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RE: st: Confusion about collinearity


From   "Yarbrough, Kevin T CADET MIL USA USMA" <Kevin.Yarbrough@usma.edu>
To   "statalist@hsphsun2.harvard.edu" <statalist@hsphsun2.harvard.edu>
Subject   RE: st: Confusion about collinearity
Date   Mon, 2 Dec 2013 01:33:36 -0500

See comments below:

>I followed that up with this code to replace the missing values:
>
>replace eitc00=0 if year==2000 & eitc00==.

>If I am reading this code right, then eitc00 still = missing for all 
>years other than 2000. That means the regression will only include 
>data from 2000. Is this really what you want? How about this instead?
>
>replace eitc00 = 0 if eitc00 == .

Thanks for that. I caught it too and made the change. However, the regressions still have an omitted coefficient on the interaction term because of collinearity. 


-----Original Message-----
From: owner-statalist@hsphsun2.harvard.edu [mailto:owner-statalist@hsphsun2.harvard.edu] On Behalf Of Richard Williams
Sent: Monday, December 02, 2013 1:15 AM
To: statalist@hsphsun2.harvard.edu; statalist@hsphsun2.harvard.edu
Subject: Re: st: Confusion about collinearity

See comments below.

At 12:40 AM 12/2/2013, Yarbrough, Kevin T CADET MIL USA USMA wrote:
>I'm having a problem with collinearity in my 
>difference-in-differences model. I'm using Stata 12 for Windows.
>
>
>
>I'm using pooled cross section from a 5% sample of ACS data from 
>2011 to 2011 across all 50 states and Washington D.C. I'm attempting 
>to analyze a policy implementation with the 
>difference-in-difference(DID) identification method. 25 states have 
>implemented this policy in different years. I'm trying to measure 
>the effect on income. From my knowledge, a correct use of DID should 
>result in a model: y=B0+B1(Treatment_group)+B2(post-policy year)+ 
>B3(interaction term of treatment_group and post-policy year).
>
>
>
>I began by creating a dummy variable for each year that equals 1 if 
>a state had the program in that year. For example:
>
>gen eitc00=1 if year==2000 &  (statefip==08 |statefip==11 | 
>statefip==17 |statefip==19 | statefip==20 | statefip==23 | 
>statefip==24 |statefip==25 |statefip==27 |statefip==34 |statefip==36 
>|statefip==41 | statefip==44 |statefip==50 |statefip==55)
>
>
>
>I followed that up with this code to replace the missing values:
>
>replace eitc00=0 if year==2000 & eitc00==.

If I am reading this code right, then eitc00 still = missing for all 
years other than 2000. That means the regression will only include 
data from 2000. Is this really what you want? How about this instead?

replace eitc00 = 0 if eitc00 == .

>I then created a dummy variable for years:
>
>gen yr02=year==2002

In 2000, yr02 = 0.

>And the interaction term between the two:
>
>gen eitc00yr02=eitc00*yr02

In 2000, the interaction term = 0. In all other years it is missing 
since eitc00 is missing for all years besides 2000.

>My regression is
>
>Reg lnincwage eitc00 yr02 eitc00yr02

In 2000, yr02 and eitc00yr02 both equal 0. All other years get 
dropped because eitc00 is missing for all other years.

>Which results in the interaction term being omitted because of 
>collinearity. I cannot figure out why.

I'm surprised only the interaction gets dropped.

I may be making a mistake somewhere. But have you run descriptive 
statistics on your created vars?

As a sidelight I would use factor variable notation for my 
interactions and dummy variables.

-------------------------------------------
Richard Williams, Notre Dame Dept of Sociology
OFFICE: (574)631-6668, (574)631-6463
HOME:   (574)289-5227
EMAIL:  Richard.A.Williams.5@ND.Edu
WWW:    http://www.nd.edu/~rwilliam

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