CAAR T-Test

[George Bonje]

Dear readers,

Recently i've been working on an Event study, however i ran into a slight problem. I've been able to calculate the T-test for the abnormal returns (in excel), however i was wondering if it was possible for stata to calculate the t-statistic (p-value or t-value) for the CAR's and for the CAAR (Cum. Average abnormal return).

I've added the excel spreadsheet, It includes the CAR of different firms on different event dates (no overlapping windows) and the CAAR.
The dataset contains 96 event dates of approximately 40 different firms.

Thank you in advance for your time to read my question,

George

[Carlo Lazzaro]

George:
please see the FAQ on posting what you typed and what Stata geve you back and/or presenting an excerpt/example of your dataset via -dataex- (type -search dataex- from within Stata to install it). Thanks.

[George Bonje]

Dear Carlo,

Thanks for the advice, i had read through the FAQ however i seemed to have overlooked a thing or two, My apologies.

The following code is a sample of the 96 observations in my event study, it contains 5 event dates named: A B C D E.

The Stata commands used to obtain the CAAR:

egen row_total = rowtotal ( A B C D E)
generate CAAR = row_total/5
reg CAAR if diff==0, robust

The result i obtain:

reg CAAR if dif==0, robust
dif not found
r(111);

I've run the code with "if dif==0" and it works and gives me a P-value, However i'm not quite sure if this is allowed as i'm not quite sure what that part of the command does.

* Example generated by -dataex-. To install: ssc install dataex
clear
input double(A B C D E) float row_total double CAAR
  .0016772089270972832  -.004696154228928164 -.0028088634023134716  -.004309027249896302     -.00843247888534052  -.018569315   -.003713862970471382
   -.00098210840375412  -.008314228899294463    .00989811422194958  -.008864236486836645    -.004358769983862722   -.01262123   -.002524245996028185
  -.002989053355109633   .003612363489093433   .013052783504671853  -.012394020733958087    -.021769678085645394  -.020487605   -.004097520839422941
  .0033666581462515155 -.0004754719083413829  .0006916117608176016  -.008243382715948378     -.03180552964529912  -.036466114   -.007293222937732935
  .0034417388084507514  .0009317347505308493  -.007196240096770583   .003294164932143479     .001781917006635221  .0022533154  .00045066309394314885
  -.000509310724117988   .006476402090207728  -.009692332246797886   .016369976590136497  .000012576300573942725   .012657313   .0025314625818282366
  -.004342325369428365  .0025235673898185273   .018933033410152973   .019533369801033543   -.0061648004639516495    .03048285   .0060965693555772305
-.00011364253686250384   .009911041437695198    .01745776918174841   .005797522796897121     -.00681496246214062    .02623773    .005247545428574085
 .00003122927268432024    .00957226932712238  -.006613175940785115 -.0043592837380519705    -.014216729255535621   -.01558569  -.0031171380542218685
  -.008015307738917083   .004402480863877801 -.0077477788942707584  -.009344770528499788    -.014413844569162813   -.03511922   -.007023843936622143
    -.0574384599808101  .0031433434386127536  .0036060486161312924  .0008851460961921973    -.009282822395471214   -.05908674    -.01181734912097454
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  .0006614217961633067   .012945491826410657  -.015969209367570562   -.00661910355634381    .0059039119470376145  -.003077487   -.000615497468970716
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  -.005839285257922239  -.024141293636546296 -.0057040879502699825  -.017147703656549395      .00798776561830596    -.0448446    -.00896892137825489
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  -.007335042830992934 -.0024839966539182733   -.03925662904764912  -.013467197884658907    .0025107351381496775   -.06003214    -.01200642716139555
 -.0010448550351719373  .0003786067440496195   -.03895904960420929  -.013311958476427192     .010291908237730114   -.04264535    -.00852906983345747
  .0011076284072593246  .0046524481978202185 -.0003789914568402698  -.005505597471848445      .00827853527874957  .0081540225   .0016308045014739037
   -.03364356948655024    .01810149779845995   -.01157082171725971   .014090698713802537     .004322090425448396  -.008700104  -.0017400209326297045
  -.024386827340119068   .017662788096239078  -.003398540245843979  .0075269728210740645     .014571276142943729    .01197567   .0023951339535415173
   .008086817372821107   .005326278516102948   .009641671007396536  -.012593440627521707 -.000045144492660006974   .010416182     .00208323635160923
    .02580817923744583  -.007595351668233757  -.011355906179049014  -.022654479054826964    -.008126671026690707   -.02392423   -.004784845747053623
   .012626986812162106    -.0088513599516041   .000889713737518321  -.013103472285280096     .006784878551072427 -.0016532532  -.0003306506550870836
   .003497857179997744  .0024416411405535285   .015155187849653329  .0023795456939752144     -.00790943743433682   .015564794   .0031129587441682816
   .014461360040102445   .004495028252985176  .0044985277852705174   .007831494215907842     -.02647396439777714   .004812446   .0009624892845749855
   -.00551377219079692   .005180842311241264   .008485302429377947 -.0005905183676306843    -.021638142769339324   -.01407629  -.0028152577579021454
 -.0032496583110486277   .025638334004817086   .006896342577193423   -.00710143411236646    -.010826933228185155   .011356653    .002271330449730158
   .003898915642389402     .0339735256044075   .005250540302852459  -.007807771332847447      .01694011946972114    .05225533    .010451065376400948
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  .0015307016911316961  -.005762787094335255   .013680165517504773  -.015067777195810265   -.0010048483841846147  -.006624545  -.0013249090407043695
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  -.004961691607206333   .000823704651645094  -.014768070312888642 -.0015169353735745537    .0015075582282123232  -.018915433  -.0037830867804586887
  -.012913822584928215 -.0017944847292215953  -.008418060168469422  -.008805237666038118     .002971313647253277   -.02896029   -.005792058072984219
  -.007338132255000804  .0037292955622439785  -.002259203989207934  -.006832169344733335     .003964359797675596   -.00873585  -.0017471701139584184
 -.0049288669330267475   .004432906876527068  -.006651823059916774  .0020836947665162676    .0016532458416735753 -.0034108425  -.0006821685237810016
  -.005006653892962044  .0005121804649997909   .009025671681195958  .0034917873370935992      -.0722811593501419   -.06425817   -.012851634994149208
  -.003763687936096775  -.004511954044957313  .0037507106817326104  -.010330216663198069     -.09754508450384378   -.11240023    -.02248004637658596
  -.008653473221364628 .00028443756294796885  -.013193097781846276  -.010305556056760118     -.03341066230459949   -.06527835   -.013055670075118542
   .002988507255207073   .001082471843444342  -.009377817686084318  -.005214995366637112   -.0016134153073267474   -.01213525  -.0024270496796816587
   .008783280945882446  -.007406947461691007  -.004474349827110554  -.008569915535796762   -.0028575357145802956  -.014525468  -.0029050935991108418
-.00041743442671187737  -.056169911796835864   .008299767994963021  -.005331662357821249    -.008228709358126966   -.06184795   -.012369589880108833
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   -.01269108890373006   .005158850593853889   .015008224395672459   .007372884738404451    .0075061364273118205   .022355007    .004471001215279102
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   .003292779839079947   -.03294933704806563 -.0019583518555134904   -.04605015121124176    -.013604160897804281   -.09126922    -.01825384423136711
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end

Kind regards,

George

[Carlo Lazzaro]

George:
thanks for providing an excerpt of your dataset via -dataex-.
Unfortunately, I was not able to find the variable -diff- (as per the Stata error message reported in your code).
Anyway, the code you typed should have given you back the mean of CAAR when diff==0.
I doubt that it was what you were searching for.

[George Bonje]

Dear Carlo,

I've completely misunderstood a part of the guide i was reading and you explanation completely makes sense now. If i have all the CAR variables lined up as i have right now, I should be able to:

egen row_total = rowtotal ( A B C D E)
reg row_total, robust

I should be recieving the average of the CAR, which is the CAAR and thereby also recieve the accompanying T-statistics on CAAR.

Kind regards,

George

[Carlo Lazzaro]

George:
does -robust- make sense in your case?
Can't you get the same results without it?

[George Bonje]

I was taught to use the robust standard as a conservative measure. However i'll be stating the regular standard errors and the robust and examine them both. I havent completely checked if my dataset is suffering from heteroskedasticity

Thanks a lot for your help Carlo, I truly appreciate it.

Kind regards,

George