st: How to estimate Fixed and random effects for a long panel dataset.

[Herman Haugland <herman.haugland@gmail.com>]

Dear all,

I think I have sent this e-mail before, but I don't know if it made it
through Majordomo.


I have a long panel dataset, meaning my N is much smaller than my T.
I have N = 5, T = 61. I am trying to perform OLS, Fixed-effects and
Random-effects analysis, using vce(cluster id).

I tried to estimate my model using xtreg for FE and RE, but I get an
error related to the fact that I do not have enough degrees of freedom
for performing the estimation.

This is what I get:

Wald chi2(4)       =        .
Prob > chi2        =        .


Stata sends me here for help:  help j_robustsingular  // My case is
explained under the title "Are you using a svy estimator or did you
specify the vce(cluster clustvar) option?"

So, after reading that, I have assumed that I cannot trust the output
of that estimation, because the errors might be biased.

First question: Am I right on thinking that?

In addition, in the book "Microeconometrics using Stata", the author
clearly indicates that the xtreg command, with the vce(cluster id)
option for calculating robust errors, is mostly appropriate for short
panels, which is not my case.

An alternative is to use the command xtregar for estimating random and
fixed effects, which is based on an AR(1) process for the errors.
However, I tested using xtserial, and the errors do not show serial
autocorrelation. However, the xtregar command has the option rhof(#),
where # indicates the desired rho value (AR(rho)).

My main questions are:

1) What is the right way to calculate Fixed and Random Effects for a
long panel dataset, in which the number of variables is larger than
the N?

2) Would specifying rho = 0 completely eliminate the AR(1) process for
the errors, and leave me with an estimation that fits my data?


Thank you for your answers.

Best regards,
Herman Haugland
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