maturity, gross proceeds, and yield to maturity) are available for 7,926 issues.
The issuers of 7,744 issues can be found in Standard & Poor’s Compustat using the links provided in the CRSP/Compusat merged database. We obtain IPO information from the SDC database for firms that went public during 1980-2009 that account for 1,457 bond issues.3 Lagged values of key firm characteristics from CRSP/Compustat are available for a total of 1,299 post-IPO bond issues by 424 firms, including 431 issues by 209 firms after at least one year and within five years since the IPO. For the rest of the paper, we call the 1,299 bond issues, which include bond offerings at any time after one year since the IPO, the extended sample, and we call the 431 issues that are between one and five years after the IPO the focused sample or the (IPO+1, IPO+5] sample.4
3
We do not include IPOs prior to 1980, because we do not know whether they are backed by buyout groups, although anecdotal evidence suggests that very few were. We thank Jerry Cao for kindly sharing his classifications of buyout-backed IPOs from 1980-2009. As is common in the literature, closed-end funds, Real Estate Investment Trusts (REITs), Special Purpose Acquisition Companies (SPACs), banks and savings & loans (S&Ls), American Depositary Receipts (ADRs), units, partnerships, and IPOs with an offer price of less than $5 are excluded. We also exclude other financial IPOs because we do not examine bond offerings by financial firms in this paper.
4
For the focused sample, United Parcel Service Inc. (UPS) is the most frequent issuer and had 87 of the 431 issues.
9 We report the sample distribution and the summary statistics for both the extended sample and the focused sample in this and the next sub-sections. Bond and bond issuer characteristics can be quite different depending on whether the issuer’s IPO has buyout sponsorship. To highlight the differences between the two categories of bonds, we also report the sample distribution and the summary statistics for each category separately.
Figure 1 reports the sample distribution sorted on several different dimensions. Graph A of Figure 1 shows the sample distribution sorted by IPO type and the number of years from the IPO to the bond offering date. Newly public firms often have greater financing needs and are more likely to raise external capital (Helwege and Liang (1996)). It is interesting to know how quickly these firms start to access the public debt market. Firms offer bonds to the public even during the first several years after their IPOs. For example, during the second year after their IPO, the buyout-backed firms have 25 bond offerings and the other (non-buyout-backed) firms have 118 bond offerings. Only a small number of bonds are offered more than 13 years after buyout-backed IPOs, partly because a firm would have had to go public before 1997 to compete 13 post-IPO years by December 31, 2009.
As the time since the IPO increases, the influence of buyout groups in the IPO firms is likely to decrease. We thus focus on the period of after one year but no more than five years since the IPO, during which period the buyout-backed firms have 93 bond offerings and the other firms have 338 bond
offerings, or a total of 431 bond offerings. For comparison purposes, we also present some results for the extended sample, which includes all of the 1,299 bonds offered at least one year after the IPO.
Graphs B and C of Figure 1 show the distribution of the (IPO+1, IPO+5)] sample and the extended sample, respectively, by IPO type and credit ratings. Note that the lowest S&P rating and the lowest Moody’s rating for the bonds in the extended sample are CCC and Caa3, respectively. Graph B
whether we include the UPS issues or not. Among the 209 firms, 142 firms had one bond issue, 37 firms had two issues, and 30 firms had more than two issues. In our regressions, we correct the standard errors of the coefficients for potential clustering at the firm level.
10 shows the distribution of the bonds in the (IPO+1, IPO+5] sample.5 Nearly 45% and 48% of the 431 bonds are rated below investment grade by S&P and Moody’s, respectively. The bonds offered by the buyout-backed IPO firms are more likely to be rated speculative grade than the bonds by the other firms, perhaps because buyout groups can help high risk firms offer bonds to the general public. For example, based on the S&P rating, roughly 69% of the bonds by buyout-backed IPO firms and 39% of the bonds by the other firms are rated speculative grade. In the (IPO+1, IPO+5)] sample, the non-buyout-backed IPO firms have 86 AAA rated bonds. In contrast, the buyout-backed firms have only one bond with an S&P rating of A+ or higher (rated AA).
Graph C shows the distribution of the bonds in the extended sample by IPO type and credit ratings. About 48% and 50% of the 1,299 bonds are rated below investment grade by S&P and Moody’s, respectively. For the extended sample, the bonds by the buyout-backed IPO firms continue to receive lower ratings than the bonds by the other firms, and about 61% of the bonds by the buyout-backed IPO firms and 45% of the bonds by the other firms are rated below investment grade by Standard and Poor’s. Only two bonds issued by the buyout-backed firms have an S&P rating or A+ or higher, and none have a Moody’s rating of A1 or higher.
2.2. Variable Definitions and Summary Statistics
We first briefly describe the variables used in our credit rating and yield regressions in this sub-section. We will describe the additional variables used in our investment and dividend regressions later. Following the literature (e.g., Anderson, Mansi, and Reeb (2003) and Ashbaugh-Skaife, Collins, and LaFond (2006)), we convert letter ratings by Standard and Poor’s and Moody’s into scores with the highest rating (AAA by S&P and Aaa by Moody’s) receiving a value of 19 and the lowest rating (CCC- or Caa3 in our sample) receiving a value of 1.6 We use these rating scores as the dependent variable in our credit rating regressions. We denote the S&P rating score as SP_RATING and the Moody’s rating
5
Moody’s rating has a similar pattern to that of S&P’s, and we mainly focus on the S&P rating in our discussion. For example, all of the 86 AAA rated (by S&P) and 87 Aaa rated (by Moody’s) bonds were issued by UPS. Only one of the 87 issues by UPS was rated below AAA by Standard and Poor’s.
6
Note that we do not have any bond with a rating of below CCC- or Caa3 in our final samples. It is virtually impossible for firms to offer new bonds with a rating of below CCC- or Caa3 to the public.
11 score as MDY_RATING. The dependent variable in our yield spread regressions is the percentage yield spread (YIELD_SPREAD (%)), defined as the difference between the bond’s percentage yield-to-maturity and the percentage yield-to-yield-to-maturity on the constant yield-to-maturity Treasury security with a similar maturity at the time of issuance.
Among the independent variables, we focus on a dummy variable (BUYOUT) that equals one for a bond offered by a firm that has its IPO sponsored by one or more buyout groups, and zero otherwise. Note that the buyout-backed IPOs include both reverse leveraged buyouts, or RLBOs, and IPOs of buyout-backed private firms or divisions of public or private firms that have never gone through public-to-private transactions. Strömberg (2007) shows that most buyout activities consist of acquisitions of private firms rather than public firms.
We follow the literature to choose the control variables in credit rating and yield spread regressions (e.g., Anderson, Mansi, and Reeb (2003), Ashbaugh-Skaife, Collins, and LaFond (2006), Blume, Lim, and MacKinlay (1998), and Livingston and Zhou (2002, 2010)). Table 1 reports the detailed definitions and the summary statistics (means, medians, and standard deviations) of these variables.
Given the limited space in the table, we provide detailed discussions on the interest coverage ratio (ICR) variables here. We use four interest coverage ratio variables, ICRi, t-1 (i=0, 5, 10, 20), where the subscript t-1 refers to the fact that the variable is measured for the fiscal year before the bond offering year, to capture the non-linear effect of the ICR on credit risk (see Ashbaugh-Skaife, Collins, and LaFond (2006) and Blume, Lim, and MacKinlay (1998)). The ICRt-1 is calculated as (operating income after depreciation + interest expense) / interest expense during the fiscal year immediately prior to the bond offering date. We then set ICRt-1 to zero if it is negative and to 100 if it is greater than 100, because a value less than zero or greater than 100 is unlikely to convey additional information. We define ICRi, t-1 (i=0, 5, 10, 20) as follows:
12
ICR0, t-1 ICR5, t-1 ICR10, t-1 ICR20, t-1
0≤ICRt-1 <5 ICRt-1 0 0 0
5≤ICRt-1 <10 5 ICRt-1 – 5 0 0
10≤ICRt-1 <20 5 5 ICRt-1 – 10 0
20≤ICRt-1 <100 5 5 10 ICRt-1 – 20
Overall, Table 1 suggests that the buyout-backed IPO firms in the (IPO+1, IPO+5] sample are riskier than the buyout-backed IPO firms in the extended sample, and that the buyout-backed IPO firms are riskier than the other IPO firms in both samples, although the risk difference between the two types of firms is smaller in the extended sample. Because the sub-sample of non-buyout-backed IPOs includes 87 bonds by United Parcel Service Inc. (UPS), we also report the summary statistics for the sub-sample after excluding the UPS issues.
Panel A of Table 1 reports the conditional and unconditional means and medians for the (IPO+1, IPO+5] sample. Regardless of whether the UPS issues are excluded, bonds issued by buyout-backed firms have lower rating scores, indicating lower credit ratings. For both S&P and Moody’s ratings, the bonds offered by buyout-backed IPOs have a mean value slightly above 7, which is BB- for S&P ratings and Ba3 for Moody’s. For the bonds offered by non-buyout backed IPOs, the average rating score, with AAA=19, when the UPS issues are included is slightly above 11, or BBB for S&P and Baa2 for Moody’s, and the average score drops to 8.35 when the UPS issues are excluded. The mean YIELD_SPREAD (%) is 3.28% on the bonds offered after buyout-backed IPOs and 2.43% (2.97%) on the bonds after the other IPOs if the UPS issues are included (excluded). The difference of 0.85% (0.31%) is economically significant, especially if we compare it to the mean values. The medians of YIELD_SPREAD (%) on the two categories of bonds are 2.67% and 1.38%, respectively, with the difference being 1.29%. The
difference in the medians shrinks to 0.13% if we exclude the 87 UPS issues.
The mean value of a dummy variable equals the fraction of observations for which the dummy variable equals one. For example, about 18% of the bonds by the buyout-backed IPO firms are shelf registered. The bonds by the buyout-backed IPO firms are less likely to be shelf registered and more
13 likely to be offered in the Rule 144A market. These results are consistent with the findings in the
literature that the Rule 144A market allows low credit quality firms to issue speculative grade bonds quickly to meet unexpected financing needs (Denis and Mihov (2003), Fenn (2000), Livingston and Zhou (2002), and Huang and Ramirez (2010)).
The buyout-backed IPO firms are smaller than the other bond issuers, as measured by the market capitalization, especially if the UPS issues are included. Both the buyout-backed and the other IPO firms that conduct bond offerings are generally much older than the overall IPO firms, which have a median age of about eight years, as reported in Table 2 of Loughran and Ritter (2004) and updated on Jay Ritter’s website. Non-buyout-backed IPO firms are much more likely to be dividend payers, even if we exclude UPS. The issuers of bonds after buyout-backed IPOs are more likely than the other issuers to have incurred a loss in the fiscal year prior to the bond offering date. On average, the buyout-backed IPO firms have lower interest coverage ratios ICR0, t-1- ICR10, t-1 than the other IPO firms, while the opposite is true for ICR20, t-1. Note that a higher interest coverage ratio is desirable. The buyout-backed firms have higher mean and median leverage ratios and betas and lower mean and median market-to-book ratios than the other firms.
Panel B of Table 1 reports the summary statistics for the extended sample. The bonds issued by the buyout-backed firms continue to have lower credit ratings and higher yield spreads than the bonds by other IPO firms. The differences in the issuer characteristics between the two categories of bonds also suggest that the buyout-backed IPO firms are generally riskier than the other firms, although the differences are often smaller for the extended sample.
2.3. Ownership and Directorship for Buyout- and VC-Sponsored IPO Firms
The wealth expropriation and the reputation acquisition hypotheses, as well as the discussions of the regression results in Sections 3 and 4, rely on an implicit assumption that buyout groups play an important role in their portfolio firms after the IPO. Although anecdotal evidence and some limited evidence in the literature suggest that this assumption is valid, it is useful to provide direct evidence for the IPO firms in our sample. Because we make some comparisons between buyout groups and venture
14 capital (VC) sponsors in our robustness checks, and also because it is an interesting digression to know how VC firms do after the IPO of their sponsored firms, we collect data from EDGAR on the SEC website for all buyout- and VC-backed IPO firms starting on May 16, 1996 that did bond offerings and are thus in our (IPO+1, IPO+5] sample. We start at May 16, 1996 because it is the offer date of the first IPO for which the IPO prospectus is available through EDGAR. We only include IPOs that have IPO prospectuses in EDGAR so that we can use the prospectus to determine the names of the buyout or VC sponsors. We have 46 IPOs, including 34 buyout-backed and 12 VC-backed ones, that have an IPO prospectus in EDGAR.7 For these 46 IPOs, we read through their IPO prospectus and the first five years’ proxy statements to collect the ownership and directorship information for their IPO sponsors and other institutional investors.
We report the ownership and directorship information for the 46 IPOs in Table 2. Panel A of Table 2 reports the information for the lead investor/sponsor for buyout-sponsored IPOs, and Panel B does it for VC-sponsored IPOs. We define a lead investor or a lead sponsor as the investor that has the largest equity ownership immediately after a firm’s IPO. For buyout-backed IPO firms in Panel A, the average equity ownership of the lead buyout sponsor remains above 20% for the first five years after the IPO, while the median remains above 10% for the first four years. Note that due to “club” deals in which several buyout firms jointly control a portfolio company, the lead buyout firm’s average ownership share is lower than the combined shares (Demiroglu and James (2010)). The mean and median numbers of directors on the board that are affiliated with the lead buyout sponsor remain at one or more for the first five years. For more than 60% of the sponsored firms for the first five years (90% for the first two years), the lead buyout sponsor has one or more board seats. This ownership and directorship pattern validates the implicit assumption for our hypotheses that buyout firms remain important stakeholders for their sponsored firms after IPO.
7
We have 209 IPO firms that issued bonds for the (IPO+1, IPO+5] sample, and 91 of them had an IPO after May 16, 1996. 46 of the 91 firms are sponsored by private equity or VC.
15 For VC-backed IPOs in Panel B of Table 2, the lead VC sponsor unloads its equity stake at a faster rate and the average and median ownership only remains above 10% for the first year. However, the median number of lead VC-affiliated directors remains at one for the first five years after the IPO, and nearly 90% of the firms have their VC-affiliated directors on the board for the first four years after IPO. Because few VC-sponsored IPO firms issue bonds to the public within five years of the IPO, we want to caution that the number of VC-backed firms for which we have information through EDGAR is very small – only 12 firms. But the data do suggest that lead VC sponsors remain influential for the first few years after the IPO.
For both buyout- and VC-backed firms, institutional investors other than the lead sponsor can and do get involved. We define the institutional investors, excluding the lead as defined above, that have reported equity ownership in the IPO prospectus as co-investors. We report the ownership and
directorship information for the co-investors in Panel C of Table 2. Note that we set the ownership and directorship at zero if a firm does not have co-investors. Panel C also reports the information on how new institutional investors, defined as those that do not appear in the IPO prospectus, gradually increase their ownership after a firm’s IPO. For both buyout- and VC-backed IPOs, co-investors have a significant ownership stake before and immediately after the IPO. For a majority of the firms that they invest in, the co-investors also have their affiliated directors on the board for the first few years after the IPO. For new institutional investors, VC-backed firms seem to attract them at a faster pace.
3. Buyout Sponsorship, Credit Ratings, and Yield Spreads
3.1. The Effect of Buyout Groups on Credit Ratings
Credit ratings are useful to issuers, investment banks, and investors. Rating agencies do extensive research on the credit worthiness of LBOs. A special comment by Moody’s dated November 2009 finds that companies affiliated with the 14 largest buyout groups have experienced similar default rates to other companies over the course of the January 2008 – September 2009 period (see Moody’s (2009)). Another special comment by Moody’s dated March 2010 finds that nearly half of U.S.
non-16 financial corporations that defaulted in 2009 had private equity sponsors and that creditors of private equity-backed companies may realize better recoveries than other creditors (see Moody’s (2010)). Neither comment fully controls for other issue and issuer risk attributes and both of Moody’s comments are based on a sample concentrated on a short period of time during which a major financial crisis occurred. In this section we do multivariate analysis of the effect of buyout groups on credit ratings and yield spreads controlling for all related issue and issuer risk attributes using bond offerings over a longer period of time. We are thus able to make more robust statistical inferences on the role of buyout groups in bond offerings of their portfolio firms.
We estimate several variations of the following equation to evaluate the effect of buyout groups on credit ratings. Note that in this and all of the following equations, a subscript t-1 for a variable indicates that the variable is measured using information for the fiscal year prior to the bond offering.
(1)
SP_RATING/MDY_RATING = f (BUYOUT dummy, DEFAULT_SPREAD,
LN(MATURITY), SHELF dummy, RULE_144A dummy , FIRST_BOND dummy,
LN(NUM_BONDS), LN(MARKET_CAP)t-1, LN(AGE), DIV_PAYERt-1 dummy, ROAt-1,
LOSSt-1 dummy, ICRi, t-1 (i=0,5,10,20), LEVERAGE_RATIOt-1, BETAt-1, STD_RETURNt-1,
RETURNt-1, MARKET_TO_BOOKt-1, TANGIBILITYt-1, UTILITYt-1 dummy, YEAR
dummies).
Since the credit rating score takes 19 ordinal (i.e., categorical and ordered) values, we estimate ordered logit regressions. Note that the actual values of the rating score in the ordered logit regressions are irrelevant except that larger values correspond to higher rating categories.
Table 3 reports the results of the ordered logit regressions. The first two regressions use the (IPO+1, IPO+5] sample of 431 bond issues and the last two regressions use the extended sample of 1,299 bond issues. The dependent variable is the rating score by S&P in regressions (1) and (3), and the rating score by Moody’s in regressions (2) and (4). We also estimate these regressions by excluding the UPS issues and our major results (not tabulated) are essentially the same.
We are particularly interested in the coefficient on the BUYOUT dummy variable. The
17 suggest that, after controlling for observable issue and issuer characteristics, neither S&P nor Moody’s views bonds offered by the buyout-backed IPO firms as being riskier than bonds offered by the other IPO firms.
The coefficients for the control variables are largely expected and are consistent with the literature. The coefficient for LN(PROCEEDS) is negative and statistically significant in all four regressions, suggesting that holding other observable characteristics constant, larger bond offerings receive lower ratings, perhaps because larger bond offerings are likely to increase the interest burden and the default risk of the issuers. The coefficient for the RULE_144A dummy is negative in all four
regressions and statistically significant in regressions (1), (3), and (4). The negative coefficient suggests that bonds offered in the Rule 144A market receive lower credit ratings, consistent with the finding in the literature that low credit quality firms issue bonds in the 144A market due to desire for the speed of issuance (Fenn (2000) and Huang and Ramirez (2010)).
The coefficients for LN(NUM_BONDS) and the FIRST_BOND dummy variable are statistically significant at the 1% or 5% levels for the focused sample, but they are insignificant for the extended sample. The unexpected positive relation between the FIRST_BOND dummy and ratings is perhaps because rating agencies want to attract first-time issuers. The positive relation between
LN(NUM_BONDS) and credit ratings suggests that frequent issuers receive higher credit ratings.8 This is perhaps because rating agencies favor their frequent customers or because frequent interactions have resulted in less information asymmetry between rating agencies and the issuers.
The positive relation between LN(MARKET_CAP)t-1 and ratings suggests that bonds offered by larger firms receive higher credit ratings. This is expected because larger firms are likely to be less risky. The coefficients for the DIV_PAYERt-1 dummy are statistically significant for the extended sample at the 1% level, while being only marginally significant for the focused sample. These findings are consistent with the hypothesis that being able to pay dividends is more relevant as a signal of stable profitability for
8
When the 87 UPS issues are excluded from the (IPO+1, IPO+5] sample, the coefficient on LN(NUM_BONDS) in regression (1) changes from 0.64 to 0.49 and is statistically significant at the 5% level.
18 older and more mature firms. Profitable firms should have lower default risk and thus higher credit ratings. Consistent with this expectation, the coefficient on ROAt-1 is positive and statistically significant in regression (2). The coefficient for the LOSSt-1 dummy in regression (1) is negative and statistically significant at the 10% level, suggesting that firms losing money receive lower credit ratings.
The positive coefficient on ICR5, t-1 is expected since higher interest coverage ratios imply greater capacities for making interest payments and thus lower default risk. The coefficients for ICR10, t-1 and ICR20, t-1 are only statistically significant for the extended sample, suggesting that the nonlinearity of the interest coverage ratio is more relevant for the issuing firms with a longer public record. Since firms with a higher stock return volatility are riskier, the negative relation between STD_RETURNt-1 (%) and credit ratings is also expected. Firms with a higher stock market valuation should receive higher credit ratings. Inconsistent with this expectation, there is some evidence that firms with a higher market-to-book ratio and pre-issue stock return receive lower credit ratings, likely because rating agencies are concerned about the large financing needs of growth firms, and the regression specification also controls for
LN(MARKET_CAP)t-1.
3.2. The Effect of Buyout Groups on Yield Spreads
Credit rating agencies and other bond market analysts are likely to have different opinions about the credit worthiness of a bond. Using a sample of over 3,200 private equity-backed companies acquired in a buyout or similar transaction between 2000 and 2009 and held through 2008-2009, a publication dated March 2010 by the Private Equity Council finds that, during the financial crisis of 2008-2009, private equity-backed businesses defaulted at less than one-half the rate of comparable companies: 2.84% versus 6.17% per year (see Thomas (2010)). In this section we study bond investors’ view of buyout groups’ role in their portfolio firms’ post-IPO bond offerings. We hope to shed light on the debate on whether buyout groups are associated with riskier debt (or reckless leverage in light of the context of the great recession of 2008-2009). More importantly, we use the bond offerings by buyout-backed IPO firms to shed light on how buyout groups continue to work with their portfolio firms and other investors even after their IPOs.
19 If the wealth expropriation hypothesis is more relevant and bond investors are more concerned with the wealth expropriation incentives of buyout groups, these bond investors would view bonds offered after buyout-backed IPOs as being riskier than bonds offered after other IPOs. In turn they will require a higher risk premium on the bonds offered after buyout-backed IPOs. On the other hand, if the reputation acquisition hypothesis is more relevant and bond investors have developed a trust with buyout groups, the investors in bonds issued by buyout-backed firms would face less default risk and a higher recovery rate if default does happen. They will then charge a relatively lower yield on the bonds offered after buyout-backed IPOs. To distinguish these competing arguments, we estimate several variations of the following equation:
(2)
YIELD_SPREAD(%) = f (BUYOUT dummy, DEFAULT_SPREAD, LN(MATURITY),
SHELF dummy, RULE_144A dummy, FIRST_BOND dummy, LN(NUM_BONDS),
LN(MARKET_CAP)t-1, LN(AGE), DIV_PAYERt-1 dummy, ROAt-1, LOSSt-1 dummy, ICRi, t-1
(i=0,5,10,20), LEVERAGE_RATIOt-1, BETAt-1, STD_RETURNt-1, RETURNt-1,
MARKET_TO_BOOKt-1, TANGIBILITYt-1, UTILITYt-1 dummy, YEAR dummies,
SP_RATING_RES, MDY_RATING_RES).
In the previous sub-section, we examined the variables that are expected to explain credit ratings. In this sub-section, we continue to include these variables as independent variables in the yield spread regressions defined in Eq. (2). If bond investors and credit rating agencies have the same interpretation of information, then statistically significant variables in credit rating regressions will continue to be
statistically significant with an opposite sign in yield spread regressions that do not include credit ratings, while statistically insignificant variables will remain statistically insignificant.
Credit rating agencies such as Standard & Poor’s and Moody’s use information beyond
CRSP/Compustat to evaluate credit risk. Controlling for credit ratings in yield spread regressions should help to sharpen our explanation for the determination of yield spreads. However, if credit ratings are included as additional independent variables in yield spread regressions, they are likely to pick up the effects of the other independent variables. Similar to Anderson, Mansi, and Reeb (2003), we thus include purged S&P and Moody’s ratings as additional independent variables in our yield spread regressions to
20 avoid this problem. The purged S&P rating (SP_RATING_RES) is the residual from an OLS regression with the S&P rating as the dependent variable and the independent variables used in the previous sub-section as independent variables. Thus, the purged S&P rating is orthogonal to the independent variables. The purged Moody’s rating (MDY_RATING_RES) is the residual from an OLS regression that uses the Moody’s rating as the dependent variable and further includes the S&P rating, in addition to the other independent variables, as an independent variable. Thus the purged Moody’s rating is also orthogonal to the S&P rating.
Table 4 reports the regression results for the determination of yield spreads. We analyze both the (IPO+1, IPO+5] sample and the extended sample. But to save space, we focus on the (IPO+1, IPO+5] sample in the table and in our discussions. In all of the four regressions in Table 4, year dummy variables are included to capture changes in the macroeconomic environment across time. For brevity, the
coefficients and the t-statistics for the year dummies are not reported.
Regressions (1), (2), and (3) are estimated for the (IPO+1, IPO+5] sample, and regression (4) is estimated for the extended sample. These regressions are also estimated after excluding the 87 UPS issues. Since the major results remain essentially the same, they are not tabulated. We use regression (1) as the baseline regression. The coefficient for the BUYOUT dummy variable in regression (1), -0.67, is statistically significant at the 1% level. The magnitude of this coefficient suggests that yield spreads of bonds offered by buyout-backed IPO firms are on average 67 basis points lower than bonds by other firms (e.g., 1.94% versus 2.61%). Given the average proceeds of $350 million for the bonds issued by the buyout-backed IPO firms in the sample, the reduction in the yield spread by 67 basis points represents average savings of roughly $2.35 million each year for an average bond issue.
We include NET_DEBTt, which is defined as the change in the book value of debt (excluding convertible debt) during the bond offering fiscal year scaled by the beginning of year assets, as an additional control variable in regression (2). The use of current bond offering proceeds could affect the risk level of the firm. For example, it could be less risky if the proceeds are used to retire senior debt compared to the proceeds being used to take on risky projects. This effect may not be captured by other
21 control variables such as lagged leverage ratios. Furthermore, the issuing firm could also have an external financing plan in place at the bond offering and the expected future debt offerings can affect the risk level of the current bond offering. For these reasons, we include the net debt issuance as an additional control variable in regression (2). We do not include NET_DEBT in the baseline regression because this variable is partly forward-looking and could introduce a look-ahead bias.
The coefficient on NET_DEBTt is statistically indistinguishable from zero, suggesting that net debt issuance during the same fiscal year has little impact or has little additional information on the current bond yield. Not surprisingly, the coefficient for BUYOUT in regression (2) also remains largely unchanged, both statistically and economically.
Since the literature suggests that issuing firms could simultaneously determine yield spreads and other issue characteristics (e.g., issue size, maturity, registration method, and market), we thus estimate a reduced-form regression (3) by excluding other issue characteristics from the set of independent variables. The coefficient for BUYOUT decreases to 0.58 in regression (3) and remains statistically significant at the 1% level. Economically, the 58 basis point reduction in offering yield spreads still represents interest savings of about $2.03 million each year for an average bond issue.
These results suggest that bond investors view bonds offered by buyout-backed IPO firms as being less risky than other bonds, consistent with Kaplan and Strömberg (2009), who find a lower default rate for firms that go through leveraged buyouts.9 Bond investors do not appear to punish buyout-backed IPO firms for the potential wealth expropriation incentives of buyout groups, perhaps because buyout groups do not want to tarnish their reputation by taking advantage of bondholders. These results thus are supportive of the reputation acquisition hypothesis.
9
For all US bond issuers rated by Moody’s, the average annual default rate of is about 1.6% during 1980-2002 (Moody’s (2006)). In comparison, Kaplan and Strömberg (2009) document an average default rate of 1.2% per year for a large sample of private equity-sponsored buyout transactions occurred during 1970-2002. The lower default rate is surprising, because the target firms following leverage buyouts often have relatively higher debt ratios than other firms. Kaplan and Strömberg suggest that a lack of data for some post-transaction outcomes could be responsible for the lower default rate for LBOs. Our analysis of yield spreads for public firms circumvents this potential problem.
22 The role of buyout groups in a buyout-backed IPO firm is likely to decline as the time from the IPO increases. We thus expect that the coefficient for the BUYOUT dummy variable is larger and more statistically significant for the (IPO+1, IPO+5] sample than it is for the extended sample. As expected, the effect of buyout groups on yield spreads is much smaller for the extended sample, as reported in regression (4). The coefficient for BUYOUT decreases to -0.20 and remains statistically significant only at the 10% level, suggesting that buyout groups play a less important role in their portfolio firms as the time since the IPO increases. This result also suggests that the significance of the coefficients for the BUYOUT dummy variable for the (IPO+1, IPO+5] sample is not driven by firm fixed effects for which we do not (and cannot) control, because otherwise the coefficients for the BUYOUT dummy would not be less important for the extended sample, both statistically and economically. It is also worth noting that the (IPO+1, IPO+5] sample size of 431 is 33% of the extended sample sample size of 1,299, and the ratio of buyout dummy coefficients is -0.20/-0.67=0.30, suggesting that that effect of buyout sponsors on yield spreads for newly issued bonds comes almost entirely from issues in the first five years, before the buyout sponsors have largely exited. This is strong evidence that we have identified a buyout sponsor effect, as we posit.
The coefficients for the control variables are generally consistent with the literature. For brevity, we will only highlight some interesting variables. The coefficient for the RULE_144A dummy is positive and statistically significant at the 5% or 1% levels in all three regressions for which it is included. This result suggests that investors require higher yield spreads for bonds offered in the Rule 144A market, perhaps because these bonds are perceived as being riskier or having lower liquidity.
The literature documents that bonds offered by larger firms are associated with lower yield spreads, partly because larger firms are less likely to default. Consistent with the literature, the
coefficient for LN(MARKET_CAP)t-1 is negative and statistically significant at the 1% level in all four regressions. The coefficients are economically significant. With a coefficient of -0.29 in the baseline regression (1), an increase of one standard deviation (2.07, as reported in Table 1) in this variable on
23 average reduces the yield spread by about 60 basis points (e.g., from 2.61% to 2.01% for the focused sample).
Dividend payers with outstanding bonds have the option to reduce dividends before defaulting on their bonds. Therefore, we expect bonds of dividend payers to be associated with lower yield spreads. As expected, the coefficient for the DIV_PAYERt-1 dummy is negative and statistically significant at the 1% level in all of the four regressions. The coefficients are also economically significant. In the baseline regression (1), for example, yield spreads on bonds of dividend payers are 49 basis points lower than those on other bonds.
Firms with a higher standard deviation of residual returns from the market model have a higher firm specific risk, so we expect a positive coefficient for STD_RETURNt-1 (%). As expected, its coefficient is always positive and statistically significant at the 1% level. The coefficients are also economically significant. For example, if the value of this variable increases by one standard deviation, the coefficient of 0.48 in the baseline regression (1) corresponds to an increase of 61 basis points in the yield spread.
As we discussed earlier, SP_RATING_RES is orthogonal to all of the previous independent variables and MDY_RATING_RES is further orthogonal to the S&P rating. The coefficients for both variables are negative and statistically significant in all of the four regressions. In the baseline regression for the (IPO+1, IPO+5] sample, the standard deviations of SP_RATING_RES and MDY_RATING_RES are 1.83 and 0.67, respectively (untabulated). Therefore, one standard deviation increases of
SP_RATING_RES and MDY_RATING_RES correspond to decreases of about 46 basis points and 16 basis points, respectively, in the yield spread in regression (1). These results suggest that credit ratings contain useful information beyond what is captured by the widely observable issuer and issue
characteristics. Such information helps to explain the variations in yield spreads on bonds at the time of issuance.
To summarize, our results in Table 3 suggest that, after controlling for issue and issuer
24 ratings. However, bond investors apparently are willing to accept lower yields on bonds by buyout-backed firms as reported in Table 4. These lower yields result in millions of dollars of annual interest savings for an average bond offering by a buyout-backed IPO firm in our sample and are economically significant. We argue that the reputational concerns of buyout groups and their repeated interaction with bond investors help alleviate the typical conflicts of interest between equity and bond holders. This reputational concern effect is the reason for the lower yield spread for bond offerings by buyout-backed IPO firms.
4. Buyout Groups and Their Portfolio Firms’ Investment Decisions and Dividend Policies In addition to the “symptoms” shown in the bond offerings, if the reputation acquisition
hypothesis is true, we would be able to observe that the repeated interactions between buyout groups and bond investors help to alleviate the agency problems between equity and bond holders in many corporate decisions. To shed light on this issue, we examine the investment decisions of buyout-backed and non-buyout-backed IPO firms in Section 4.1. In Section 4.2, we examine the dividend policies of these IPO firms.
4.1. Buyout Groups and Their Portfolio Firms’ Investment Decisions
Investments decisions are one of the most important corporate policies. Agency problems among equityholders, bondholders, and the managers of a firm can influence the firm’s investments in various ways that affect firm value and/or result in wealth transfers among different stakeholders. As reported in Table 2, buyout groups in our sample retain significant equity stakes and board seats after a firm’s IPO. As large blockholders, they can play an important role in these agency problems. The existing evidence on how a large shareholder affects a firm’s investments is limited and mixed. Agrawal and Nasser (2011) show that a large shareholder with a board seat is associated with higher investments. They argue that this is related to the large shareholder’s monitoring of the managers, with the effect being for the
managers not to have as quiet a life as would otherwise be the case (Bertrand and Mullainathan (2003)). On the other hand, Becker, Cronqvist, and Fahlenbrach (2011) suggest that large individual
(non-25 institutional) shareholders help reduce investments, due to better monitoring of the management.
Anderson, Duru, and Reeb (2010) show that family ownership in the U.S. decreases a firm’s investments, due to the family owner’s risk aversion.
Theoretically, both increases and decreases in investments can either benefit or harm bondholders. Increases in investments often result in lower future stock returns due to possible empire building
incentives (Titman, Wei, and Xie (2004)). Asset growth is also shown to be related to lower stock returns (Cooper, Gulen, and Schill (2008)). If such investments and asset growth are simply due to less
profitable projects while the cash flows and tangible assets of the firm are nevertheless growing, this could be beneficial to bondholders. However, if debt financing is used to support investments and asset growth and the firm’s leverage ratio is getting higher, a lower future stock return is also likely to be bad news for bondholders. Furthermore, CEOs who are forced out of a quiet life or CEOs who are
incentivized into asset substitutions are likely to over-invest. This is also likely to harm bond investors (Jensen and Meckling (1976)).
On the other hand, underinvestment could also harm bond investors (Myers (1977)). However, underinvestment is unlikely to be a concern for a firm during the period right after a bond offering. As discussed earlier, empirical studies find that firms that raise external capital and invest more are more likely to have poor post-issue stock performance. When compared to similar firms also with bond
offering proceeds, a buyout sponsor’s decision to engage in more aggressive investments is more likely to be bad news for the bond investors, even though the existing theories cannot provide an unambiguous prediction for the relation between investment levels and the existence of a large block shareholder. So we hypothesize that, if the reputational concerns are not important, the buyout sponsors of an IPO firm would have an incentive to engage the firm in more and riskier investments, everything else equal.10 For
10
One key prediction of the underinvestment argument in Myers (1977) is that a firm’s powerful shareholders would transfer wealth from the bondholders by having the firm skip positive NPV projects and pay excessive dividends. However, our analysis of the dividend policies in the next sub-section suggests that buyout-sponsored firms are not more likely to engage in aggressive payout policies.
26 presentation convenience, this hypothesis is termed the over-investment hypothesis, as discussed in the introduction.
Following the literature, we use a firm’s capital expenditure during the bond offering year scaled by beginning-of-year tangible assets to measure the investment level and use firm size (market
capitalization), age, profitability (ROA and market to book ratio), leverage, and other related variables as control variables (see, e.g., Fazzari, Hubbard, and Petersen (1988), Polk and Sapienza (2008), and Becker, Cronqvist, and Fahlenbrach (2011), among others). The specification of the baseline regression is as follows:
(3)
CAPX_TANG(%)t = f (BUYOUT dummy, TANGIBILITYt-1, LN(MARKET_CAP)t-1, LN(AGE),
DIV_PAYERt-1 dummy, ROAt-1, LOSSt-1 dummy, LEVERAGE_RATIOt-1,
MARKET_TO_BOOKt-1, UTILITYt-1 dummy, YEAR dummies, CAPX_TANG(%)t-1).
The results of the baseline regressions are reported in columns (1) and (2) in Table 5. Both regressions, as well as regressions (3)-(5), are Tobit regressions since capital expenditure and R&D are always non-negative. Note that the dependent variables are expressed in percentages, and their mean values and standard deviations are reported at the top of the table. For comparison purposes, in regression (1), we include the lagged dependent variable, while we do not in regression (2). The very significant coefficient on the lagged dependent variable suggests that investment levels are quite persistent. To focus on the changes in investment levels and to remain conservative, we will focus on the regression with the lagged dependent variable. The coefficient on the buyout dummy is negative and statistically significant at the 5% level. Economically, the coefficient of -8.2%, is about 23% of the mean investment level for all IPOs firms that issue debt. This is modest given that the investment levels vary a lot with a standard deviation of 35.8%. So both statistically and economically, the regression results suggest that buyout sponsored IPO firms pursue a modestly conservative investment policy after they do bond offerings. This suggests that the alternative of the over-investment hypothesis is true.
It could be a concern that the investment levels used in regressions (1) and (2) are for the bond offering year, and the longer term investment policies are more relevant for bond investors. We thus use
27 the average of the three-year investment levels since the bond offering year (inclusive) as the dependent variable in regression (3). To avoid losing many observations, we use the lagged one year investment level instead of the lagged three year average to control for the existing investment levels. The coefficient on the buyout dummy is similar to that in regression (1) and is statistically significant at the 5% level. This suggests buyout sponsored firms use a consistently conservative investment policy.
The literature also uses capital expenditures scaled by total assets or uses capital expenditure plus R&D scaled by total assets as measures for investment levels (e.g., Agrawal and Nasser (2011), Anderson, Duru, and Reeb (2010), among others). We report the results using these two measures in regressions (4) and (5). Following Frank and Goyal (2003), we also use a broader and cash flow-related measure of investments that includes acquisitions and sales of assets and investments in addition to capital
expenditures. The results are reported as regression (6). Regression (6) is an OLS regression since the dependent variable can be negative. The coefficient on the buyout dummy remains negative in
regressions (4)-(6), and is statistically significant at the 10% level in regressions (4) and (5).
Economically, the coefficients on the buyout dummy imply a very similar, modest impact of the buyout sponsorship on the investment levels.
Overall, the results reported in Table 5 suggest that buyout groups potentially help their portfolio firms to adopt a more conservative investment policy that is friendly to bondholders. This is supportive of the reputation acquisition hypothesis.11
4.2. Buyout Groups and Their Portfolio Firms’ Dividend Policies
Bond investors are always concerned about cash payouts to equity holders. This is especially true for bond investors of buyout-sponsored companies, given the attention-grabbing press reports on big special dividends paid to the sponsors. Given the popular view of buyout groups’ big payout habits, it is interesting in itself to examine broadly the influence of buyout groups on their portfolio firms’ dividend payouts. More particularly, if the wealth expropriation hypothesis dominates, we would observe high
11
Harford and Kolasinski (2012) report that the investment policy of buyout-sponsored firms does not differ from that of comparable public firms. Although they do not require that the sample firms have large capital injections such as bond offerings, their evidence is generally consistent with ours.
28 dividend payout after bond offerings by buyout-backed firms. We call this the excessive dividend hypothesis. On the other hand, if the reputation acquisition hypothesis dominates and buyout groups’ reputation concerns at least offset their incentive to expropriate bond investors, we would expect that buyout-backed IPO firms adopt no more aggressive dividend policies than other IPO firms.
To shed light on the dividend payouts of all firms that issue bonds within five years of their IPOs, we report summary statistics of dividend policies in Panel A of Table 6. For the 209 firms that make at least one bond offering that is included in our focused sample, we compare their dividend policies in different ways from the most recent fiscal year that ends before the IPO date (year IPO-1) to the sixth fiscal year that ends after the IPO date (IPO+5). Note that the IPO year is defined as the first fiscal year that ends after the IPO offer date, and part of it is before the IPO. For each fiscal year, we first report the total number of firms and the number of firms that do pay dividends. Note that the total number of firms varies from year to year and can be less than 209 firms because of missing data. Consistent with the firm characteristics that suggest that buyout-backed IPOs are more leveraged and more financially constrained, it is not surprising to observe that buyout-sponsored firms are less likely to pay dividends before and after the IPO, consistent with the findings of Martin and Zeckhauser (2010).
For the rest of the columns of Panel A of Table 6, we report the dividend yield, the dividend/asset ratio, and the payout ratio for the firms that pay dividends. That is, all of the summary statistics for these three payout measures are conditioning on a non-zero dividend. It is not trivial to define the relative size of a dividend. We follow Barclay, Holderness, and Sheehan (2009) and use three different measures to capture the relative dividend size. The dividend yield (DIV_YIELD (%)) is defined as common dividends per share in the fiscal year as a percentage of end-of-year stock price per share, or common dividends in the year as a percentage of end-of-year market value of equity if dividends per share are missing. For fiscal year IPO-1, the end-of-year market value of equity is set to the market value of equity at the market close on the IPO date. The dividend/assets ratio (DIV_AT (%)) is common dividends in the fiscal year as a percentage of beginning-of-year total assets. The dividend payout ratio (DIV_PAYOUT) is expressed as a fraction and is defined as common dividends in the fiscal year divided by earnings
29 before extraordinary items. For all three measures, the mean is always greater than the median, and in many cases the difference is quite large. This positive skewness is mostly driven by small denominators, not by large dividends. This also highlights the challenge of measuring the relative dividend size, and this is why we use all three measures for the relative dividend size.
Bondholders are more at risk if a firm pays a large dividend in any particular year. So for all three measures, we report the percentage of firms that pay big dividends. For dividend yields, there is evidence that buyout-backed payers are more likely to pay big dividends (dividend yield ≥5%) than other payers. For the dividend/assets ratio, the percent of buyout-backed payers that pay big dividends
(dividend/assets ≥5%) is smaller than the percent of other payers before the bond issue, but not afterwards. For the payout ratio, we do not see a clear pattern on whether buyout-payers are more likely to pay big dividends (dividend payout ratio≥30%) than other payers.
Given that our focus is the potential conflicts between equity and bond holders instead of any valuation concerns, it is difficult to draw conclusions based on the dividend yield and dividend/asset ratio measures due to the noise in stock prices and asset sizes. However, it will be a concern for bondholders if the firm cannot generate enough cash to support its dividend payments. So in addition to the mean, median, and percentage of ≥30% dividend payers, we also report the payout ratio at the 75th percentile and the maximum. For the buyout-backed IPO firms, the payout ratio at the 75th percentile is 5.58 (or 558% of earnings) and the maximum is 10.67 in the year before the IPO. For the non-buyout sponsored IPO firms, the payout ratio at the 75th percentile and the maximum are, respectively, 0.97 and 4.93 in the IPO year.
This pattern of higher payouts by buyout-backed IPOs is an indication of a special dividend payout before the IPO. But if we put all the numbers in perspective, the number of buyout-backed payers that pay a big dividend is small, largely because most buyout-backed firms do not pay dividends. These patterns are consistent with the pre-IPO dividend payout pattern for the broad IPO sample reported by Martin and Zeckhauser (2010). Therefore, although a few buyout-backed firms have grabbed media attention when they paid big dividends, the vast majority of buyout-backed firms have clearly protected
