st: RE: questions about Fixed Effect models

["Wooldridge, Jeffrey" <wooldri1@msu.edu>]

Because I've been doing some work estimating teacher value added, I'll take a crack at this. First is an issue of terminology. While it is common to say things like "teacher fixed effects" when using student-level data, I'm not sure using the fixed effects commands in Stata (xtreg) is the right way to go. In fact, mechanically I'm not sure how you're doing it. Aren't the teacher effects the main quantities of interest? If so, you should just being using pooled OLS, putting in the lagged proficiency, and then including a full set of teacher dummy variables (with, presumably, a base teacher represented by the constant).

None of the statistics that you mention would be relevant except perhaps the error variances. An interesting calculation is to compute the usual variance of the OLS residuals and then also compute the variance of the teacher effects. (You might have to export them or put them into a Stata matrix to do this.) This would tell you how important the teacher effect is relative to the overall variance in student proficiency.

My Stata session would look something like this:

xtset studentid year
gen score_1 = l.score
reg score score_1 i.teacherid i.year, cluster(studentid)

(or just include a full set of teacher dummies if you have created them).

It is also common to use student fixed or random effects on the differenced score:

gen dscore = d.score
xtreg dscore i.teacherid i.year, fe cluster(studentid)

Jeff W.

-----Original Message-----
From: owner-statalist@hsphsun2.harvard.edu [mailto:owner-statalist@hsphsun2.harvard.edu] On Behalf Of Stata Email
Sent: Friday, February 25, 2011 3:05 PM
To: statalist@hsphsun2.harvard.edu
Subject: st: questions about Fixed Effect models

Dear Statalist members

I am new in panel data and I am working with fixed effect models. I
would like to confirm if I am doing the right thing

When working with panel data, the data set is such that we have
information about individuals i and we observe these individuals
through different time periods t. My questions are

1) Which part of the Stata output shows me that the fixed effect is important?
2) What does it mean exactly R-sq within? R-sq between?
3) If I run a fixed effect model, the sigma-u is the std dev of the
residuals inside (within) each group of individuals i. So a higher
number means that I have more variability inside each group?
4) sigma-e show the std dev of the residuals after excluding the
variability inside each group i? If that is true, a higher number
means that I have a big variability among groups i and therefore the
fixed effect is important?

Now let me explain what kind of data set I have. I have a data set
with the proficiency level of students, followed for 5 years. But I
know who is the teacher for every student in all 5 years. I want to
calculate a teacher fixed effect (and I control for the proficiency
level from the previous year instead of having a student fixed
effect). My other questions are

5) My individuals i here are the teachers and, instead of having a
time t, I have students s with the same teacher
6) All within statistic will refer the the differences among students
with the same teacher?

I really appreciate any comment
Isabel

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