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									Earnings Management Preceding Reverse Leveraged Buyouts




                       De-Wai Chou
             National Chung Cheng University
                     Chia-Yi, Taiwan


                       Jeremy Goh
                    Drexel University
                 Philadelphia, PA 19104


                    Michael Gombola
                    Drexel University
                   nd
                 32 and Market Streets
                 Philadelphia, PA 19104


                     Feng-Ying Liu
                    Rider University
                2083 Lawrenceville Road
                Lawrenceville, NJ 08550

                 Current version: 2/24/02
            Earnings Management Preceding Reverse Leveraged Buyouts

                                         Abstract

Information asymmetry between investors and issuers of equity provides motivation and
opportunities for issuers to manage earnings around the time of the offering. This study
examines earnings management around the time of the equity offering of reverse LBOs.
Using a sample of 225 reverse LBOs during 1980-1998, we find significantly higher
abnormal discretionary current accruals around the time of the reverse LBO offering.
Earnings management is particularly evident for firms where buyout specialists played a
role in the going-private transaction. As in the case with other fo rms of equity offerings,
managers appear to manipulate earnings upward prior to offering stock in a reverse LBO.
            Earnings Management Preceding Reverse Leveraged Buyouts


1.     Introduction

       Several studies find evidence of earnings manipulation around the time of equity

offerings. Such manipulation could affect the offering prices of the stocks being sold.

Earnings manipulation, or at least earnings management, is evident around the time of

initial public offerings (IPOs) (Teoh, Welch and Wong, 1998a), seasoned equity offerings

(Rangan, 1998; Teoh, Welch and Wong, 1998b), and management buyout offerings

(Perry and Williams, 1994). Information asymmetry between investors and equity issuers

provides motivation for issuers to manage earnings around the time of the offering. Teoh,

Welch and Wong (1998s) point out that the IPO process is particularly susceptible to

earning management due to high information asymmetry between investors and issuers at

the time of the offering. Reverse LBOs are very similar to IPOs in the offering process.

Reverse LBOs offer even more motivation to manage earnings than IPOs, because the

proceeds of the equity offering go to the entrepreneurs who took the firm private, rather

than to the issuing firm.

       This study examines earnings management around the time of the reverse LBO

offering using a sample 225 reverse LBOs during the 1980-1998 period. We use

discretionary current accruals as the proxy for earnings management and use a regression

model to estimate abnormal accruals. We find that abnormal discretionary current

accruals are positive and significantly different from zero during the equity offering of

reverse LBOs. Those firms with buyout specialists participating in the original buyout

show particularly strong evidence of earnings management preceding the subsequent
reverse LBO. This finding provides evidence that managers manage earnings when

planning reverse LBOs.

2.     Earnings Management in Securities Offerings

       The reverse LBO is one of two forms of post-buyout behavior observed by

Kaplan (1991, 1993). In one of these LBO forms, the LBO serves as a more efficient

managerial form under which the LBO firm should remain private for a significant period

of time. In the other form, the LBO serves as a shock to accomplish one-time changes.

After the one-time change has been accomplished, the changed firm can go public again

in a reverse LBO. This first form can be likened to a revolving door process for LBOs.

       The revolving-door process for LBOs can also result from insiders trying to time

the market for the company’s stock, buying when the price is low and selling at a higher

price. The availability of superior information held by insiders (including management

and LBO specialists) can aid in the timing of this exit from and re-entry into public

markets. By taking advantage of temporary declines or increases in stock prices, they are

afforded the opportunity to buy stock at as low a price as possible in an LBO and to re-

sell at a much higher price in a reverse LBO. Selling at the highest price could involve

improving the offering price through the manipulation of earnings during a reverse LBO.

       Motivation for earnings management during a reverse LBO stems from

information asymmetry between investors and issuers present during IPOs, of which

reverse LBOs are a special form. Teoh, Welch and Wong (1998s) point out that the IPO

process is particularly susceptible to earning management due to high information

asymmetry between investors and issuers at the time of the offering. Rao (1993) reports

that there is almost no news media coverage of firms in the years before the IPO. This




2
scarcity of information about the issuer forces investors to rely heavily on the prospectus,

which could contain only one to three years of financial statements. Therefore, IPO firms

are susceptible to earnings management by borrowing earnings from future periods. High

reported earnings would translate directly into a higher offering price.

        Based on the same rationale, firms conducting reverse LBOs are likely to engage

in the same form of earnings management that has been observed for IPOs in general.

The opportunity to take advantage of private information could be less for reverse LBOs

than for other forms of IPOs since considerable information is available for reverse LBOs

during the prior period when they were publicly held firms. The opportunity to manage

earnings should be even greater for reverse LBOs than for other IPOs since reverse LBOs

are priced on the value of earnings from assets in place rather tha n the value of future

investment opportunities. In the case of IPOs of “concept” stocks or startup companies

with with no earnings record, earnings management is impossible since there are no

earnings to manage. The typical LBO company, on the other hand, typically has a long

earnings record but few growth opportunities, as indicated by Tobin’s q values less than

one (citation).

        Earnings management has been observed in a variety of corporate events. Jones

(1991) tests whether firms that would benefit from import relief (e.g. tariff increases and

quota reductions) attempted to decrease earnings through earnings management during

import relief investigations by the United States International Trade Commission (ITC).

Explicit use of accounting numbers in tariff regulation provides incentives for managers

to manage earnings. Lowered earnings improves the likelihood of obtaining import relief

and/or increase the amount of relief granted. Jones (1991) finds results supporting the




3
earnings management hypothesis, suggesting that managers make income-decreasing

accruals during import relief investigations.

       Teoh, Welch and Wong (1998a) examine whether issuers of initial public

offerings increase accruals and thereby report earnings in excess of cash flows prior to

IPOs. They find evidence that issuers with unusually high accruals in the IPO year (and

presumably correspondingly high stock prices) experience poor stock return performance

in the three years thereafter. They classify earnings management into several quartiles,

including “aggressive” and “conservative”. IPO issuers in the most “aggressive” quartile

of earnings management have a three-year aftermarket stock return approximately 20%

lower than IPO issuers in the most “conservative” quartile. These differences are

statistically and economically significant. In another study, (1998b) they report that

seasoned equity issuers experience higher net income growth in the issue year than their

non- issuing industry peers. Rangan (1998) also finds evidence of earnings ma nagement

by companies involved in seasoned equity offerings.

       Perry and Williams (1994) investigate earnings management preceding

management buyouts (MBOs) offers using a sample of 175 MBOs during the period from

1981 through 1988. Going-private restructurings provide unique opportunities to

manipulate earnings since managers face a conflict of interest when engaged in buying

the firm’s stock in order to take it private. As representatives of stockholders, managers

have a fiduciary duty to them. This duty conflicts with a strong incentive to buy the

firm’s stock at the lowest possible price. Their personal stake in an MBO may motivate

management to depress pre-buyout accounting earnings to portray a less favorable picture

of the firm, either through decisions on the timing of discretionary cash flow or in the




4
selection of accounting methods or estimates. Perry and Williams (1994) find increases in

discretionary accruals in the predicted direction in the year preceding the public

announcement of management’s intention to bid for control of the company.

        Perry and Williams limit their consideration to buyout offers by management

since management has no interest in earnings management to benefit an outside takeover

group. In the case of reverse LBOs, however, not only management can have the motive

and opportunity to manage earnings, but so can other shareholder groups. Buyout

specialist groups serve to monitor management and reduce the agency problems between

managers and shareholders. Cotter and Peck (2001) show that when buyout specialists

control the majority of post-LBO equity, the transaction is financed less by short-term

debt or senior debt. Monitoring by buyout specialists rather than restrictive debt

covenants is less likely to lead to financial distress and avoids the bankruptcy costs

associated with extensive debt financing. They also show that buyout specialists have

greater representation on smaller boards, which also indicates that buyout specialists

actively monitor managers.

        Halpern, Kieshnick and Rotenberg (1999) show that buyout specialists engage in

the type of LBO transaction where managers do not own a substantial portion of the

firm’s stock prior to the LBO transaction. When managers effectively control the pre-

buyout firm, a management buyout is more likely to take place than a buyout by a

specialist firm.

        If a buyout specialist has the opportunity to influence management t manage

earnings, they have a greater incentive to manage earnings than do managers. Earnings

management involves borrowing earnings from future periods rather than permanent




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creation of earnings. In the future period when the borrowed earnings must be “paid

back”, the buyout group might no longer be associated with the firm. Their intent is to

take a firm private, enhance value, cash out, and move to the next deal rather than

establishing a career-long relationship with the LBO firm. Managers, on the other hand

will expect a longer relationship with the firm and will suffer with new shareholders

when the earnings debt acquired prior to an LBO is later repaid. Consequently, although

earnings management could be a feature of any reverse LBO, it should be particularly

evident in reverse LBOs in which a buyout specialist is a participant.

3.     Data and Methodology

A.      The Sample

       The initial sample contains 246 reverse LBOs during the period from 1980

through 1998. The sample is obtained from Securities Data Company (SDC). Firms are

excluded if the companies is eventually delisted through a process that involves neither

leveraged buyout nor management buyout. To ensure that these were in fact reverse

LBOs, the sample is checked against the Dow Jones News Retrieval and LEXIS&NEXIS

for a story about both the LBO and the IPO, and against the prospectuses in the offering.

This exclusion process reduces the sample for this study to 225. In order to study

earnings management behavior, IPOs must have available COMPUSTAT financial data

both in the year of and the year prior to the offering. No closed-end funds (SIC code

6726) are in the final sample.

       Table1 provides descriptive statistics for the sample in this study. The sample

includes 225 reverse LBOs from 1980 through 1998. Equity values are computed from




6
the product of common shares outstanding and the closing price of common stock at the

end of the fiscal year immediately preceding the calendar year of the offering dates.

        Table 2 provides the mean and median proceeds of reverse LBOs in our sample.

Table 3 provides the distribution of SIC codes for those companies. The presence of sixty

separate SIC codes, with seventeen of these representing at least 1% of the sample

(fifteen reverse LBOs), indicates a wide selection of industries. Not surprising for our

sample period, there is a concentration of reverse LBOs in the computer and electronics

industries. Additionally, the wholesale and retail industries comprise almost 22% of

reverse LBOs in the sample.

        Table 4 provides the time distribution when the samples undertake LBOs. The

frequency of LBOs accelerates beginning in 1983 and slows down in 1991. Most of the

LBOs in this sample are clustered within the period between 1985 to 1990, with almost

80% of the sample taken from those six years.

        Table 5 provides descriptive statistics for the number of years reverse LBOs stay

private. Lengths of one though five years dominate the others, with three years as the

mean length for LBOs staying private . During the period of private ownership, a detailed

five-year operating plan is usually scheduled for the company, which includes any new

investment, debt reduction, restructuring, improvements in market position, changes in

operations, and contingency plans for a business downturn or large business risk. The

plan is thoroughly researched and both management and investors should agree on the

plan.

B.      The Control Sample




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           To test the earnings management of reverse LBOs, a set of matched firms is

created in order to generate a benchmark for earnings or accruals in the absence of a

reverse LBO. This control sample is generated by matching each reverse LBO firm with

a company within an appropriate corresponding Standard Industrial Classification (SIC)

classification, as obtained from the Center for Research in Security Prices (CRSP) data

files. 1

           We assume firms in the same industry are subject to similar economic and

competitive factors, and therefore have comparable operating, investing, and financing

opportunity sets. As a result, each matched pair should also have comparable voluntary

accounting choice sets. If this comparability is realized in the matching process, the

control firms provide a benchmark against which tests of the reverse LBOs can be

evaluated.

C.         Measuring Accruals

           A variety of methods in accounting choice can be employed in order to manage

earnings. These accounting choices can include the use of accruals, changes in

accounting methods, and changes in capital structure (e.g. debt defeasance, debt-equity

swaps). This study focuses on current accruals as the source of earnings management. We

measure total accruals as the difference between net income and cash flow from

operations. Typically, reported earnings consist of cash flows from operations and

accounting adjustments called accruals. DeAngelo (1986) used a random walk model of


1
  To ensure that the estimated coefficients obtained from the regression are not biased, th e number of
matched control samp les is required at least more than 30. Four-d igit SIC codes are used for matching to
the extent possible (30 out of 225 have 2736 four-dig it SIC code matched samples). If no appropriate match
is found, three-digit (46 out of 225 have 3010 three-dig it SIC code matched samples) or two-d igit (149 out
of 225 have 18392 two-d igit matched samples) codes are chosen. In addition to the filter of appropriate SIC
codes, non-ordinary common stocks are removed fro m the samples. For examp le, A merican Depository
Receipts, closed-end funds, and real estate investments trusts identified by CRSP are eliminated.


8
accruals to identify abnormal observations. Some historical series of accruals are often

important components of the benchmark. The benchmark should ideally incorporate the

level of economic activities of the firm during the hypothesized manipulation period.

Jones (1991) and other recent earnings management studies (Cahan, 1992; Boynton et.

al., 1992) use a regression-based expectations model that incorporates the economic

activities of the firm during the test period.

        Perry and Williams (1994) compute total accruals as the change in noncash

working capital (excluding current maturities of long-term debt less total depreciation

expense for the current period). Their definition is similar to Jones (1991), differing by

the exclusion of the adjustment she makes for income taxes. Perry and Williams (1994)

include income tax in their model because they believe the incentive in management

buyouts is to reduce reported net income, and the income tax accrual may be an important

component of an earnings management strategy.

        On the other hand, Teoh, Welch and Wong (1998) differentiate among accruals

by separating total accruals into current and long-term components. These two

components can be evaluated separately because they claim that entrepreneurs have more

discretion over short-term than over long-term accruals. In particular, current accrual

adjustments involve short-term assets and liabilities that support the day-to-day

operations of the firm. Managers can increase current accruals, for example, by

advancing recognition of revenues with credit sales (before cash is received), by delaying

recognition of expenses through the assumption of a low provision for bad debts, or by

deferring recognition of expenses when cash is advanced to suppliers. As for long-term

accrual adjustments, which involve long-term net assets, decelerating depreciation can




9
increase these, decreasing deferred taxes (the difference between tax expenses recognized

for financial reporting and actual taxes paid), or realizing unusual gains. Following Teoh,

Welch and Wong (1998), this study also separates total accruals (AC) into four accrual

variables, including discretionary current accruals (DCA), nondiscretionary current

accruals (NDCA, discretionary long-term accruals (DLA), and nondiscretionary long-

term accruals (NDLA), which four variables are measured using COMPUSTAT annual

item numbers in parentheses as follows:



AC = Net Income (172) – Cash Flows from Operations (308),                                    (1)


where AC is total accruals consisting of current accruals and long-term accruals;



CA =  [current assets (4) – Cash (1)] -  [(current liabilities (5) – current maturity of

      long-term debt (44)],                                                                  (2)



where CA is current accruals and is defined as the change in noncash current assets

minus the change in operating current liabilities. To reduce the influence of nonstandard

classifications of certain items, we redefine the CA as follows [see Teoh, Welch and

Wong (1998)]:



CA =  [accounts receivables (2) + inventory (3) +other current assets (68)] –

       [accounts payable (70) + tax payable (71) + other current liabilities (72)].         (3)




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D.       Estimating Expected and Abnormal Accruals

         In order to identify abnormal accruals, a benchmark for earnings or accruals

values in the absence of manipulation must be generated. It is difficult for investors to

infer how much of the accruals are discretionary. Some accrual adjustments are

appropriate and necessary given the business conditions faced by the firm in its industry.

Therefore, we need a model to separate accruals into two components, one component

that is dictated by firm and industry conditions and one component more under

management control managed by the entrepreneur. Particularly, focusing on discretionary

accruals allows a more powerful test of the accruals under managerial control

         An extension of the cross-sectional model use by Jones (1991) is employed to

generate expected accruals. In this model, current accruals (CA) are regressed on the

change in sales in a cross-sectional regression using all firms with the same two-digit SIC

code as the issuer, but excluding the issuer and other reverse LBO firms. To reduce

heteroskedasticity in the data, all variables in the regression are scaled by beginning

assets for the year. The specific form of the model is as follows:



CAj, t / TAj, t-1 = 0 (1/TAj, t-1 ) + 1 ( Salesj, t / TAj, t-1 ) + j, t ,                (4)


where jestimated samples,  Sales is the change in sales, and TA is total assets (6). The

expected accruals [E(CA)] represented by nondiscretionary current accruals are

calculated as follows:


                                                    
E(CAi, t ) = NDCAi, t =         0 (1/TAj, t-1 ) +  1 [( Salesj, t -  TR) / TAj, t-1 ],   (5)




11
                                            
where  0 is the estimated intercept and  1 is the slope coefficient for reverse LBO firm i

in year t, and  TRi, t is the change in trade receivables (151) in year t for issuer i. The

increase in trade receivables is subtracted from the change in sales to allow for the

possibility of credit sales manipulation by the issuer. For example, reverse LBOs firms

can change their credit sale policy from conservative to generous in order to obtain high

sales prior to the offering. Using the expected accruals from our model in Eq. (5),

abnormal accruals (AA) are defined as follows,



AAi, t = DCAi, t = CAj, t / TAj, t-1 – E(CA) = CAj, t / TAj, t-1 – NDCAi, t ,                  (6)


where DCAi, t , discretionary current accruals, is abnormal accruals represented by AA for

reverse LBO firm i in year t. The long-term discretionary and nondiscretionary

(expected) accruals are not the main source of manipulation; therefore, they are not under

discussion in this study.

4.      Results

        Table 6 provides the results of testing for significant discretionary current

accruals during the offering period for reverse LBOs. Results indicate that for reverse

LBO companies, discretionary current accruals are much higher than for control firms.

The difference in discretionary current accruals between the reverse LBO sample and the

control sample is statistically significant at the 0.01 level (t=2.64). This e vidence is

consistent with the finding by Teoh, Welch and Wong (1998) who document that IPOs in

general have unusually high accruals in the IPO year.

        In order to identify the role management plays, the sample is divided into two

subgroups: one with management involved in the previous leveraged buyout transaction,


12
which is typically referred to as a Management Buyout (MBO) and one without such

management involvement. Significant generation of abnormal accruals is shown for both

the MBO group and the non-MBO group, with t-statistics that are statistically significant

at the .05 or .10 level. The difference in the level of accruals is not statistically

significant.

        Similarly, in order to identify the role that buyout specialists play in such

activities, the sample is again divided into two subgroups: one with buyout specialists

involved in the previous leveraged buyout and one without such involvement. Results of

testing for differences in these subgroups are presented in Panel C. The subgroup where

specialists are involved shows unusually high accruals, statistically significant at the 0.01

level (t=2.45). Abnormal accruals for the other subgroup are not statistically significant at

any traditional level. This finding is consistent with the proposition that b uyout

specialists have a greater incentive than managers to manage earnings prior to a reverse

LBO and that buyout specialists have the power to cause earnings management to occur.

5.      Summary and Conclusion

        Information asymmetry between investors and equity issuers provides both

motivation and opportunity for issuers to manage earnings around the time of the

offering. Earnings management, to the extent that it leads to a higher offering price in the

reverse LBO, directly benefits managers and owners of the private firm who sell to

outsiders at a higher price. This study examines whether managers offering stock in

reverse LBOs manage reported earnings upward at the time of the reverse LBO offering.

Using a sample 225 reverse LBOs during the 1980-1998 period, we find that abnormal




13
discretionary current accruals are positive and significantly different from zero during the

year of offering.

       Significant abnormal discretionary accruals conforms to findings of IPOs in

general, where upward management of reported earnings is also in evidence. Given the

evidence, investors may wan to examine accruals of reverse LBO firms for evidence of

abnormal discretionary increases.

       This study also demonstrates differences between of abnormal accruals for

reverse LBOs where buyout specialists are involved and those that do not involve buyout

specialists. Discretionary accruals are greater in the presence of a buyout specialist. These

buyout specialists have an even greater incentive to cash out at the highest possible price

than managers, since the buyout specialist can sever all future relations with the reverse

LBO firm.




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                                      References


Boynton, Charles E., Paul S. Dobbins and George A. Plesko. “Earnings Management and
the Corporate Alternative Minimum Tax,” Journal of Accounting Research, 1992,
v30(Supp), 131-153.

Cahan, Steven F. “The Effect of Antitrust Investigations on Discretionary Accruals: A
Refined Test of the Political-Cost Hypothesis,” Accounting Review, 1992, v67(1), 77-95.

Cotter, James F. and Sarah W. Peck. “The Structure of Debt and Active Equity Investors:
The Case of the Buyout Specialist,” Journal of Financial Economics, 2001, v59, 101-
147.

Degeorge, Francois and Richard Zeckhauser. “The Reverse LBO Decision and Firm
Performance: Theory and Evidence,” Journal of Finance, 1993, v48(4), 1323-1348.

Halpern, Paul, Robert Kieschnick, and Wendy Rotenberg. “On the Heterogeneity of
Leveraged Going-Private Transactions” Review of Financial Studies, 1999, v12(2), 281-
309.

Holthausen, Robert W. and David F. Larcker. “The Financial Performance of Reverse
Leveraged Buyouts,” Journal of Financial Economics, 1996, v42(3,Nov), 293-332.

Jones, Jennifer J. “Earnings Management during Import Relief Investigations,” Journal
of Accounting Research, 1991, v29(2), 193-228.

Perry, Susan E. and Thomas H. Williams. “Earnings Management Preceding
Management Buyout Offers,” Journal of Accounting and Economics, 1994, v18(2), 157-
179.

Rangan, Srinivasan. “Earnings Management and the Performance of Seasoned Equity
Offerings,” Journal of Financial Economics, 1998, v50, 101-122.

Teoh, Siew Hong, Ivo Welch and T. J. Wong. “Earnings Management and the Long-Run
Market Performance of Initial Public Offerings,” Journal of Finance, 1998a, v53(6,Dec),
1935-1974.

Teoh, Siew Hong, Ivo Welch and T. J. Wong. “Earnings Management and the
Underperformance of Seasoned Equity Offering,” Journal of Financial Economics,
1998b, v50, 63-99.




15
Table 1        Total Equity Distribution of Reverse LBOs

The sample includes 225 going-private announcements from 1980 through 1996. Equity values
are computed from the product of common shares outstanding and closing price of common
stock at the end of the fiscal year immediately preceding the calendar year of the announcement
dates.

                                               Total Equity Distribution of Reverse LBOs

Fiscal Year-End              N                   Mean Equity                  Median Equity       Stan

       1986                  12                   121808.52                      95402.50
       1987                  24                   133763.06                     398141.50
       1988                  11                   293027.00                     135150.00
       1989                   7                   179660.43                     150564.38
       1990                  12                   199057.49                      92300.00
       1991                  53                   310555.59                     106037.75
       1992                  57                   335446.40                     170665.75
       1993                  42                   270544.83                     126856.88
       1994                   7                    97679.48                     100464.00

       Total                225                   262969.58                     133269.38




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Table 2        Total Proceeds Distribution of Reverse LBOs


The sample includes 225 reverse LBOs from 1980 through 1998. Gross proceeds are obtained
from the Security Data Company.

                                          Total Proceeds Distribution of Reverse LBOs

Fiscal Year-End              N            Mean Proceeds ($mil)       Median Proceeds
($mil) Standard Deviation

       1986                  12                 33.69                       27.30
       1987                  24                 38.90                       34.95
       1988                  11                 52.77                       40.80
       1989                   7                 52.05                       47.90
       1990                  12                 42.82                       31.60
       1991                  53                 92.42                       29.00
       1992                  57                 88.87                       48.40
       1993                  42                 76.22                       48.00
       1994                   7                 35.84                       37.20

       Total                225                 72.06                       44.00




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Table 3        SIC Distribution of Reverse LBOs

The presence of sixty separate SIC codes, with seventeen of these representing at least 1% of the
sample (fifteen reverse LBOs), indicates a wide selection of industries.

                                                    SIC Distribution of Reverse LBOs

Industry                                                    Two-digit SIC Codes
       Freq.                                                 %

Food Products                                       20                                               7
Chemical Products                                   28                                               8
Electronic Equipment                                36                                              17
Scientific Instruments                              38                                               5
Communications                                      48                                               5
Eating and Drinking Establishments                  58                                               8
Health                                              80                                              14
Fabric and Clothes                                  22, 23                                          11
Paper and Paper Products                            24-27                                           16
Manufacturing                                       30-34                                           14
Computer Hardware & Software                        35, 73                                          19
Transportation                                      37, 39, 40, 42, 45                              14
Whole Sale and Retail                               50-54, 56, 57, 59                               50
Finance, Insurance and Real Estate                  60, 62, 63, 65, 67                              22
All Others                                          8, 13, 15, 16, 17, 21, 47, 55,
                                                    70, 75, 78, 79, 82, 83, 87, 89, 95              15
Total
225   100.0%




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Table 4        Time Distribution of LBOs of Reverse LBOs

This table provides the time distribution when the samples undertake LBOs. Surprisingly, most
of the LBOs in this sample are centered between 1985 to 1990 when almost 80% of LBOs occur.
The trend of LBOs takes off in 1983 and slows down in 1991.

                                                  Time Distribution of LBOs of Reverse
LBOs


Fiscal Year-End                     Freq.                         %
        Cum. Freq.                   %

       1980                          1                           0.4                              1
       1981                          1                           0.4                              2
       1982                          1                           0.4                              3
       1983                          4                           1.8                              7
       1984                          7                           3.1                             14
       1985                         25                          11.1                             39
       1986                         41                          18.2                             80
       1987                         32                          14.2                            112
       1988                         49                          21.8                            161
       1989                         30                          13.3                            191
       1990                         17                           7.6                            208
       1991                          6                           2.7                            214
       1992                          8                           3.6                            222
       1993                          3                           1.3                            225

       Total                      225                          100.0%




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Table 5        Time Distribution for LBOs Staying Private


This Table provides descriptive statistics for the length of years those reverse LBOs staying for
private. The length of one though five years dominates the others, especially length of three
years, which is the mean of the length for staying private.


                                                      Time Distribution for LBOs Staying
Private

       Years                        Freq.                              %
       Cum. Freq.                    %

        0                             6                                2.7                            6
        1                            34                               15.1                           40
        2                            43                               19.1                           83
        3                            45                               20.0                          128
        4                            42                               18.7                          170
        5                            23                               10.2                          193
        6                            19                                8.4                          212
        7                             6                                2.7                          218
        8                             2                                0.9                          220
        9                             3                                1.3                          223
       10                             2                                0.9                          225

       Total                        225                             100.0%




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Table 6          Tests on Abnormal Accruals

This table provides the results of whether the abnormal accruals are significantly different from ze ro or
not under different specifications during reverse LBO transactions (The coefficients of expected model
are generated from a matched sample where each firm shares the same four-digit SIC code , if no four-
digit code is available, the three- or two-digit SIC code is used instead). Panel A tests the whole sample;
Panel B tests the sample with MBO as a dummy, taking on the value of 1 if the reverse LBO firms have
management involved in the previous leveraged buyout deals, 0 otherwise. Likewise, Panel C tests the
sample with Investor a 0, 1 dummy variable taking on the value of 1 if the reverse LBO firms have
investor involved in the previous LBO transactions.


Analysis Variable: abnormal accruals

Panel A                      N            Mean              Std Error        T-Stat.        P-value           Minimum

                           133          0.0398322           0.0150888        2.64***        0.0093            -0.3646620

Panel B       MBO            N           Mean               Std Error        T-Stat.        P-value           Minimum

                 0           45         0.0449415           0.0207351        2.17**         0.0357            -0.3646620

                 1           88         0.0372196           0.0202645        1.84**         0.0697            -0.2796273

Panel C       Investor       N            Mean              Std Error        T-Stat.        P-value           Minimum

                 0           23         0.0372096           0.0383294        0.97           0.3422            -0.3646620

                 1         110          0.0403806           0.0164725        2.45***        0.0158            -0.2796273

*** Indicates statistical significance at the 0.01 level.
 ** Indicates statistical significance at the 0.05 level.
  * Indicates statistical significance at the 0.10 level.




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