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st: Re: Event studies significance test


From   "Martin Weiss" <martin.weiss1@gmx.de>
To   <statalist@hsphsun2.harvard.edu>
Subject   st: Re: Event studies significance test
Date   Wed, 3 Jun 2009 21:28:55 +0200

That last line simply runs -regress- w/o covariates, which is equivalent to a t-test. The robust option -which the text describes as the major advantage over the t-test- does not make any difference here.

****
sysuse auto, clear
reg pr, nohead
reg pr, robust nohead
ttest pr==0
****


I have cleaned the code if anyone wants to chime in. First time through the code, you have to comment in those first two -use- and -save- commands to get your hands on the datasets. Be warned, the second dataset takes a considerable amount of time to download...

****
//from http://dss.princeton.edu/usingdata/stata/analysis/eventstudydataprep.html

/*
set memory 200m
use http://dss.princeton.edu/sampleData/eventdates.dta  /* about 11k */
save eventdates, replace
use http://dss.princeton.edu/sampleData/stockdata.dta, clear /* about 90m */
save stockdata, replace
*/

clear*

   use eventdates, clear
   by company_id: gen eventcount=_N
   by company_id: keep if _n==1
   sort company_id
   keep company_id eventcount
   save eventcount, replace
   use stockdata, clear
   sort company_id
   merge company_id using eventcount
   tab _merge
   keep if _merge==3
   drop _merge
   expand eventcount
   drop eventcount
   sort company_id date
   by company_id date: gen set=_n
   sort company_id set
   save stockdata2, replace
   use eventdates, clear
   by company_id: gen set=_n
   sort company_id set
   save eventdates2, replace
   use stockdata2, clear
   merge company_id set using eventdates2
   tab _merge
   list company_id if _merge==2
   keep if _merge==3
   drop _merge
   egen group_id = group(company_id set)

******************
// from http://dss.princeton.edu/usingdata/stata/analysis/eventstudy.html#test2

   sort company_id date
   by company_id: gen datenum=_n
   by company_id: gen target=datenum if date==event_date
   egen td=min(target), by(company_id)
   drop target
   gen dif=datenum-td

//    gen dif=date-event_date
   by company_id: gen event_window=1 if dif>=-2 & dif<=2
   egen count_event_obs=count(event_window), by(company_id)
   by company_id: gen estimation_window=1 if dif<-30 & dif>=-60
   egen count_est_obs=count(estimation_window), by(company_id)
   replace event_window=0 if event_window==.
   replace estimation_window=0 if estimation_window==.
   tab company_id if count_event_obs<5
   tab company_id if count_est_obs<30
    drop if count_event_obs < 5
    drop if count_est_obs < 30
set more off /* this command just keeps stata from pausing after each screen of output */
   gen predicted_return=.
   egen id=group(company_id)
    /* for multiple event dates, use: egen id = group(group_id) */
   su id, mean
qui forvalues i=1(1)`=r(max)' { /*note: replace N with the highest value of id */
    l id company_id if id==`i' & dif==0
    reg ret market_return if id==`i' & estimation_window==1
    predict p if id==`i'
    replace predicted_return = p if id==`i' & event_window==1
    drop p
    }
   sort id date
   gen abnormal_return=ret-predicted_return if event_window==1
   by id: egen cumulative_abnormal_return = sum(abnormal_return)
   * test = (1/n SAR)/(AR_SD)
   sort id date
   by id: egen ar_sd = sd(abnormal_return)
* gen test =(1/sqrt(number of days in event window)) * ( cumulative_abnormal_return /ar_sd)
*    list company_id cumulative_abnormal_return test if dif==0
// Testing Across All Events
/*Instead of, or in addition to, looking at the average abnormal return for each company, you probably want to calculate the cumulative abnormal for all companies treated as a group. Here's the code for that: */
reg cumulative_abnormal_return if dif==0, robust
****

HTH
Martin
_______________
----- Original Message ----- From: <lschoele@rumms.uni-mannheim.de>
To: <statalist@hsphsun2.harvard.edu>
Sent: Wednesday, June 03, 2009 5:06 PM
Subject: st: Event studies significance test


Dear Statalist,

I have a question about testing the significance across all events. I copied the text, that is on the stata website:

Testing Across All Events
Instead of, or in addition to, looking at the average abnormal return for each company, you probably want to calculate the cumulative abnormal for all companies treated as a group. Here's the code for that:

reg cumulative_abnormal_return if dif==0, robust
The P-value on the constant from this regression will give you the significance of the cumulative abnormal return across all companies. This test preferable to a t-test because it allows you to use robust standard errors.

My question: How is this test called, that is used here and why is it better than a t-test?

Thank you very much
Lisa

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