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RE: st: Year Fixed Effect Interpretation

From   Mauro Mastrogiacomo <[email protected]>
To   "'[email protected]'" <[email protected]>
Subject   RE: st: Year Fixed Effect Interpretation
Date   Thu, 8 Sep 2011 10:22:13 +0200

One other alternative is the method of 
Angus Deaton & Christina Paxson, 1998. "Saving and growth: another look at the cohort evidence," Working Papers 225, Princeton University.
They use a linear transformation of the time dummies (dropping 2), which somehow goes back to Maarten's suggestion. In this way they manage to include at the same time, age time and cohort effects, which are otherwise linearly related.

-----Original Message-----
From: [email protected] [mailto:[email protected]] On Behalf Of Maarten Buis
Sent: donderdag 8 september 2011 10:10
To: [email protected]
Subject: Re: st: Year Fixed Effect Interpretation

On Wed, Sep 7, 2011 at 10:18 PM, Venkiteshwaran, Vinod wrote:
> I am running a pooled regression with dummies(t-1 dummies) as controls for year effects. I have chosen to drop the first year so that I can interpret the coefficients on the remaining year dummies in terms of the first year. At this stage I have to include an additional independent variable that is collinear with these year dummies so Stata automatically drops another dummy , for the last year, before running the regression. My focus is on whether or not the coefficients on the dummy variables systematically increase or decrease over time. However, since the dropped dummies are at the beginning and end of the sample the trend in the dummy coefficient is no longer present. I have tried to drop two year dummies at the beginning of the sample but still the time trend seems to have vanished!

Sorry, what you want to do is impossible. The fact that your year
dummy is perfectly collinear with your covariate means your data does
not contain the necessary information to get separate estimates of
both variables. So part of the effect of your covariate should be
included in your time trend, but there is no information in your data
to determine which part or how large that part would be. One way to
solve this is to add time is linear curve or maybe a spline rather
than as a set of dummies.

Hope this helps,

Maarten L. Buis
Institut fuer Soziologie
Universitaet Tuebingen
Wilhelmstrasse 36
72074 Tuebingen

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