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คณะพาณชยศาสตรและการบัญช มหาวทยาลัยธรรมศาสตร

ปท 34 ฉบับท 130 เมษายน-มถนายน 2554

59

Understanding the Event Study

Dr.Thitima Sitthipongpanich Assistant Professor of Department of Finance,

Faculty of Business Administration,Dhurakij Pundit University

บทคัดยอารศกษาเหตการณ (Event Study) เปนวธวจัยท ใชอยางกวางขวางสหรับงานวจัยทางดานบรหารธรกจ การดเนนงานวจัยดวยการศกษา

เหตการณมสวนเก ยวของถ งการระบเหตการณท สนใจ การประมาณการณผลตอบแทนสวนเกน และการทดสอบความมนัยสคัญของเหตการณ บทความน จะบรรยายถงการใชวธวจัยการศกษาเหตการณ ขั นตอนการทว จัยดวยวธการศกษาเหตการณ และความแตกตางของการใชวธวจัยดังกลาว

vent studies are widely used in businessresearch. Conducting an event studyinvolves identifying an event of interest,

estimating abnormal stock returns relatingto the event and then testing the significance of theevent. This paper describes the application of eventstudy methodology, and reviews the practice andvariations of the method.

ABSTRACT

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วารสารบรหารธรก จ60


INTRODUCTION An event study is an empirical analysis that

is normally used to measure the effect of an event onstock prices (returns). Although the majority ofprevious literature investigates stock prices, severalstudies examine stock trading volume, or returnvolatility. The event study is of importance because itcan be used to evaluate the impact of companypolicies on firm value. The empirically conductedstudy is based on the following assumptions.

• Under the market efficiency hypothesis, the

impact of an event will be instantly reflected in stockprices. Therefore, the market reaction to the eventcan be measured by stock returns over the studytime period.

• The event is unforeseen . Abnorma l(excess) stock returns indicate the market reaction tothe unanticipated event.

• During the event window, there are noconfounding effects, meaning that the effect of otherevents is isolated.

This paper discusses the purposes of anevent study and provides examples of previous eventstudies. The discussion includes an explanation ofthe applications and procedures in conducting such astudy. The last part of the paper describes thelimitations of the event study method.

PURPOSES AND EXAMPLES OF

EVENTS An event study is commonly developed to

attempt to measure whether an unanticipated eventcould have an effect on stock prices and thedirection and magnitude any perceived effects mighthave on those stock prices. The event study method

is applied in different research areas, such asaccounting and finance, management, marketing,

information technology, law and economics. Earlyliterature on event studies are include an investigationof the impact of annual earnings announcement on

stock prices (Ball and Brown, 1968) and a study ofthe announcement of stock splits on stock returns(Fama et al., 1969).

Ball and Brown (1968) concluded that annualaccounting income data contains information that isrelated to stock prices. They found that incomeforecast errors, which are measured by the differencebetween announced and exp ected accounting

earnings, have a positive impact on the abnormalperformance index around the annual reportannouncement date.

Fama et al (1969) also note that stock pricesappear to adjust to new information. Stock splitsgenerally occur following periods when stock pricessignificantly increase relative to the market. Theyfound that, after a split announcement, stock prices

seem to quickly reflect all available information anddo not generate any abnormal returns. The resultsdemonstrate the efficiency of the capital market.

In th is paper , examples of events areprovided, including firm-specific events and economy-wide events. The firm-specific events mainly involve achange in or a new implementation of companypolicy. Examples of firm-specific events used in

previous event studies are as follows.• The announcement and completion of a

takeover bid/divestiture (Agrawal and Mandelker,1990; Lys and Vincent, 1995; Gregory, 1997; Bruner,1999)

• Initial public offering (Ritter, 1991; Loughranand Ritter, 1995; Espenlaub et al., 2001)

• Seasoned equity offering (Loughran andRitter, 1995; Carlson et al., 2006)

• Earning management practices before IPOand SEO (Teoh et al., 1998a; Teoh et al., 1998b)

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61

• Obtaining new bank loans or loan renewal(Lummer and McConnell, 1989)

• Selecting an auditor and its reputation

(Weber et al., 2008)• An appointm ent of a new CEO wi th

financial expertise (Defond et al., 2005)• Top executive changes (Bonnier and

Bruner, 1989; Dahya et al., 1998)• Sudden CEO vacancy (Lambertides, 2009)• Compensation plan policy (DeFusco et al.,

1990; Yermack, 1997; Yeo et al., 1999)• An internet name change (Mase, 2009)

• An advertising campaign (Kim and Morris,2003; Choong et al., 2007)

• Football results of listed European clubs(Benkraiem et al., 2009)

• IT investments (Roztocki and Weistroffer,2009)

• Enterprise resource planning system (ERP)implementation (Benco and Prather, 2008)

Economy-wide events are often used in largesample event studies, which examine the effect of aparticular event on relevant firms. The followingstudies are examples of economy-wide events.

• A new item of legislature (Schipper andThompson, 1983; Schumann, 1988)

• Sarbanes Oxley Act (Small et al., 2007)• A financial crisis (Baek et al., 2004)• The “9/11” terrorist attack in New York

(Homan, 2006)

RESEARCH DES IGN AND

PROCEDURES OF AN EVENT

STUDY Event studies can be designed in different

ways to reflect specific purposes and researchquestions. The event study can be used in both

clinical studies and large sample studies. A clinicalstudy investigates the effect of an event on stockprices of a single company, such as an analysis of

the market reaction to a takeover announcement;where the study focuses on the acquiring firm and/oron the target firm (Lys and Vincent, 1995; Bruner,1999). Large sample studies examine the impact ofan event on prices of different sample stocks.Examples of this type of event study include theeffect of company policy implementation in a largesample of listed firms, such as a stock split, a topmanagement compensation policy, or a director

appointment policy (Fama et al., 1969; Yermack,1997; Defond et al., 2005).

In addition to the effect of an event on stockreturns, researchers have examined the impact of anevent on stock volatility (DeFusco et al., 1990; Engleand Ng, 1993; Jayaraman and Shastri, 1993), onstock trading volume (Benkraiem et al . , 2009;Karafiath, 2009), or on accounting performance

(Barber and Lyon, 1996). Furthermore, not onlycompany stocks, but also other types of securitiescan be considered in the event study. Prior researchusing event studies has analyzed effects on companybonds , whe r e abno rma l bond r e tu r n s c andemon s t r a t e t h e ma r k e t impa c t o f e v e n tannouncements (Gugler et al., 2004; Asquith andWizman, 1990; DeFusco et al., 1990; Steiner andHeinke, 2001).

When designing an event study, the length ofthe event periods and the expected availability ofdata will be considered in determining the returnfrequency. Choices of return frequency can be daily,weekly, monthly, or annually. Daily and monthlyreturns are commonly found in previous literature.Daily data is often used for short-term event studies(Lummer and McConnell, 1989; Small et al., 2007),

whilst monthly data is normally chosen for long-termstudies (Ritter, 1991; Teoh et al., 1998b).

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63

The expected return, , is used as thebenchmark return in the normal situation to comparewith the actual return during the event window(s).The benchmark return represents the return that isnot related to the event of interest. There are choicesof model to estimate expected returns.

3.1) Mean-adjusted return

The mean return is the average return overthe estimation period. Each stock can use theaverage return during the estimation period as its

own expected return (Brown and Warner, 1985;Lambertides, 2009).

3.2) Market-adjusted return

The expected return is t he market returnat the same period of time, assuming that all

stocks, on average, generate the same rate of return(Ritter, 1991; Bruner, 1999; Teoh et al., 1998b; Weber

et al., 2008). Using the market-adjusted return methoddoes not require an estimation period.

3.3) Market-model-adjusted return

The expected return is computed based on asingle factor market model. The parameters of themarket model, i.e. and , are estimated usingOrdinary Least Square (OLS) regression over the

estimation period. This method is used to control therelation between stock returns and market returns, orallows for the variation in risk associated with aselected stock. The market-model-adjusted return iscommonly found as an expected return in previousevent studies (Bonnier and Bruner, 1989; Lummer andMcConnell, 1989; Schipper and Thompson, 1983;Homan, 2006; Small et al., 2007).

3.4) CAPM-adjusted return

Using the Capital Asset Pricing Model(CAPM), the expected return is the outcome of therisk-free rate return plus market risk premium(Espenlaub et al., 2001). of the model measuresthe risk of stock (i), assuming that an investo rrequires higher return to compensate for higher risk.

3.5) Reference portfoliosThe expected return in this method is the

return of the reference portfol io. The portfol io

comprises stocks based on the criteria of size, thebook-to-market ratio, or both size and the book-to-market ratio. To calculate this benchmark expectedreturn , the est imation per iod is not required.Researchers generally rank all firms into differentgroups by a particular characteristic; for example, intoten size-different groups. Then an average return fora l l stocks in each group is ca lculated as theexpected return of a reference portfolio. Examples of

event studies using this method are Ritter (1991) andBarber & Lyon (1997)1.

3.6) Matched firm approachSimilar to the reference portfolio method, the

expected return is assumed to be the same as thereturn of matched stocks during the test period. Thematching process will be done on the basis ofrelevant risk characteristics and the matched stocks

not being exposed to the event of interest. Thecommon matching characteristics are size (i.e. equitymarket value), the book-to-market ratio, and thecombinat ion of both . For example , using sizecharacteristics, the abnormal return of an event stockis the difference between its actual return and theportfolio return of matched stocks in the same rangeof equity market value (Ritter, 1991; Loughran and

1Reference portfolio: by size (Ritter, 1991; Barber & Lyon, 1997), by book-to-market ratio (Barber & Lyon, 1997), by size and book-to-market ratio (Barber & Lyon, 1997).

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Ritter, 1995; Barber and Lyon, 1997). Several authorshave reported the use of combined size and book-to-market matching (Barber and Lyon, 1997; Teoh et al.,1998a; Hertzel et al., 2002; Carlson et al., 2006).

3.7) Fama-French three factor model

This method is an extension of the CAPM-adjusted return, combining more risk factors, i.e. amarket excess return factor, a factor forsize (small minus big, SMB) and a factor for book-to-market-equity ratio (high minus low, HML) (Fama and

French, 1993). SMB is t he difference betweenaverage returns of small stock portfolios and those ofbig stock portfolios. HML is the difference in averagereturns between high and low book-to-market stockportfolios. This method uses monthly returns over along period of time. It can be implemented as in theCAPM and is widely used in previous work (Barberand Lyon, 1997; Loughran and Ritter, 1995; Teoh etal., 1998b; Hertzel et al., 2002; Dutta and Jog, 2009).

Step 4. Computing abnormal (or excess)returns.

An abnormal return for an individual stock isthe difference between the actual return on time (t) inthe event window and the expected return of anindividual stock.

To calculate the cumulative abnormal return(CAR) for an individual stock, the abnormal return ofeach stock is aggregated over the event window(-T

2 to T

3).

The buy-and-hold abnormal return (BHAR)for an individual stock is the difference between thebuy-and-hold return of a sample firm and that of thebenchmark expected return, assuming that aninvestor buys a stock and holds it until the end of theevent period (Ritter, 1991;Teoh et al., 1998a; Hertzelet al., 2002).

The average abnormal return for all sample

stocks on time (t) can be calculated as follows.

Step 5. Testing the significance of abnormal(excess) returns.

To test the significance of abnormal returns,most event studies use a parametr ic test of t-statistics (e.g. Brown and Warner, 1985; Barber and

Lyon, 1997); however, non-parametric tests, such as asign test, or a rank test (e.g. Benco and Prather,2008; Benkraiem et al., 2009), can be applied toconfirm the results2.

For an individual firm (i), whether or not theabnormal return is different from zero can be testedby t-statistics as follows.

Across firms, the fol lowing formulae giveparametr ic test stat ist ics , which are used toinvestigate if the average cumulative, or buy-and-holdabnormal returns are equal to zero.

2Parametric tests have some specific assumptions, such as normal distribution of returns; while non-parametric tests allow for anydistribution of data.

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65

LIMITATIONS OF THE EVENT

STUDY The event study is a simple research method

which allows uncomplicated interpretation of results.The method has been commonly used by researchersto examine how events can affect both gains and

losses in company value as perceived by the market.I t is a lso used to measure the market-basedperformance in terms of abnormal stock returns ins i tua t ions where researchers ant ic ipa te tha tinaccuracies in financial statements may give aninaccurate measure of company performance. Although the event study methodology is useful inseveral ways, there are some major limitations.

First of all, the assumptions used in events tudy me thodo logy a r e no t va l i d i n somecircumstances. Due to market inefficiency observedstock prices may not fully and immediately reflect allinformation. Furthermore, events might be anticipatedin some situations, whilst unforeseen coexistingevents could also have an effect on the samplestocks, which could lead to biased stock returns.Therefore, abnormal returns are not entirely the resultof market reaction to the specific event of interest.

Secondly, variations in estimation and testperiods are commonly found in event studies. Preciseestimation periods are not easy to determine. Thelength of the estimation period is subject to atradeoff between improved estimation accuracy andpotential parameter shifts. Moreover, the estimationperiod is difficult to control for other confoundingeffects if researchers select long test periods, or long

event windows.

Thirdly, the choice of model to estimateexpected returns will have a bearing on the results inthe magnitude and the significance of abnormalreturns. For example, using the average returnmethod is simple, b ut it produces upwardly, ordownwardly biased abnormal returns in bull and bearmarkets, respectively. Ritter (1991) also documentsthat using different market i ndices to calculatemarket-adjusted returns can show differences in long-term performance results. More importantly, if theexpected return is incorrectly estimated, other factorsthat are not properly controlled could lead to biased

information in the event study results.

Fourthly, not all stocks trade every day. Thintrading over the estimation and test period is aproblem in event studies. For example, stock andmarket returns might not be available on the selecteddays throughout the estimation period if researchersapply the market model or Fama-French three factormodel.

Fifthly, calendar time clustering of events is aproblem of cross-sectional dependence if testper iods, or event dates of sample stocks areclustered in the same calendar time period (Brownand Warner, 1980). When the test periods of thosestocks overlap in calendar time, the problem ofcross-correlation in abnormal returns could exist.However, in traditional large sample studies, the event

of interest is assumed to be isolated from othereffects . Calendar t ime is not expected to b eproblematic because the effects of other events aresupposed to be cancelled out across the largesample of firms.

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Bibliography

AGRAWAL, A. & MANDELKER, G.

N . ( 1 9 9 0 ) L a r g eShareholders and theMonitoring of Managers:The Case of AntitakeoverCharter Amendments.Journal of Financial &Quantitative Analysis , 25,143-161.

ASQUITH, P. & WIZMAN , T. A.( 1 9 9 0 ) E v e n t r i s k ,c o v e n a n t s , a n dbondholder returns inl e v e r a g e d b u y o u t s .Jou r na l o f F i n anc i a lEconomics , 27, 195-213.

BAEK, J. S., KANG, J. K. & SUH

P A R K , K . ( 2 0 0 4 )Corporate governanceand firm value: evidencefrom the Korean financialcrisis. Journal of FinancialEconomics , 71, 265-313.

BALL, R. & BROWN, P. (1968) AnEmpirical Evaluation of

A c c o u n t i n g I n c omeNumbers . Journa l o fAccounting Research , 6,159-178

BARBER, B. M. & LYON, J. D.( 1 9 9 6 ) D e t e c t i n ga bno rma l ope r a t i n gp e r f o r m a n c e : T h e

empi r ica l power andspec i f i ca t ion o f tes t

s ta t i s t i c s . Journa l o fFinancial Economics , 41,359-399.

BARBER, B. M. & LYON, J. D.(1997) Detecting long-runabnormal stock returns:The empirical power andspec i f i ca t ion o f tes ts ta t i s t i c s . Journa l o f

Financial Economics , 43,341-372.

BENCO, D. & PRATHER, L. (2008)Ma r k e t R e a c t i o n t o

Announcements to Investi n E R P S y s t e m s .Quar te r l y Jou rna l o fFinance and Accounting ,

47, 145-169.

BENKRAIEM, R., LOUHICHI, W. &MARQUES, P . (2009)Ma r k e t r e a c t i o n t os p o r t i n g r e s u l t s .Management Decision ,47, 100-109.

BONNIER, K.-A. & BRUNER, R. F.(1989) An analysis ofstock price reaction tomanagement change indistressed firms. Journalo f A c c o u n t i n g a n dEconomics , 11, 95-106.

BROWN, S. J. & WARNER, J. B.

(1980) Measuring securityp r i c e p e r f o rm a n c e .

Jou r na l o f F i n anc i a lEconomics , 8, 205-258.

BROWN, S. J. & WARNER, J. B.(1985) Using daily stockre turns : The Case ofEvent Studies. Journal ofFinancial Economics , 14,3-31.

BRUNER, R. F. (1999) An analysisof value destruction andrecovery in the allianceand proposed merger ofV o l v o a n d R e n a u l t .Jou r na l o f F i n anc i a lEconomics , 51, 125-166.

CARLSON, M. , FISHER, A. &

GIAMMARINO, R. O. N.( 2 0 0 6 ) C o r p o r a t eInvestment and AssetP r i c e D y n a m i c s :Impl ica t ions for SEOEvent Studies and Long-

Run Performance. Journalof Finance , 61, 1009-

1034.

CHOONG, P. , FILBECK, G. &TOMPKINS, D. (2007)

Advertising Strategy andReturns on Advertising: AMarket Value Approach.The Business Review ,Cambridge, 8, 17-23.

DAHYA , J . , LON IE , A . A . &

POWER, D. M. (1998)Ownership Structure ,

Do

w

n

l

o

ad

จ

า

ก

วา

ร

ส

า

ร

บร

ห

า

ร

ธ

รก

จ


9/10



67

Firm Performance andTop Executive Change:

An Analysis of UK Firms.Jou r na l o f Bus i ne s sFinance & Accounting ,25, 1089-1118.

DEFOND, M. L., HANN, R. N. &HU, X. (2005) Does theMarket Value FinancialE x p e r t i s e o n A u d i tCommittees of Boards of

Directors? Journal ofAccounting Research , 43,153-193.

DEFUSCO, R. A., JOHNSON, R. R.& ZORN, T. S. (1990) TheEffect of Executive StockO p t i o n P l a n s o nS t o c k h o l d e r s a n d

Bondholders. Journal ofFinance , 45, 617-627.

DUTTA, S. & JOG, V. (2009) Thelong-term performance ofacquir ing f i rms: A re-

e x a m i n a t i o n o f a nanoma l y . Jou rna l o fBanking & Finance , 33,

1400-1412.

ENGLE, R. F. & NG, V. K. (1993)Measuring and Testingthe Impact of News onVo la t i l i t y . Journa l o fFinance , 48, 1749-1778.

ESPENLAUB, S., GOERGEN, M. &

KHURSHED, A. (2001)IPO Lock-in Agreements

in the UK. Journal ofBus i ne s s F i n ance &Accounting , 28, 1235-

1278.

FAMA, E. F., FISHER, L., JENSEN,M. C. & ROLL, R. (1969)The Adjustment of StockP r i c e s t o N e w

Information. InternationalEconomic Review , 10, 1-

21.

FAMA, E. F. & FRENCH, K. R.( 1993 ) Com mon r i skfactors in the returns ons t o c k s a n d b o n d s .Jou r na l o f F i n anc i a lEconomics , 33, 3-56.

G R E G O R Y , A . ( 1 9 9 7 ) A n

Examination of the LongRun Performance of UK Acquir ing Firms. Journalof Business Finance &Accounting , 24, 971-1002.

GUGLER, K., MUELLER, D. C. &YURTOGLU, B. B. (2004)Marginal q, Tobin’s q,

C a s h F l o w , a n dInvestment . SouthernEconomic Journal , 70,512-531.

HERTZEL , M. , LEMM ON, M. ,LINCK, J. S. & REES, L.( 2 0 0 2 ) L o n g - R u nPerformance following

Private Placements ofE q u i t y . J o u r n a l o f

Finance , 57, 2595-2617.

HOMAN, A. C. (2006) The Impactof 9/11 on Financial Risk,Volatility and Returns ofMarine Firms. MaritimeEconomics & Logistics , 8,387-401.

JAYARAMAN, N. & SHASTRI, K.(1993) The effects of thea n n o u n c e m e n t s o f

dividend increases onstock return volatility: thee v i d e n c e f r om t h eoptions market. Journalof Business Finance &Accounting , 20, 673-685.

KARAFIATH, I. (2009) Detectingcumula t ive abnorma l

volume: a comparison ofevent study methods.App l i e d E c o n om i c sLetters , 16, 797-802.

KIM, J. & MORRIS, J. D. (2003)The effect of advertisingon the market value offirms: Empirical evidence

from the Super Bowl ads.Journa l o f Targe t ing ,M e a s u r e m e n t a n dAnalysis for Marketing ,12, 53-65.

LAMBERTIDES, N. (2009) SuddenCEO vacancy and thel o n g - r u n e c o n om i c

c o n s e q u e n c e s .Managerial Finance , 35,

Do

w

n

l

o

ad

จ

า

ก

วา

ร

ส

า

ร

บร

ห

า

ร

ธ

รก

จ


10/10



645-661.

LOUGHRAN, T. & RITTER, J. R.(1995) The New IssuesP u z z l e . J o u r n a l o fFinance , 50, 23-51.

LUMMER, S. L. & MCCONNELL,J . J . ( 1989 ) Fu r t h e rEvidence on the BankLending Process and theCapital-Market Response

t o B a n k L o a n Agreements . Journal ofFinancial Economics , 25,99-122.

LYS, T. & VINCENT, L. (1995) Ana n a l y s i s o f v a l u edestruction in AT&T’sacqu i s i t i on o f NCR .

Jou r na l o f F i n anc i a lEconomics , 39, 353-378.

MASE, B. (2009) The impact ofn a m e c h a n g e s o nc o m p a n y v a l u e .Managerial Finance , 35,316-324.

RITTER, J. R. (1991) The Long- Run Pe r fo r mance o f

Initial Public Offerings.J o u r n a l o f F i n a n c e ,46, 3-27.

ROZTOCKI, N. & WEISTROFFER,H. (2009) InformationTechnology Investments:Does Ac t i v i t y Based

Cost ing matte r? TheJourna l o f Compute r

Information Systems , 50,31-41.

SCHIPPER, K. & THOMPSON, R.E. X. (1983) The Impacto f M e r g e r - R e l a t e dRegu l a t i o n s o n t h eShareholders of AcquiringF i r m s . J o u r n a l o fAccounting Research , 21,184-221.

SCHUMANN, L . (1988) StateRegulation of Takeoversand Shareholder Wealth:The Case of New York’s1985 Takeover Statutes.The Rand Journa l o fEconomics , 19, 557-567.

SMALL, K., IONICI, O. & ZHU, H.

(2007) Size Does Matter: An Exam ina tio n of theEconomic Impac t o fSarbanes-Oxley. Reviewof Business , 27, 47-55.

STEINER, M. & HEINKE, V. G.( 2 0 0 1 ) E v e n t s t u d yconcerning international

bond pr ice effects ofcredit rat ing act ions.International Journal ofFinance & Economics , 6,139-157.

TEOH, S. H., WELCH, I. & WONG,T. J. (1998a) Earningsmanagement and the

l o n g - r u n m a r k e tperformance of in i t ia l

public offerings. Journalof Finance , 53, 1935-

1974.

TEOH, S. H., WELCH, I. & WONG,T. J. (1998b) Earningsmanagement and theunderper formance ofs e a s o n e d e q u i t yo f fe r i ngs . Journa l o fFinancial Economics , 50,63-99.

WEBER, J., WILLENBORG, M. &ZHANG, J. (2008) Does A u d i t o r R e p u t a t i o nMatte r? Th e Case ofKPMG Germany andComROAD AG. Journalof Accounting Research ,46, 941-972.

YEO, G. H. H., CHEN, S., HO, K.W . & LEE , C . ( 1999 )E f fec ts o f execu t i veshare option plans onshareholder wealth andfirm performance: TheSingapore evidence. TheFinancial Review , 34, 1-

20.

YERMACK , D . ( 1997 ) GoodT im i n g : CEO S t o c kOp t i o n Awa r d s a ndC o m p a n y N e w s

Announcements. Journalof Finance , 52, 449-476.

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