Early Refinancing and Maturity Management in the Corporate Bond Market. September 27, 2014

Transcription

1 Early Refinancing and Maturity Management in the Corporate Bond Market Qiping Xu September 27, 2014 Abstract This paper studies early refinancing activities in the corporate bond market and its implications for debt maturity structure. In additional to interest rate reduction, speculative-grade firms constantly extend maturity through early refinancing. Moreover, they take advantage of accommodating credit market conditions to extend maturity on a large scale, leading to pro-cyclical debt maturity structure. The evidence is consistent with precautionary maturity management, where speculative-grade firms extend maturity in order to hedge against future refinancing risk, as the longer maturity reduces the possibility of being forced to refinancing at high yield rates. In contrast, investment-grade firms do not appear to manage their maturity similarly, as they are less exposed to refinancing risk. I am extremely grateful for my advisors Douglas Diamond, Zhiguo He, Anil Kashyap, Gregor Matvos and Amir Sufi for their invaluable input. I would also like to thank Stephen Kaplan, Kelly Shue, and Michael Weisbach, as well as seminar participants at the University of Chicago and London Business School Trans-Atlantic Doctoral Conference. Research support from the Deutsche Bank and Bradley Foundation is gratefully acknowledged; any opinions expressed herein are those of the author. qxu@chicagobooth.edu 1

2 1 Introduction Early refinancing, where firms retire their outstanding bonds before scheduled due dates and issue new bonds as replacements, is a common practice in the corporate bond market. Every year hundred billions dollars of outstanding corporate bonds are refinanced early. Previous studies attribute early refinancing mainly to firms desire for interest rate reductions: when yields drop, firms retire their outstanding bonds and issue new ones at cheaper rates. That helps to reduce firms interest payments (Merton [1974], Brennan and Schwartz [1977], Vu [1986], Mauer [1993], Longstaff and Tuckman [1994], Acharya and Carpenter [2002], Jarrow et al. [2010]). This paper studies early refinancing activities, its determinants, its outcomes, and its implications for capital structure, in particular debt maturity structure. Throughout the paper maturity measures the remaining time to scheduled due dates. For example, maturity equals 1 year for a 10-year bond issued 9 years ago. It provides novel evidence that firms, in particular speculative-grade firms, refinance early to extend debt maturity. The majority of speculative-grade firms bonds are refinanced before scheduled due dates. During early refinancing, speculative-grade firms target bonds with shorter maturity left, and issue new bonds with longer maturity as replacements. In contrast, investment-grade firms behave quite differently. The majority of investment-grade firms bonds are refinanced at the scheduled due dates, and only a small fraction are refinanced early. During early refinancing, investment-grade firms retire more expensive bonds and replace them with cheaper, but of similar maturity bonds. Early refinancing does not change the maturity structure for investment-grade firms. Moreover, this paper highlights credit market conditions as a key driving force: speculative-grade firms take advantage of credit market improvements to extend maturity on a large scale, resulting in procyclical debt maturity. Figure 1 plots the average early refinancing activities and corresponding changes in the maturity structure for speculative-grade and investment-grade firms in the sample. For speculativegrade firms on the left, early refinancing is strongly pro-cyclical with credit market conditions: they early refinance 10%-15% of total outstanding bonds during good credit periods, such as and , but only about 2% during credit market downturns. Maturity structure moves closely with the early refinancing activities - it extends significantly when firms refinance early on a large scale, and shortens when early refinancing activities are less pervasive. Investment-grade firms, in contrast, refinance only 1%-2% of total outstanding bonds even during good credit periods. Their maturity structure does not move with the early refinancing activities. 2

3 Figure 1: Early refinancing and Changes in Maturity 15 Speculative grade 15 3 Investment grade 15 Early Refinancing Fraction % Change in Maturity % Early Refinancing Fraction Change in Maturity Each firm year, early refinancing fraction (left scale) is the ratio of early refinancing dollar amount to the total dollar amount of outstanding bonds at previous year end. Change in maturity (right scale) is calculated as the change in maturity divided by previous year end maturity. Both series are calculated by taking the average across sample firms in a given year. However, establishing a causal relationship between early refinancing and maturity extension remains difficult due to endogeneity concerns. For example, firms that choose to refinance early might happen to be firms experiencing investment opportunity changes. If there are new long-term projects coming up and firms desire to issue long-term bonds to match the duration of their assets and debt (Modigliani and Sutch [1966], Myers [1977], Vasicek [1977]), then the maturity extension observed would be an outcome of duration matching for the new projects. Moreover, within-firm analysis suffers from dynamic versions of the same endogeneity concerns: time periods in which a firm chooses to refinance early might happen to be time periods that a firm experiences investment opportunity changes. Thus, omitted variables may bias the estimates of the impact of early refinancing on maturity. As an identification strategy, I exploit the variation in the callable structure of corporate bonds. Firms commonly embed call provisions when issuing bonds, which entitle firms the right to call back bonds during a defined time interval at the pre-specified call prices. There are two important features of call provisions. First, calls make it easier for firms to refinance early. Bond holders have to return the bonds 3

4 when firms call. In other methods of early refinancing, such as repurchases and tender offers, bond holders might choose to hold on if they do not find the price attractive enough or due to some nonprice reasons. Also, when lower interest rates are available, the value of outstanding bonds increase correspondingly due to lower discount rates. If the discounted values exceed the contemporaneous call prices, firms can transfer value from bond holders to themselves by calling back at the contemporaneous call prices. It essentially makes calls a subsidized way for firms to refinance early. Second, the lengthy and standard protection period of call provisions makes it possible to shock firms with the ability of early refinancing. A protection period defines the period during which firms cannot call outstanding bonds, starting from the issuing date. It provides the bondholders with a guaranteed length of time that they will be able to hold the bonds, and receive the originally promised coupon payments. he average protection period is 50 months for sample speculative-grade firms bonds. The standard practice is to set the protection period to last 50% of maturity at issuance: for example a 10-year bond normally has a 5-year protection period. I use two methods to exploit the variation of the callable structure. First, I instrument firms early refinancing activities with a dummy variable D(turn callable), which indicates some bond(s) is scheduled to end the protection period and to become callable in a given firm-year. The identification assumption is that the timing of a bond turning callable is uncorrelated with current unobservable factors making firms demand longer maturity. The lengthy and standard protection period setting plays a key role in this identification strategy, as it is unlikely that future movement of the unobservable, such as investment opportunities would always coincide with the timing of turning callable. To provide supportive evidence for the identifying assumption, I tabulate firm characteristics for firm-year with and without bonds turning callable. Those two groups are statistically comparable in common financial characteristics such as size, profitability, distress level, liquidity position, growth prospect, etc. The second method is to instrument firms early refinancing activities with the interaction between firm s callable fraction of outstanding bonds and credit market conditions. Conditional on the fraction of callable bonds, firms with more bonds that are already callable bonds are fundamentally more sensitive to credit market improvements in their early refinancing. By instrumenting early refinancing activities with the interaction term, I exploit the variation of credit market shocks through the callable structure. Identification requires that firms with different fractions of callable bonds do not differ in their response to credit market improvements other than through the early refinancing activities. In other words, firms with higher fractions of callable bonds receive larger shocks to their early refinancing ability when credit market conditions improve, but their demand to adjust maturity due to the unobservable factors is similar to firms with lower fractions of callable bonds. To provide supportive evidence for the identifying assumption, I tabulate firm characteristics for firms with low callable fractions and high callable fractions. Those two groups are statistically comparable in common financial characteristics. Instrumental variable test results show that speculative-grade firms extend debt maturity through early 4

5 refinancing. In terms of economic magnitude, a one standard deviation increase in the probability of early refinancing leads to about a 20% increase in the fraction of book debt with maturity greater or equal to 5 years, and more than one year longer average maturity for outstanding bonds. Within the speculativegrade segment, firms with shorter maturity are more aggressive in maturity extension, compared to firms with longer maturity. In contrast, investment grade firms do not extend maturity through early refinancing. Both groups reduce their interest payments, but neither group relaxes the covenant strictness through early refinancing. In this paper, I focus on the different exposures to refinancing risk to explain the distinct early refinancing behavior and maturity outcomes across credit ratings. Refinancing when credit spreads are high can be costly: firms might have to refinance at a significantly higher rate (Froot et al. [1993]), experience excessive liquidation by creditors (Diamond [1991]), sell assets in a fire sale (Brunnermeier and Yogo [2009], Choi et al. [2013]), suffer increasing credit risk (Leland and Toft [1996a], He and Xiong [2012]), or decrease investments (Almeida et al. [2009]). Refinancing risk motivates precautionary maturity management, where forward-looking firms constantly extend their maturity before due dates, especially during accommodating credit periods when credit spreads are low. The longer maturity structure serves as an insurance against future refinancing risk, as it reduces the possibility of being forced to refinance at high interest rates. Lower rated firms are more exposed to refinancing risk, as the changing credit market conditions disproportionately affect the financing costs faced by lower rated firms (Greenwood and Hanson [2013]). Moreover, speculative-grade firms are constrained in the maturity that they can issue at, as they are screened out of the long-term bond market (with maturity longer than 10 years). The constrained in maturity at issuance should be interpreted as an equilibrium where speculative firms are only offered at most the intermediate maturity at their acceptable rates. The combination of maturity constraint and volatile financing costs subject speculative-grade firms to severe refinancing risk, resulting in more precautionary maturity management than their investment-grade counterparts. This paper complements several studies on refinancing risk. He and Xiong [2012] show that firms face refinancing losses from issuing new bonds to replace maturing bonds when debt market liquidity deteriorates. The surge in refinancing losses can cause the firm to default at a higher fundamental threshold. In practice, rating agencies commonly name refinancing risk as a reason to downgrade firms, 1 and they also upgrade firms after firms accomplish refinancing activities. 2 While Harford et al. [2014] suggests increasing cash holding as a way to mitigate refinancing risk, this paper shows that firms also hedge 1 April 25, 2014 Moody s Investors Service downgraded Black Elk Energy Offshore Operations LLC s (BEE) Probability of Default Rating (PDR) to Caa3-PD from Caa2-PD. These actions were prompted by BEE s tight liquidity and heightened refinancing risk. BEE s 13.75% notes will become due December 1, Without a substantial improvement in operating performance and cash flows, the company will be challenged to refinance this debt. 2 October 07, 2010 Moody s Investors Service upgraded the ratings on West Corporation s (West) existing senior secured term loan to Ba3 from B1 and the rating on $650 million of existing senior notes due 2014 to B3 from Caa1 upon the closing of its recent refinancing transactions. 5

6 against refinancing risk through maturity extension. Firms that are more exposed to refinancing risk, such as speculative-grade firms, have strong incentive to manage their maturity beforehand. While firms who are less exposed to refinance risk, such as investment-grade firms, simply refinance when the bonds are due. This paper contributes to corporate debt maturity literature. Previous studies on corporate debt maturity focus on the cross-sectional relationship between firms characteristics and corporate debt maturity (Diamond [1991, 1993],Barclay and Smith [1995], Guedes and Opler [1996], Johnson [2003], Berger et al. [2005]). In contrast, this paper emphasizes the dynamics of maturity through early refinancing process and the important role of credit market conditions. It also highlights the fact that firms across rating segments manage maturity differently. The time series dynamics and the variation across firms creditworthiness help us form a more complete understanding of how corporate debt maturity evolves. The fact that firms constantly adjust maturity after issuance also suggests that it is important to sdy the effect of ex-post refinancing on the ex-ante choice of maturity at issuance. This paper also related to several studies suggesting that capital market segmentation and credit supply conditions significantly influence observed financial structures and corporate behavior (Faulkender and Petersen [2006], Leary [2009], Sufi [2009b], Tang [2009], Lemmon and Roberts [2010], Chernenko and Sunderam [2012], Erel et al. [2012]). These studies differ from much of the extant capital structure literature, which assume capital supply is perfectly elastic and capital structures are determined solely by corporate demand for debt. This paper adds to this line of research by presenting maturity as an important channel that credit market conditions operate through. More specifically, the effect of credit supply conditions on capital structures mainly concentrates on the speculative-grade segment. A closely related empirical paper is Mian and Santos [2011]. Mian and Santos show that creditworthy firms try to actively manage the maturity of syndicated loans in normal times. Liquidity demand then becomes counter-cyclical for creditworthy firms as they choose not to refinance when liquidity costs rise. In contrast, this paper shows weaker firms are those who display a pro-cyclical pattern in early refinancing and maturity extension in the corporate bond market. This paper is related to the literature on debt renegotiation. We have accumulated ample evidence about firms renegotiation in their bank loans (Roberts and Sufi [2009]). However, renegotiation in corporate bonds is difficult (Bolton and Scharfstein [1996]) due to the large number of debt holders outstanding. The literature has been focusing on the distressed exchanges and chapter 11 reorganizations (Asquith et al. [1994], Franks and Torous [1994], James [1996, 1995]). My paper shows that while private debt can be augmented by renegotiation, public debt can be implicitly augmented by early refinancing. The remainder of the paper proceeds as follows. Section 2 describes the data and summarizes the characteristics of bonds and firms in the sample. Section 3 describes describes the empirical strategy, and Section 4 presents the results for the empirical strategy. Section 5 offers precautionary maturity management as the interpretation. Section 6 discusses the relationship between precautionary maturity 6

7 management and other forms of internal liquidity holdings. Section 7 concludes. 2 Data and Sample Statistics 2.1 Data and Sample Construction The Mergent Fixed Income Securities Database (FISD) is a comprehensive database of publicly-offered U.S. bonds. FISD includes the majority of corporate bonds and provides details on bond issuance and the issuers. From April 1995 FISD began tracking changes in the outstanding amount of publicly traded corporate bonds. Thus in addition to the characteristics of the bonds at issuance, FISD contains a detailed history of changes in the amount outstanding for the bonds. FISD records the reasons, the effective dates of the changes in amount outstanding, the exact amount changed and the remaining principal balance afterward. Built upon Compustat and Capital IQ information, the final merged data contains the following information of bonds outstanding for a firm in a given fiscal year: bond characteristics and contract terms at issuance, type and dollar amount of actions taken to the outstanding bonds, as well as principle amount remained outstanding after actions. In order to be included in the sample, a firm has to have at least 3 consecutive annual observations with public bonds outstanding. The final sample includes 1,497 nonfinancial US firms and 15,196 fiscal year observations, with the effective sample period starting from A total of 31,640 bonds are included in the sample. I also collected Bloomberg data of bond characteristics at issuance and yield to maturity to complement the data set. BAA-AAA spread, constant maturity treasury rates and yields on different rating indexes are obtained from the Federal Reserve. 2.2 Summary Statistics Table 1 Panel (a) presents a summary of firm characteristic with mean, standard deviation and median tabulated, together with summary statistics of the non-financial firms in the Compustat database during the same time period, All variable definitions appear in Appendix A. The sample panel contains 15,196 firm year observations corresponding to 1,497 firms, though the count of observations varies depending on the non-missing data on the particular variable. Relative to the average Compustat firm, sample firms tend to be larger in asset size, more profitable, have higher leverage and are more likely to have an S&P long-term issuer credit rating. These differences are consistent with the fact that sample firms are qualified to enter the corporate bond market. Table 1 Panel (b) presents sample firm distribution across industries. 4 While non-uniform, it is quite representative to the overall Compustat 3 To mitigate the impact of outliers and the possible coding errors, all ratios are winsorized at the upper and lower one percentiles and the winsorization is applied to all the analysis in this paper industry definitions are obtained from Fama French data library. 7

8 distribution. Business Equipment and Healthcare industries have higher percentage in Compustat sample, while manufacturing industry has a relatively larger composition in the data sample. Comparing the distribution more broadly, there are similar percentages overall, particularly in Consumer Product and Wholesale, Retail, & Some Services. The distribution of sample firms across industries is representative of all firms in general. This addresses the concern of industry clustering for the data sample due to the merging process. Table 2 tabulates summary statistics for 31,640 sample bonds. Table 2 Panel (a) presents basic contract terms at issuance. Sample bonds are large in terms of the dollar amount: the median offering amount is $100 millions, with an average around $ 224 millions. Maturity at issuance has a mean of 10.3 years, with average coupon rate 6.60%. 30% of the bonds are rated as speculative-grade at issuance. Almost all the bonds have some covenants associated with them, and the average covenant count is about Table 2 Panel (b) summarizes the dollar amount of early refinancing, maturity, new issuance and total bonds outstanding in the market for the sample period. Total dollar amount of sample bonds grows from around 600 billion dollars in 1996 to roughly 2400 billion dollars in To better access the variation in time series, Figure 2 plots the early refinancing amount over time. The Hodrick Prescott filter is applied to separate the cyclical component of the time series from the raw data. Amount filtered is calculated as the difference between the raw data and the cyclical component. As we can see in Figure 1, the filtered early refinancing amount drops sharply in and , which coincides with the two financial market crashes of the last decade. On the upside, early refinancing activities peak in , as well as around Empirical Strategy 3.1 The Outcome of Early Refinancing I define a case as refinancing if within a three-month time window centered at the month when a bond gets retired, firms issue other bond(s) with dollar amount comparable to the retired amount. For every early refinancing, I match the early-retired bond to newly-issued bond. After matching all the early refinancing pairs, t-tests are conducted at firm-year level by averaging across observations at that firm-year. The mean values of characteristics for retired bonds and matching new bonds, the differences, and P value for t test are presented separately for the investment-grade and speculative-grade firms in Table 3. It shows that when firms conduct early refinancing, speculative-grade firms get significant extensions in maturity. Investment-grade firms simply issue new bonds at similar maturity. Both groups get cheaper rates when they conduct early refinancing and we also observe some reduction in covenant strictness. Table 3 s first row presents the change in maturity dimension: speculative-grade firms extend the 8

9 maturity from 3.91 years to 8.79 years, a more than doubled extension which is statistically significant at the 1% level. Investment-grade firms maturity move from 11.5 years to about 12.5 years with an insignificant t statistic. For maturity at issuance, it seems speculative-grade firms do not adjust maturity at sisuance, as the retired bonds and the new bonds have maturity at issuance of 8.6 and 8.8 years. Investment-grade firms, on the other hand, shorten the maturity at issuance all the way from years to about 13 years. In terms of interest payments, both groups replace more expensive bonds with cheaper ones. The average yield to maturity decreases by 2.24% for speculative-grade firms and 1.31% for investmentgrade firms. Coupon rate decreases 1.18% for speculative-grade firms, and 1.89% for investment-grade firms. For covenant strictness, speculative-grade firms get a drop of about one covenant through early refinancing: the covenant count decreases from 6.97 to Investment-grade firms merely experience a drop in covenant count from 3.45 to However, we do not observe any significant changes in the covenant dummy. 3.2 Callable Structure of Bonds However, establishing the causual effect between early refinancing and maturity extension remains difficult. The biggest challenge comes from the endogeneity concerns. For example, firms that choose to refinance early might happen to be firms experiencing invesment opportunity changes. If there are new long-term projects coming up and firms desire to issue long-term bonds to match the duration of their assets and debt (Modigliani and Sutch [1966], Myers [1977], Vasicek [1977]), then the maturity extension observed would be an outcome of duration matching for the new projects. Moreover, within-firm analysis suffers from dynamic versions of the same endogeneity concerns: time periods in which a firm chooses to refinance early might happen to be time periods that a firm experiences investment opportunity changes. Thus, omitted variables may bias the estimates of the impact of early refinancing on maturity. In order to estimate the causual impact of early refinancing on maturity extension, the ideal experiment is to randomly assign the ability of early refinancing to speculative-grade firms. If speculative-grade firms do desire maturity extension when they have the chance to reshape their contract terms through early refinancing, then firms more able to conduct early refinancing are expected to extend maturity by a larger magnitude than firms less able to conduct early refinancing. A randomly assigned ability to refinance early would allow us to rule out the concerns over the potential unobservable factors driving firms demand for longer maturity, such as movement in the investment opportunity sets. Of course, it is difficult to randomly assign the early refinancing ability. But a shock to firms early refinancing ability, which is uncorrelated with the contemporaneous confounding factors, will suffice the purpose. As an identification strategy, I exploit the callable structure of corporate bonds. Firms can embed call provisions when issuing bonds, which entitle firms the right to call back bonds during a defined time 9

10 interval before maturity according to a pre-specified price schedule. Bonds that are already callable make early refinancing easier for firms. More importantly, the lengthy and standard protection period setting make it possible to shock firms with the ability to refinance early while controlling for the impact of potential confounding factors. Let me first introduce call provisions in more details. If a call provision is included at issuance, call schedule, call prices and protection period are contracted. Protection period defines the period during which the company can not call the bond, starting from the issuing date. It provides the bondholders with a guaranteed length of time that they will be able to hold the bond, and receive the originally promised coupon payments. For example, Kroger issued a callable 10-year senior debenture on June 15, 1993 with the scheduled maturity on June 15, The embedded call provision states that Kroger would be able to call the debenture starting from June 15, 1998, 5 years after the issuance day with a call price Call price decreases to on June 1999, to on June 15,2000, and finally to 100 on June 15, The 5-year protection period translates into 50% of maturity at issuance. In my sample, 89.4% of speculative-grade firms bonds have call provisions. The average protection period is 49.7 months with standard deviation of 13 months. The protection period setting is quite standard: a 10-year bond normally has a 5-year protection period, while a 7-year bond normally has a 3.5-year protection period. The protection period on average lasts 47.8% of maturity at issuance with standard deviation of 9.8%. 06/93 Protection Period 06/98 06/99 06/00 06/01 06/03 issuance Call Schedule for Kroger 10-year Senior Debenture Here I would like to emphasize the advantage of calls in early refinancing: calls make early refinancing easier for firms. First, call provisions grant firms the right to call back bonds at discretion. It facilitates firms to retire outstanding bonds, as bond holders have to return the bonds upon calling. While for tender offers and repurchases, bond holders retain the right not to respond if the offered prices are not attractive enough, or bond holders have other non-price reasons for holding the bonds. Second, when a lower interest rate is available, either due to a drop in prevailing market rate or better individual firm performance, the value of an outstanding bond increases correspondingly due to lower discount rates. If the discounted value exceeds contemporaneous scheduled call prices, firms indeed transfer values from bond holders to themselves by calling back outstanding bonds at scheduled call prices. Early refinancing conducted through tender offers, repurchases and make whole calls do not make similar transfers. Firms 5 74% of the callable bonds can be called at a continuous form. The rest can be called discretely, such as monthly, quarterly and semi-annually. 10

11 need to pay at least the market prices in repurchases, and usually plus some premium in tender offers, to induce bond holders to comply. A make whole call is even more expensive as all the future coupons have to be paid at a discount rate close to the treasury rate. Of course, if a bond is not callable yet due to the protection period, then the firm can only conduct early refinancing through tender offers, repurchases and et al. How important are calls as a method of early refinancing? Figure 4 decomposes early refinancing based on methods of redemption. Calls, where issuers exercise call provisions to buy back outstanding bonds, turn out to be a major method of early refinancing. A large percentage of early refinancing is achieved by calls, while tender offers account for the majority of the rest. In years such as period, about $30 billion of outstanding corporate bonds are called by firms, while the total number of early refinancing is around $60 billion. Also, the plot displays the very familiar pro-cyclical fluctuation: call amounts increase sharply in and , and decrease during two market downturns in the previous decade. This is one of the components for the pro-cyclical pattern in the aggregate early refinancing activities in the sample. 3.3 Instrumental Variable Strategy 1: My first instrumental variable strategy explores the timing of protection period. I instrument early refinancing activities with a dummy indicating some bond(s) is scheduled to turn callable for firm i at year t. Consider two otherwise identical firms A and B who both issued a 10-year bond with 5-year protection period. Firm A issued the bond 5 years ago and the protection period is scheduled to end at year t. Firm B issued the bond only 3 years ago and the protection period is not over yet. In year t, the timing of the protection period puts firms A in a better position refinancing its outstanding bonds and extending maturity, if it wants to. While firm B is constrained in its ability to refinance early simply due to the fact that the outstanding 10-year bond will not be callable in another two years. Of course, firm B can use other methods such as tender offers or repurchase. But those methods might not be as desirable as calls. Maturity i,t = δ 0 + δ 1 D( Early re f i) i,t + δ i controls i,t + ε it 2nd stage D(Early re f i) i,t = β 0 + β 1 D(turn callable) i,t + β i controls i,t + e i,t 1st stage Here D(turn-callable) equals one if some outstanding bond(s) is scheduled to end the protection period and to become callable for firm i at year t. Take the Kroger 10-year senior debenture as an example, the turn-callable indicator for this debenture switches to 1 at year 1998, and remains 0 for other years. 11

12 That leads to D(turn-callable)=1 for Kroger in year D (Early-refinance) equals one if firm i early refinances at year t. The exclusion restriction requires that the instrument D(turn callable) i,t only relates to the outcome variable Maturity i,t through its effect on early refinancing. The identification assumption is that the timing of some bond(s) issued a few years ago turning callable is uncorrelated with any current unobservable factors that might lead firms to adjust maturity today. The lengthy and standard protection period setting of call provisions plays a key role in this identification strategy, as they make it unlikely that future movements of the unobservables such as the investment opportunity would always coincide with the timing of turning callable. To stengthen the identification assumption, I exclude bonds with protection periods shorter than 3 years. To support the validity of the identification assumption, I tabulate firm characteristics by D(turn callable) i,t. Table 4 presents a firm characteristic summary for these two groups and two sample t-tests results. Firm characteristics are statistically comparable across two groups at a 5% confidence level. Market/Book ratio, profitability, liquidity position, growth opportunity, K-Z index and payout ratio are all similar between firm-year with bonds turning callable or not. The only variables showing statistically different values are asset size and look leverage. The standard errors for asset size and book leverage are 1.12 and 0.22 in the sample of speculative-grade firms. Compared to the standard errors, the magnitude of differences is not very significant. Moreover, all factors are included in the instrumental variable tests as controls. The test is restricted to the speculative-grade firms. Firm characteristics and interest rate conditions are controlled in the regressions. Firm characteristic controls include Ln(Assets), book leverage, EBITDA/Assets, Cash/Assets, Tangible/Assets, Market/Book and S&P rating. Ln (Assets) measures a firm s ability to collateralize the debt and also captures the liquidation value in a distressed state. Leverage captures a firm s financial health. Market/Book is used to measure future investment prospects. EBITDA/Assets and Cash/Assets measure a firm s profitability and short-term liquidity. Tangible/Assets measures the pledgeability of assets. S&P rating is included as a general control for a firm s default risk, as well as any outcome changes due to a firm s credit rating change. Interest rate controls include risk-free rate (3 month T-bill), term spread (10 year corporate bond yield minus 1 year corporate bond yield) and BAA-AAA. In order to control for time-unvarying unobservables which might also affect firm s maturity choice, I first-difference all the variables. 3.4 Instrumental Variable Strategy 2: My second instrumental variable strategy explores the fact that firms take advantage of credit market improvements to refinance early and extend maturity. I instrument firms early refinancing activities with the interaction between the callable fraction (the fraction of outstanding bonds which is callable by firm i at year t ) and credit market conditions. Given that callable bonds make early refinancing easier and 12

13 cheaper, firms with more bonds that are already callable receive a larger shock in their early refinancing ability when the credit market improves. That leads to more early refinancing and hence more maturity extension, compared to firms with fewer bonds that are ready to be called. Consider two otherwise identical firms A and B, who both issued a few 10-year bonds with 5-year protection periods. Firm A issued these bonds 5 years ago, and as time goes by those bonds are callable now as the protection periods end. Let us assume 80% of the total amount of bonds outstanding is callable for firm A. Firm B issued a few similar 10-year bonds only 2-3 years ago and none of its outstanding bonds is callable yet. When credit market conditions improve, firm A is able to early refinance a larger fraction of its outstanding bonds and extend maturity more, while firm B is constrained in its ability to take advantage of the credit market improvements. The test is specified as the following: Maturity i,t = δ 0 + δ 1 D( Early re f i) i,t + δ i controls i,t + ε it 2nd stage D(Early re f i) i,t = β 0 + β 1 F(callable) i,t BAA AAA + β i controls i,t + e i,t 1st stage callable Here F(callable) it = amount i,t 1 total amount outstanding i,t 1, and D (Early Refinance) equals one if firm i early refinances at year t. I use credit spread BAA-AAA to capture credit market conditions. As in Figure 2, credit spread increases sharply during credit market downturns, and decreases during good credit market periods. The exclusion restriction requires that the interaction terms, F(callable) i,t BAA AAA, only relates to the outcome variable Maturity i,t through its effect on early refinancing. The identifying assumption is that firms with different fractions of callable bonds do not differ in their responses to credit market improvements other than through the early refinancing activities. In other words, firms with higher fractions of callable bonds receive larger shocks to their early refinancing ability when credit markets improve, but their demand to adjust maturity due to the investment opportunity changes remains similar to firms with lower fractions of callable bonds. The lengthy and standard protection period setting of call provisions again plays an important role in this identification strategy. Notice that callable fraction and credit spread BAA-AAA are not themselves excluded instruments and they are included in the second-stage regression as well. I do not assume the choice to embed call provisions is random. In fact, firms with different fractions of callable bonds might as well have different propensity to conduct early refinancing. However, conditional on the fractions of bonds that firms are able to call back at a given time point, the improvements in credit market conditions will affect firms with more callable bonds by a larger magnitude. Those firms are in a better position to conduct early refinancing and lengthen maturity. By using the interaction term as an instrument, I explore only the variations of credit market conditions through the callable structure. To support the validity of the identification assumption, I tabulate firm characteristics by their callable fractions. To confirm that firms are comparable even though their callable fraction might vary, each year 13

14 speculative-grade firms are separated into two groups based on their callable fraction. If the callable fraction for firm i is greater than the median callable fraction within the speculative-grade segment, then firm i is put into the high group. Otherwise it is indexed as in the low group. Table 7 presents a firm characteristic summary for these two groups and two sample t-tests results. Firm characteristics are statistically comparable across the high and low groups at a 5% confidence level. Asset size, profitability, liquidity position, growth opportunity, K-Z index and payout ratio are all similar between firms with high and low callable fractions. The only variables showing statistically different values are Book leverage and Market/Book ratio. The standard errors for book leverage and Market/Book ratio are 0.22 and 0.56 in the sample of speculative-grade firms. Compared to the standard errors, the magnitude of differences is not very significant. Moreover, all factors are included in the instrumental variable tests as controls. Firm characteristics and interest rate conditions are controlled in the regressions. Firm characteristic controls include Ln(Assets), book leverage, EBITDA/Assets, Cash/Assets, Tangible/Assets, Market/Book, S&P rating and callable fraction. Ln (Assets) measures a firm s ability to collateralize the debt and also captures the liquidation value in a distressed state. Leverage captures a firm s financial health. Market/Book is used to measure future investment prospects. EBITDA/Assets and Cash/Assets measure a firm s profitability and short-term liquidity. Tangible/Assets measures the pledgeability of assets. S&P rating is included as a general control for a firm s default risk, as well as any outcome changes due to a firm s credit rating change. Interest rate controls include risk-free rate (3 month T-bill), term spread (10 year corporate bond yield minus 1 year corporate bond yield) and BAA-AAA. In order to control for time-unvarying unobservables which might also affect firm s maturity choice, I first-difference all the variables. The test will be run for speculative-grade firms first, and then a for speculative-grade firms and investment-grade firms together to test the heterogeneity across those two groups. In this paper I will be agnostic about what drives variations in credit market conditions. It could be the counter-cyclical variation in the economy wide prices of risk, or feedback effects from yields to default risks. It could also be mispricing due to investor biases in evaluating credit risk over the cycles, or investor sentiment. Instead of trying to disentangle or quantify those theories, I take the variations in aggregate credit market conditions as given and study firms reactions. As a robustness check, another two indexes are used in the test to index credit market conditions. The first one is EBP(excess bond premium) from Gilchrist and Zakrajšek [2011], which is a credit spread measure clear of default risk. An increase in the excess bond premium reflects a reduction in the effective risk-bearing capacity of the financial sector and, as a result, a contraction in the supply of credit. Test results with EBP are presented in the appendix Table A1 and Table A2. The third index of credit market condition is high-yield fraction, which is the fraction of new corporate issuance rated speculative-grade. Greenwood and Hanson [2013] show that a decline in issuer quality is a reliable signal of credit market overheating. Test results with high-yield fraction are presented in the appendix Table A3 and Table A4. All of the three indexes generate very similar results. The use of different indexes to capture credit market conditions serves as robustness 14

15 checks for the validity of results. 4 Results 4.1 Instrumental Variables Strategy 1 I begin by exploiting the timing of protection periods. The instrument is a dummy D(turn callable), which indicates some bond(s) is scheduled to turn callable for firm i at year t. The identifying assumption is that the timing of some bond(s) issued a few years ago turning callable now is uncorrelated with any current unobservable factors that might lead firms to adjust maturity today. The sample is restricted to speculative-grade firms. Table 5 presents the IV regression first stage results in Panel (a) and the reduced form regression in Panel (b). I use two different measures to capture firms early refinancing activities: the first one is a dummy D(Early-refi) indicating whether firm i conducted early refinancing activities in year t; and the second one is F(Early-refi), which measures the fraction of the total amount of outstanding bonds being early refinanced for firm i in year t. I also use two different variables to measure firms maturity structure: the first one is the fraction of total book debt with maturity 5-year or longer, which captures the overall maturity structure of firms book debt; the second one is the average maturity of all the outstanding bonds, which measures the maturity structure of corporate bonds. In Panel (a) first stage IV results show strong results for both indexes of early refinancing activities, with F-statistics greatly exceeding 10 (the rule of thumb threshold for weak instruments concerns). In terms of economic magnitude, the dummy indicating some bond(s) turning callable increases the probability of early refinancing by 7.9%, and the fraction of early refinancing by 2.3%. In Panel (b) the instrument is also strongly correlated with both maturity measurements in reduced form regressions after controlling for other firm characteristic and interest rate variables. Table 6 Panel (a) shows the IV test results with F(debt 5Y ) as the outcome variable, and panel (b) shows the IV test results with Bond Maturity as the outcome variable. Both tables present the estimates from the OLS tests (Column 1 without firm characteristic controls and Column 2 with firm characteristic controls), and IV2 test results (Column 3 without firm characteristic controls and Column 4 with firm characteristic controls). Here I only present the result of D(Early-refi) as the instrumented variables. OLS estimates are both positive, and adding firm characteristics does not seem to change the coefficients on early refinancing much. IV tests show stronger effects than the OLS test: early refinancing leads to a larger fraction of book debt with 5-year or longer maturity, as well as a longer average maturity of outstanding bonds. In terms of economic magnitude, estimates suggest one standard deviation increase in the probability of early refinancing leads to a 14% increase in the fraction of book debt with maturity greater or equal to 5 years, and an average maturity extension of 1.5 years for all the outstanding bonds. 15

16 Including firm characteristic controls, again, does not change the estimates much in IV tests. It assures that the instrumental variable is at least not correlated with the observable firm characteristics. 4.2 Instrumental Variables Strategy 2 Now I turn to the second instrument, which exploits the fact that improvements in credit market conditions impact firms with a larger fraction of callable bonds more. Following the methodology specified in instrumental variable strategy 2, I instrument the early refinancing activities with the interaction between callable fraction and BAA-AAA. The analysis does not assume the choice to embed call provisions is random. Instead, the identification assumption is that firms with different fractions of callable bonds do not differ in their responses to credit market improvements other than through the early refinancing activities. The sample is restricted to speculative-grade firms. Table 8 presents the IV regression first stage results in Panel (a) and the reduced form regression in Panel (b). I use two different measures to capture firms early refinancing activities: the first one is a dummy D(Early-refi) indicating whether firm i conducted early refinancing activities in year t; and the second one is F(Early-refi), which measures the fraction of the total amount of outstanding bonds being early refinanced for firm i in year t. I also use two different variables to measure firms maturity structure: the first one is the fraction of total book debt with maturity 5-year or longer, which captures the overall maturity structure of firms book debt; and the second one is the average maturity of all the outstanding bonds, which measures the maturity structure of corporate bonds. In Panel (a) first stage IV results show strong results for both indexes of early refinancing activities, with F-statistics greatly exceeding 10 ( the rule of thumb threshold for weak instruments concerns). In terms of economic magnitude, a one standard deviation drop in the instrument, which is the interaction between callable fraction and BAA-AAA, increases the probability of early refinancing by 4.6%, and increase the fraction of early refinancing by 3.5%. In Panel (b) the instrument is also strongly correlated with both maturity measurements in reduced form regressions after controlling for other firm characteristic and interest rate variables. Table 9 Panel (a) shows the IV tests results with F(debt 5Y ) as the outcome variable, and panel (b) shows the IV test results with Bond Maturity as the outcome variable. Both tables present the estimates from both the OLS tests (Column 1 without firm characteristic controls and Column 2 with firm characteristic controls), and IV2 test results (Column 3 without firm characteristic controls and Column 4 with firm characteristic controls). Here I only present the result of D(Early-refi) as the instrumented variables. OLS estimates are both positive, and adding firm characteristics does not seem to change the coefficients on early refinancing much. IV tests show stronger effects than the OLS test: early refinancing leads to a larger fraction of book debt with 5-year or longer maturity, as well as a longer average maturity of outstanding bonds. In terms of economic magnitude, estimates suggest one standard deviation increase in the probability of early refinancing leads a 21% increase in the fraction of book debt with maturity 16

17 greater or equal to 5 years. an average maturity extension of 1 year for all the outstanding bonds. The magnitude is qualitatively similar to the results from instrumental variable strategy Heterogeneity test Based on the evidence presented in early sections, we only observe large scale early refinance and maturity extension by speculative-grade firms, while investment-grade firms mainly refinance when the bonds are due, or refinance early but not extend maturity. The fact that speculative-grade firms are more exposed to refinancing risk predicts the heterogeneity between these two groups. In order to show the heterogeneity in the regression form, I interact the early refinancing activities with D(speculative), which equals one if firm i receives Standard&Poor s domestic long term issuer credit rating below or equal to BB+. The regressions are run both as OLS and IV tests. In IV tests, I interact both the instrument and instrumented variables with D(speculative). Moreover, firms with shorter average debt maturity or more short-term debt are more exposed to refinancing risk (He and Xiong [2012]). That rationale predicts firms with shorter maturity to be more aggressive in maturity extension, compared to firms with longer maturity. I dig deeper into the heterogeneity by comparing firms with shorter maturity to firms with longer maturity within the speculative-grade segment. In terms of the regression test, I interact early refinancing activities with D(speculative), and a double interaction term D(speculative)*D(short). D(short) equals one if firm i s maturity is shorter than the median maturity among all speculative-grade firms in year t-1. In IV tests, I interact both the instrument and instrumented variables with D(speculative) and the double interaction term D(speculative)*D(short). 6 Table 10 presents heterogeneity test results across investment-grade and speculative-grade firms, as well as firms with different maturity length within the speculative-grade segment. Both measures of firms maturity structure are used in the tests: the first one is F(Debt 5Y ) - the fraction of total book debt with maturity 5-year or longer, which captures the overall maturity structure of firms book debt; the second one is Bond Maturity- the average maturity of all the outstanding bonds, which measures the maturity structure of corporate bonds. Panel(a) displays both the OLS and IV results with outcome variable F(Debt 5Y ), while Panel (b) displays the results with outcome variable Bond Maturity. The instrument here is the interaction between callable fraction and BAA-AAA. It turns out both the OLS and IV results show similar results across two outcome variables. Speculativegrade firms extend maturity through early refinancing, but not investment-grade firms. Firms with shorter maturity are the most aggressive ones in maturity extension through early refinancing. In Panel (a) Column 3 and Column 4 the coefficients for investment-grade firms remain insignificantly different from 0. In Column 3 the coefficient for speculative-grade is significantly higher than that of investment- 6 Please refer to Appendix Section E for detailed specifications of the IV test. 17

18 grade firms. Within the speculative-grade segment (Column 4), firms with shorter maturity are the ones driving the positive results. The coefficient for D(Early-refi)*D(Speculative)*D(Short) is with statistical significance. Panel (b) shows a similar story, in Column 3 and Column 4 the coefficients for investment-grade firms remain insignificantly different from 0. In Column 3 the coefficient for speculative-grade is significantly higher than that of investment-grade firms. Within speculativegrade segment (Column 4), firms with shorter maturity extend maturity significantly more than firms with shorter maturity. In addition, Table 11 presents OLS and IV results for yield to maturity and covenant strictness across investment-grade and speculative-grade firms. Yield to maturity and covenant measures are both calculated by averaging across all the bonds outstanding within a firm-year. For yield to maturity in Column 1 and Column 2, both speculative-grade and investment-grade groups decrease yield to maturity on outstanding bonds through early refinancing, while speculative-grade firms show a larger reduction. For covenant counts in Column 3 to Column 6, neither group shows significant covenant loosening through early refinancing. Covenant strictness doesn t seem to be the major goal that firms want to achieve when they conduct early refinancing. This should not be too surprising as normally bond covenants are quite uniform and less strict than the covenants embedded in the bank loans. 5 Precautionary Maturity Management The identification strategy shows that speculative-grade firms desire maturity extension when they have the opportunity to reshape their contract terms, while investment-grade firms do not. In this section, I focus on the precautionary maturity management hypothesis to explain the distinct early refinancing activities and maturity outcomes across the credit rating segments. Speculative-grade firms are constrained in the maturity that they can issue at, as they are screened out of the long-term bond market (with maturity longer than 10 years). Meanwhile, the changing credit market conditions disproportionately affect the financing costs faced by lower rated firms (Greenwood and Hanson [2013]). The combination of maturity constraint and volatile financing costs subject speculative-grade firms to severe refinancing risk. That motivates precautionary maturity management, where forward-looking speculative-grade firms constantly extend their maturity before due dates, especially during accommodating credit periods when yields are low. The longer maturity structure serves as an insurance against future refinancing risk, as it reduces the possibility of being forced to refinance at high interest rates. The fact that speculative-grade firms are screened out of long-term bond market should be interpreted as an equilibrium outcome after taking into consideration the rates charged by creditors. Besides the higher credit risk, there exist different mechanisms leading creditors to keep speculative-grade firms on short-leash. For example, short-term debt provides creditors with additional flexibility to monitor managers frequently (Rajan and Winton [1995], Stulz [2001] ) and reduce managerial incentives to increase 18

19 risk (Barnea et al. [1980], Leland and Toft [1996b]). It also enables the transfer of control rights, including the right to liquidate when entrenched managers have no incentive to pull the trigger. Long-term bonds implicitly deprive investors of all these benefits. Also, if cash flows are uncertain and the true information can only be revealed in the future (Diamond [1991]), then keeping firms on short-term debt allows creditors to retract if information turns out to be unfavorable. All the above mechanisms, which are more pronounced in the speculative-grade segment, leading creditors demanding higher returns for long-term bonds. Additionally, the high rates required can induce substitution into risky low-quality projects. Credit rationing (Stiglitz and Weiss [1981]) leads to maturity rationing, where low-quality firms are shut out of the long-term corporate bond market even if they might be willing to pay the higher rates. Thus, the equilibrium turns out to be one where speculative firms are only offered at most the intermediate maturity at their desirable rates. Speculative-grade firms are more exposed to refinancing risk, also because the changing credit market conditions disproportionately affect the financing costs faced by lower rated firms (Greenwood and Hanson [2013]). Figure 2 plots the Bank of America Merrill Lynch US corporate index for different rating groups during the period 1997 to This plot highlights the large time series variation of yields for lower rated groups. While yields for AAA, AA and A ratings remain relatively stable throughout the period, the yields for speculative-grades are highly volatile. Take the C rating group as an example: the yield was lower than 15% during normal credit periods and went up to more than 25% around 2001 and 40% during the 2008 financial crisis. 5.1 Model Appendix A presents a model that captures the essentials of the precautionary maturity management. Two risk neutral firms have long-term projects which pay off at t=3 and need to issue bonds at t=0 to fund the projects. The prospect of the projects remain constant from the beginning to the end. At t=1 and t=2, there are i.i.d shocks to the aggregate risk aversion in the market. The risk aversion shock is independent of the projects, and results in lenders either being risk neutral (indicating good credit market conditions), or more risk averse (indicating bad credit market conditions). Firm V L, whose expected terminal payoff is too risky to issue long-term bonds matching the length of the project, can only issue a short-term or an intermediate-term bond to begin with. The short maturity forces firm V L coming back to the capital market for refinancing. However, refinancing is risky. If lenders turn out to be more risk averse at the refinancing point, firm V L has to default, which is inefficient from firm s point of view as lenders undervalue the continuation value of the firm. Under this scenario, the dominant strategy for firm V L is to issue bonds with intermediate maturity to begin with, and refinance early at low aggregate risk aversion for maturity extension in order to mitigate refinancing risk. The option of early refinancing is valuable, as it enables firm V L to get cheap funding when aggregate risk aversion is low, and reduces 19

20 the probability of default due to refinancing under high aggregate risk aversion. Both parts increase the expected payoff for firm V L. On the other hand, firm V H has an expected payoff good enough for it to issue a long-term bond matching the length of the project. The dominant strategy for firm V H is then to issue long-term bond to fund the project, and refinance early to reduce the interest payments under low aggregate risk aversion. Given firm V H will not default, a long-term bond with the option to refinance early maximizes the chance of getting cheap financing from lenders, and serves as the dominant financing strategy for firm V H. This model presents some interesting observations about firms maturity choice and maturity management after issuance in the corporate bond market. Low value firms are constrained in the maturity at issuance, as their cash flow is too uncertain for risk-averse lenders to hold a long-term claim. Keeping the refinancing risk in mind, the optimal choice for low value firms is to issue intermediate-term bonds to begin with, and refinance early to extend maturity under good credit market conditions. Essentially, low value firms synthesize the longer term by early refinancing intermediate-term bonds. In contrast, high value firms are not constrained in the maturity when issuing bonds. They can start with long term bonds which match the term of the projects better, and refinance early only for lower rates under good credit market conditions. 5.2 Maturity at Issuance I also collected empirical evidence to support the idea that speculative-grade firms are screened out of the long-term bond market. Figure 5 plots the distribution of maturity at issuance for speculative-grade and investment-grade firms bonds in the sample, with the summary statistics tabulated on top. For speculative-grade firms, their maturity at issuance is highly clustered: the average maturity at issuance is 8.7 years with standard deviation only 2.3 years. In fact, about half of the bonds are issued with maturity about 10 years, and another about 40% are issued with maturity around 7 years. Speculative-grade firms rarely issue bonds longer than 10 years, and the maximum maturity is 30 years. They also do not issue bonds shorter than 7 years much. In contrast, the distribution for investment-grade firms is much more spread out: the average maturity at issuance is 11.1 years with standard deviation 10.2 years. Investmentgrade firms commonly issue bonds longer than 10 years, and the maximum maturity shoots all the way up to 100 years. 7 They also often issue short-term bonds with maturity shorter than or equal to 5 years, which accounts for almost 40% of the total issuance. However, not issuing long-term bonds does not rule out the possibility that speculative-grade firms simply do not invest in long-term projects. Speculative-grade firms might only invest in relatively shortterm projects, which matches to the short term maturity structure of their bonds. Documenting the length of investments is empirically challenging, as we do not have access to the characteristics of firms in- 7 For example, the Walt Disney Company issued senior debentures in 1993 which are due in 2093-the so called sleeping beauty bond. 20