This article is forthcoming in The Financial Review.
Evaluating the SDC Mergers and Acquisitions Database
Beau Grant Barnes*
Washington State University
237G Todd Hall
Pullman, WA 99164-4729
509-335-4472 (Phone)
509-335-4275 (Fax)
[email protected]
Nancy Harp
Clemson University
Clemson, SC
864-656-0431 (Phone)
864-656-4892 (Fax)
[email protected]
Derek Oler
Texas Tech University
Lubbock, TX
806-742-2354 (Phone)
806-742-3182 (Fax)
[email protected]
Abstract
We compare 20 years of data from SDC’s Mergers and Acquisitions database with a handcollected database, providing evidence on the completeness and accuracy of SDC data across
time. We find that our hand-collected data is generally more accurate than SDC, but SDC’s
accuracy and coverage improves over time. Our investigation of discrepancies between the
databases finds that SDC is more prone to errors on smaller, high book-to-market acquirers with
a weak announcement period market response. Preliminary analyses suggest that this potential
bias is not significant, but could affect inferences when examining smaller, high book-to-market
firms.
JEL: G34
Keywords: SDC, Mergers, Acquisitions
* Corresponding Author
We are grateful for the contribution of an initial data set of 947 acquisitions provided by Tim Loughran. We are also
grateful for the research assistance of Sari Ruben, Andrea Caggiano, Khary Barnes, Zenyep Eroglu, and Troy
Engstrom in the development of this database. We are also thankful for the thoughtful comments received during the
review process.
1. Introduction
Researchers require data that is relatively complete and accurate to draw meaningful
conclusions. The Thompson Financial SDC Platinum (SDC) database has facilitated a significant
amount of research into mergers and acquisitions (MA) and has been cited regularly in major
accounting and finance journals over the past decade.1 Some authors express concern over the
completeness of the information provided by SDC, but there is little agreement on the precise
year that data in SDC becomes reliable enough to warrant its use in research. For example,
Aboody, Kasznik, and Williams (2000, p. 272) report that they begin their sample with 1991
because “this is the first year for which the acquisition data provided by SDC are complete.” In
contrast, Baker and Savasoglu (2002, p. 97) use 1981 as their starting year, noting that “prior to
1981, SDC does not provide full coverage of mergers and acquisitions.” Other papers using SDC
typically report a starting year within these two extremes, in one case stating that “coverage is
more likely to be spotty in the 1980s than in the 1990s” (Pontiff and Woodgate, 2008, p. 931).
The accuracy of data reported in SDC’s MA database has also been questioned. For
example, Bharadwaj and Shivdasani (2003) report using the acquirer’s 14D-1 SEC filings as a
better source of information for financing data, where available, because SDC’s data appears to
be less reliable. Faccio and Masulis (2005, p. 1351) use the SDC MA database for mergers
between 1997 and 2000 and note that they “…found (and fixed) a number of mistakes in the
SDC database” when attempting to calculate merger size. While concerns over SDC accuracy
1
A search for articles in the Journal of Finance, Journal of Financial Economics, Journal of Accounting and
Economics, Journal of Accounting Research, Review of Accounting Studies, Review of Financial Studies, and the
Accounting Review from 2000-2010 yields 52 merger and acquisition studies that reference SDC.
1
have accumulated in the literature, there has been little empirical work that addresses the degree
of completeness and accuracy of the SDC MA database.2
Our paper compliments the recent work of Netter, Stegemoller, and Wintoki (2011), who
examine the effect of various screens placed on data from SDC. They show that the conclusions
drawn by researchers on acquisition waves and the market response to acquisition
announcements are sensitive to the screens used (for example, if private target firms are
excluded, or if only acquirers with Compustat data available are used). While they focus on the
effect of broad and commonly used data screens, we focus on observations from SDC that meet
the more commonly used screens (both the target and acquirer must be included in the CRSP
database, the acquirer must also be included in Compustat, and the target must be 100% acquired
and delisted). Our study also contrasts Netter, Stegemoller, and Wintoki in that we focus on
providing detailed information about the accuracy and completeness of SDC across time. Our
purpose is to inform future researchers' use of SDC and hand-collection. While evaluating
whether specific prior research findings using SDC are sensitive to accuracy/completeness errors
is largely beyond the scope of our study, we perform some limited analyses that suggest
accuracy/completeness errors are not a significant concern.
A considerable amount of research focuses on market response to the announcement of
an acquisition. Accordingly, we analyze the completeness of SDC reported acquisitions from
1978 to 1995 and from 2003 to 2004 by comparing these acquisitions with a hand-collected MA
database for the same years. We analyze 1978 through 1995 data to identify potential coverage
and accuracy problems and improvements in these earliest 18 years of data available on SDC’s
2
One exception regarding accuracy is Fuller, Netter, and Stegemoller (2002) who, in their investigation of 1990s
acquiring-firm returns, randomly sample 500 acquisitions and attempt to verify the corresponding SDC
announcement date. They report an SDC error rate of 7.4%.
2
database. We then arbitrarily select 2003 and 2004 as additional years to provide evidence on
SDC’s more recent data. This comparison reveals some coverage weaknesses in the SDC data,
but also calls attention to potential hand-collection errors.
To analyze the accuracy of reported data, we compare acquisitions reported in our handcollected database with acquisitions in SDC. In many cases, especially from 1984 onward, we
find that the data sets agree on the acquirer, target, and announcement date. Where the data sets
agree on the target but disagree on the acquirer or announcement date, we attempt to determine
which data set is correct.
We find that the completeness of SDC is largely dependent on the years of interest, with
a general trend of improvement in coverage over time. Compared with our hand-collected data
set, the latest years we examine (2003 and 2004) are relatively complete, offering some comfort
to researchers whose interest lies in MA activity during the past decade. SDC also appears to be
fairly complete from 1984 onward; however, coverage before 1984 appears to be poor to
moderate compared with our hand-collected data set.
We also compare announcement dates reported by SDC with our hand-collected data, and
where differences exist, we determine which source appears to be more reliable. Overall, we find
that our hand-collected data is more reliable. Differences in the reported announcement date
sometimes reflect cases where SDC reports a “strong rumor” that precedes the date of the official
announcement where the acquirer and target endorse an agreement to merge (or, in the case of a
takeover offer, where the acquirer unilaterally announces the desire to purchase the target’s stock
without the target’s acceptance). However, the market response to both announcement dates (i.e.,
the date reported by SDC and the date reported in our hand-collected data set) is often strong,
suggesting that the market treats both dates as important informational events.
3
Given the uncertainty noted in prior work about the completeness of SDC data, especially
in early years, we investigate cases where one data set reports an acquisition that is not included
in the other data set. In some of these cases differences are attributable to our arbitrary choice of
year cut-offs and do not reflect errors in either data set. For example, if SDC provides an
effective date of January 1, 2005, but the hand-collected data set reports a delisting date of
December 31, 2004, the observation will be included in our hand-collected data set but excluded
from our data download from SDC. In other cases where one data set includes observations that
are missing in the other, we find that SDC sometimes reports acquisitions where the acquirer or
target is mislabeled as a public firm when it is actually a private or foreign firm. We find that
SDC is more likely to miss earlier acquisitions, especially announcements involving smaller,
value acquirers with a more muted announcement date response. The clustering of SDC errors in
acquisitions involving acquirers with specific attributes (i.e., smaller, value firms) suggests a
systematic bias in SDC that could potentially impact conclusions from prior research. Thus, we
examine selected prior MA findings that could be vulnerable to this particular sample bias using
a data set corrected for SDC errors; inferences from prior research show little change, providing
comfort that the impact of SDC’s systematic bias is not significant. However, researchers who
focus on small, high book-to-market firms should be cautious about concluding there are no
results, because we show that results for small acquirers get stronger after correcting the errors
we detect.
In addition to our accuracy and completeness findings, our comparison between SDC and
hand-collected data provides valuable insights into both data sets. For example, we find that SDC
correctly reports multiple bidders and rumored acquisitions, but a researcher who hand-collects
data on acquisitions will likely miss these multiple bidders and rumors based on the process used
4
for hand-collecting (i.e., searching news and announcements, or collecting data based on a
CRSP-reported delisting date where the delisting is the result of an acquisition). One solution to
this problem is to spend more time analyzing post-announcement news articles to determine if
subsequent bidders emerge. However, news articles between the first announcement and the
consummation of the acquisition can number in the thousands, and this checking process can add
months to the time needed for data collection. Because we find that SDC occasionally mislabels
acquirers’ and targets’ public status, a researcher may wish to ignore these variables (“APUB”
and “TPUB”) as reported by SDC and attempt to match all acquirers and targets with CRSP data.
This will produce many cases where a match cannot be found, because the firms involved may
not be publicly traded. The researcher doing this should expect to see a large number of SDC
acquirers and targets where no CRSP permno is available.
2. Data sets used
2.1 SDC’s Mergers and Acquisitions database
SDC offers a number of financial databases, and we investigate only a subsample of its
Mergers and Acquisitions (MA) database, where a U.S. public firm acquires a U.S. public target.
SDC reports that it identifies acquisitions through a number of possible sources: SEC filings,
press releases, and newswires. We retrieve acquisitions that meet the following criteria:
i.
ii.
The acquisition was announced between 1978 and 1995 and between 2003 and
2004 (SDC’s documentation states that the database begins with 1979; however, it
contains a number of acquisitions announced in 1978 and one acquisition
announced in 1977, which we ignore).3
Both target and acquirer must be U.S., public firms.4
3
We select 1995 and 2004 as cut-offs merely because our hand-collected data set ends in those years.
We screen for public acquirers and targets when we match our SDC data with CRSP data. SDC also identifies
public targets and acquirers through the variables “TPUB” and “APUB,” which we discuss in more detail later in the
paper.
4
5
iii.
The acquirer must not have owned more than 50% of the target before the
transaction took place.5
Using data downloaded from SDC on March 8, 2010, we retrieved 86,493 acquisitions,
of which 2,117 are ultimately suitable for comparison purposes. To create a data set comparable
to our own hand collected data set, we retain only acquisitions for which we are able to find a
CRSP permno for the acquirer and target firm. Matching with CRSP is done through a two-stage
process, where we first match with the 6-digit CUSIP reported by SDC (and reported by CRSP
in its names file), and then match remaining unmatched firms based on ticker.6 We exclude
acquisitions where the target or acquirer is an ADR, REIT, or a closed-end fund. We also
exclude observations where no actual acquisition took place, or where the effective date of the
acquisition was between January 1, 1996 and December 31, 2002 or after December 31, 2004.
We also exclude acquisitions where no price information was available on the target firm’s
delisting date or where the target firm was trading below $3 per share on the delisting date. There
were some acquisitions that were reported twice in the SDC data set. We define duplicates as
instances where the same acquirer CUSIP, target CUSIP, and announcement date combination is
listed within the SDC data more than once. We delete the duplicates, keeping only one unique
combination of acquirer, target, and announcement date.7
As in the hand-collected data set, we eliminate observations where Compustat or CRSP
financial information needed to calculate our variables of interest is missing. This results in a
5
Specifically, we include deal types 1 and 2 (disclosed value and undisclosed value acquisitions), and exclude deal
types 10 (acquisition of minority stake) and 11 (acquisitions of remaining interest).
6
It is also possible that we mismatch SDC data with our CRSP data when we attempt to find each firm’s permno.
We identify mismatches when we compare our SDC data with our hand-collected data in Tables 2 through 7.
7
Duplicates seem to reflect errors in SDC’s data updating process. When new or updated information is available on
a given acquisition we would expect SDC to update the deal’s existing record with the new information (e.g., deal
value, effective date, etc.). In the case of a duplicate, a new record is created which includes the updated
information. Given the small number of duplicates (119), the creation of a new record is not the norm.
6
total of 2,117 (1,649) observations where the acquirer (target) has the financial information
necessary to calculate our variables of interest.
[INSERT TABLE 1 HERE]
2.2 Hand-collected data set
Our hand-collected data set contains a total of 2,223 acquisitions. We collect 1,974
acquisitions from 1978 to 1995 and 249 acquisitions from 2003 to 2004 using the following
technique:8
i.
ii.
iii.
iv.
v.
vi.
We select all firms delisted from the CRSP database between January 1, 1978 and
December 31, 1995 and between January 1, 2003 and December 31, 2004 with a
2xx delisting code (delisting because of merger or acquisition)
We exclude acquirers and targets that are American Depository Receipts (ADRs),
Real Estate Investment Trusts (REITS), and closed-end funds.
We exclude target shares trading at less than $3 per share on the final trading date
to eliminate firms that are very small or in distress.
In many cases (especially where stock is offered as consideration by the acquirer)
the acquirer permno is provided by CRSP (reported as newperm). In cases where
the acquirer permno is not provided, we search the CCH Capital Changes
Reporter (CCH) or perform a media search using Lexis-Nexis to determine the
identity of the acquiring firm. The permno of the acquirer is determined by
matching the acquirer name from CCH or the published acquisition
announcement with data in the CRSP names file.9
CCH provides details on the consideration offered, and confirms the delisting date
provided by CRSP. We also search Lexis-Nexis for newswire announcements of
acquisitions and confirm acquisition information provided by CRSP. We confirm
that the acquisition took place for all firms, including those with an acquirer
permno provided by CRSP, using CCH or Lexis-Nexis media searches.
For all acquisitions, we use various public-media search engines (Wall Street
Journal Index, Dow Jones Online (later renamed Factiva), and Lexis-Nexis) to
determine the announcement date. Reviewing the media reports related to the
acquisition also confirms the target and acquiring firm. Also, because CRSP does
not distinguish between a merger where the target was previously not controlled
by the acquirer and one where the “acquirer” was merely acquiring the minority
interest, we used the news media search to eliminate “mergers” where the target
was already controlled by the acquirer.
8
This method is based on the data collection technique reported by Loughran and Vijh (1997).
CCH is used for acquisitions related in the period from January 1, 1978 to December 31, 1995. Lexis-Nexis is used
to search for acquisition announcements for observations in the period January 1, 2003 to December 31, 2004.
9
7
vii.
We eliminate observations from our data where Compustat or CRSP financial
information that is required to calculate all our variables of interest is missing.
These steps result in a total of 2,223 (1,993) observations where the acquirer (target) has
all the financial information necessary to calculate our variables of interest. Our data collection
technique allows for cross-verification of several elements in our database. However, handcollection can have certain disadvantages.
One general disadvantage is that hand-collection takes a considerable amount of time,
and care must be taken to track the progress of data collection. For example, we are unable to
produce a table similar to Table 1 for our hand-collected data set because (1) a significant portion
of the completed data was graciously provided by Tim Loughran (the data was used in Loughran
and Vijh, 1997), and therefore we did not have details on data collection for 1978 to 1989; (2) we
did not retain counts of data excluded at various stages (e.g., observations excluded because of
the inability to find the announcement date). Retaining this data during the collection process in
2001 did not seem important, as few papers at that time reported the transition from initial
observations to the final, useable data set (e.g., Loughran and Vijh, 1997; Rau and Vermaelen,
1998; Moeller, Schlingmann, and Stulz, 2004). In comparison, extracting data from a
professionally created (and maintained) data set like SDC allows for relatively easy tracking of
observations lost at various stages. Although we do not provide a detailed table showing initial
observations to the final useable hand-collected sample, our detailed explanation above regarding
each step taken to arrive at our final sample provides future hand-collectors with a guide on how
to construct a hand-collected MA sample.
Our hand-collected data is also affected by factors specific to studying acquisitions.
Given that our starting point is the delisting of firms from the CRSP database, we can only detect
8
takeovers where the target was 100% acquired. If the CRSP delisting code is incorrect, or if the
target was delisted for a non-acquisition reason before being acquired, we will not detect the
acquisition. Indeed, subsequent analysis reveals that hand-collection efforts missed at least 37
acquisitions due to incorrect CRSP delisting codes (see Table 6). Also, hand-collection is costly
and time-consuming, and data entry errors are always a possibility. In our data set, for example,
it is possible that the acquirer permno is incorrect because of a mistake in matching the name of
the acquirer from CCH or the acquisition announcement found in our media search with a similar
name in CRSP.
3. Comparison of SDC data set with the hand-collected data set
3.1 Number of acquisitions reported
Table 2 provides a breakdown of mergers and acquisitions reported by the hand-collected
data set and SDC by year. For comparative purposes, we show the total SDC acquisitions
reported as a percentage of hand-collected acquisitions. Overall, SDC’s 2,117 reported
acquisitions represent 95% of the hand-collected data set’s 2,223; however, year-by-year
comparison shows greater differences in coverage. The SDC coverage ratio (calculated as the
number of observations from SDC divided by the number of hand-collected observations for that
year) ranges from a low of 7% for 1979 to a high of 140% in 1990, when the SDC data set
reports 80 acquisitions versus 57 in the hand-collected data set. The 1978 to 1980 period is the
sparsest for SDC, but from 1981 onward, SDC’s coverage improves dramatically.
Merely comparing the total number of observations by year can be misleading because
the actual acquisitions reported by SDC may not be the same as those in our hand-collected data
set. Accordingly, we also calculate the percentage of acquisitions in the “complete match”
9
column (i.e., acquisitions where SDC and hand-collected data sets completely agree on the
acquirer, target, and announcement date) that are in the SDC column.10 Overall, there are 1,407
observations in our “complete match” category, representing 63% of the acquisitions reported by
SDC. In other words, for nearly two-thirds of our data, SDC matches up very closely with our
hand-collected data. These results suggest that the agreement between our data sets is low from
1978 through 1980, moderate from 1981 to 1983, and fairly good from 1984 onward.
Our subsequent columns break out observations where one or more data points differ
between our data sets. The “Acquirer differs” column reports 35 acquisitions where the same
target firm and announcement date are reported in both data sets, but the reported acquiring firm
differs. “Date differs” reports 271 acquisitions that are in both data sets with the same target firm
and the same acquiring firm, but the announcement dates differ. Finally, “Acquirer & date
differ” reports 41 acquisitions where the same target firm is reported in both SDC and handcollected data sets, but neither the acquiring firm nor the announcement dates agrees between the
two data sets. Overall, the very low percentage of observations in these categories implies that
when SDC and the hand-collected data sets report the same acquisition (i.e., the same target firm
is listed in both data sets as being acquired), the two data sets generally find the same acquiring
firm and same announcement date. However, we investigate each acquisition in these categories
to determine which data set was in error, and present our results in Tables 3 to 5.
Finally, we report in Table 2 the number of observations where a target firm reported by
one data set is not reported in the other data set. “Not in hand-collected” refers to observations
where the acquisition (specifically, the acquisition of the target firm) was reported by SDC, but
not by the hand-collected data set. Overall, about 18% (375 out of 2,117) of observations
10
Throughout this paper, we consider SDC and hand-collected announcement dates to be the same when the
reported announcement dates are no more than one day apart.
10
reported by SDC are not in the hand-collected data set. This represents a significant difference
between SDC data compared with hand-collected data, which we investigate further in Table 6.
Finally, “Not in SDC” refers to observations where the acquisition was reported by the handcollected data set, but not SDC. Even in years where SDC reports more observations than the
hand-collected data set (i.e., 1981 – 1993, 1995, 2003, and 2004) there are several acquisitions
that are reported by the hand-collected data set that are not in SDC. We investigate these further
in Table 7.
[INSERT TABLE 2 HERE]
3.2 Differences between SDC and the hand-collected data sets
In this section we provide analysis of differences in acquisition information reported by
SDC and the hand-collected data sets to provide additional empirical evidence on the accuracy of
SDC. We perform a detailed analysis of individual observations from the categories from Table
2 that indicate the presence of differences between the SDC and hand-collected data sets (e.g.,
“Acquirer differs,” “Date differs,” etc.).
3.2.1 Investigation of 35 observations where “Acquirer differs”
Table 3 shows the results of our investigation into each observation reported in Table 2
where the target firm and announcement date are the same, but where each data set reports
different acquirers. We determine which data set is correct using the following approach. For
each observation, we first perform a media search of merger/acquisition announcements using
Lexis-Nexis. Then, if we are not able to determine which data set reported the correct acquirer
using the media search, we determine whether one of the acquirers reported by the data sets is
11
not publicly traded (as proxied by lack of availability in CRSP around the announcement date).11
The acquirer with data available in CRSP is deemed the correct acquirer.12 Finally, for
observations where the media search cannot determine the correct acquirer and both the handcollected and SDC reported acquirers have time-series CRSP data available, we search for spikes
in trading volume around the acquisition announcement date as reported by CRSP. We assume
that the firm with a greater increase in trading volume around the announcement date is the
acquirer.
Table 3 reports our findings based on the technique described above. Our results suggest
that the hand-collected data set reports the correct acquirer for 51% of our observations, and that
that the SDC-reported acquirer is correct for 17% of our observations. We also find that neither
data set is in error for about 31% of observations, mostly because the hand-collected acquirer is
the ultimate parent of the SDC-reported acquirer.13 Overall, we conclude that when the acquirer
is different between SDC and the hand-collected data set, our hand-collection technique tends to
yield more accurate information.
We also report the financial characteristics of the acquirer (size and book-to-market) and
the announcement date response to the reported acquirer and target for observations where data
is available.14 Because SDC and the hand-collected data set report different acquirers for this
subset of acquisitions, we show figures for both. For comparative purposes we also show the
11
Both the SDC reported acquirer and the hand-collected reported acquirer have permnos on CRSP. However, one
firm might not have trading information as of a particular announcement date.
12
SDC reported the acquirer as being a public firm that is presumably covered by CRSP. If CRSP does not cover the
firm, then our results will incorrectly attribute the mistake to SDC.
13
One observation listed in Table 3 is “Other/Indeterminate.” Based on the name of the acquirer in the
announcement and permnos associated with that name in CRSP, we were unable to tell if SDC or hand-collection
selected the correct permno for the acquirer. Additionally, CRSP and Compustat data were available for both
acquirers, and both experienced similar spikes in trading volume around the announcement date.
14
We measure size by calculating a firm’s market capitalization 30 days prior to the announcement date. Since our
data ranges from 1978 to 2004, we scale market capitalization using the consumer price index. All values of market
capitalization throughout the paper are reported in 2004 dollars.
12
same variables for the 1,407 “complete match” observations from Table 2. This comparison
suggests that observations where disagreement exists over the acquirer reflect a smaller acquirer
(market cap of $908 thousand for the SDC acquirer vs. $5.7 million for the “complete match”
observations), a “value” acquirer (book-to-market of 0.78 vs. 0.61), and a more muted acquirer
response on the announcement (2.4% abnormal returns vs. -4.6%). Overall, these results suggest
that errors are more likely to occur in both SDC and in our hand-collected data set when the
acquirer is smaller, has a higher book-to-market ratio, and has a weaker market response to the
acquisition. This could be attributable to news coverage being biased towards larger and more
prominent acquisitions.
[INSERT TABLE 3 HERE]
3.2.2 Investigation of 271 observations where “Date differs”
Table 4 shows the results of our investigation into each observation reported in Table 2
where the target firm and acquirer match but the announcement date differs by more than one
day. Because of differences in media search engines that are commonly used to determine
announcement dates, it is not surprising to find slight differences in announcement dates between
databases. This is generally not a concern, because a common window length for the study of
market response is three days (i.e., one day both before and after the announcement date).
However, announcement dates that are outside of a +/- one day window centered on the other
data set’s announcement date represent potentially significant differences that we investigate.
It is critical to clearly define an acquisition announcement. We define an acquisition
announcement as a joint public statement of an agreement to merge, acquire, or be acquired, that
is endorsed by both the acquirer and target managers (although a formal definitive agreement is
13
not necessary). Where the bid is hostile, we do not require consensus from the target managers.
SDC defines the announcement date as:
The date one or more parties involved in the transaction makes the first public
disclosure of common or unilateral intent to pursue the transaction (no formal
agreement is required). Among other things, Date Announced is determined by
the disclosure of discussions between parties, disclosure of a unilateral approach
made by a potential bidder, and the disclosure of a signed Memorandum of
Understanding (MOU) or other agreement….
Although SDC’s definition allows for announcements of acquisitions that ultimately are
not consummated, we eliminate any transactions reported in SDC that were not ultimately
consummated by removing observations with the “Effective Date” missing (See Table 1). Thus,
the hand-collected acquisitions and the SDC-reported acquisitions seem to have very similar
definitions for announcement date.
We perform Lexis-Nexis media searches on all observations in this sub-set to determine
which data set reports the announcement date most consistent with our definition. We find that
the hand-collected announcement date is correct for about 195 (72%) of the observations where
the announcement date differs between SDC and the hand-collected data set. The announcement
date reported by SDC appears to be correct in 15% of these cases (40 observations); while we are
unable to determine the correct announcement date in 13% of these cases (36 observations).
When SDC reports the correct date, it tends to be an earlier announcement as compared with the
announcement date reported by the hand-collected data set. This could be due to differences in
data collection between SDC and hand-collection. More specifically, our hand-collection method
requires that we begin our search backwards from the date the target delists. Starting at the
delisting date, hand-collectors must carefully search back in time to find the earliest
announcement. This search is made even more difficult for large firms that have hundreds or
14
thousands of articles mentioning the announcement in a reasonable search window. A typical
practice for hand-collection is to stop searching once a reasonably clear announcement is found.
Notwithstanding these difficulties in hand-collection, overall, based on our investigation reported
in Table 4, we conclude that our hand-collection method tends to report more accurate
announcement dates.
As with our analysis of observations where the acquirer differs in Table 3, we find that
errors in the SDC reported announcement date are more likely to occur for smaller acquirers (2.3
million of market capitalization for SDC acquirers vs. 5.7 million), value acquirers (book-tomarket of 0.75 vs. 0.61), and have a more muted announcement response (-1.4% vs. -4.6%).
Although fewer in number, but similar in terms of acquirer book-to-market and the market
response to the announcement, observations where the SDC announcement date appears to be
correct are for significantly larger acquirers (market cap of 17.96 million vs. 5.7). Because the
announcement dates differ between our data sets, we show figures for both dates in Table 4.
[INSERT TABLE 4 HERE]
3.2.3 Investigation of 41 observations where “Acquirers and dates differ”
In Table 5 we report the results of our investigation into each observation in Table 2
where both the acquirer and announcement date differ. As with our “Dates differ” investigation,
we perform Lexis-Nexis media searches for each acquisition and determine that our handcollected data set is correct 88% of the time (36 observations), with most differences occurring
because SDC appears to report the announced sale of a subsidiary incorrectly as the sale of a
publicly traded firm. For example, in October of 1978 Carrier Corp. and Jenn Air Corp.
announced an agreement for Carrier to acquire Jenn Air – an acquisition correctly reported in the
hand-collected data set (but missed by SDC). Jenn Air was then sold by Carrier Corp to Maytag
15
in April of 1982. Thus, the same target (Jenn Air) is reported by both the SDC and the handcollected data sets; the hand-collected data set reports the original sale of Jenn Air when it was a
stand-alone public firm to Carrier Corp in October 1978, whereas SDC reports only the April
1982 sale of Carrier Corp’s subsidiary to Maytag.15 Upon further examination, we find that in
roughly half of these cases the SDC variable “TPUB” indicates that the acquired company
is "private." During our data collection and screening of SDC information as described in Table
1 and in Section 2, we did not remove “non-public” firms using the SDC variables “TPUB” and
“APUB,” but instead relied on our CRSP permno matching procedures to determine whether
acquirers and targets were public firms. SDC defines these variables as follows:
TPUB – Target Public Status: Form of ownership of the target company at the
time of the transaction.
APUB – Acquirer Public Status: Public status of acquiring company: public,
private, subsidiary, joint venture, government owned
In supplementary analyses, we remove all observations that do not contain “public”
acquirers and targets as indicated by the SDC variables “TPUB” and “APUB.” In applying those
screens, we lose 505 acquisitions from the SDC data set. The screens appear to improve the
accuracy of SDC, but at significant cost because several viable observations are also lost. For
example, observations in the “Not in hand-collected” category (which represents many SDC
errors – see Table 6) fall from 375 observations to 144. The category “Not in SDC” (which
includes acquisitions reported by our hand-collection method that were apparently missed by
SDC) increases from 469 observations to 742 when we remove non-public firms per “TPUB”
15
We remove observations from the SDC sample when we are unable to make a CRSP permno match for either the
target or the acquirer. Although Jenn Air was not a stand-alone public firm in the CRSP database at the
announcement date recorded by SDC, we were able to match a CRSP permno to Jenn Air since it was previously a
public firm until the 1978 acquisition by Carrier Corp. Researchers studying target announcement date returns
would exclude this observation since CRSP price data is not available for the target around the announcement date.
However, those interested in acquirer returns might incorrectly include this observation in their sample as an
acquisition of a public target.
16
and “APUB” fields. In sum, our supplementary analysis on the effect of screening by “TPUB”
and “APUB” variables indicates that there is a trade-off in using these SDC variables: a
researcher can improve the accuracy of the data by applying these screens, but at the cost of
reducing power because useable observations are also excluded. Researchers hand-collecting
acquisition data can avoid improperly including acquisitions of private firms or subsidiaries of
public companies by basing their sample on the CRSP delisting file since non-public targets and
subsidiaries will not be included in this sample. Further, when gathering media announcements
during hand-collection, researchers should carefully examine the announcement to ensure they
are selecting the sale of a stand-alone target, not a subsequent sale when the target was already a
subsidiary of another company.
As with our prior tables we find that observations where the acquirer and announcement
date differ between our data sets involve smaller, value acquirers where the announcement date
response to the acquirer is smaller. Overall, our detailed analysis of individual acquisitions
shown in Table 5 confirms our initial proposition discussed earlier that hand-collection is likely
to be more accurate in this category based on higher returns for the hand-collected acquisitions.
[INSERT TABLE 5 HERE]
3.2.4 Investigation of 375 observations where SDC reports acquisitions not in the hand-collected
data set
In Table 6 we report the results of our investigation into each observation reported in the
column “Not in hand-collected” from Table 2. For each observation, we first attempt to
determine whether the missing acquisition represents a hand-collection data set error (i.e., it was
missed by hand-collection, but included properly in the SDC data set) by examining SDC and
CRSP reported details, and where needed, the related media announcements. We find that about
17
19% (71 of 375) of the acquisitions reported in this table represent errors made in the handcollection process. Thirty-four of those 71 cases appear to be human error as we are unable to
find any systematic explanation for why our hand-collected data set missed the acquisition. The
remaining 37 hand-collection errors occurred because CRSP reported a delisting code that was
not an “acquisition” code (i.e., 2xx) for the observation, but based on our media search the
observation appeared to be a valid acquisition.16 Thus, researchers hand-collecting their data
based on CRSP “2xx” delistings will miss some viable observations where the CRSP delisting
code reflects a non-acquisition delisting event that occurs before the target is acquired.17 In
another 200 cases (53%) the acquisition should have been excluded by SDC but was not (for
example, in 13 cases SDC reports non-acquisition events as acquisitions,18 in 19 cases the
acquiring firm was actually a foreign or private firm, and in another 107 cases the target firm was
a private firm).
Another 74 observations (20%) were reported in SDC but not in the hand-collected data
set because the delisting date reported by CRSP fell outside of our scope (for example, a
delisting date reported by CRSP as January 2, 2005, is excluded from our hand-collected data set
even though SDC might have reported an announcement date in 2004 which would have been
16
This is not necessarily a CRSP error, because the target firm can be delisted for various reasons before being
acquired.
17
The delisting codes reported by CRSP are “3xx” (exchanges) for 19 of the 37 observations that we confirmed
were correctly reported by SDC as acquisitions. Other delisting codes in the group of 37 included “4xx”
(liquidations) and “5xx” (drops by current exchange).
18
For example, SDC reports an announcement made on March 17, 1982 in which the Sybron Corporation acquires
American Hospital Supply Corporation. However, through our examination of the media announcement, we
determined that Sybron actually agreed to purchase only the dental manufacturing and distribution operations of
American Hospital Supply. The CRSP delisting file confirms that this “acquisition” reported by SDC did not result
in the target delisting. Further, SDC reports this target as being acquired a second time three years later. This second
acquisition matches with an acquisition reported in the hand-collected data set, and resulted in the target delisting
per CRSP. Thus, the first “acquisition” per SDC is classified as “Not in hand-collected” and the second acquisition
per SDC is classified as “In both SDC and hand-collected.”
18
included in our SDC sample). Finally, in 30 cases we were not able to find information to
confirm that an acquisition did or did not take place.
[INSERT TABLE 6 HERE]
3.2.5 Investigation of 469 observations where the hand-collected data set reports acquisitions
not in the SDC data set
We perform additional media searches on observations unique to the hand-collected data
set (i.e., “Not in SDC”) as reported in Table 2 to determine if the acquisitions are properly
recorded in the hand-collected data set. As reported in Table 7, our Lexis-Nexis searches confirm
that 445 of the 469 (about 95%) are appropriately recorded as acquisitions in our hand-collected
data set. While examining the announcements for these 445 acquisitions, we searched for
potential reasons why the acquisition was missed by SDC. We report that most of these 445
observations are most likely missed by SDC because they represent older announcements, when
SDC’s coverage was not as good (i.e., 266 of the 445 were announced prior to 1985).
Additionally, 62 of the 445 represent acquisitions involving financial institutions. We are unable
to determine a reason why SDC missed the acquisition for 117 observations.
We find that 24 of the 469 acquisitions (about 5%) are hand-collection errors. These
errors are primarily due to our failure to exclude acquisitions of minority interests (10 of 24). We
are unable to find any acquisition announcements for 6 of the 24. Other errors include incorrectly
classifying non-MA activity as an acquisition (e.g., corporate reorganizations, spin-offs, etc.), an
isolated duplicate observation, and an isolated acquisition involving an ADR (which should have
been excluded according to our data collection technique described in Section 2). These errors
19
highlight the difficulties inherent in hand-collection. When examining thousands of
announcements it is difficult to avoid human error.
In Table 7 we further compare the acquirer size, book-to-market, and announcement date
response for our 469 observations in the hand-collected data set but not in the SDC data set
versus acquirers in the “complete match” category of Table 2. Consistent with our prior results,
acquisitions that are more likely to be missed by SDC involve smaller acquirers (mean market
cap of $3.5 million, vs. $5.7 million), value acquirers (mean book-to-market of 0.96 vs. 0.61),
and a more muted announcement date response (-3.0% vs. -4.6%).
[INSERT TABLE 7 HERE]
4. Implications for MA research
Analyses in Tables 3 through 7 suggest that SDC is systematically more likely to miss (or
report inaccurately) smaller, value acquirers with more muted announcement period responses.
Nonrandom data errors such as these raise the suspicion that previously examined associations
between these firm characteristics and announcement period returns could be impacted by a
systematic bias in the data. Firm characteristics such as size and book-to-market serve as
important controls in MA research (e.g., Officer, Poulsen, and Stegemoller, 2009) and are
sometimes the primary interest of the study (e.g., Moeller, Schilingemann, and Stulz, 2004).
Whether or not the SDC errors noted in this study have a significant impact on inferences from
prior studies is an open empirical question. A thorough analysis on the effect of SDC’s bias is
beyond the scope of this study; however, we perform the following limited analyses to provide
insights on whether MA researchers using SDC should be concerned with its bias against small,
value acquirers.
20
To analyze the bias, we begin by developing a “corrected” SDC data set. We start with
the SDC observations detailed in Table 1 as our base file and then correct acquirers and
announcement dates for observations where differences between hand-collected and SDC data
sets were determined to be the result of SDC errors (see Tables 3, 4, and 5). Additionally, we
delete any observations that SDC includes by error (see Table 6), and add any observations that
SDC excludes in error (see Table 7). We are left with a “corrected” SDC sample of 2,385
acquisitions, 694 of which contain corrections using hand-collected information.19
Descriptive statistics on the 2,385 observations in the corrected SDC sample indicate that
the 694 “corrected” acquisitions have a slightly more muted market response (-2.5% for
corrected acquisitions versus -2.8% for those remaining acquisitions that did not require
correction) and involve more value acquirers (the average BTM ratios are 0.889 for corrected
acquisitions versus 0.631 for those remaining acquisitions that did not require correction) which
is consistent with an SDC bias. We create an indicator variable to identify “small acquirers”
(defined following Moeller, Schilingemann, and Stulz, 2004) and find that small acquirers in our
“corrected” acquisitions data set have a mean announcement period return of 2.4%, whereas
small acquirers that did not require correction have a mean announcement period return of 3.5%.
Again, we see that acquisitions representing corrections to SDC’s data set display more muted
market responses, consistent with the bias discussed previously.
19
Corrections to SDC are as follows: 18 (Table 3) + 195 (Table 4) + 36 (Table 5) + 200 (Table 6) + 445 (Table 7) =
894. The corrected observations that remain in the sample total to 694, because 200 corrections from Table 6
represent observations that were inappropriately included in SDC, and needed to be subtracted from the sample. The
final corrected sample of 2,385 results from the following: 2,117 (SDC base file – see Table 2) + 445 (Table 7) –
200 (Table 6) + 23 = 2,385. The 23 observations added represent acquisitions where information was not available
when using incorrect SDC-reported information (such as acquirer or announcement date), but information was
available when using the corrected hand-collected information. The corrected SDC sample used in the regression
analysis in Table 8, Panel B is 2,348 because 37 observations did not have control variable information required for
the regression (i.e., consideration paid or diversification information was missing).
21
We next perform regression analysis on both the “corrected” SDC sample and the
original SDC sample (without any corrections) to examine whether selected relations shown in
prior research change after adjusting for SDC’s bias. Prior research finds that small acquirers
exhibit superior performance compared to larger acquirers (Moeller, Schilingemann, and Stulz,
2004). However, if the SDC data set systematically excludes small acquirer deals with more
muted announcement period returns, then it is possible that this size effect is driven by SDC’s
sampling bias. Using corrected and uncorrected samples, we regress commonly examined
variables and controls from MA research on announcement period returns. Variables examined
include acquirer book-to-market (BTM), an indicator variable for acquirer size (SMALL_AQ) as
defined in Moeller, Schilingemann, and Stulz, an indicator variable equal to 1 when a target is
purchased using only stock consideration (STOCK), an indicator variable equal to 1 when the
acquirer and target have differing two-digit SIC industry codes (DIVERSE), and dummies for
the announcement year (YEAR) and the acquirer’s industry (INDUSTRY). An exhaustive set of
control variables is not available due to the limited amount of information hand-collected. Our
regression model (Model 1) is shown below:
AQ_Returns = 0 + 1BTM + 2SMALL_AQ + 3STOCK + 4DIVERSE + 523YEAR + 24-87INDUSTRY + .
(1)
Univariate tests of variable means suggest that the corrected and original SDC samples
are similar. OLS regression results are presented in Table 8. Panel A shows the results from
fitting Model 1 to the uncorrected SDC data, whereas Panel B details the results from fitting
Model 1 to the corrected SDC data set. The results support the prior MA research findings across
both data sets. Specifically, in both samples acquirers with higher book-to-market ratios have
higher returns (although the magnitude of the estimated coefficient shrinks from 24.3 to 8.0),
22
small acquirers have higher returns (consistent with Moeller Schilingemann, and Stulz, 2004,
although the magnitude of the estimated coefficient increases from 0.039 to 0.055), and deals
involving 100% stock payment have lower returns (consistent with Travlos, 1987; Servaes, 1991;
and Bhagat, Dong, Hirshleifer, and Noah, 2005).20 In both samples, diversifications have
negative coefficients (consistent with Morck, Shleifer, and Vishny, 1990; and Moeller,
Schilingemann, and Stulz, 2004); however, the relation is not statistically significant in either
sample.
Our results from Tables 3 to 7 suggest that the most significant errors in SDC data are
clustered in smaller, high book-to-market firms, especially in the period before 1989.
Accordingly, in Panels C to F of Table 8 we show our regression results where we limit our
observations to small (market cap below the median) and high BTM (BTM above the median)
acquirers (Panels C and D), and then add the restriction of observations from 1989 or earlier
(Panels E and F). Results from Panel C suggest that the researcher would conclude that the
market reaction is associated with the acquirer’s size and stock consideration. After correcting
for the errors we identify, the results for stock consideration lose significance, and results for
acquirer size become stronger. Our restricted data sets show that the diversification dummy is
marginally significant for the uncorrected data (-0.025, p=0.07, Panel C), but insignificant for the
corrected data in Panel D. When we restrict our samples to include only small, value firms from
1979 to 1989 (Panels E and F), only the small acquirer dummy remains significant (in both the
uncorrected and corrected data sets). Our overall loss of significance for other variables across is
20
To be consistent with Moeller, Schlingmann, and Stulz (2004), we exclude acquirer market capitalization as
another independent variable. As a robustness check we include this variable and find that the small acquirer dummy
continues to have a significantly positive regression coefficient.
23
likely due the overall lack of power (for example, Panel E has 376 observations, versus 597
observations in Panel C).
Overall, we do not find substantial evidence suggesting SDC’s sample bias impacts
previous results from MA research on firm size and book-to-market. Although the current study
indicates a systematic bias in SDC data, the greatest threat appears to be that noisier data for
small/high BTM acquirers could obscure significant findings. Researchers using SDC who focus
on smaller value firms should consider checking their data; for example, they could hand-collect
data for an earlier year to estimate the number of missed observations, or could verify the SDCprovided announcement date with their own media search.
[INSERT TABLE 8 HERE]
5. Limitations, conclusions, and recommendations
A significant limitation of this study is that it is inherently biased by what CRSP reports.
For example, Table 1 shows that out of 86,493 acquisitions reported by SDC over our years
investigated, we are unable to find CRSP permnos for either the acquirer or target for 77,989
acquisitions, or 90% of the possible observations. Thus, CRSP errors (or our errors in utilizing
CRSP data) will have a serious impact on our results. We find that other papers (e.g. Moeller,
Schlingemann, and Stulz, 2004) report similar numbers of observations from SDC as we do,
suggesting that our approach is at least consistent with that used by others. Matching issues have
gained limited attention by previous research and the impact of such issues has been insignificant
(Chan, Jegadeesh, and Lakonishok, 1995); however, future research could provide a more
complete picture regarding the extent to which matching issues affect MA research. Along these
lines, we note that MA researchers are forced to make several sample selection decisions when
24
compiling observations. Netter, Stegemoller, and Wintoki (2011) highlight some of these
decisions and find that they can affect the inferences of MA research; however, the sensitivity of
MA research to several decisions is left unexamined. For example, while eliminating firms
trading at less than a certain dollar amount ($3 in the current study) is a relatively common
technique for excluding distressed firms (e.g., Loughran and Vijh, 1997; Oler, 2008), it is unclear
whether or not this screen introduces a systematic bias towards excluding small firms in general
(both financially distressed and healthy). For this reason, it will be beneficial for future research
to (1) quantify potential biases created by unexamined sample selection decisions, (2) develop
and employ more direct criteria for identifying and excluding firms with particular characteristics
(i.e., financially distressed), and (3) confirm the legitimacy of different decisions in specific
contexts.
Both CRSP and SDC update and correct their databases continually. Therefore, many of
the potential errors we discuss here may be corrected in the future. Of course, given the volume
of data involved, mistakes are likely to persist. Further, SDC provides much more data on
mergers and acquisitions (for example, acquisitions by private acquirers) that we have not
attempted to evaluate. Research into the persistence and significance of bias over time as well as
the accuracy of non-public acquisition information can help researchers make appropriate sample
selection decisions that maximize power while eliminating expected bias.
For ease of data collection and scope of coverage, SDC offers a premier database for MA
researchers, as evidenced by its use in a number of recent published papers. For research into
MA activity from 1984 and onward, SDC is likely the best database to use at this time. Possible
errors and reduced coverage in the early 1980s make the SDC database less useful for that
25
period. Using SDC data for the 1978 to 1980 period is not recommended; researchers interested
in this time period (or earlier) should find alternative data sources.
Researchers using SDC should not be surprised to find that not all the acquirers and
targets they download from SDC (even if tagged as public firms) are included in the CRSP data
set. In addition, researchers could find some variation in SDC data as to what exactly constitutes
the announcement of an acquisition. However, our overall take-away from this work is that SDC
offers a reasonably accurate and complete data set of acquisitions that is much easier (and less
costly) to obtain than hand-collection, and that hand-collection cannot prevent all errors anyway.
Perhaps most importantly, SDC coverage tends to be better for (1) acquirers with higher
market capitalization, (2) acquirers and targets that have lower book-to-market ratios (i.e., more
likely to be glamour firms as opposed to value firms), and (3) acquisitions where there is a larger
abnormal return to the acquirer and target in the announcement period. Firms meeting these
criteria enjoy greater media attention, and therefore are more easily detected by data collectors.
This bias should be taken into consideration when conducting MA research; however, our
limited regression analyses examining the extent to which the bias impacts the inferences of prior
research (such as Moeller, Schlingemann, and Stulz, 2004) suggests that SDC’s bias is not a
major concern. However, researchers with a specific interest in small firms or value firms
should, at a minimum, consider the potential for sample selection bias in their studies and adjust
research designs appropriately.
26
References
Aboody, D., R. Kasznik, and M. Williams, 2000. Purchase versus pooling in stock-for-stock
acquisitions: Why do firms care? Journal of Accounting and Economics 29, 261-286.
Baker, M. and S. Savasoglu, 2002. Limited arbitrage in mergers and acquisitions, Journal of
Financial Economics 64, 91-115.
Bhagat, S., M. Dong, D. Hirshleifer, and R. Noah, 2005. Do tender offers create value? New
methods and evidence, Journal of Financial Economics 76, 3-60.
Bharadwaj, A. and A. Shivdasani, 2003. Valuation effects of bank financing in acquisitions,
Journal of Financial Economics 67, 113-148.
Chan, L. K., N. Jegadeesh, and J. Lakonishok, 1995. Evaluating the performance of value versus
glamour stocks: The impact of selection bias. Journal of Financial Economics 38, 269296.
Faccio, M. and R. W. Masulis, 2005. The choice of payment method in European mergers and
acquisitions, Journal of Finance 60, 1345-1388.
Fuller, K., J. Netter, and M. Stegemoller, 2002. What do returns to acquiring firms tell us?
Evidence from firms that make many acquisitions, Journal of Finance 57, 1763-1794.
Loughran, T. and A. M. Vijh, 1997. Do long-term shareholders benefit from corporate
acquisitions? Journal of Finance 52, 1765-1790.
Moeller, S. B., F. P. Schlingemann, and R. M. Stulz, 2004. Firm size and gains from
acquisitions, Journal of Financial Economics 73, 201-228.
Morck, R., A. Shleifer, and R. W. Vishny, 1990. Do managerial objectives drive bad
acquisitions? The Journal of Finance 45, 31-48.
Netter, J., M. Stegemoller, and M. B. Wintoki, 2011. Implications of data screens on merger and
acquisition analysis: A large sample study of mergers and acquisitions from 1992 to
2009, Review of Financial Studies 24, 2316-2357.
Officer, M., A. Poulsen, and M. Stegemoller, 2009. Target firm information asymmetry and
acquirer returns, Review of Finance 13, 467 – 493.
Oler, D. K., 2008. Does acquirer cash level predict post-acquisition returns? Review of
Accounting Studies 13, 479-511.
Pontiff, J. and A. Woodgate, 2008. Share issuance and cross-sectional returns, Journal of
Finance 63, 921-945.
27
Rau, P. R., and T. Vermaelen, 1998. Glamour, value, and the post-acquisition performance of
acquiring firms, Journal of Financial Economics 49, 223-253.
Servaes, H., 1991. Tobin’s Q and the gains from takeovers, Journal of Finance 46, 409419.
Travlos, N. G., 1987. Corporate takeover bids, methods of payment, and bidding firms’ stock
returns, Journal of Finance 42, 943-963.
28
Table 1
Sample selection procedure (SDC)
This table reports the number of observations from SDC’s Mergers and Acquisitions (Domestic) database on March 8, 2010. For comparability
with the hand-collected database, we limit the initial SDC download to the years of interest. We then remove duplicate observations (i.e., SDC
reports the same acquirer, target, and announcement date multiple times), observations where the acquirer or target permno is not available on
CRSP, observations where the acquirer's stock was not publicly traded at the announcement date, observations where the target was not 100%
acquired and delisted, observations where the acquirer or target was an American Depository Receipt (ADR), Real Estate Investment Trust
(REIT), or closed-end fund, where the target delisting price was unavailable or less than $3 on the delisting date, where we did not have
information to calculate acquirer or target market capitalization at 30 days before the announcement, or where information was not available to
calculate acquirer and target cumulative abnormal returns around the announcement date. Finally, we remove acquisitions where the deal effective
date is missing in SDC.
Acquirers
86,493
Acquisitions reported by SDC during the years of interest
Remove:
Duplicate observations
Acquisitions where either target or acquirer permno is not found on CRSP
Acquirers delisted prior to the announcement date
Acquisition does not result in 100% acquirer ownership
Either target or acquirer is an ADR, REIT, or closed-end fund
No delisting price information available in CRSP
Firms trading below $3 per share on CRSP delisting date
Compustat / CRSP information unavailable to calculate variables of interest (i.e., bookto-market, market capitalization, and announcement period market returns)
SDC gives no effective date
Remaining SDC acquisitions for the sampled years
(119)
(119)
(77,989)
(2,919)
(1,935)
(286)
(137)
(510)
(77,989)
(2,919)
(1,935)
(286)
(137)
(510)
(396)
(85)
(874)
(75)
2,117
29
Targets
86,493
1,649
Table 2
Comparing SDC with our hand-collected data set
This table compares the number of observations in our SDC data set with our hand-collected data set. An observation is categorized a "Match"
(i.e., the same observation is found in both the hand-collected and SDC data sets) by satisfying three criteria: (1) both data sets report the same
target permno (2) both data sets report the same acquirer permno and (3) the data sets agree on the announcement date +/- one day. Observations
in "Acquirer differs" satisfy only criteria 1 & 3. Observations in "Date differs" satisfy only criteria 1 & 2. Observations which only satisfy the first
criterion appear in "Acquirer & date differ." “Not in hand-collected” refers to observations which appear only in the SDC data set, and “Not in
SDC” refers to observations found only in the hand-collected data set. Numbers of acquisitions will not reconcile by year because of differences in
announcement dates for some acquisitions.
30
Table 2 (continued)
Comparing SDC with our hand-collected data set
Year
1978
1979
1980
1981
1982
1983
1984
1985
1986
1987
1988
1989
1990
1991
1992
1993
1994
1995
2003
2004
SDC
17
8
26
88
98
104
106
146
155
120
145
108
80
85
100
125
200
146
148
112
handcollected
117
115
80
86
89
97
97
144
139
114
117
97
57
74
88
118
207
138
144
105
Totals
2,117
2,223
SDC as a
%of handcollected
15%
7%
33%
102%
110%
107%
109%
101%
112%
105%
124%
111%
140%
115%
114%
106%
97%
106%
103%
107%
95%
Complete
match
10
6
15
43
46
49
65
100
100
90
83
71
44
59
68
95
151
109
114
89
Complete
match as a %
of handcollected
8.5%
5.2%
18.8%
50.0%
51.7%
50.5%
67.0%
69.4%
71.9%
78.9%
70.9%
73.2%
77.2%
79.7%
77.3%
80.5%
72.9%
79.0%
79.2%
84.8%
Acquirer
differs
1
0
1
0
0
0
2
1
2
1
3
4
5
2
2
2
5
3
0
1
Date
differs
3
4
11
22
21
26
24
24
20
13
21
10
5
8
8
4
23
10
9
5
Acquirer
& date
differ
13
7
5
2
3
2
0
0
1
1
1
0
1
1
1
0
1
1
0
1
Not in
handcollected
2
1
3
20
29
23
27
18
28
16
31
24
21
15
18
20
20
22
21
16
Not in
SDC
90
98
48
19
19
20
6
19
16
9
9
12
2
4
9
17
27
15
21
9
1,407
63.3%
35
271
41
375
469
Table 3
Table 4
Table 5
Table 6
Table 7
Further analysis on observations:
31
Table 3
Acquirer differences
This table shows our analysis of the 35 observations from the Table 3 column "Acquirer differs," where the SDC and hand-collected data sets
agree on the target being acquired and the announcement date, but report different acquirers. To determine which data set is correct, we perform a
media search, then verify the public status of the reported acquirer, and finally search for a spike in trading volume. Market capitalization is
calculated as of 30 days before the announcement, book-to-market (BTM) is calculated as the book value of equity divided by the market cap of
the firm, and announcement returns are cumulative abnormal returns over a 5-day window centered on the announcement date.
32
Table 3 (continued)
Acquirer differences
Acquirer market cap
Acquirer BTM
Announcement
period returns
handSDC
collected
Acquirer Acquirer
TG
Count
Percent
SDC
handcollected
SDC
handcollected
4
11%
1,175,327
3,349,685
1.039
0.596
0.7%
-0.7%
20.3%
11
31%
N/A
1,156,873
N/A
0.679
N/A
-0.5%
17.6%
3
9%
666,411
1,018,549
0.741
0.783
3.0%
2.7%
15.7%
18
51%
793,640
1,621,111
0.816
0.678
2.4%
0.0%
17.9%
SDC Acquirer is correct based on media
search
5
14%
667,526
3,735,875
0.552
0.553
-9.3%
3.1%
20.0%
SDC Acquirer is correct based on spike
in trading volume
1
3%
1,019,371
2,363,346
0.745
0.555
12.0%
-6.7%
2.2%
6
17%
755,488
3,507,120
0.600
0.553
-4.0%
1.5%
16.4%
10
29%
1,197,877
5,925,119
0.920
0.863
11.9%
3.8%
22.3%
1
11
3%
31%
231,566
1,059,833
626,277
5,443,406
0.593
0.873
0.476
0.828
-29.1%
6.1%
5.5%
4.0%
37.7%
23.7%
35
100%
907,689
3,145,719
0.785
0.704
2.4%
1.5%
19.7%
Hand-collected Acquirer is correct
Hand-collected Acquirer is correct based
on a media search
Hand-collected Acquirer is correct
because the SDC Acquirer was not
publicly traded around the announcement
date
Hand-collected Acquirer is correct based
on a spike in trading volume
SDC Acquirer is correct
Neither data set can be classified as in error
Hand-collected Acquirer is the SDC
Ultimate parent Acquirer
Other/Indeterminate
Total
Comparison with "Complete match" obs
1,407
5,701,842
33
0.614
-4.62%
21.9%
Table 4
Announcement date differences
This table shows our analysis of the 271 observations from the Table 2 column "Date differs," where SDC and hand-collected agree on the
acquirer but the announcement date reported differs by more than a day. We perform a media search in Lexis-Nexis and categorize observations
by reason for the discrepancy. We then calculate market capitalization, book-to-market, and announcement period returns for each type of
discrepancy. Market capitalization, book-to-market (BTM), and announcement returns are calculated as described in Table 3.
Hand-collected announcement date is correct
Acquirer market cap
handSDC
collected
Acquirer BTM
handSDC collected
Acquirer returns
handSDC collected
TG returns
handSDC collected
Count
Percent
82
30%
1,525,723
3,008,946
0.848
0.830
-2.3%
-2.2%
18.1%
10.4%
59
22%
2,248,734
2,330,724
0.675
0.688
-0.7%
-0.1%
13.7%
15.7%
SDC reports a subsequent announcement but not
the earliest announcement
27
10%
4,409,533
4,183,927
0.621
0.635
-1.7%
-1.2%
7.0%
19.4%
SDC reports an earlier announcement that
resulted in less than 100% of the target being
acquired
16
6%
1,144,603
1,078,746
0.824
0.931
-0.8%
-2.2%
18.7%
6.1%
SDC reports an announcement of negotiations
that did not result in an acquisition
11
4%
3,073,173
2,977,521
0.856
0.738
-0.9%
-6.9%
17.6%
9.5%
195
72%
2,297,091
2,806,282
0.750
-1.4%
-1.7%
15.6%
12.8%
SDC reports an announcement of a milestone in
negotiations other than a mutual agreement
between firms
A supporting media announcement cannot be
identified for SDC, but can be identified for
hand-collected
Comparison with "Complete match" observations
1,407
5,701,842
34
0.763
0.614
-4.62%
21.92%
Table 4 (continued)
Announcement date differences
SDC announcement date is correct
Acquirer market cap
handSDC
collected
Acquirer BTM
handSDC collected
Acquirer returns
handSDC collected
TG returns
handSDC collected
Count
Percent
Hand-collected reports a subsequent
announcement but not the earliest announcement
19
7%
22,626,461
19,871,371
0.662
0.747
-2.4%
-3.2%
6.3%
2.6%
Hand-collected reports media information other
than an agreement to merge
12
4%
1,477,975
4,678,856
0.683
0.566
-5.6%
-4.0%
26.7%
13.4%
Announcement date reflects a data entry error in
hand-collected
5
2%
48,146,227
27,904,591
0.235
0.487
5.1%
-6.8%
41.2%
1.8%
Hand-collected reports an announcement of
negotiations that did not result in an acquisition
(i.e., talks broke down, but were later picked up)
4
1%
70,734
2,273,835
0.419
0.819
13.7%
-4.3%
27.7%
19.7%
40
15%
17,962,799
14,558,016
0.597
0.667
-1.1%
-4.0%
19.5%
8.6%
36
13%
4,771,493
4,888,126
0.751
0.819
-2.3%
1.5%
20.0%
15.8%
271
100%
4,472,655
4,817,148
0.728
0.756
-1.4%
-1.6%
16.4%
12.5%
Indeterminate
Total
Comparison with "Complete match" observations
1,407
5,701,842
35
0.614
-4.62%
21.92%
Table 5
Both acquirers and announcement dates differ
This table shows our analysis of the 41 observations from the Table 2 column "Acquirer & date differ," where SDC and hand-collected report
different acquirers and announcement dates. Market capitalization, book-to-market (BTM), and announcement returns are calculated as described
in Table 3.
Acquirer market cap
Hand-collected is correct
Count
Percent
SDC responds to sale of subsidiary
27
66%
SDC responding to source which
cannot be verified
6
15%
SDC reports announcement of nonacquiring firm obtaining a minority
interest in target
1
2%
Indeterminate / other
2
36
5
5%
88%
12%
Total
41
100%
One data set reports the ultimate parent
while the other reports the actual
acquiring firm. SDC announces
milestone in negotiations other than an
agreement to merge.
Comparison with "Complete match"
1,407
Acquirer BTM
Announcement returns
handhandhandSDC
collected
SDC
collected
collected Acquirer Acquirer
TG
TG
handcollected
SDC
1,498,492
1,806,492
0.826
1.004
0.2%
-1.6%
-3.2%
17.0%
1,127,614
1,458,242
0.966
0.705
-2.6%
-1.5%
9.6%
14.9%
26,923,592
N/A
0.138
N/A
6.8%
N/A
2.8%
N/A
1,433,991
5,597,750
18,504,113
3,410,169
2,540,009
N/A
0.851
0.317
0.540
0.903
0.880
N/A
-0.3%
-10.5%
-4.8%
-1.4%
-4.9%
17.4%
13.4%
19.4%
-1.8%
16.6%
12.3%
1,717,572
3,304,052
0.754
0.901
-0.3%
-1.8%
13.5%
15.5%
SDC
N/A
5,701,842
36
0.614
-4.62%
21.92%
Table 6
Observations missing from the hand-collected data set
This table shows our analysis of the 375 observations from the Table 2 column "Not in hand-collected," where the target is reported as being
acquired by SDC but not in the hand-collected data set. Market capitalization, book-to-market (BTM), and announcement returns are calculated as
described in Table 3. Within the category of hand-collected data set errors below, 37 errors were made based on the delisting code provided by
CRSP being outside of scope for selection in the hand-collected data set. We formed our hand-collected data set by selecting only CRSP delistings
with the "2xx" merger and acquisition code. To determine whether these 37 acquisitions were properly recorded as mergers and acquisitions by
SDC, we performed a Lexis-Nexis media search for each acquisition. The 37 acquisitions reported here appear to be valid merger/acquisitions
based on our review of announcements.
Announcement
Returns
Acquirer
Acquirer
market cap
BTM
SDC
Hand-collected data set errors
Count Percent
SDC
SDC
Acquirer SDC TG
Hand-collected missed the acquisition
34
9%
5,096,979
0.737
1.0%
20.3%
Valid acquisition missed due to non-"2xx" CRSP delisting code
37
10%
6,377,999
0.751
0.8%
23.1%
71
19%
5,764,553
0.744
0.9%
21.6%
SDC data set errors
Acquirer was actually foreign or private
19
5%
9,018,943
0.695
0.1%
12.1%
Target was a private firm
107
29%
3,106,954
0.604
2.2%
8.2%
Acquisition is a purchase of minority interest by majority shareholder
26
7%
2,243,784
0.843
-0.6%
16.7%
Announced acquisition that was not consummated
11
3%
1,637,748
0.740
1.5%
1.5%
SDC picked up a non-acquisition announcement
13
3%
1,313,121
0.735
2.1%
-1.3%
SDC reports acquisition of liquidating/bankrupt firm
15
4%
3,547,538
0.665
-1.7%
25.3%
Acquiring entity is a joint venture between two firms; SDC reports one of
the parties as an acquirer (hand-collected only collects acquisitions with a
single, U.S. public company acquirer).
5
1%
4,343,087
0.110
-2.5%
5.4%
SDC reports a duplicate with an incorrect date
4
1%
484,531
0.970
-5.5%
NA
200
53%
3,370,474
0.659
1.0%
11.1%
37
Table 6 (continued)
Observations missing from the hand-collected data set
Announcement
returns
Neither data set can be classified as in error
Delisting date is outside of scope – not an error
Other/Indeterminate
Count Percent
74
20%
30
8%
104
28%
375
100%
Total
Comparison with "Complete match" observations
1,407
38
Acquirer
market cap
SDC
3,850,175
6,159,109
4,516,214
4,141,505
5,701,842
Acquirer
BTM
SDC
0.792
0.651
0.751
0.701
0.614
SDC
Acquirer SDC TG
3.0%
8.9%
-0.2%
8.3%
2.1%
8.7%
1.3%
14.6%
-4.6%
21.9%
Table 7
Observations missing from the SDC data set
This table shows our analysis of the 469 observations from the Table 2 column "Not in SDC," where the target is reported as being acquired by the
hand-collected data set but is not reported in SDC. Market capitalization, book-to-market (BTM), and announcement returns are calculated as
described in Table 3. Four errors represent non-acquisition events (such as corporate reorganizations, spin-offs, etc.) that the hand-collected data
set improperly reports as acquisitions. An additional four hand-collected data set errors are categorized below as “Other” and have miscellaneous
reasons why SDC could have missed them. For example, one of these is an acquisition involving an ADR (which should have been excluded
according to our data collection method). The majority of SDC errors (266 errors) represent acquisitions where the announcement occurred
between 1978 and 1984, when SDC coverage was poor. Based on our media searches, we were not able to determine why SDC missed 117
acquisitions that involved nonfinancial institutions and were outside the 1978 through 1984 poor coverage time frame.
Hand-collected data set errors
Count
Acquisition is a purchase of minority interest by majority shareholder
No acquisition announcements found in our new media search
Hand-collected data set picked up a non-acquisition announcement
Other
Percent
Acquirer
market
cap handcollected
Announcement
Acquirer
returns
BTM
handhandhandcollected collected
collected Acquirer
TG
10
6
4
4
24
2%
1%
1%
1%
5%
10,070,738
1,572,767
2,932,993
3,565,769
5,672,459
0.920
1.206
0.717
1.458
1.047
5.2%
-4.8%
-0.7%
-11.7%
-1.1%
11.1%
20.7%
13.5%
0.7%
13.3%
62
266
117
445
13%
57%
25%
95%
2,253,162
2,494,247
6,016,971
3,386,857
1.249
0.974
0.739
0.951
-9.5%
-1.8%
-2.5%
-3.1%
10.3%
17.4%
14.3%
16.4%
Total
469
100%
3,503,818
0.956
-3.0%
16.3%
Comparison with "Complete match" observations
1,407
5,701,842
0.614
-4.6%
21.9%
SDC data set errors
Valid acquisition per announcement involving a financial institution
Valid acquisition per announcement from 1978-1984
Nonfinancial institution, post-1984 announcement
39
Table 8
Regressions, SDC vs. SDC-corrected data sets
This table shows the regression results where AQ_Returns are regressed on the independent variables
shown below plus YEAR and INDUSTRY dummies (not shown to save space). P-values shown are
adjusted for heteroskedasticity. Panel A shows results when using SDC data without corrections and
Panel B shows the results when using SDC data corrected with hand-collected data where appropriate
(i.e., when SDC was determined to be in error). Panel C (Panel D) reports results when the model is fit to
SDC (Corrected) acquirers that are both below the median in market cap (“small”) and above the median
in BTM (“value”). Panel E (Panel F) shows the resulting coefficients and p-values when using an SDC
(Corrected) sample of only small, value acquirers prior to 1989. Comparisons can be made between Panel
A and B, C and D, or E and F to assess the impact of the SDC bias, with the results in panels C and E
being most vulnerable to the bias.
Intercept
BTM
SMALL_AQ
STOCK
DIVERSE
Adj. R2
Panel A: SDC (N=2,117)
Coefficient
0.008
p-value
0.687
24.332
0.020
0.039
<0.001
-0.023
<0.001
-0.006
0.272
0.1391
Panel B: Corrected (N=2,348)
Coefficient
-0.147
p-value
<0.001
8.041
0.025
0.055
<0.001
-0.022
<0.001
-0.003
0.528
0.1209
0.037
<0.001
-0.026
0.017
-0.025
0.074
0.1284
Panel D: Corrected small, value acquirers (N=660)
Coefficient
0.011
3.487
0.065
p-value
0.604
0.264
<0.001
-0.008
0.426
-0.018
0.139
0.1431
Panel E: SDC small, value acquirers prior to 1989 (N=376)
Coefficient
0.158
30.777
0.048
p-value
<0.001
0.153
<0.001
-0.005
0.714
-0.011
0.338
0.1851
-0.01
0.466
-0.004
0.665
0.1588
Panel C: SDC small, value acquirers (N=597)
Coefficient
0.079
28.605
p-value
0.289
0.129
Panel F: Corrected small, value acquirers prior to 1989 (N=478)
Coefficient
-0.019
4.153
0.063
p-value
0.489
0.178
<0.001
Variables Defined:
AQ_Returns: cumulative abnormal returns over a 5-day window centered on the announcement date
BTM: the acquirer’s book value of equity divided by the market cap of the firm
SMALL_AQ: equals 1 if the acquirer is below the 25th percentile of NYSE firms based on market cap in
the year prior to the announcement
STOCK: equals 1 when transactions are paid for in 100% stock
DIVERSE: equals 1 when target and acquirer two-digit SIC codes are unequal
40
41