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

From   Stata <[email protected]>
To   [email protected]
Subject   st: Panel Data Regression - Serial Correlation - Multi-Collinearity - Fixed vs Random Effects
Date   Thu, 28 Jan 2010 22:57:40 +0100


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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