Is the Event Study Methodology Useful for Merger Analysis? A Comparison of Stock Market and Accounting Data

Transcription

1 Discussio Paper No. 163 Is the Evet Study Methodology Useful for Merger Aalysis? A Compariso of Stock Market ad Accoutig Data Tomaso Duso* laus Gugler** Burci Yurtoglu*** September 2006 *Tomaso Duso Humboldt Uiversy Berli ad WZB duso@wz-berli.de **laus Gugler Uiversy of Viea klaus.gugler@uivie.ac.at ***Burci Yurtoglu Uiversy of Viea burci.yurtoglu@uivie.ac.at Fiacial support from the Deutsche Forschugsgemeischaft through SFB/TR 15 is gratefully ackowledged. Soderforschugsbereich/Trasregio 15 Uiversät Maheim Freie Uiversät Berli Humboldt-Uiversät zu Berli Ludwig-Maximilias-Uiversät Müche Rheiische Friedrich-Wilhelms-Uiversät Bo Zetrum für Europäische Wirtschaftsforschug Maheim Speaker: Prof. orad Stahl Ph.D. Departmet of Ecoomics Uiversy of Maheim D Maheim Phoe: +49(0621) Fax: +49(0621)

2 Is the Evet Study Methodology Useful for Merger Aalysis? A Compariso of Stock Market ad Accoutig Data Tomaso Duso Humboldt Uiversy Berli ad WZB duso@wz-berli.de laus Gugler Uiversy of Viea klaus.gugler@uivie.ac.at Burci Yurtoglu Uiversy of Viea burci.yurtoglu@uivie.ac.at September Abstract Usig a sample of 167 mergers durig the period ivolvig 544 firms eher as mergig firms or competors we cotrast a measure of the merger s profabily based o evet studies wh oe based o accoutig data. We fid posive ad sigificat correlatios betwee them whe usig a log widow aroud the aoucemet date ad for rivals i case of aticompetive mergers. eywords: Mergers Merger Cotrol Evet Studies Ex-post Evaluatio JEL Codes: L4 21 G34 Ackowledgmets: T Duso gratefully ackowledges fiacial support from the Deutsche Forschugsgemeischaft through SFB/TR 15.. Gugler ad B. B. Yurtoglu ackowledge fiacial support from the OeNB through project Correspodig author: Tomaso Duso Social Sciece Research Ceter Berli (WZB) Reichpietschufer 50 D Berli Germay. Tel: Fax: duso@wz-berli.de.

3 1. Itroductio The assessmet of the competive s of large mergers is oe of the most importat tasks for atrust authories worldwide. Ufortuately these s are ot observed at the time whe the authory must make s decisio to allow or block the merger or let the merger through wh remedies. I priciple stock markets could help predictig the future profabily sice they are forward lookig. However may ecoomists i particular idustrial orgaizatio ecoomists are skeptical about the markets abily to correctly aticipate mergers competive s. Thus the pioeerig efforts of Eckbo (1983) have ot bee widely applied i merger aalysis. This paper tries to close the gap betwee the fiace ad idustrial orgaizatio leratures by estimatig (1) (ex ate) aoucemet s of mergers o both mergig ad rival firms (2) (ex post) balace sheet prof s of these mergers o mergig ad rival firms up to five years postmergers ad (3) comparig these estimates by correlatio aalysis. 2. Measurig Profabily 2.1. Evet Studies Uder the assumptios of efficiet markets ad ratioal expectatios the market model predicts that firm i s stock retur at time t ( R ) is proportioal to a market retur ( R = α + β + ε ). We R mt estimate the market model over 240 tradig days startig 50 days prior to the aoucemet day. We use the estimated values for the model s parameters to predict what firm i s stock price would have bee had the merger ot bee aouced ( Rˆ ). For firm i we the calculate the abormal retur aroud the mergers aoucemet day t (AR it ) as: AR = R Rˆ = R ( ˆ α + ˆ βr ). The cumulative abormal retur (CAR) over a evet widow (m) is the defied to be: CAR τ = = AR. We calculate these measures for each of the mergig rival firms. 1 im i τ τ = m mt 2.2. Ex-post Profabily We use the methodology of Gugler et al. (2003) to predict the merger s ex post prof s. The method compares reported prof levels post merger wh predicted prof levels i the absece of the merger. Our couterfactual is the developmet of profs ad total assets of the media firm (i terms of profabily) i the same 3-dig idustry as the mergig firms or their rivals operate. We used a umber of other couterfactuals such as similar size or geographical regios but oe chaged our results sigificatly. 1 See Duso Gugler ad Yurtoglu (2006) for a descriptio of the lerature the data ad a more complete descriptio of the methodology. 1

4 IG t 1 t+ The projected chage i the returs o the acquirer s assets from year t-1 to t+ are defied as: Π = IGt+ IGt+ Π IGt 1 IGt 1 where Π IGt+ are the media firm s (icome statemet) profs ad IDt+ are the media firm s assets both i the same 3-dig idustry of the acquired compay i year t+. We defie ID tt+ for the acquired firm s idustry aalogously to IG t-1t+. The predicted profs of the combied compay M i year t+ is the: Π predicted Mt+ = Π + + Π + IG t + ID t Gt 1 + G t 1 IGt 1 t+ Dt D t IDt t+ IG t 1 ID t where Π Gt+ (Π Dt ) are the profs ad Gt+ ( Dt ) are the assets of the acquirig (acquired) compay i year t+ (t). The same logic ca be applied to the rivals. I fact atrust markets are differet tha idustries based o the SIC classificatio. The advatage of our database is that we have iformatio o the mergig firms ive rivals i the ivolved product markets. These firms are ot a good couterfactual sice they are iflueced by the merger just as much as the mergig firms are. However the merger should ot strogly affect the rest of the idustry which makes the 3-dig SIC classificatio a good couterfactual for the merger oce we exclude the mergig ad rivals firms. We ca hece get a measure of the projected chage i the returs ad of the predicted prof for the rivals i absece of the merger which is somethig ovel i the lerature. Our measure of firm i's merger (i=mergig ety or rivals) is the the differece betwee actual (observed) profs i year t+ ad the predicted profs: + = actual predicted The Data ad Correlatios Our sample cosists of 167 cocetratios that were aalyzed by the Europea Commissio (EC) durig the period We idetify 544 differet firms eher as mergig or as rival firms. The relevat markets ad thus rivals are defied i the EC reports. Table 1 reports the media values for the CARs based o differet evet widows ad the profabily s ( + ) for mergig firms ad rivals up to five years after the merger. I the full sample all media values (wh the possible exceptio for CAR (22) for rivals which is close to zero) have the same sig. Table 2 reports pairwise correlatios amog CARs ad profabily s. For mergig firms the correlatio coefficiets betwee CAR (50 5) ad firms prof are always posive ad mostly sigificat. The prof s four years after the merger seem to be very well captured by all 2 Our sample icludes almost all phase II mergers completed by the EU by the ed of 2001 ad a radomly matched sample of phase I cases which ru up to Jue See Duso Neve ad Röller (2006). 2

5 measures of abormal returs. However CARs based o log widows seem to perform better. The picture is differet for rivals: CARs based o short widows produce very misleadig results sice they are egatively ad sigificatly correlated to the real prof s. However for rivals the CARs based o log widows (30 or 55 days) also seem to capture very well the log term merger s prof s. Table 3 spls the sample o pro ad aticompetive mergers. 3 Iterestigly the market correctly aticipates ati-competive mergers whe usig log pre-aoucemet periods (25 to 50 days) as wessed by the large ad sigificat correlatio coefficiets for rivals up to five years post merger. Also the market predicts mergig firms rets stemmig from icreased efficiecies (procompetive mergers) more precisely tha those stemmig from a icrease i market power (aticompetive mergers). 4. Coclusios This paper establishes empirical evidece that the evet study methodology is useful for the competive aalysis of mergers. I particular for a large sample of EU mergers durig the period we show that abormal returs ad ex post profabily of mergers are posively ad sigificatly correlated. This is particularly true whe usig log evet widows ad for rivals i ati-competive mergers. Refereces Duso T. D. Neve ad L.-H. Röller (2006) The polical ecoomy of Europea Merger Cotrol The Joural of Law ad Ecoomics forthcomig. Duso T.. Gugler ad B. Yurtoglu (2006) EU merger remedies: A empirical assessmet i J. Steek ad V. Goshal Eds. The Polical Ecoomy of Atrust North Hollad forthcomig. Eckbo B. E. (1983) Horizotal mergers collusio ad stockholder wealth Joural of Fiacial Ecoomics Gugler. D.C. Mueller B. B. Yurtoglu ad C. Zuleher (2003) The s of mergers: A eratioal compariso Iteratioal Joural of Idustrial Orgaizatio The argumet follows Eckbo (1983). We defie a merger to be aticompetive if the aggregated CAR of rivals (i.e. the weighted sum of the CARs of all rivals for each merger) i the (255) widow is posive. See Duso Neve ad Röller (2006) for a formal derivatio of the correspodece betwee icrease i rivals prof ad decrease i cosumers surplus. 3

6 Table 1: Prelimiary Statistics CAR(22) CAR(255) CAR(505) M t+ 1 MERGING FIRMS M t+ 2 M t+ 3 M t+ 4 M t+ 5 Media Obs RIVALS CAR(22) CAR(255) CAR(505) Media Obs Notes: All values are expressed i Millio US$. The CAR(m) variables represet the cumulative abormal returs over the widow spaig from m days before the evet to days after the evet. The variables represet the aggregated prof + chage from oe year before the merger to years after the merger if compared to the media firm i the same SIC3 idustry. Table 2: Pairwise Correlatios: all mergers MERGING FIRMS RIVALS CAR(11) CAR(22) CAR(55) CAR(255) CAR(505) CAR(11) CAR(22) CAR(55) CAR(255) CAR(505) ** *** ** *** ** *** *** ** *** *** *** *** ** ** ** ** *** ** *** ** Notes: We report pairwise correlatio coefficiets (first row) as well as p-values (secod row).*** ** * represet sigificace at the 1% 5% ad 10% level respectively. 4

7 Table 3: Pairwise Correlatios: Mergers spl o pro- ad ati-competive MERGING FIRMS PROCOMPETITIVE ANTICOMPETITIVE CAR(11) CAR(22) CAR(55) CAR(255) CAR(505) CAR(11) CAR(22) CAR(55) CAR(255) CAR(505) ** * *** *** * * *** ** ** RIVALS PROCOMPETITIVE ANTICOMPETITIVE CAR(11) CAR(22) CAR(55) CAR(255) CAR(505) CAR(11) CAR(22) CAR(55) CAR(255) CAR(505) *** *** * ** ** *** ** *** *** *** *** *** *** *** ** ** * ** *** *** *** *** *** *** ** Notes: We report pairwise correlatio coefficiets (first row) as well as p-values (secod row).*** ** * represet sigificace at the 1% 5% ad 10% level respectively. A merger is defied to be aticompetive (procompetive) if the aggregated cumulative abormal returs of the rivals - CAR(255) - are posive (egative). The sample icludes all observatios for which the variable was ot missig