Dear all,

`I have a panel of 33 countries over 7 periods (7*3 year period
``averages). I am trying to perform a test for poolability.
`

`My restricted model is a fixed effect model with homogeneous slopes, my
``unrestricted model is a fixed effect model with slopes on the variable
``of interest varying across countries (maintaining the assumption that
``the coefficients on all control variables are constant across
``countries).
`

`Following Vaona (2008) ("A quick trick to perform a Roy-Zellner test for
``poolability") I have created 33 interaction terms between the countries
``and the variable of interest and am able to run regressions with these
``33 interaction terms.
`

`My question concerns the testing procedure. Having read previous Stata
``posts on this topic (see e.g.:
``http://hsphsun3.harvard.edu/cgi-bin/lwgate/STATALIST/archives/statalist.0303/Subject/article-391.html) I remain unsure about which of the following approaches is valid:
`

`(1) Run the unrestricted model including all interaction terms using a
``fixed effect estimator, then use an F-test to test the equality of all
``coefficients.
`

`(2) Same procedure as in (1) but using panel robust (clustered) errors
``(or alternatively bootstrapped errors) (having tested for
``autocorrelation, heteroscedasticity and spatial correlation I am using
``these robust errors throughout the whole paper).
``Problem: Using cluster robust errors reduces the degrees of freedom and
``as a result I cannot test the equality of all interaction terms
``simultaneously (while I expected the degrees of freedom to be reduced to
``the number of clusters-1, Stata in fact allows me to test only 14
``coefficients at a time (all additional constraints are dropped))
`

`(3) Perform a Roy-Zellner test instead of a Chow test given the presence
``of non-spherical errors (e.g. "Econometrics", Baltagi 2008 ) - how would
``this be different from (2) which is also robust to non-spherical errors?
`Problem: How do I perform a Roy-Zellner test in this case?
Thank you for any help and advice,
Best regards,
Carla Müller
Emmanuel College
Cambridge University
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