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# st: panel data analysis

 From Danielle Koopmans To statalist@hsphsun2.harvard.edu Subject st: panel data analysis Date Tue, 15 Jun 2010 12:41:28 +0200

```Hello,

it's my first time here and I have some questions. I have a dataset
with variables of 32 firms over a timespan of 10 years, I am examing
whether tenure (of a specific person) and other variables has
influence on the profitability (y) of firm i.
First I have a question about the xi command because I have some
categorical variables: I wanted to create dummies for the variable
years xi i . years and for education xi i . education, I tried this
command but nothing happenend, not even a note that I did something
wrong.

Second, because I have a dataset with cross-section data and
timeseries I ran a paneldata regression (fe, be and re) with i=firms
and t=years. It look likes this but then with a lot more variables
like financial variables, education dummy, age etc  :

y           tenure        year t      firm i
8,45        6,614        1995         1
7,39        7,616        1996         1
3,10        0,611        1997         1
9,93        1,633        1998         1
12,39      2,611        1999         1
19,24      3,614         2000        1
0,49        4,614         2001        1
1,13        0,611         2002        1
4,69        1,611         2003        1
9,14        2,614         2004        1
12,64      3,614         2005        1
3,69        2,633        1995         2
7,43        3,636        1996         2
10,30      4,636        1997         2
11,64      5,636        1998         2
10,01      6,636        1999         2

The R^2 differs between the models:

Be

R-sq:  within  = 0.0298
between = 0.5908
overall = 0.2349

Re

R-sq:  within  = 0.2412
between = 0.1820
overall = 0.2260

Fe

R-sq:  within  = 0.2611
between = 0.0194
overall = 0.0007
It doesn't seem good to me these results but which model should I
choose and which R^2 do I have to look at: within, between or overall?
My constant is also negtive at the fe model, how come?

And how to check for heteroskedastiscity, serial correlation
(Durbin-Watson test?) and collinearity?

Hopefully someone can help me on this. This is all very new to me.
Danielle

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