Corporate Diversification and Credit Risk

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					                          Corporate Diversification and Credit Risk

                               Hsien-hsing Liao∗ Tzu-Ling Huang**

                                              Abstract

    We investigate the effects of corporate diversification on credit risk using diversifying firms
engaged in mergers and acquisitions from 1980 to 2005. Consistent with coinsurance effect,
default probabilities of risky firms decline when they diversify. However, those of safe firms
increase when diversifying.   Additionally, we find that diversification does not destroy or enhance a
firm’s value. Empirical evidences show that only wealth transfer effect exists and the directions of
the transfer are opposite according to the credit quality of diversifying firms.


Key words: diversification, credit risk, wealth transfer effect, coinsurance effect, risk effect




∗
   Corresponding Author. Professor, Department of Finance, National Taiwan University, Email:
hliao@ntu.edu.tw, Phone/Fax:(886) 02-2363-8897, Address: Rm. 814, Building #2, College of
Management, National Taiwan University, 85, Sec. 4 Roosevelt Road, Taipei 106, Taiwan
**
   Investment Analyst, Aegon Insurance Life (Taiwan) Inc..
                                                  1
                                           I. Introduction

     Existing literature has documented a lot of research efforts on the issues of diversification

discount and diversification premium, most of them trying to explain the rationales why firms


diversify or focus, especially to uncover the benefits and costs of diversification.   However, few of

them explore the relationship between corporate diversification and corporate credit risk.     It is the


purpose of this study to investigate the effects of corporate diversification on credit risk using

American diversifying firms engaged in mergers and acquisitions from 1980 to 2005.


     Several potential benefits of diversification have been discussed. Lewellen (1971) assert a

coinsurance effect due to non-perfectly correlated cash flows in a diversification decision.   Besides,


diversified firm can achieve tax savings by offsetting losses in some segments against profits in other

ones. Due to tax codes’ asymmetric treatment of profits and losses, this kind of ability brings


another benefit to diversified firms.   However, Berger and Ofek (1995) argue that tax saving effect

is not significant and is only 0.1% to sales.    Second, since firms have considerable overheads to


allocate through segments, the more segments, the less overhead a segment has to absorb. Finally,

diversified firms have an internal capital market, which provides not only less costly capital resources


but also knowledgeable investors. They help alleviating the problem of underinvestment.           Stein

(1997) contends that by doing a good job in the winner-picking dimension, managers can create


value for the firm.



                                                   2
       There are also many studies exploring the costs of diversification.                       Cross-subsidization


between segments is a main consideration in prior literature.                Berger and Ofek (1995) assert that

overinvestment is associated with diversified firms’ lower value. Rajan, Servaes, and Zingales (2000)


contend the distortions generated in the allocation of resources in a diversified firm and find out

that resources flow from efficient segments toward inefficient ones.                       There are also researches


arguing that the negative effects of diversification manifest themselves in ways other than just

inefficient investment policy.1


        There are still other explanations for diversification discount.                   Doukas and Kan (2004)

discuss the effect on cash flow and stress that there is a positive and significant association between


excess cash flow decreases and excess value losses after acquisitions.               They also state bidders who

involve in an unrelated acquisition will experience larger excess cash flow declines and value discount


than those which involve in a related diversification. Maksimovic and Philips (2002) explore the

essence of diversified firms and document that firms tend to diversify just because they don’t have


any competitive advantages in their original business.                 Diversification discount, therefore, just

comes from the facts that conglomerates do not have any competitive advantages in their own


businesses.2 Whited (2001) argues that the results in the prior literature appear to be artifacts of

measurement error.

1   See, for example, Burch and Manda (2003)
2   Maksimovic and Philips (2002) discuss this issue in the framework of microeconomics.

                                                            3
       The literature previously reviewed stress mostly on the wealth of stockholders. Another line


of literature pays more attention to the wealth of debt holders regarding the corporate

diversification issues. Lewellen (1971) states mergers may increase the wealth of debt holders


through coinsurance effect, which stems from non-perfectly correlated cash flow between acquirer

firms and target firms. Galai and Masulis (1976) further argue that in a conglomerate merge3, the


increase in debt holders’ wealth through coinsurance effect comes from the decrease in

stockholders’ wealth, the so called wealth transfer effect.4                Billett, King, and Mauer (2004) show


that below investment grade target bonds earn significantly positive announcement returns, which is

consistent with coinsurance effect. They also state a risk effect, which means relatively risky debt


benefits the most from a decrease in risk, while relatively safe debt loses the most from an increase

in risk. 5 Mansi and Reeb (2002) provide evidence that diversification discount stems from


risk-reduction through corporate diversification.                  They found that shareholders’ losses are

functions of firm leverage.             When considering the wealth enhancement of debt holders,


diversification discount disappears.            Wealth just transfers from stockholders to debt holders.

Titman, Tompaidis, and Tsyplakov (2004) also argue that wealth transfer between debt holders and


stockholders is large.

3 Conglomerate merge could also be viewed as non-synergy merge.
4 According to Black-Scholes (1973), equity value can be viewed as a call option on firm assets. Non-perfectly
correlated cash flows in a conglomerate merge declines the volatility of firm value. It enhances the wealth of debt
holders, but it also destroys the wealth of stockholders due to the lower volatility. Therefore, there is a wealth transfer
effect between debt holders and stockholders in a conglomerate merge.
5 Their empirical results in target bonds provide evidences for this argument.


                                                             4
         In this study, we define acquirer firms as diversifying firms which engage in a merger and


acquisition when the acquirer firm and the target firm are in different industries at least by 2-digit

SIC code level.             We investigate the changes in default probability when firms conduct


diversification.       We divide our sample into several sub-samples to examine whether firms behave

differently when they are different in characteristics of credit quality and degree of diversification


(or numbers of business segments). According to prior literature, we forecast that no matter what

levels of credit quality firms are, coinsurance effect exists and positively affects their credit quality.


On the other hand, firms with different level of credit quality bear different consequences of risk

effects because of diversification, risky firms win and safe firms lose.                          More specifically, when


acquirer firms are relatively risky, we expect a reduction in credit risk because of coinsurance effect

and risk effect. On the contrary, when acquirer firms are relatively safe, coinsurance effect and risk


effect exert opposite influences on a firm’s credit risk.6 It is also one of our research inquiries to

examine which of the two effects is more significant in this conflicting scenario. We use a firm’s


credit quality instead of leverage ratio as one of the criteria to divide our sub-samples because the

latter cannot reflect the effect of the volatility of a firm value. We examine which types of firms


are more sensitive to coinsurance effect.                    In addition, we investigate whether diversification

discount or premium still exists after considering market value of both equity and debt


6   The coinsurance effect improves the firm’s credit risk while the risk effect impairs its credit quality.

                                                                 5
simultaneously.


      Our empirical results show that default probability of risky firms declines when firms diversify,

which is consistent with coinsurance effect and risk effect. Market value of equity also decreases


because of lower asset volatility after diversification. However, when we consider changes in

market value of debt, we find that wealth transfers from stockholders to debt holders, which is


consistent with the empirical results of Mansi and Reeb (2002). On the other hand, default

probability of safe (investment grade) firms increases when diversifying, which is inconsistent with


coinsurance effect.   We find that there is a trade off relationship between coinsurance effect and

risk effect. In this case, risk effect has greater impact than coinsurance effect.    Besides, market


value of equity increases due to the characteristics of call option. However, the market measure

based excess firm value analysis shows that wealth transfers from debt holders to stockholders.    We


conclude that there is a phenomenon of wealth transfer when firms diversify but the directions of

the transfer are not always the same. Wealth transfers from stockholders to debt holders when


risky firms diversify while wealth transfers from debt holders to stockholders when safe (investment

grade) firms do.


     The remainder of this paper is organized as follows. In section II, we introduce the data and

methodology. In section III, we present and analyze our empirical results. Finally, we conclude


the study in section IV.

                                                   6
                                         II. Methodology

A. Sample Selection

    We use the Securities Data Corporation’s (SDC) Mergers and Acquisitions Database to derive


the sample of merger and acquisition announcements during the period from 1980 to 2005.          In

this study, we take acquirer firms as firms conducting diversification. We exclude the samples when


target firms and acquirer firms are in a same industry by two-digit SIC code level to get a real

diversification sample.   We use primary SIC code as our criterion to obtain our sample of


diversifying firms.   Because of using primary SIC code as criterion, we may wrongly label a firm a

diversifying one which has more than one segment. In the cases that acquirer firms are risky firms,


the coinsurance effect and the risk effects exert impact on a firm in the same direction.       The

co-work of two effects makes firms’ credit risk declines.   It will not affect our results. However,


when firms with good credit quality (investment grade), the results of the combined results of the

two effects may be different.        The coinsurance effect may be offset by the risk effect.


Nonetheless, because our sample is large and the offsetting effects are equal in focus firms and

diversified firms, it should be not a serious problem in this case. We also exclude the samples when


acquirer firms engage in two or more mergers and acquisitions within one year to avoid intersection

effects. We require that acquirer firms be publicly traded within our observation period and




                                                  7
therefore we can find daily stock prices from CRSP.7 We also require acquirer firms’ total debt be


available on the COMPUSTAT and their numbers of segments be available on the COMPUSTAT

Segment Database during our observation period.                  Screened by the above criteria, we obtain a


sample of 906 acquirer firms.                Combining with one year T-bill rate derived from the

DATASTREAM, we calculate each acquirer firms’ default probabilities for further investigations.


We discuss more details in related variable measures in the next section.


B. Variable Measures

                   B.1. Two dimensions for dividing sample into four sub samples

      The first dimension is the differentiation of focus firms and diversified firms.                 We can obtain

numbers of segments of an acquirer firm on the latest reporting date before the announcement date


of an M&A on the COMPUSTAT Segment. When there is only one segment in the acquirer firm,

we define it as a focus firm.         If the acquirer firm has two or more segments, we define it as a


diversified firm. The second dimension is credit quality. Following Merton (1974), we derive

default probability on the latest reporting date before the announcement date of an M&A. We


assign a firm into investment grade or non-investment grade firm by mapping the derived default

probability to S&P’s Cumulative Default Rates (1981-2002).




7 Our observational period begins in the latest 20th quarterly reporting date before announcement date, and ends in the

12th quarterly reporting date after announcement date.

                                                            8
                    B.2 Changes of default probabilities when firms diversify

    Following Merton (1974), we assume market value of firms follow a geometric Brownian

motion as in (1):

                                            dVF = µVF dt + σ FVFW                                 (1)

Where V F means total value of firms, and µ represents the expected continually compounded


return of firm value. In this study, we use quarterly data from past 20 quarters to obtain µ . σ F is


the volatility of firm value, and W states standard Wiener Process. According to Black-Scholes


(1973) and Merton (1974), equity value is viewed as a call option on firm value and can be expressed

as (2).


                                       VE = VF N (d1 ) − Xe − rT N (d 2 )

                                                      1 2
                                   ln(V F / X ) + (r + σ F )T
                              d1 =                    2       , d 2 = d1 − σ F T                  (2)
                                              σF T

Where VE indicates market value of equity, X is the face value of debt, and T means time to


maturity. N is the cumulative density function (CDF) of Standard Normal Distribution.

    In this study, we use daily data from past 150 days on CRSP to calculate the volatility of

equity σ E . Using call option formula and the relationship between σ F and σ E , we can calculate


the distance to default (DD) as (3):

                                                                 1 2
                                             ln(V F / X ) + ( µ − σ F )T
                                        DD =                     2                                (3)
                                                        σF T

                                                       9
Then, we can get default probabilities as (4).

                                                                           ⎛    1 2⎞
                                                             ln(VF / X ) + ⎜ µ − σ F ⎟T
                                Pdefault   = N (− DD) = N (−               ⎝    2    ⎠            (4)
                                                                        σF T

      After obtaining default probability of firms, we calculate changes in default probability when

firms diversify.      Considering long run performance, we calculate differences between default


probability of the latest reporting date before announcement date of an M&A and that of the

1st ,2nd ,…and 12th reporting date after the announcement date.


                         B.3 Changes of excess firm value when firms diversify

      In this part, we follow Berger and Ofek (1995) and Mansi and Reeb (2002) to calculate the


excess firm values.      We derive all information of segments from COMPUSTAT Segment Database.

At first, we exclude the firms which sales are less than $20 million, and delete firms which have one


or more segments in financial industries. Following Berger and Ofek (1995) and Mansi and Reeb

(2002), we define the excess firm value as (5):

                                                       Actual _ value
                                            EV=LN (                   )                           (5)
                                                      Imputed _ value

      In book measure, actual value means the sum of market value of equity and book value of debt.


In market measure, actual value means the sum of market value of equity and debt. In other

words, the market measure considers changes of debt holders’ wealth.8 In this study, we use



8   See Mansi and Reeb (2002)

                                                         10
market value of asset derived in B.2.


      According to Berger and Ofek (1995) and Mansi and Reeb (2002), imputed value represents the

sum of a firm’s segments as focus firms using multipliers. For every segment of firms, we pick five


or more firms which have only one segment and have the same four-digit SIC code to calculate

market to sales ratio (MSR)9 as (6):

                                                             MKE + BKD
                                   MSR (book measure) =                                           (6)
                                                             Total _ sales

Where MKE means the market value of equity and BKD means the book value of debt. This


ratio represents value of assets for one unit sales. After we calculate the five or more one-segment

firms’ MSR, we choose the median as this segment’s MSR. Then, we can calculate imputed value


of a segment as (7):

                                Imputed value of segment= MSRsegment × Sales Segment              (7)


After adding all imputed value of segments, we derive imputed value of firms. In the cases that we

can not find five one-segment firms to calculate MSR on four-digit SIC code level, we try to find out


firms on three-digit or two-digit level.     If we can not find five or more one-segment firms to

calculate MSR on two-digit level, we exclude this sample. After this process, we finally derive a


sample of 433 acquirer firms.

       In market measure, we substitute market value of debt for book value of debt and derive


9   See Mansi and Reeb (2002)

                                                    11
market value of assets from B.2 calculation. Finally, we derive a sample of 250 acquirer firms.


   After getting excess firm value, we calculate changes of excess firm value when firms diversify.

Considering long run performance, we calculate differences between excess firm value of the latest


yearly reporting date before announcement date of an M&A and that of the 1st ,2nd and 3rd yearly

reporting date after the announcement date.


                                     III. Empirical Results

      As mentioned previously, we want to explore the following questions:             Are changes in

default probabilities different when firms with different characteristics diversify?    Is coinsurance


effect the only one factor which affects firms’ default probabilities when they diversify?    Do the

sample firms exhibit the phenomenon of coinsurance effect?        Does market value of equity have


the characteristics of call options? And, does diversification discount or premium disappear after

considering market value of equity and debt simultaneously?


A. Changes in default probabilities

   First, we use two dimensions to classify our sample into four sub-samples. The first dimension


is the degree of diversification. We define focus firms as firms which have only one segment on

the latest reporting date before announcement date of an M&A.       Diversified firms are firms with


two or more segments.     The second dimension is the level of credit quality. We divide samples

into investment grade and under investment grade according to default probabilities calculated and

                                                 12
S&P’s Cumulative Default Rates (1981-2002). The criterion for an investment grade firm is that its

calculated one year default probabilities are below 0.915% which is the BBB- one year default probability


approximated by the average one year cumulative default rates of rating BBB and BB shown in the S&P’s


Cumulative Default Rates Table (1981-2002).       Considering long run performance, we calculate

differences between default probabilities of the latest reporting date before announcement date of


an M&A and that of the 1st ,2nd ,…and 12th reporting date after announcement date, where “1”

indicates the difference between default probabilities of the latest reporting date before


announcement date and that of the 1st reporting date after announcement date. Table I shows the

results of changes of default probabilities when firms diversify. The results shown in the Table are


the default probabilities after the M&A minus those before the M&A. We exhibit both mean and

median results in the Table.


                                          [Insert Table I Here]

    We find that firms do exhibit different behaviors when they diversify. In the sample of risky


firms, the change in default probabilities is negative.   It means that the default probabilities of the

firms decline when the firms belong to under-investment grade group. This result is consistent


with coinsurance effect.       It has to be noted that mergers and acquisitions are not organic

expansions.   The changes in default probabilities are affected by target firms.    But when firms are


risky, coinsurance effect and risk effect have effects in the same direction. It may result from the

                                                   13
small numbers of samples. While it still economically significant.          But in the sample of safe


firms, the change of default probabilities is positive. It states that default probabilities of the firms

increase when the firms are investment grade level. This result violates coinsurance effect and risk


reduction hypothesis. Considering risk effect stated in Billett, King, and Mauer (2004), there is a

trade off relationship between coinsurance effect and risk effect when investment grade firms


diversify. Safer firms have higher probabilities to act as the relatively safe counterparty when they

engage in merges and acquisitions. Our empirical results show that risk effect is greater than


coinsurance effect when acquirer firms are safe.

    We conclude that firms with different characteristics do have different behaviors when they


diversify. Default probabilities of under-investment grade firms decline when they diversify, while,

on the contrary, those of investment grade firms increase when diversifying.


Robustness Examination

    To examine the consistency of our empirical results, we divide our sample with different criteria.

First, we re-define the first dimension.   We still define focus firms as firms which have only one


segment on COMPUSTAT Segment Database.              However, now we define diversified firms as firms

which have two or three segments. We define a new group, the extremely diversified firms, of


which the firms have four or more segments.             The second dimension remains unchanged.

Considering long run effects, we calculate differences between default probability of the latest

                                                   14
reporting date before announcement date of an M&A and that of the 1st ,2nd ,…and 12th reporting


date after announcement date.    The results shown in Table II are the default probabilities after the

M&A minus those before the M&A. We exhibit both mean and median results in the Table.


Table II shows that the new results are similar to those of Table I. Default probabilities of

under-investment grade firms decline when they diversify while those of investment grade firms


increase when diversifying.

   Second, we remain the first dimension unchanged as Table I and define firms as safe firms when


firms’ one year default probabilities are below 0.05% which is corresponding to one year default rate

of single A or above ratings in the S&P’s Cumulative Default Rates Table (1981-2002).       Firms are


viewed as medium firms when firms’ default probabilities are between 0.05% and 1.47% which is

corresponding to one year default rate between single A and BB ratings in the S&P’s Cumulative


Default Rates Table (1981-2002).       And we view firms as risky firms when firms’ default

probabilities are above 1.47%.      Considering long run performance, we calculate differences


between default probability of the latest reporting date before announcement date of an M&A and

that of the 1st ,2nd ,…and 12th reporting date after announcement date. The results shown in the


Table are the default probabilities after the M&A minus those before the M&A. The empirical

results are shown in Table III. We also exhibit both mean and median results in the Table. Similarly,


changes in default probabilities of risky firms are negative.   It is consistent with both coinsurance

                                                  15
effect and previous results. Default probabilities of safe firms are still positive.


                                           [Insert Table II and III Here]

       Finally, we combine the new definitions of the two dimensions as employed in Table II and


Table III. That is, we divide our sample into nine sub-samples. Because the numbers of firms

assigned into groups of “extremely diversified medium” and “extreme diversified risky” are only 17


and 5 respectively, we exclude these two groups. From Table IV we find the conclusions remain

the same.       In sum, we find the firms with different characteristics exhibit different behaviors when


diversifying.      Diversification results in decreases in default probabilities when firms are originally

risky, while it causes increases in default probabilities when firms are originally safe.   We conclude


that when firms are risky, their behaviors are consistent with coinsurance effect and risk effect stated

in prior literature.10 But when firms are originally safe, their behaviors are inconsistent with prior


studies. Although the empirical results of Billett, King, and Mauer (2004) do not support risk

effect on acquirer firms, our results state that risk effect is greater than coinsurance effect and,


therefore, default probabilities of safe firms tend to increase when they diversify.


                                                [Insert Table IV Here]

        The results previously obtained lead us to conjecture that there may be different behaviors of

changes in market value of equity for firms with different characteristics when diversifying.          To


10   See Lewellen (1971) and Billett, King, and Mauer (2004)

                                                               16
investigate this prediction, we use excess firm value of both book and market measure to examine


this inquiry.

B. Changes of excess firm values (book measure)

     In this section, we investigate the changes of excess firm values in book measure.   We do not

consider the changes in debt values in this section. Following last section, we divide sample into


four sub-samples to investigate their difference in behaviors. We define focus firms as firms which

have only one segment on the latest annually reporting date before announcement date of an M&A.


Diversified firms are firms which have two or more segments. Risky firms mean their default

probability is larger than 0.915%. We calculate the differences in excess firm values between the


latest annually reporting date before announcement date of an M&A and that of the 1st ,2nd and 3rd

annually reporting date after announcement date to verify different behaviors of market value of


equity when diversifying.   Table V shows the empirical results.


                                        [Insert Table V Here]

     The results in Table V show that changes in market value of equity are positively related to

changes in default probabilities. Default probabilities of risky firms decline when firms diversify


and their equity market values decline, too. When diversifying, both default probabilities and equity

market values of safe firms increase. Due to insufficient sample firms in two sub-groups, results in


them are inconsistent with our economic intuition.        Excluding these cases, the other results

                                                  17
conform to expectation.           Since equity can be viewed as a call option on firms’ value, a decrease in


default probability is expected to be accompanied with a decrease in equity market value.                  The

results indicate that when we only consider the wealth of stockholders, for risky firms,


diversification results in the phenomenon of diversification discount whereas, for safe firms, it

creates diversification premium.11


Robustness Examination

      To examine the robustness of prior empirical results, we divide our sample with different criteria

in this section to conduct the investigation again. Because there are only 433 acquirer firms left in


the sample, and risky firms are too few to divide into more sub-samples, we keep the dimension of

diversification unchanged and redefine the degree of credit quality (default probabilities). We view


firms with default probabilities less than 0.05% as safe firms.            Firms are defined as medium-safe

firms when their default probabilities are between 0.05% and 1.47%.               Finally, we define risky firms


as those with default probabilities above 1.47%. In Table VI, firms suffer the decline in equity

market value when their default probability decline.             Some insignificant or strange results of risky


firms could be attributed to insufficient firms in those sub-samples. When diversifying, both

default probabilities and equity market value increase for safe firms.


                                                [Insert Table VI Here]

11   This result is consistent with Mansi and Reeb (2002)

                                                            18
     From above results, we conclude that both diversification discount and premium exist when we


only consider the wealth of stockholders.   Risky firms bear the effects of diversification discount

and safe firms gain from the outcomes of diversification premium. In the following section, we


investigate whether diversification discount and premium still exist when considering the wealth of

both debt holders and stockholders simultaneously.


C. Changes of excess firm value (market measure)

   In this section, we consider market value of debt and equity simultaneously.         Under this

measurement, we aim to examine whether diversification destroys/enhances firms’ value or just


re-allocate wealth among stakeholders. To identify the different behaviors of individual sub-sample,

we remain the same criteria to divide our sample into four sub-samples.


   Table VII shows the results. Because the criteria result in only one firm in the sub-sample of

diversified risky firm, we ignore this sub-sample.    From Table VII, there is a very interesting


finding that, when diversifying, changes in excess firm values are insignificant in all sub-samples,

which indicates that the phenomena of both diversification discount of risky firms and


diversification premium of safe firms disappear.         There is no deadweight loss or value

enhancement through diversification. There are only wealth transfer from one stakeholder to


another when a firm conducting diversification. Combining with previous results, we find that, for

risky firms, wealth transfer from stockholders to debt holders while for safe firms wealth transfer

                                                 19
from debt holders to stockholders. No matter what types of credit quality firms, we all observe the


phenomenon of wealth transfer when firms diversify.


                                        [Insert Table VII Here]


Robustness Examination

    To examine the robustness of previous empirical results, again we divide our sample through

different criteria in this section.   Because there are only few risky firms, we do not change the


criterion of our first dimension, the diversification.   We redefine the dimension of credit quality

(the default probabilities). We define safe firms as those with default probabilities below 0.05%.


Firms are viewed as medium risky firms if their default probabilities are between 0.05% and 1.47%.

Firms with default probabilities above 1.47% are classified as risky firms.   The criteria result in very


few firms in the sub-sample of diversified-risky and diversified-medium, we exclude these two sub-

samples. The results shown in Table VIII are almost consistent with wealth transfer effect found


previously. It implies that there is no diversification discount or premium and confirm that there is

only the effect of wealth transfer.


                                        [Insert Table VIII Here]


                                           IV. Conclusions

    In this study, we obtain several interesting findings.   First, we observe that default probabilities



                                                   20
change in different directions when firms with different characteristics diversify.             Default


probabilities of risky firms decline when diversifying, which is consistent with coinsurance effect

and risk effect, while, on the contrary, those of safe firms increase, which violates coinsurance effect


hypothesis. It can be explained by a strong risk effect suggested by Billett, King, and Mauer (2004).

Second, market values of equity move in the same direction with default probabilities.             It is


consistent with the option theory based credit model originated from Black-Scholes (1973) and

Merton (1974).     We find that risky firms bear diversification discount and safe firms enjoy


diversification premium when we only consider the wealth of stockholders.          Finally, we provide

empirical evidences for wealth transfer effect.      We find there is no deadweight loss or value


enhancement through diversification. Wealth transfers among stakeholders.




                                                   21
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     59, 831-868.

Whited, Toni, 2001, “Is it inefficient investment that causes the diversification discount?”,

     Journal of Finance 56, 1667-1691.




                                              23
                Table I. Changes of default probabilities when firms diversify
In this table, we show the changes of default probabilities when firms diversify.             We divide samples
into four sub-samples. “Focus_risky” means that firms have only one segment and are assigned
into under investment grade. “Focus_safe” means that firms have only one segment and are assigned
into investment grade. “Diversified_risky” means that firms have two or more segments and are
assigned into under investment grade.             Diversified_safe” means that firms have two or more
segments and are assigned into investment grade.            The criterion for an investment grade firm is that
its calculated one year default probabilities are below 0.915% which is the BBB- one year default
probability approximated by the average one year cumulative default rates of rating BBB and BB
shown in the S&P’s Cumulative Default Rates Table (1981-2002).                            Considering long run
performance, we calculate differences between default probabilities of the latest reporting date
before announcement date of an M&A and that of the 1st ,2nd ,…and 12th reporting date after
announcement date, where “1” indicates the difference between default probabilities of the latest
reporting date before announcement date and that of the 1st reporting date after announcement date.
The results shown in the Table are the default probabilities after the M&A minus those before the
M&A.     We exhibit both mean and median results in the Table.

           Focus_risky                 Focus_safe               Diversified_risky            Diversified_safe
         Mean           Median       Mean         Median         Mean          Median       Mean           Median

 1     -0.01353*** -0.01194**       0.00040**     0.00000      -0.00426        -0.00219   0.00019*         0.00000
 2     -0.01142        -0.01625**   0.00240**     0.00000      -0.03687**      -0.00933   0.00045*         0.00000
 3     -0.00424        -0.01837     0.00294**     0.00000      -0.04990*** -0.01942       0.00095***       0.00000
 4     -0.01142        -0.01875     0.00455*** 0.00000         -0.05663*** -0.01927       0.00106***       0.00000
 5     -0.01606        -0.02000     0.00628*** 0.00000         -0.06637*** -0.02161       0.00162***       0.00000
 6     -0.00912        -0.02487     0.00627*** 0.00000         -0.06319*** -0.01896       0.00253***       0.00000
 7     -0.01309        -0.02084     0.00780*** 0.00000         -0.03706        -0.02219   0.00397***       0.00000
 8     -0.01052        -0.02030     0.00814*** 0.00000         -0.04176        -0.02222   0.00411***       0.00000
 9     -0.00603        -0.01971     0.00787*** 0.00000         -0.04095        -0.22613   0.00444***       0.00000
 10    -0.00659        -0.01971     0.00888*** 0.00000         -0.03842        -0.02610   0.00610***       0.00000
 11    -0.00939        -0.02060     0.01225*** 0.00000         -0.03006        -0.02224   0.00628***       0.00000
 12    -0.00387        -0.21971     0.01456*** 0.00000         -0.04278        -0.01923   0.00645***       0.00000
 N                57                        486                           27                         336

***, **, and * indicate statistical significance at the 1%, 5% and 10% levels.




                                                        24
                                                  Table II. Changes of default probabilities (Robustness)
We re-define the first dimension. We still define focus firms as firms which have only one segment.                Diversified firms are firms which have two or
three segments.        The extreme diversified firms are defined as firms which have four or more segments.           The second dimension remains unchanged.
The criterion for an investment grade firm (safe firm) is that its calculated one year default probabilities are below 0.915% which is the one year
default probability of rating BBB- approximated by the average one year cumulative default rates of rating BBB and BB shown in the S&P’s
Cumulative Default Rates Table (1981-2002).             Considering long run performance, we calculate differences between default probability of the latest
reporting date before announcement date of an M&A and that of the 1st ,2nd ,…and 12th reporting date after announcement date.                            The results
shown in the Table are the default probabilities after the M&A minus those before the M&A.                    We exhibit both mean and median results in the
Table.     ***, **, and * indicate statistical significance at the 1%, 5% and 10% levels.

               Focus_risky                   Focus_safe              Diversified_risky          Diversified_safe        Extreme_Div_risky           Extreme_Div_safe
           Mean              Median        Mean         Median      Mean             Median     Mean         Median      Mean          Median        Mean          Median

 1       -0.01353***        -0.01194**   0.00040**      0.00000   -0.01269          -0.00618   0.00009**     0.00000 0.00800           -0.00048   0.000472         0.00000
 2       -0.01142           -0.01625**   0.00240**      0.00000   -0.06187**        -0.02464   0.00023**     0.00000 -0.00049          -0.00314   0.001088         0.00000
 3       -0.00424           -0.01837     0.00294**      0.00000   -0.06996**        -0.03060   0.00068***    0.00000 -0.02071**        -0.01120   0.001718*        0.00000
 4       -0.01142           -0.01875     0.00455***     0.00000   -0.07909**        -0.03228   0.00086***    0.00000 -0.02397**        -0.01308   0.001647**       0.00000
 5       -0.01606           -0.02000     0.00628***     0.00000   -0.09523***       -0.04717   0.00140***    0.00000 -0.02439***       -0.01120   0.002275**       0.00000
 6       -0.00912           -0.02487     0.00627***     0.00000   -0.10039***       -0.04463   0.00227***    0.00000 -0.00908          -0.01120   0.003319***      0.00000
 7       -0.01309           -0.02084     0.00780***     0.00000   -0.09574**        -0.03931   0.00281***    0.00000 0.04830           -0.01210   0.007274***      0.00000
 8       -0.01052           -0.02030     0.00814***     0.00000   -0.08031*         -0.04366   0.00289***    0.00000 0.01430           -0.01283   0.007583**       0.00000
 9       -0.00603           -0.01971     0.00787***     0.00000   -0.07890*         -0.05350   0.00340***    0.00000 0.01425           -0.01285   0.007415**       0.00000
 10      -0.00660           -0.01971     0.00888***     0.00000   -0.07912*         -0.05235   0.00530***    0.00000 0.02079           -0.01285   0.008412**       0.00000
 11      -0.00939           -0.02060     0.01225***     0.00000   -0.07536*         -0.04521   0.00516***    0.00000 0.03584           -0.01286   0.009479**       0.00000
 12      -0.00387           -0.21971     0.01456***     0.00000   -0.10995**        -0.02723   0.00531***    0.00000 0.05493           -0.01287   0.009716**       0.00000
 N                     57                         486                          16                      249                        11                          87


                                                                                      25
                                                  Table III. Changes of default probabilities (Robustness)
“Focus” means firms which have only one segment and “Diversified” means firms which have two or more segments.                                      We define firms as safe
firms when firms’ one year default probabilities are below 0.05% which is corresponding to one year default rate of single A or above ratings in the
S&P’s Cumulative Default Rates Table (1981-2002).                  Firms are viewed as medium firms when firms’ default probabilities are between 0.05% and
1.47% which is corresponding to one year default rate between single A and BB ratings in the S&P’s Cumulative Default Rates Table (1981-2002).
And we view firms as risky firms when firms’ default probabilities are above 1.47%.                    Considering long run performance, we calculate differences
between default probability of the latest reporting date before announcement date of an M&A and that of the 1st ,2nd ,…and 12th reporting date
after announcement date.           The results shown in the Table are the default probabilities after the M&A minus those before the M&A.                         We exhibit
both mean and median results in the Table.               ***, **, and * indicate statistical significance at the 1%, 5% and 10% levels.

            Focus_risky                  Focus_medium                  Focus_safe            Diversified_risky          Diversified_medium              Diversified_safe
         Mean             Median        Median            Mean       Median       Mean     Median            Mean       Median            Mean          Median         Mean

 1   -0.01526***        -0.01493*** 0.00154             -0.00027   0.00024**     0.00000 -0.01357*          -0.00397    0.00375          -0.00016    0.00017           0.00000
 2   -0.01416           -0.01850** 0.01298              -0.00031   0.00100***    0.00000 -0.05545**         -0.02204    0.00373*         -0.00026    0.00019***        0.00000
 3   -0.00822           -0.02019      0.01626**         -0.00076   0.00139***    0.00000 -0.07025***        -0.03539    0.00337          -0.00039    0.00055***        0.00000
 4   -0.01680           -0.02095      0.02265***        -0.00088   0.00236***    0.00000 -0.07888***        -0.04634*   0.00160          -0.00077    0.00086***        0.00000
 5   -0.02203           -0.02820*     0.02479***        -0.00091   0.00401***    0.00000 -0.09013***        -0.05273*   0.00226          -0.00073    0.00123***        0.00000
 6   -0.01451           -0.02856      0.01954***        -0.00104   0.00478***    0.00000 -0.08562***        -0.05274*   0.00395          -0.00076    0.00202***        0.00000
 7   -0.01845           -0.02791      0.02541***        -0.00084   0.00561***    0.00000 -0.04882           -0.05275    0.00772*         -0.00076    0.00311***        0.00000
 8   -0.01793           -0.02896      0.02814***        -0.00103   0.00588***    0.00000 -0.06794           -0.04596    0.01691*         -0.00074    0.00281***        0.00000
 9   -0.01248           -0.02102      0.02920***        -0.00089   0.00537***    0.00000 -0.06592           -0.05425    0.01654*         -0.00098    0.00317***        0.00000
 10 -0.01361            -0.02901*     0.03282***        -0.00109   0.00603***    0.00000 -0.06160           -0.05275    0.02236**        -0.00081    0.00418***        0.00000
 11 -0.01896            -0.03718** 0.03478***           -0.00079   0.00984***    0.00000 -0.04706           -0.05275    0.02268**        -0.00081    0.00417***        0.00000
 12 -0.01110            -0.02845      0.03456***        -0.00101   0.01228***    0.00000 -0.05612           -0.04298    0.01849**        -0.00080    0.00436**         0.00000
 N                 51                              62                      430                         19                           41                           303


                                                                                      26
                                             Table IV. Changes of default probabilities (Robustness)
We re-define both degree of diversification and level of credit quality and divide our sample into nine sub-samples. We define focus firms as firms
which have only one segment. Diversified firms are firms which have two or three segments. The extreme diversified firms are defined as firms
which have four or above segments. We define firms as safe firms when firms’ one year default probabilities are below 0.05% which is
corresponding to one year default rate of single A or above ratings in the S&P’s Cumulative Default Rates Table (1981-2002). Firms are viewed as
medium firms when firms’ default probabilities are between 0.05% and 1.47% which is corresponding to one year default rate between single A and
BB ratings in the S&P’s Cumulative Default Rates Table (1981-2002). And we view firms as risky firms when firms’ default probabilities are above
1.47%. Considering long run performance, we calculate differences between default probability of the latest reporting date before announcement
date of an M&A and that of the 1st ,2nd ,…and 12th reporting date after announcement date. The results shown in the Table are the default
probabilities after the M&A minus those before the M&A. We exhibit both mean and median results in the Table.
           Focus_risky             Focus_medium               Focus_safe               Diversified_risky       Diversified_medium           Diversified_safe
         Mean         Median      Median        Mean       Median         Mean        Median         Mean       Median          Mean      Median           Mean

  1   -0.01526*** -0.01493***    0.00154        -0.00027   0.00024**      0.00000 -0.01873*         -0.01405   0.00270         -0.00017   0.00007**        0.00000
  2   -0.01416    -0.01850**     0.01298        -0.00031   0.00100*** 0.00000 -0.07368**            -0.02707   0.00200         -0.00022   0.00022***       0.00000
  3   -0.00822    -0.02019       0.01626**      -0.00076   0.00139*** 0.00000 -0.08133**            -0.04507   0.00233*        -0.00038   0.00058**        0.00000
  4   -0.01680    -0.02095       0.02265***     -0.00088   0.00236*** 0.00000 -0.09021**            -0.04957   0.00207         -0.00069   0.00071***       0.00000
  5   -0.02203    -0.02820*      0.02479***     -0.00091   0.00401*** 0.00000 -0.10770***           -0.05885   0.00500         -0.00068   0.00093***       0.00000
  6   -0.01451    -0.02856       0.01954***     -0.00104   0.00478*** 0.00000 -0.11385***           -0.05892   0.00736         -0.00058   0.00165**        0.00000
  7   -0.01845    -0.02791       0.02541***     -0.00084   0.00561*** 0.00000 -0.10902**            -0.05883   0.00959*        -0.00042   0.00204*         0.00000
  8   -0.01793    -0.02896       0.02814***     -0.00103   0.00588*** 0.00000 -0.10832**            -0.05854   0.02020*        -0.00043   0.00206**        0.00000
  9   -0.01248    -0.02102       0.02920***     -0.00089   0.00537*** 0.00000 -0.10552**            -0.05817   0.01805*        -0.00070   0.00276**        0.00000
 10 -0.01361      -0.02901*      0.03282***     -0.00109   0.00603*** 0.00000 -0.10473**            -0.06321   0.02671*        -0.00058   0.00386**        0.00000
 11 -0.01896      -0.03718**     0.03478***     -0.00079   0.00984*** 0.00000 -0.09687**            -0.07267   0.02536*        -0.00069   0.00364**        0.00000
 12 -0.01110      -0.02845       0.03456***     -0.00101   0.01228*** 0.00000 -0.12421**            -0.04302   0.01904         -0.00069   0.00372***       0.00000
 N               51                        62                       430                        14                         24                         227

.***, **, and * indicate statistical significance at the 1%, 5% and 10% levels.


                                                                                 27
                                 Table IV. Changes of default probabilities (Robustness) (Continued)
We re-define both degree of diversification and level of credit quality and divide our sample into nine sub-samples. We define focus firms as firms
which have only one segment. Diversified firms are firms which have two or three segments. The extreme diversified firms are defined as firms
which have four or above segments. We define firms as safe firms when firms’ one year default probabilities are below 0.05% which is
corresponding to one year default rate of single A or above ratings in the S&P’s Cumulative Default Rates Table (1981-2002). Firms are viewed as
medium firms when firms’ default probabilities are between 0.05% and 1.47% which is corresponding to one year default rate between single A and
BB ratings in the S&P’s Cumulative Default Rates Table (1981-2002). And we view firms as risky firms when firms’ default probabilities are above
1.47%. Considering long run performance, we calculate differences between default probability of the latest reporting date before announcement
date of an M&A and that of the 1st ,2nd ,…and 12th reporting date after announcement date. The results shown in the Table are the default
probabilities after the M&A minus those before the M&A. We exhibit both mean and median results in the Table.
                                          Extreme_Div_risky           Extreme_Div_medium           Extreme_Div_safe
                                         Mean            Median         Mean           Median       Mean           Median

                                1      0.00090          -0.00048      0.00523         -0.00001     0.00047         0.00000
                                2     - 0.00440         -0.00933      0.00617         -0.00074     0.00009         0.00000
                                3     - 0.03920**       -0.03539*     0.00483         -0.00074     0.00047         0.00000
                                4     - 0.04713**       -0.04634**    0.00093         -0.00081     0.00131*        0.00000
                                5     - 0.04091**       -0.04025**   - 0.00160        -0.00077     0.00212**       0.00000
                                6     - 0.00658         -0.02210     - 0.00087        -0.00122     0.00311**       0.00000
                                7      0.11976          -0.02766      0.00506         -0.00151     0.00631***      0.00000
                                8      0.04512          -0.04124      0.01225         -0.00151     0.00504**       0.00000
                                9      0.04495          -0.04294      0.01440         -0.00151     0.00437*        0.00000
                                10     0.05916          -0.04298      0.01622         -0.00151     0.00512*        0.00000
                                11     0.09240          -0.04298      0.01890         -0.00151     0.00573         0.00000
                                12     0.13454          -0.04298      0.01770         -0.00151     0.00626         0.00000
                                N                   5                            17                           76

                             ***, **, and * indicate statistical significance at the 1%, 5% and 10% levels

                                                                          28
                     Table V. Changes of excess firm values (book measure)

Excess firm value is defined as ln(actual value/ imputed value), where actual value equals market

value of equity plus book value of debt.      Imputed value represents the sum of a firm’s segments as

focus firms using multipliers.     Here, we divide our sample into four sub- samples to examine the

different behaviors In changes of excess firm values after diversification. “Focus” means there is

only one segment in the firm on the latest reporting date before announcement date of an M&A.

“Diversified” means there are two or above segments in the firm.         “Safe” means investment grade

firms with calculated one year default probabilities are below 0.915% which is the BBB- one year

default probability approximated by the average one year cumulative default rates of rating BBB and

BB shown in the S&P’s Cumulative Default Rates Table (1981-2002).          Here we calculate the changes

in excess firm value to investigate different behaviors of market value of firms after diversification.

Because COMPUSTAT Segment Database has only annually data, we calculate excess firm value on

yearly basis. Considering long run performance, we calculate differences between excess firm value

of the latest yearly reporting date before announcement date of an M&A and that of the 1st ,2nd and

3rd yearly reporting date after announcement date.         The results shown in the Table are the excess

firm values after the M&A minus those before the M&A.           We exhibit both mean and median results

in the Table.


        Focus_risky                  Focus_safe               Diversified_risky         Diversified_safe
     Mean         Median    N    Mean       Median    N      Mean     Median      N    Mean      Median N

1 - .01539      - 0.00138   34 0.13430**   0.10883*   284 - 0.52000   -0.07093 8      0.18192*   0.09144 107
2 - 0.07695      0.07733    30 0.15289**   0.03055    254 - 0.65270   -0.42972 5      0.27115** 0.21600* 94
3 0.10450 -0.18594          28 0.10184     0.035570 222 0.25136        0.26509 4      0.12427    0.13801   81

***, **, and * indicate statistical significance at the 1%, 5% and 10% levels.




                                                      29
                                        Table VI. Changes of excess firm value (book measure)

Excess firm value is defined as ln (actual value/imputed value), where actual value equals market value of equity plus book value of debt.

Imputed value represents the sum of a firm’s segments as stand-alone firms using multipliers.         “Focus” means firms which have only one

segment and “Diversified” means firms which have two or more segments.               We define firms as safe firms when firms’ one year default

probabilities are below 0.05% which is corresponding to one year default rate of single A or above ratings in the S&P’s Cumulative Default

Rates Table (1981-2002).     Firms are viewed as medium firms when firms’ default probabilities are between 0.05% and 1.47% which is

corresponding to one year default rate between single A and BB ratings in the S&P’s Cumulative Default Rates Table (1981-2002). And we

view firms as risky firms when firms’ default probabilities are above 1.47%.         Considering long run performance, we calculate differences

between excess firm value of the latest yearly reporting date before announcement date of an M&A and that of the 1st ,2nd and 3rd yearly

reporting date after announcement date.      The results shown in the Table are the excess firm values after the M&A minus those before the

M&A.     We exhibit both mean and median results in the Table.

        Focus_risky           Focus_medium                 Focus_safe             Diversified_risky   Diversified_medium      Diversified_safe
     Mean     Median N       Mean     Median N         Mean       Median    N     Mean   Median N     Mean     Median N      Mean    Median N

1   0.00765 -0.07552 29 -0.15295      0.07649 33     0.16579**    0.10883 256 -0.47302 -0.06751 7     -0.12265 -0.34224 9 0.19920** 0.13538      99
2 -0.08962    0.12385 25    0.18584   0.22466 33     0.14439**    0.01101 226 -0.65266 -0.42972 5     -0.14866 0.45020   6 0.29978** 0.20511* 88
3   0.27459 -0.09406 23 -0.19329 -0.15261 26         0.12062      0.03792 201 0.25136 0.26509 4        0.56220 0.78782   5 0.09546   0.13028     76

***, **, and * indicate statistical significance at the 1%, 5% and 10% levels..




                                                                           30
                Table VII. Changes of excess firm values (market measure)

Excess firm value is defined as ln (actual value/ imputed value), where actual value represents the

sum of market value of equity and market value of debt. Imputed value also represents the sum

of a firm’s segments as one-segment firms using multipliers in market measure. We divide

sample into four sub-samples as what we do in Table V. “Focus_risky” means firms which have

only one segment and are assigned into under investment grade. “Focus_safe” means firms which

have only one segment and are assigned into investment grade. “Diversified_risky” means firms

which have two or more segments and are assigned into under investment grade.

Diversified_safe” means firms which have two or more segments and are assigned into investment

grade.    The criterion for an investment grade firm is that its calculated one year default

probabilities are below 0.915% which is the BBB- one year default probability approximated by

the average one year cumulative default rate of rating BBB and BB shown in the S&P’s

Cumulative Default Rates Table (1981-2002).         Considering long run performance, we calculate

differences between excess firm value of the latest yearly reporting date before announcement

date of an M&A and that of the 1st ,2nd and 3rd yearly reporting date after announcement date.

The results shown in the Table are the excess firm values after the M&A minus those before the

M&A.      We exhibit both mean and median results in the Table.



            Focus_risky               Focus_safe          Diversified_risky         Diversified_safe
         Mean     Median    N     Mean     Median       N Mean Median N           Mean     Median      N

 1    0.20728     0.17788   23   0.01549   0.04031 177 ---      ---       --     0.02863 - 0.01500     48
 2    0.14853     0.10371   20   0.03220 - 0.01089 162 ---      ---              0.01782   0.03017     41
 3    0.43530     0.20573   19 - 0.01927   0.01529 143 ---      ---            - 0.01318   0.25936     35

***, **, and * indicate statistical significance at the 1%, 5% and 10% levels.




                                                   31
                                      Table VIII. Changes of excess firm values (market measure)

Excess firm value is defined as ln(actual value/imputed value), where actual value represents the sum of market value of equity and market
value of debt.    Imputed value also represents the sum of a firm’s segments as stand-alone firms using multipliers in market measure.                  We
remain the same standard to define the degree of diversification as Table VII. “Focus” means firms which have only one segment and
“Diversified” means firms which have two or more segments.           We redefine the levels of credit quality in this investigation. We define firms
as safe firms when firms’ one year default probabilities are below 0.05% which is corresponding to one year default rate of single A or above
ratings in the S&P’s Cumulative Default Rates Table (1981-2002).         Firms are viewed as medium firms when firms’ default probabilities are
between 0.05% and 1.47% which is corresponding to one year default rate between single A and BB ratings in the S&P’s Cumulative Default
Rates Table (1981-2002).     And we view firms as risky firms when firms’ default probabilities are above 1.47%.                  Considering long run
performance, we calculate differences between excess firm value of the latest yearly reporting date before announcement date of an M&A and
that of the 1st ,2nd and 3rd yearly reporting date after announcement date.      The results shown in the Table are the excess firm values after the
M&A minus those before the M&A.         We exhibit both mean and median results in the Table.



           Focus_risky             Focus_medium                  Focus_safe              Diversified_risky   Diversified_medium      Diversified_safe
       Mean      Median N      Mean       Median      N     Mean       Median    N Mean Median          N    Mean Median N         Mean     Median N

  1   0.22242    0.21258 20 0.134606     0.12095      21   0.00147    -0.01633 159 ---       ---      ---    ---   ---     ---    0.07052 0.06615 43
  2   0.09731    0.03455 17 0.334472     0.15046      21 - 0.00341    -0.02322 144 ---       ---      ---    ---   ---     ---    0.01019 0.03017 37
  3   0.56107    0.30285 16 0.190656     0.42491**    17 - 0.05196    -0.02634 129 ---       ---      ---    ---   ---     ---    -0.03578 0.25936 33

.***, **, and * indicate statistical significance at the 1%, 5% and 10% levels




                                                                           32