Debt Rating Initiations_ Natural Evolution or Opportunistic Behavior

8/12/2019 Debt Rating Initiations_ Natural Evolution or Opportunistic Behavior

1/22

Journal of Modern Accounting and Auditing, ISSN 1548-6583December 2013, Vol. 9, No. 12, 1574-1595

Debt Rating Initiations: Natural Evolution or Opportunistic

Behavior?

Laurence Booth

University of Toronto, Toronto, Canada

Sean Cleary, Lynnette Purda

Queens University, Kingston, Canada

The authors examine a firms decision to begin issuing debt in public bond markets and find that it is a function of

both life cycle influences and opportunistic timing. Defining life cycle factors to encompass both a firms age in

years and its underlying characteristics, the authors confirm that bond market participation is generally restricted to

large, mature firms. Summary statistics show that firms obtain their initial bond ratings on average 9.5 years after

their equity initial public offering (IPO) and 11.8 years after initiating dividend payments. Growth rates, capital

expenditures, and cash flow volatility all decline as the firm accesses public debt markets, consistent with entry

into the mature phase of its life cycle. With respect to opportunistic timing, it is asked whether entry into public

bond markets follows strong performance (or precedes weak performance) at both the firm and market levels. At

the firm level, the authors find that the debt IPO occurs following periods of strong operating performance and

high excess stock returns. At the market level, entry coincides with favorable interest rates and default spreads.

The benefits of careful timing result in firms receiving initial bond ratings that are stronger than what would be

predicted; however, there is no evidence of abnormal numbers of downgrades for these firms in subsequent years.

Keywords:debt rating, debt issuance, bond rating, firm life cycle, market timing

Introduction

Life cycle theory, based for example on the arguments of Mueller (1972), suggests that firms go through

several stages, along with associated significant corporate events, as they develop into mature firms. Recent

research has examined how corporate financing changes through this life cycle. For example, H. DeAngelo,

L. DeAngelo, and Stulz (2010) have looked at the composition of firms that issue equity. However, in stark

contrast to the voluminous literature on the equity initial public offering (IPO) decision1and as noted by Chang,

Hilary, Shih, and Tam (2010), there has been minimal attention paid to a firms decision to access public debt

markets for the first time, that is, the debt IPO decision. This is the focus of this research.

It is well known that firms that issue debt in public markets are different from those that raise debt only

Acknowledgment: The authors thank David Barr and Chen Liu for excellent research assistance.Laurence Booth, professor of Finance, Rotman School of Management, University of Toronto.

Sean Cleary, professor of Finance, Queens School of Business, Queens University.Lynnette Purda, associate professor of Finance, Queens School of Business, Queens University.

Correspondence concerning this article should be addressed to Lynnette Purda, Queens School of Business, Queens University,Room 372E, Goodes Hall, Kingston ON, Canada K7L 3N6. Email: [email protected]; Tel.: (613) 533-6980.1See Ritter (2003) and Jenkinson and Ljungqvist (2001) for comprehensive reviews of research related to equity IPO.

DAVID PUBLISHING

D


2/22

DEBT RATING INITIATIONS: NATURAL EVOLUTION OR OPPORTUNISTIC BEHAVIOR? 1575

through private sources such as banks. The authors argue that this transition to becoming a public debt market

issuer through a debt IPO is a logical progression through the life cycle. The authors also argue that the debt

IPO decision is anticipated by management who will carefully time the decision to get the best possible market

access and cheapest financing. A firm will not want to see its debt issue be poorly received, or receive a bad

credit rating, any more than it would want to see its common stock stuck with the underwriter. In both cases, a

firm will seek a successful IPO, whether equity or debt.

This notion that the debt IPO decision reflects both market timing by the firm as well as life cycle

influences is consistent with the recent evidence of DeAngelo et al. (2010) who found that a seasoned equity

offering (SEO) similarly is a function of both life cycle effects and market timing. Results support both

hypotheses and suggest that mature firms time their initial public debt offerings after a careful consideration of

both internal and market factors.

Consistent with the life cycle theory, the authors find that firms obtain their initial public debt ratings on

average (median) 9.5 (5.0) years after their equity IPO2. The debt rating initiation also occurs on average

(median) 11.8 (7.0) years after paying their initial dividends, although these numbers cannot be compareddirectly with the years since IPO, because not all firms that receive a debt rating pay dividends. The fact that

the dividend initiation occurs well before the initial debt rating is not surprising. In contrast to informed bank

debt, public market debt is mainly arms length debt purchased by large institutions investing as fiduciaries,

that is, investing other peoples money. As such, they are governed by prudent investor rules that dictate the

types of investments they can make. In contrast to bank debt, this implies a greater need for the firm to

communicate with bond investors by adopting specific stable financial policies. This is consistent with the

observation of Aivazian, Booth, and Cleary (2006) that public debt issuers are much more likely to pay

dividends.

While the number of years that a firm has been public is an indicator of age, it need not correspond

perfectly to the stage of its life cycle. Some firms transition quickly from start-up to maturity, while others take

longer time to work through the various phases of growth. For this reason, the authors proxy for firm age by

using company size and the proportion of equity represented by retained earnings, a variable used by both

Altman (1968) and more recently by H. DeAngelo, L. DeAngelo, and Stulz (2006) to capture life cycle effects.

In addition, the authors ask how the debt IPO decision relates to firm characteristics measuring asset structure,

growth, profitability, and risk that will all logically differ across various stages of the life cycle. Consistent with

a firm accessing public debt markets in later stages of its life cycle, the authors find a reduced pace of growth

and reduction in risk subsequent to the debt IPO.

The authors also provide evidence that the debt IPO decision appears to be well-timed. For example, it is

found that stock prices for debt IPO firms rise in the period prior to their initial debt ratings and fallsubsequently. Further, there is strong evidence that earnings also tend to drop afterwards

3. Debt rating

initiations are also negatively related to various interest rate measures, suggesting good timing of market factors.

Taken together, this suggests that decisions to access public debt markets are on average well-timed.

2The authors use a firms initial appearance in the Center for Research in Security Prices (CRSP) database to identify the year of

IPO. Using the IPO date provided by Compustat resulted in a large number of missing data points.3The authors considered the possibility that firms may be managing their earnings prior to their debt IPO and found that while

firms do engage in some form of earnings manipulation surrounding the debt rating initiation period resulting in abnormal levelsof accruals, it has been minor. In addition, this practice has declined significantly through time to the point where it is virtually

non-existent in the later years of the sample.


3/22

DEBT RATING INITIATIONS: NATURAL EVOLUTION OR OPPORTUNISTIC BEHAVIOR?1576

The strong evidence in support of opportunistic timing leads us to ask whether the bond rating received is

unduly high when the firm launches a public debt program. While the authors find some evidence that initial

rating assignments are higher than what would otherwise be expected based on a model of rating prediction,

there is no evidence of large-scale revisions to ratings in the 5-year period following the debt IPO. Careful

choice of timing leads to strong ratings, perhaps due to qualitative factors unaccounted for in the prediction

model, but these ratings do not appear to be inappropriate.

The rest of this paper is organized as follows. Section 2 provides the theoretical motivation for the study

by reviewing the relevant literature on firm life cycle and the opportunistic timing of raising capital. Section 3

discusses data sources, sample characteristics, and the link between a firm securing an initial debt rating and its

access to public bond markets. Evidence from the sample suggests that the authors can follow prior works

(Aivazian et al., 2006; Faulkender & Petersen, 2006) in using the existence of a debt rating to proxy for a firms

ability to access public debt markets. As a result, the authors use the year of rating initiation to proxy for the

timing of the debt IPO in the remainder of the paper. Section 4 discusses trends in financial and market

variables surrounding the rating initiation period. Section 5 uses logistic regression analysis to examine factorsaffecting the rating initiation decision. Section 6 examines the initial debt rating level and subsequent rating

revisions, while Section 7 concludes.

Theoretical Motivation

Life Cycle of the Firm

Mueller (1972) developed a life cycle theory of the firm which suggests that firms go through several

stages as they develop. This idea was refined by Myers (1999) who discussed the financial architecture of the

firm in the context of the gradual reduction in the importance of agency costs and the role of the founder.

Myers (1999), for example, explained how, for successful firms, intangible growth options get transformed into

tangible real assets and expectations get transformed into reality. As the firm moves from test marketing and

innovation into full-scale production, the importance of the founder declines. At this stage, the firm often

undergoes an equity IPO, so that with publicly traded shares the founder can (partially) cash out as their

importance to the firm recedes. Myers (1999) then argued that the importance of the founder drops to almost

zero, as the firm branches out into other lines of business, often using its shares as an acquisition vehicle.

During this phase, the firm is more likely to hire professional management and use stock-based compensation.

The financial counterpart to Myers (1999) evolutionary trail is that during the initial growth phase,

stockholders prefer that the firm should reinvest its profits to take advantage of its growth opportunities. At

some point, the firm may also raise additional external capital to further exploit these opportunities. Eventually,

this high growth phase subsides as competition develops, and profit opportunities begin to decline. At thisstage, stockholders may prefer that the firm pay out some of its profits as cash dividends, since growth

opportunities are shrinking.

Mueller (1972) argued that value-maximizing managers will adjust their dividend policy and investing

activity according to this progression through the life cycle. However, growth-maximizing managers may pay

smaller dividends than they should and over-invest, thereby causing their firms to have sub-optimal market

values. He suggested that stockholders may be unable to prevent this sub-optimal behavior, since the firms

internally generated funds may be sufficient to fund over-investment without resorting to external capital.

While Mueller (1972) did not pursue this argument, it is easy to recognize this behavior as consistent with


4/22


5/22


not only are they able to handle more debt and successfully issue public debt, but they may want to in order to

constrain managements ability to over-invest using the firms free cash flows. At the same time, they will want

to raise debt as cheaply as possible in order to maintain profit margins which are likely to be squeezed due to

increased competition. This suggests that at some point during the middle-to-later stages of maturity, firms will

want to access public debt markets through a debt IPO.

Opportunistic Behavior

There are several papers providing evidence that firms display significant market timing ability when

deciding to issue new equity. For example, Loughran and Ritter (1995) documented an economically

significant long-run underperformance of firms following an IPO or an SEO. They also showed that this is not

due to long-term reversals, since extreme winners that do not issue equity dramatically outperform extreme

winners that issue equity. Spiess and Affleck-Graves (1995) found that the median return in the 5-year period

following an SEO is 10%, much lower than the median 5-year holding-period return of 42.3% of similar size,

non-issuing firms in similar industries. Lee (1997) investigated whether or not managers of SEO firms

knowingly sell overvalued equity by looking at insider trading activities. He found that those primary and

secondary issuers whose managers sell their shares before the SEO seem to be knowingly selling overvalued

equity, while those primary issuers with top managers who purchase shares before issuing do not seem to be

knowingly selling overvalued equity.

Several additional studies, such as Graham and Harvey (2001), Burch, Christie, and Nanda (2004), and

Chang et al. (2010), have verified that firms have issued equity in response to favorable market conditions

going back as far as the 1930s, and they continue to do so. Finally, Chan, Ikenberry, and Lee (2007) found a

significant positive relationship between stock repurchase amounts and long-run abnormal stock returns. They

suggested that this supports the hypothesis that managers have market timing ability, at least for stock

repurchases.

Chang et al. (2010) noted that the literature has typically focused on equity rather than debt issues for

evidence of managements timing ability. One exception is the work of Barry, Mann, Mihov, and Rodriguez

(2008) that examines debt issues in general (i.e., both public and private debt and both primary and secondary

issues). Barry et al. (2008) found that firms issue more debt when interest rates are low relative to historical

rates (p. 413). For our purposes, this indicates that firms may time their initial access to public debt markets in a

way similar to that already documented for equity markets; especially when considering that firms tend to raise

funds in a lumpy manner as will be shown in the substantial increase in debt during the year of the debt IPO.

In this research, the authors focus specifically on the public debt IPO decision rather than private or secondary

debt issues and examine the role of timing in this context. While managers may consider similar market

conditions to be favorable whether it is a firms first or subsequent bond issue, the authors suggest that the debt

IPO decision will be more sensitive to other factors, most notably firm characteristics indicative of life cycle

stage, that is, not all firms are equally capable of acting opportunistically. This difference in context leads us to

broaden the view of timing to include not only external factors as defined by Barry et al. (2008) such as market

interest rates and credit spreads, but also firm level characteristics. Good timing can be influenced by internal

factors such as recent strong company performance or reduced credit risk which would tend to make the markets

more receptive to a debt issue by the company and/or translate into a strong debt rating. Hence, the authors take

a very comprehensive view of what timing can include by considering both firm and market characteristics.


6/22


The authors find that some of the factors that affect debt issues in general also play important roles in the

debt IPO decision. Firm level factors may be important either because they indicate a transition from one stage

in the firms life cycle to the next in which accessing public debt markets becomes feasible, or because they

increase the chance that the market will view a debt issue from the firm favorably. The authors examine the

influence of internal firm factors, such as asset structure (leverage, cash, and tangibility), profitability (earnings

before interest and taxes (EBIT)/sales, tax rate), age (size, retained earnings to total equity (RE/TE)), risk

(standard deviation of cash flow, Beta), and the markets view of the firm (M/B ratio, past and future stock

returns) in combination with external market conditions. The authors argue that by considering both its internal

characteristics and overall market conditions, a firm may be able to time its debt issue to obtain the best

possible initial rating and to ultimately lower its borrowing cost.

Data Sources and Sample Characteristics

The two major bond-rating agencies are Standard and Poors (S&P) and Moodys Investors Service

(Moodys). While both agencies occasionally provide unsolicited ratings, in practice, the vast majority ofratings are sought and paid for the firm (Kliger & Sarig, 2000). Soliciting the rating provides the firm with the

opportunity to convey confidential information to the agency throughout the rating process and challenge a

preliminary report for errors and omissions. It is believed that the existence of an initial bond rating is therefore

closely correlated with a conscious decision on the part of the firm to be rated and to access the public bond

market.

The authors confirm the link between rating initiation and debt issuances by examining long-term debt values

from Compustat and find that approximately 95% of the sample firms issue long-term debt during the year of

rating initiation. The authors then use the SDC Platinum new issues database to verify that the new debt is raised

via public bond markets. While not all firms have available data in SDC, for the sub-sample that does, over 85%

issue public bonds after securing a Moodys rating. Based on these findings, the authors follow previous works

(Aivaizian et al., 2006; Faulkender & Petersen, 2006) and use the existence of a bond rating to indicate that a firm

has secured access to public bond markets.

The sample examines firms that obtain their first Moodys ratings at some point during the 30-year period

from 1980 to 2010. This maximizes the sample size when compared with using S&P ratings available in

Compustat, since they are only available beginning in 19855. A firm enters the sample only once so that the

authors ignore observations where a firm regains a rating after a lapse.

Table 1 shows that 2,790 firms with available Compustat data obtained initial Moodys ratings during the

sample time period and that rating initiations reached their peak in the late 1990s. Unsurprisingly, rating

initiations slowed dramatically between 2007 and 2010 with the onset of the financial crisis and the associatedcredit crunch. For comparison purposes, Figure 1 graphs the number of equity IPOs alongside debt rating

initiations6. The authors see that the frequencies of the two events follow a similar pattern, indicating that the

same market timing factors influencing equity IPOs are most likely to influence the debt IPO decision.

Table 1 further breaks out the sample by industry grouping based on Standard Industrial Classification

(SIC) codes. The sample contains firms from eight broad industries but is concentrated in the manufacturing

5The authors examine situations in which they have available initial rating dates for both S&P and Moodys and find that in thevast majority of cases, Moodys initiation date either leads or occurs in the same year as initial coverage by S&P.6The authors acknowledge the provision of the equity IPO data from Professor Jay Ritters web page.


7/22


sector with approximately one third of the observations. Financial firms and those in transportation including

utilities and communications are the next biggest groupings. While it is common to exclude utilities and

financial firms from analysis on the basis that they are subjected to regulation, the authors refrain from doing so.

As noted by Kisgen (2006), rating considerations are just as likely to impact financial and utility firms as

industrials.

Figure 1. Debt rating initiations and equity IPOs by calendar year.

Table 1

Sample Firms Categorized by Year of Initial Rating and Industry

Year Agriculture Mining Construction Manufacturing Transport Wholesale/Retail Finance Services Unclassified Total

1980 9 1 23 3 1 9 2 1 49

1981 5 14 2 3 6 3 33

1982 2 1 13 3 7 18 6 50

1983 3 1 15 3 5 14 7 48

1984 1 4 12 7 11 8 5 1 49

1985 1 3 1 46 15 21 35 13 135

1986 2 4 5 66 20 17 33 19 1 167

1987 3 3 53 10 9 9 14 101

1988 1 24 7 8 8 7 1 56

1989 4 1 17 10 10 12 5 1 601990 2 9 10 2 4 2 29

1991 1 4 24 14 6 8 1 58

1992 4 1 33 20 10 13 13 1 95

1993 1 3 2 38 15 21 27 21 1 129

1994 7 8 44 25 13 17 7 1 122

1995 1 9 42 21 10 32 12 1 128

1996 16 1 46 35 22 27 32 2 181

1997 1 21 1 83 46 27 48 29 1 257

1998 1 15 4 91 41 35 24 51 262

0

100

200

300

400

500

600

700

800

1980

1981

1982

1983

1984

1985

1986

1987

1988

1989

1990

1991

1992

1993

1994

1995

1996

1997

1998

1999

2000

2001

2002

2003

2004

2005

2006

2007

2008

2009

2010

Number of Rating Initiations and Equity IPOs by Year

Rating Initiations

Equity IPOs


8/22


(Table 1 continued)

Year Agriculture Mining Construction Manufacturing Transport Wholesale/Retail Finance Services Unclassified Total

1999 7 6 67 61 11 25 33 2 212

2000 2 25 34 3 16 9 89

2001 5 3 26 23 4 10 8 792002 6 16 12 9 9 2 54

2003 4 1 28 10 7 10 15 75

2004 9 36 18 10 14 17 104

2005 1 11 2 34 10 8 10 22 98

2006 1 2 6 9 1 19

2007 4 6 10

2008 3 3 5 1 12

2009 3 11 6 20

2010 2 6 1 9

Total 9 161 46 933 501 290 478 357 15 2,790

Notes.Table 1 classifies sample firms by both year of Moodys rating initiation and industry. Eight broad industry classifications

are defined according to SIC codes. These classifications are: agriculture/fishing/forestry (SIC codes 0-999), mining (SIC codes

1000-1499), construction (SIC codes 1500-1799), manufacturing (SIC codes 2000-3999), transportation/communication/electric/gas

(SIC codes 4000-4999), wholesale/retail (SIC codes 5000-5999), finance/insurance/real estate (SIC codes 6000-6799), and services

(SIC codes 7000-8999).

To be part of the sample, the authors do not require rated firms to have available data for the entire 30-year

observation period. Since lagged variables are required for some of the analysis, the authors download available

Compustat data from 1979 to 2010 with many firms only appearing in Compustat for a small portion of these

years. In addition to collecting data for firms that hold debt ratings, the authors also download data for all

non-rated firms. In this way, the characteristics of rated versus non-rated firms and the roles of both firm and

market factors on the rating initiation decision can be explored.

Table 2 includes summary statistics for the sample as a whole and separately for rated and non-rated firms.

The authors present both means and medians; however, some of the means are skewed by extreme observations

despite winsorizing data at the first and the 99th percentile. The authors focus on firm characteristics that vary

predictably with a firms stage in its life cycle and examine the difference in these characteristics for rated and

non-rated firms to confirm that rated firms are more mature based on these features.

Table 2

Summary Statistics for Rated Versus Non-rated Firms

Mean Median

All firms Rated Non-rated p-value All firms Rated Non-rated p-value

Asset structure

LTD/TA 0.188 0.289 0.169 0.000 0.110 0.251 0.085 0.000

Cash/TA 0.155 0.094 0.166 0.000 0.064 0.047 0.069 0.000

Tangibility 0.292 0.343 0.283 0.000 0.210 0.292 0.196 0.000

Growth

M/B 2.319 1.688 2.438 0.000 1.316 1.278 1.327 0.000

Capex/S 0.198 0.138 0.210 0.000 0.041 0.048 0.039 0.000

Profitability

EBIT/S -0.491 0.083 -0.601 0.000 0.072 0.107 0.064 0.000

Marginal tax rate 0.285 0.340 0.273 0.000 0.331 0.343 0.318 0.000


9/22


(Table 2 continued)

Mean Median

All firms Rated Non-rated p-value All firms Rated Non-rated p-value

Risk

Std. dev. of CF 3.710 1.575 3.730 0.000 0.046 0.034 0.046 0.000Beta 1.270 1.205 1.287 0.000 1.225 1.181 1.225 0.000

Age variable

Ln(Sales) 4.354 6.604 3.925 0.000 4.438 6.626 3.991 0.000

RE/TE -0.116 0.367 -0.203 0.000 0.350 0.505 0.312 0.000

Yrs in CRSP 12.061 15.996 11.341 0.000 8 12 8 0.000

Yrs since Div. 15.812 18.381 15.043 0.000 12 15 11 0.000

Notes. The variables included are defined as: long-term debt to total assets (LTD/TA); cash to total assets (Cash/TA); net fixed

assets over total assets (Tangibility); M/B; capital expenditures to sales (Capex/S); EBIT over sales (EBIT/S); marginal tax rate;

the standard deviation of cash flows (Std. dev. of CF); the beta of the firms common stock (Beta); the natural logarithm of sales

(Ln(Sales)); RE/TE; the number of years the company has been in CRSP (Yrs in CRSP); and the number of years since the firm

initiated its first dividend payment (Yrs since Div.). Tests of the difference in mean (median) values between rated and non-rated

firms and the associatedp-values are provided in the columns following these variables.

Table 3 provides the correlation among firm characteristics expected to be related to the decision to secure

a bond rating. Variable definitions are outlined in Table 2.

Table 3

Correlation Coefficients

LTD/TA

Cash/TA

Tangibility M/B Capex/S EBIT/SMarginaltax rate

Std. dev.of CF

Beta Ln(Sales) RE/TEYrs inCRSP

Yrssince

Div.

LTD/TA 1.00

Cash/TA -0.34 1.00

Tangibility 0.32 -0.31 1.00

M/B -0.15 0.27 -0.10 1.00

Capex/S 0.16 -0.03 0.39 0.03 1.00

EBIT/S -0.11 0.33 -0.02 0.39 0.22 1.00

Marginal

tax rate

0.00 -0.04 0.06 -0.02 -0.05 0.09 1.00

Std. dev.of CF

0.02 0.03 0.01 0.05 0.23 0.27 -0.03 1.00

Beta -0.02 0.11 -0.22 -0.03 -0.07 -0.07 -0.09 0.00 1.00

Ln(Sales) 0.12 -0.22 0.12 0.05 -0.10 -0.04 0.14 -0.05 -0.24 1.00

RE/TE -0.03 0.00 0.01 0.02 -0.02 0.09 0.12 -0.01 -0.05 0.10 1.00

Yrs inCRSP

0.03 -0.10 0.08 -0.01 -0.03 -0.01 0.00 0.00 -0.26 0.42 0.06 1.00

Yrs sinceDiv.

0.06 -0.15 0.11 -0.03 -0.04 -0.02 -0.01 0.00 -0.30 0.46 0.06 0.77 1.00

The first three measures are related to balance sheet structure: LTD/TA, Cash/TA, and net fixed assets to

total assets, which measures asset tangibility (Tangibility). Within the sample, it can be seen that firm leverage is

higher for rated firms and rated firms hold significantly more tangible assets than their non-rated peers. This is

logical, since firms with more tangible assets can borrow more and should have greater access to public debt

markets. It can also be seen that Cash/TA is significantly lower for rated firms, which is consistent with these

firms being larger and more mature, observations with less need to stock pile cash for unanticipated shortfalls.


10/22


The next two measures are proxies for growth opportunities: M/B and Capex/S. Both the mean and

median M/B ratios are significantly lower for rated firms. In contrast, the mean Capex/S ratio is lower for rated

firms, while the median is higher. A priori, life cycle theory suggests that rated firms should be more mature

with lower growth opportunities. The differential M/B ratios confirm this conjecture, while the mixed message

on capital expenditures indicates that many firms are in the process of converting these intangible growth

opportunities into tangible real assets. The significant increase in debt is consistent with financing in

anticipation of these additional capital expenditures.

Two variables related to firm profitability are considered: the operating margin or EBIT/S7and the firms

marginal tax rate. The authors use simulated marginal tax rates provided by John Graham with details of their

calculation discussed in Graham (1996a; 1996b). As expected, rated firms are significantly more profitable than

non-rated firms, which results in a slightly higher marginal tax rate. This higher tax rate in turn increases the

value of the tax shield from debt financing which is particularly valuable for firms with lower risks.

Two measures to estimate firm risk are used: standard deviation of CF and Beta. The authors define cash

flow as operating cash flow before depreciation less capital expenditures and dividends scaled by sales. The

standard deviation of this measure is based on the previous three years of data. Beta estimation follows the

procedure outlined by Fama and French (1992) with a firms beta being represented by the beta-size portfolio

to which it belongs. As expected, these variables are significantly smaller for rated firms, indicating their lower

risk status.

The last four variables include more direct proxies for age: Ln(Sales), RE/TE, Yrs in CRSP, and Yrs since

Div.. Ln(Sales) controls for size, which has been shown to be closely related to a firms age and its life cycle

stage, as well as an important leverage determinant. As expected, rated firms are significantly larger than

non-rated firms. Cumulative retained earnings (RE/TE) is used as a measure of age by DeAngelo et al. (2006)

who found that it is a key measure of a firms stage in its life cycle with higher values indicating more mature

firms. As expected, the results show that rated firms have significantly higher cumulative retained earnings thannon-rated firms, implying a later life cycle stage.

The last two variables confirm that rated firms have been publicly listed longer than non-rated firms and

initiated dividend payments in the more distant past8. From Table 3, it can be seen that these age variables

correlate highly with one another (0.77) and with the size variable that also proxies for age (both correlations

exceed 0.40). To avoid multi-collinearity and to rely primarily on firm characteristics indicative of life cycle

phases rather than absolute years, the authors drop the Yrs in CRSP and Yrs since Div. variables in further

analysis. There are no other surprises in the correlation table, with all other correlations being between

-0.34 and +0.39.

Trends in Financial Characteristics and Market Variables Surrounding Debt Rating

Initiations

In this section, the authors discuss how a firm evolves during the period surrounding its debt rating

initiation, as measured by the financial ratios summarized in the previous section. The authors also begin to

study internal (firm-specific) and external (market) timing factors that may influence the debt IPO decision.

7The authors use EBIT/S rather than return on assets (ROA) or other commonly used measures of profitability, because neither

EBIT nor sales are directly influenced by the issue of new debt, unlike measures that use net income or total assets.8The Yrs in CRSP and Yrs since Div. summary statistics cannot be directly compared with each other, since many firms in

CRSP do not pay dividends.


11/22


The authors denote the calendar year that a company first receives an initial debt rating as Year 0 and examine

each variable for the five years prior to Year 0 and for the five subsequent years. Table 4 presents the median

values, which the authors use instead of the means, because, as mentioned earlier, several means are skewed by

extreme observations. For illustrative purposes, results are presented only for those firms that have available

data for the full 11-year period so that how those firms evolve in the period surrounding their rating initiations

and debt IPOs can be clearly seen. Results are similar, however, when presented for the entire sample of firms

including those with only partially available data. P-values based on one-sided non-parametric tests are

reported in the last row and show whether the median values for these ratios are significantly different in the

pre-rating period from -5 to -1 years versus the post-rating period of +1 to +5 years.

Table 4

Medians by Relative Year for Firm Characteristics and Opportunistic Market Timing

Year

Asset structure Growth Profitability Risk

LTD/TA Cash/TA Tangibility M/B Capex/S EBIT/SMarginal

tax rate

Std. dev.

of CF

Beta

-5 0.185 0.053 0.326 1.234 0.059 0.109 0.350 0.029 1.127

-4 0.171 0.051 0.321 1.267 0.056 0.112 0.348 0.029 1.106

-3 0.174 0.051 0.333 1.310 0.056 0.110 0.348 0.028 1.116

-2 0.177 0.049 0.331 1.321 0.058 0.113 0.348 0.027 1.159

-1 0.200 0.042 0.317 1.349 0.059 0.112 0.348 0.028 1.179

0 0.296 0.046 0.296 1.252 0.056 0.108 0.348 0.031 1.181

+1 0.289 0.042 0.303 1.246 0.055 0.106 0.346 0.029 1.190

+2 0.288 0.040 0.294 1.249 0.048 0.102 0.344 0.028 1.190

+3 0.283 0.042 0.292 1.223 0.045 0.102 0.340 0.027 1.179

+4 0.280 0.046 0.286 1.245 0.044 0.100 0.340 0.025 1.181

+5 0.255 0.045 0.282 1.276 0.043 0.105 0.340 0.023 1.190

p-value 0.000 0.000 0.000 0.000 0.000 0.001 0.000 0.015 0.000

YearAge variable Stock performance Interest rate

Ln(Sales) RE/TE Prior stk. ret. Future stk. ret. Historical BAA 10 yr. T-bond Term structure

-5 5.989 0.540 0.485 0.640 -0.826 7.683 2.178

-4 6.117 0.519 0.492 0.626 -0.664 7.080 2.178

-3 6.241 0.521 0.521 0.635 -0.652 7.080 2.178

-2 6.360 0.485 0.635 0.391 -0.652 6.580 2.178

-1 6.515 0.484 0.623 0.236 -0.826 6.438 1.704

0 6.700 0.478 0.619 0.199 -0.913 6.353 1.629

+1 6.821 0.474 0.381 0.247 -0.913 6.029 1.433

+2 6.915 0.508 0.229 0.308 -0.664 6.029 1.433

+3 7.014 0.511 0.200 0.328 -0.583 5.873 1.433

+4 7.099 0.515 0.250 0.339 -0.583 5.264 1.629

+5 7.196 0.528 0.332 0.287 -0.664 5.018 2.483

p-value 0.000 0.003 0.000 0.000 0.002 0.000 0.000

Notes. Year 0 is the year that the firm first obtains a Moodys rating. Negative and positive years correspond to fiscal years prior

to and following rating initiation respectively. Variables are defined in Table 2. Additional variables include: the 36-month prior

market adjusted returns (i.e., raw returns minus market returns) (prior stk. ret.); the 36-month subsequent market adjusted returns

(future stk. ret.); the difference between the average BAA yield and its 5-year historical averages (historical BAA); the yield on

10-year Treasury bonds (10 yr. T-bond); and the difference between 10-year Treasury bond yields and 3-month T-bill yields (term

structure). Tests of difference in median values between years from -5 to -1 and years from 1 to 5 are conducted with the

associatedp-values provided in the bottom row of Table 4.


12/22


The authors begin by looking at the asset structure and growth variables. As one would expect, the

LTD/TA variable increases significantly in Year 0 (due to the new debt issue) and remains higher afterwards.

This is consistent with the argument made earlier that the new debt issue and corresponding increase in debt is

a natural progression as the firm matures and sees its growth opportunities decline. This is further corroborated

by the reduction in growth opportunities, which is evident in the two measures of growth which both decline

significantly from the earlier to later period. Cash/TA and Tangibility also decline in the period following the

debt issue. In the case of Cash/TA, this is consistent with a firm continuing to grow more mature and hence has

less need for additional cash buffers on hand. However, the decline in asset tangibility is contrary to

expectations; although it is consistent with the observed decline in capital expenditures and the increase in TA

that arises due to the debt issue.

An important observation in Table 4 is that firm profitability declines significantly after Year 0, as

measured by EBIT/S9. This observation is consistent with the life cycle theory in the sense that the firm is

maturing, experiencing lower growth opportunities and lower margins. However, the significant decline

immediately following Year 0 also suggests that the firm times its debt rating initiation to follow a period ofstrong profitability.

The age variables give mixed messages. Ln(Sales) increases significantly after the debt issue, which is as

expected and is consistent with the firm getting larger (i.e., life cycle). However, contrary to expectations, the

RE/TE variable declines slightly, but significantly. Summary statistics not reported here suggest that this is

not attributable to firms issuing new equity. However, it could be a function of the lower profit margins

experienced by the firms after their debt IPOs, as well as the higher dividend payouts they maintain as more

mature firms. Although not reported in Table 4, it has been found that rated firms pay more dividends.

Consistent with Aivazian et al. (2006), the mean ratio of dividends per share to earnings per share increases

significantly surrounding rating initiation. Increasing dividend payments and the absence of new equity issues

may culminate in lower marginal contributions to retained earnings and therefore a lower value of RE/TE.

Table 4 also includes five new variables that are related to the timing argument. The first two are internal

measures of firm attractiveness to potential investors. The authors hypothesize that firms will be more inclined

to issue new debt when they are perceived as doing well by investors. While clearly some of the previous

variables such as EBIT/S and M/B will be related to investor perception, a more direct measure is to examine

the performance of the firms stock in the period prior and subsequent to obtaining an initial debt rating. If a

companys stock is doing well, its rating should reflect this, since several rating agencies have moved to

implement market-based bankruptcy prediction models based on the Mertons (1974) model and the idea that

equity is a call option on the firms underlying assets. Some rating agencies have also explicitly introduced

stock performance as a rating criterion, arguing that it provides important information about the firms ability toraise equity capital and the confidence of its trading partners and creditors to carry on day-to-day business with

the firm (S&P, 2008).

As such, the following two variables related to stock returns are introduced: the 36-month prior market

adjusted returns (i.e., raw returns minus market returns), denoted as prior stk. ret. and the 36-month

subsequent market adjusted returns, denoted as future stk. ret.. The higher the prior returns, the better the

9 Other traditional measures of profitability such as net income margin or ROA experience even larger declines. This is notsurprising, since net income is influenced adversely by the additional interest payments, while in the case of ROA, the

denominator (i.e., total assets) increases as a result of the new debt issue.


13/22


firms stock has been doing and presumably the better the time to enter the public debt markets with a new

issue, hence the authors would expect them to be higher prior to Year 0. Similarly, the authors would expect

future returns to decline afterward, i.e., the lower the subsequent returns, the better the firm did in terms of

timing their debt issue decisions. These patterns are clear and significant in Table 4.

Additional evidence supporting this internal timing hypothesis can be seen in Figure 2 which depicts the

average cumulative excess returns for the 60-month period prior to and after the initial debt rating. Year of

rating initiation is Year 0. Excess returns are defined as the difference between the stock return and the return

on the equally-weighted portfolio of stocks from the New York Stock Exchange (NYSE), National Association

of Securities Dealers Automated Quotation (NASDAQ), and American exchanges10

. The patterns in Figure 2

are consistent with timing behavior, with positive cumulative excess returns increasing dramatically prior to the

rating and then declining in Year 1, before remaining virtually flat in the following four years.

Figure 2. Mean excess stock returns in years surrounding rating initiation.

In addition to internal factors, the authors also examine the firms market timing ability by reference to

general debt market conditions. In this sense, the authors look at the demand side of the debt IPO decision byexamining how attractive the current debt market is in terms of interest rates relative to historical levels (as

cited in Barry et al., 2008), in terms of absolute levels, and in terms of the shape of the term structure11

. The

authors do so using the following three variables: the difference between the average BAA yield and its 5-year

historical averages (historical BAA); the yield on 10-year Treasury bonds (10 yr. T-bond); and the difference

between the 10-year Treasury bond yield and 3-month T-bill yields (term structure). The summary statistics

10Use of a value-weighted index did not change the results.11The authors would expect the term structure to influence new issues, since bonds reflect long-term rates. In addition, the term

structure is a well-known predictor of the stage in the business cycle, which can also influence market timing.

-0.1

0

0.1

0.2

0.3

0.4

0.5

-60 -50 -40 -30 -20 -10 0 10 20 30 40 50 60

Sample Monthly Mean Cumulative Excess Stock Returns

Cumulative stock return Cumulative stock return (excluding dividends)


14/22


indicate a significant decline in all three of these interest rate variables from the pre-rating period to the year of

rating initiation. This summary evidence is consistent with the results of Barry et al. (2008) that firms take into

consideration interest rate levels in timing their debt issues.

The summary evidence provided so far in Tables 3 and 4, as well as in Figure 2, supports the notion that

both life cycle influences and timing influences (as reflected by market conditions and firm-specific stock

returns) influence the debt IPO decision. Of final importance note that the trend values for the debt IPO firms in

Table 4 are much closer to those of rated firms even prior to the rating initiation. For example, the median

values for Cash (0.053), Tangibility (0.326), the M/B (1.23), Capex growth (0.059), EBIT/S (0.109), marginal

tax rate (0.350), std. dev. of CF (0.029), and Ln(Sales) (5.989) even five years prior to the rating initiation are

closer to those of rated rather than non-rated firms. It remains to predict when these firms move from non-rated

to rated, that is, when they choose to go through their debt IPOs.

Factors Affecting the Debt Rating Initiation Decision

Firm Level and Life Cycle Influences

The authors use a logit regression model to predict the initiation of the debt rating, similar to the approach

DeAngelo et al. (2006) and Aivazian et al. (2006) used to predict whether a firm pays a dividend or not. The

authors include all non-rated firms from Compustat during the sample time period in addition to all rated firms,

but only in the years prior to and including the year of their initial ratings. That is, only the pre-rating and

Year 0 observations are included. The dependent variable takes on a value of one in the year of a rating

initiation and zero for all other unrated periods. For independent variables, the base case model includes the

nine factors from Table 4 related to asset structure, growth, profitability, and risk. These control variables have

been shown to influence firm leverage, and hence, many of them can also be expected to be closely related to

the decision to issue public debt

12

. In this respect, it is argued that as the firm evolves through its life cycle,these standard firm characteristics are, in part, manifestations of this progress and endogenous to this path. As a

result, these variables would be expected to impact the debt IPO decision.

Column (1) of Table 5 presents the results of this base case logit regression. Overall, the model produces

a pseudo R2value of 6.9% and generally supports the notion that traditional factors affecting leverage also

influence the public debt issuance decision. The LTD/TA variable, which controls for the influence of firm

leverage, has a large positive and significant coefficient. This is as expected, since firms are likely to obtain

debt ratings in anticipation of issuing public debt and increasing their leverage ratios. This is consistent with

life cycle theory and also the observed increase in debt ratios as of the debt IPO date depicted in Table 4.

Cash/TA has a positive and significant coefficient, which is consistent with DeAngelo et al.s (2010)

finding that life cycle and timing influences on capital raising decisions are also subjected to the firms

fundamental need for cash. While Table 4 shows a general decline in cash holdings as the firm matures, this

pattern is temporarily abandoned in the year of rating initiation when cash increases due to the additional debt

issued. By Year +1, cash has declined to the level previously maintained during the year prior to rating

initiation.

12The authors do not include industry dummies, because many of the firm-level variables, such as asset tangibility, Capex, etc.,will be related to industry. Similarly, the authors do not include year dummies, because they will later include proxies for debt

market attractiveness, which are time-specific in nature.


15/22


Table 5

Debt Rating Initiation: Life Cycle Versus Timing Logit Regression (Rating Initiation = 1)

(1) Firm

characteristics

(2) Age (by firm

characteristics)

(3) Opportunistic

stock performance

(4) Debt market

timing(5) All

LTD/TA 3.474

***

3.649

***

3.636

***

3.442

***

3.734

***

[27.75] [23.20] [22.95] [25.34] [18.43]

Cash/TA 0.315 1.117*** 0.360 0.266 1.125***

[1.379] [4.580] [1.328] [1.148] [3.857]

Tangibility -0.566*** -0.662*** -0.603*** -0.379*** -0.545***

[-4.105] [-3.935] [-3.540] [-2.710] [-2.720]

M/B 0.0233*** 0.0233*** 0.0157** 0.0198*** 0.00582

[4.753] [3.977] [2.263] [3.597] [0.701]

Capex/S 0.586*** 0.892*** 0.830*** 0.611*** 0.983***

[5.350] [13.26] [4.565] [6.846] [6.742]

EBIT/S 0.166** 0.171* 0.172* 0.0499 0.195

[2.422] [1.699] [1.781] [1.296] [1.230]

Marginal tax rate 5.060*** 4.288*** 4.409*** 9.950*** 6.821***

[13.66] [9.736] [10.46] [17.07] [8.095]

Std. dev. of CF -0.169 -0.0620 -0.913** -0.117 -0.318

[-0.951] [-1.189] [-2.387] [-1.046] [-1.521]

Beta -0.144 0.472*** -0.193* 0.0317 0.477***

[-1.556] [4.629] [-1.786] [0.335] [3.947]

Ln(Sales) 0.395*** 0.353***

[22.48] [15.53]

RE/TE 0.00483 -0.0101

[0.872] [-0.996]

Prior stk. ret. 0.0391*** 0.0417**

[2.929] [2.556]

Future stk. ret. -0.152*** -0.113***

[-4.362] [-3.055]

Historical BAA -0.0722*** -0.101***

[-3.971] [-4.433]

10 yr. T-bond -0.194*** -0.0751***

[-11.54] [-3.224]

Term structure -0.0484* -0.0343

[-1.650] [-0.986]

Constant -6.723*** -9.691*** -6.351*** -7.193*** -9.767***

[-32.73] [-36.15] [-26.02] [-29.88] [-28.24]

N 93,908 92,972 66,764 93,908 66,143

PseudoR2

0.0845 0.131 0.0818 0.106 0.131Notes. Table 5 provides the estimated coefficients from a logit regression where the dependent variable is equal to one in the year

of rating initiation and zero for all other observations. The sample includes all non-rated firms from Compustat and rated firms

during their pre-rating years and year of rating initiation. T-statistics for the significance of the coefficients are reported in

brackets with variables defined in Table 2. Significance at the levels of 1%, 5%, and 10% is indicated by ***, **, and * respectively.

Asset tangibility has a negative and significant coefficient, contrary to expectations, since firms with

greater tangibility would be expected to be better able to access public debt markets. Similarly, the growth

measures M/B and Capex/S both display positive and significant coefficients, contrary to the predictions of

traditional leverage models and the life cycle theory. Part of this could be attributed to the common issues


16/22


associated with the uses of these and other measures to proxy uncertain future growth opportunities. On the

other hand, a positive coefficient on M/B is consistent with market timing theory, as well as the evidence on

prior stock returns in Figure 2 and Table 4, since it suggests that debt is issued when stock prices are higher.

The two profitability measures are both significant, with the expected sign. EBIT/S is positive and

significant, which is consistent with issuing debt when the firm is more profitable. The marginal tax rate has a

very large positive and significant coefficient, attesting to the importance of the tax shield benefits associated

with leverage and the fact that average tax rates increase with profitability. Finally, both of the risk measures

have the expected negative signs; however, only the std. dev. of CF is significant at the level of 10%.

The authors incorporate the two age variables in Column (2) of Table 5, since they are more directly

related to the life cycle theory. The size proxy (Ln(Sales)) is positive and significant, consistent with the life

cycle arguments proposed earlier, since larger firms would be expected to be more mature, and therefore more

inclined to, as well as having a greater ability to, issue public debt than smaller firms. The RE/TE has the

expected positive sign but is insignificantly different from zero. These results suggest that once controlling for

firm characteristics that are known to be related to firm leverage, life cycle influences continue to impact thedebt IPO decision but primarily through firm size.

Evidence of Timing

The logit models above include several firm level and life cycle variables that one might expect would

influence the debt IPO decision. As argued previously, the authors believe that firms carefully time this

decision. Certainly, the summary evidence provided regarding the decline in profitability after the initial rating

and superior stock returns prior to the initial rating lends support to this conjecture. The authors examine this

hypothesis more formally in Column (3) of Table 5 by adding the prior stk. ret. and future stk. ret.

variables to the base case logit regression. The coefficient signs are as expected, with prior returns being

positive and significant and future returns being negative and significant. While the pseudo R

2

of 6.6% issimilar as for the base model, the numbers are not directly comparable, because the number of observations

declines significantly due to stock return data availability.

In addition to internal factors, the authors also examine the firms market timing ability by reference to

general debt market conditions. Column (4) of Table 5 reports the logit results when three interest rate variables

are added to the base case variables. All the three variables have the expected negative and significant

coefficients, suggesting that firms issue new debt when BAA yields are low relative to their 5-year averages,

when T-bond yields are lower, and when the term spread is lower (i.e., flatter yield curve). All of these

observations are consistent with firms displaying good market timing with respect to debt market conditions.

There is an incremental improvement in the pseudo R2 value, from 6.9% to 8.0%; albeit not as great an

improvement as when the two life cycle variables are added into Column (2).

Finally, in Column (5), the authors include all life cycle and timing variables. Most of the previous results

remain unchanged. Size retains its positive and significant coefficient, and both stock performance measures

retain their expected sign and significance, attesting to their relevance. The historical BAA factor remains

negative and significant as predicted, while the term structure variable remains negative. On the other hand, the

coefficient of the T-bond yield is now positive, but insignificant. However, overall interest rate considerations

remain important. If Columns (3) and (5) which have a similar number of observations are compared, an

improvement in the pseudoR2value from 6.6% to 9.3% is seen.


17/22


Taken together, the results in this section support the notion that both life cycle and opportunistic timing

influence the rating initiation decision. Firms secure debt ratings in the mid-to-later part of their life cycles when

they are larger and able to bear more leverage. Precisely, when will these mature firms seek to issue public bonds

is influenced by their recent operating results, their stock market performance, and market interest rates.

Initial Debt Rating Levels

An additional way of exploring the timing of the rating initiation decision is to focus on the rating level

assigned by Moodys in addition to the rating decision itself. Presumably, a firm will choose to get rated when

management believes that they will get the best possible rating for the firm. To the extent that internal, firm

level factors have an important influence on this decision, the authors expect to see the stable profits and low

risk associated with a mature firm translating into a strong rating assignment. The authors focus on firm (rather

than market) characteristics for tests of opportunistic timing in this section, since the rating level should be

determined primarily by firm-specific factors, and to the extent that economic conditions impact ratings, it will

likely be through their influences on these factors.To start the analysis, Figure 3 graphs the number of rating initiations with the median rating level assigned

by Moodys across all firms receiving their initial ratings in a given year. From Figure 3, the authors see clear

evidence of opportunistic behavior at the aggregate level. Years with few rating initiations frequently overlap

with difficult economic times, such as the recessionary periods in 1982, 1992-3, 2001-2, and the recent

financial crisis. However, the few firms that obtain their initial ratings during these periods receive relatively

strong ratings with median rating levels peaking in these years. Firms that are strong enough to secure high

ratings continue to do so during difficult economic times, compared with those that cannot choose to wait until

more favorable economic conditions return. It also suggests that only higher rated firms are able to issue public

debt during tougher times, which is consistent with a flight to quality during such periods.

Figure 3. Number of rating initiations and median rating level by year.

0

2

4

68

10

12

14

16

18

20

0

50

100

150

200

250

1980

1982

1984

1986

1988

1990

1992

1994

1996

1998

2000

2002

2004

2006

2008

2010

RatingLeve

l(Aaa=21,

C=1)

NumberofInitiations

Moodys Rating Initiations and Median Rating Level by Year

Rating Initiations

Median Moody's Rating


18/22


19/22


20/22


21/22


prospects than their non-rated peers. The authors examine how these firm characteristics change as the firm

begins to access public debt markets. The authors also find that their growth rates and capital expenditures

decline throughout the period surrounding rating initiation, and their debt ratios increase, observations that are

again consistent with firms in the mid-to-later stages of their life cycles.

At the same time, the evidence shows that firm profitability increases prior to and decreases after the

rating initiation, indicating that the rating initiation was well-timed. Further support for this timing is apparent

from the positive excess stock returns firms experience prior to the initiation, versus the negative excess returns

in the year following the initiation. In addition to this equity market timing, the authors find evidence that firms

carefully consider debt market factors in their timing as well. Firms issue new debt when BAA yields are low

relative to their 5-year averages, when T-bond yields are lower, and when the term spread is lower. In times of

recession, only the strongest firms choose to secure initial ratings, while others wait until the economy recovers.

While the debt IPO decision seems to be well-timed, the authors do not find any evidence that firms obtain

inflated ratings, at least not as reflected in subsequent downgrades, as they do not appear to fool the rating

agencies. However, it is reasonable to assume that management acts as if they will obtain the best ratingpossible and that they issue at a time when they believe that the market has the greatest appetite for their debts.

Consequently, they clearly pay attention to the timing of the debt issue.

The findings of this paper contribute to both the literature on financing through a firms life cycle and the

importance of managerial timing. While additional evidence for each research stream individually is provided,

the authors also show how intertwined the two are for public debt IPOs. Clearly, public debt issues are open

only to firms in the mid-to-later stages of their life cycles; however, the evolution to this phase occurs over

several years. As a result, there is little difference between a rated firm and one that will be rated at some point

in the next five years. Since movement through the life cycle is slow, management can bide its time when

deciding on the precise moment to begin issuing public debt, and chooses to do so when internal and external

factors show that the moment is right. On balance, management does a good job in selecting this moment and

successfully achieves strong initial ratings.

References

Aivazian, V., Booth, L., & Cleary, S. (2006). Dividend smoothing and debt ratings. Journal of Financial and Quantitative

Analysis, 41(2), 439-453.

Altman, E. (1968). Financial ratios, discriminant analysis, and the prediction of corporate bankruptcy. Journal of Finance, 23(4),

589-609.

Barry, C. B., Mann, S. C., Mihov, V. T., & Rodriguez, M. (2008). Corporate debt issues and the historical level of interest rates.

Financial Management, 37(3), 413-430.

Burch, T., Christie, W., & Nanda, V. (2004). Do firms time equity offerings? Evidence from the 1930s and 1940s. Financial

Management, 33(1), 5-23.Chan, K., Ikenberry, D. L., & Lee, I. (2007). Do managers time the market? Evidence from open-market share repurchases.

Journal of Banking and Finance, 31(9), 2673-2694.

Chang, X., Hilary, G., Shih, C. M., & Tam, L. H. K. (2010). Conglomerate structure and capital market timing. Financial

Management,39(4), 1307-1338.

DeAngelo, H., DeAngelo, L., & Stulz, R. (2006). Dividend policy and the earned/contributed capital mix: A test of the life-cycle

theory.Journal of Financial Economics,81(2), 227-254.

DeAngelo, H., DeAngelo, L., & Stulz, R. (2010). Seasoned equity offerings, market timing, and the corporate life cycle. Journal

of Financial Economics,95(3), 275-295.

Fama, E., & French, K. (1992). The cross-section of expected stock returns. Journal of Finance, 47(2), 427-465.


22/22


Fama, E., & French, K. (2005). Financing decisions: Who issues stocks? Journal of Financial Economics, 76(3), 549-582.

Faulkender, M., & Petersen, M. A. (2006). Does the source of capital affect capital structure? The Review of Financial Studies,

19(1), 45-79.

Graham, J. R. (1996a). Debt and the marginal tax rate.Journal of Financial Economics, 41(1), 41-73.

Graham, J. R. (1996b). Proxies for the corporate marginal tax rate. Journal of Financial Economics, 42(2), 187-221.

Graham, J. R., & Harvey, C. (2001). The theory and practice of corporate finance: Evidence from the field. Journal of Financial

Economics,60(2-3), 187-243.

Grullon, G., Michaely, R., & Swaminathan, B. (2002). Are dividend changes a sign of firm maturity?Journal of Business, 75(3),

387-424.

Jenkinson, T., & Ljungqvist, A. (2001). Going public: The theory and evidence on how companies raise equity finance (2nd ed.).

Oxford, UK: Oxford University Press.

Jensen, M. C. (1986). Agency costs of free cash flow, corporate finance, and takeovers.American Economic Review, 76(2), 323-329.

Kisgen, D. (2006). Credit ratings and capital structure.Journal of Finance, 61(3), 1035-1072.

Kliger, D., & Sarig, O. (2000). The information value of bond ratings. Journal of Finance, 55(6), 2879-2902.

Lee, I. (1997). Do firms knowingly sell overvalued equity? Journal of Finance, 52(4), 1439-1466.

Loughran, T., & Ritter, J. (1995). The new issues puzzle.Journal of Finance, 50(1), 23-51.

Merton, R. (1974). On the pricing of corporate debt: The risk structure of interest rates. Journal of Finance, 29(2), 449-470.

Mueller, D. C. (1972). A life cycle theory of the firm.Journal of Industrial Economics, 20(3), 199-219.

Myers, S. (1999). Financial architecture.European Financial Management, 5(2), 133-141.

Rajan, R. (1992). Insiders and outsiders: The choice between informed and arms length debt.Journal of Finance, 47(4), 1367-1400.

Ritter, J. (2003). Investment banking and securities issuance. In G. Constantinides, M. Harris, & R. Stulz (Eds.), Handbook of the

economics of finance(pp. 255-306). Amsterdam: North-Holland.

Ross, S. (1977). The determination of financial structure: The incentive-signaling approach.Bell Journal of Economics,8(1), 23-40.

Spiess, D. K., & Affleck-Graves, J. (1995). Underperformance in long-run stock returns following seasoned equity offerings.

Journal of Financial Economics,38(3), 243-267.

Standard and Poors [S&P]. (2008). Corporate rating criteria: How stock prices can affect an issuers credit rating . Retrieved

from http://www.standardandpoors.com/prot/ratings/articles/en/us/?articletype=HTML&assetID=1245335375380

Documents

Debt Rating Initiations_ Natural Evolution or Opportunistic Behavior