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Re: st: Panel Data Regression - Serial Correlation - Multi-Collinearity - Fixed vs Random Effects

From   David Jacobs <[email protected]>
To   [email protected]
Subject   Re: st: Panel Data Regression - Serial Correlation - Multi-Collinearity - Fixed vs Random Effects
Date   Thu, 28 Jan 2010 17:35:21 -0500

There's much to reply to here. I can't cover everything. You haven't told us enough so I will have to speculate a bit.

First, although there may be other reasons, the most likely explanation for the exclusion of some of your explanatory variables is that the variables the fixed-effects routine is dropping remain constant over time. Fixed-effects can't estimate coefficients on such variables. Stata's fixed effects routine typically will not drop highly correlated explanatory variables.

Second, you probably need to run fixed-effects if you've done the Hauseman test correctly.

Third, the distribution of variables does not affect the degree to which they are collinear. Collinear variables may or may not be normal or non normal. Orthogonal variables (or variables with little or no correlation) may or may not be normally or non normally distributed.

Fourth, you need not employ Spearman correlations if variables are not normally distributed.

One quick way to find the amount of serial correlation is to estimate an "xtreg" model with ", pa r c(ar1)" at the end of the command (and drop the "fe"). Then after that model has run, type "xtcorr" The last command will give you an estimate of the serial correlations at various lags.

Dave Jacobs

At 04:57 PM 1/28/2010, you wrote:

I'm performing a panel data analysis (cross-sectional time series data
in long format).

Details on my data set:

       panel variable:  id (unbalanced)
       time variable:  year, 2004 to 2008, but with gaps
       delta:  1 unit

number of observations is 960 in 358 groups.

One dependent variable, ten explanatory variables (of which 4 are
industry dummies).

One of my questions is concerning my dummy variables.

After running fe and re regression with xtreg and performing the
hausman test the result was in favor of the fe regression model.
Now all my dummy variables are dropped by the regression. Is it save
to use random effects including the dummies even though the hausman
test had a p-value below 0.05?
The LM test for random effects hints at the existence of these
individual effects.

Question number two is regarding the explanatory variables and their
possible multi collinearity.
None of them are normally distributed which is why (if i'm not
mistaken) i cannot use pwcorr or corr. Instead i could use spearman
but i have some concerns since i'm
dealing with possibly auto correlated time-series variables. Is there
any option for me to get a correlation matrix for my independent
variables with significance values just like the
matrix i get when performing pwcorr, sig? I want to use the
correlation matrix to determine which explanatory variables need to be
excluded from my regression due to correlation
above 50%. Also i want to do this pre estimation.
And more general.. is it useful to look at correlations year-wise or
on an aggregate level?

The third questions is a follow up to the second. How do i test for
serial correlation? i used xtserial for each variable. is it save to
trust or do i have to include all the variables from
my regression?

Kind Regards Jan

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