9:28 a.m.
Hello!
I would like to better understand the rational for using the following formula for
determining the denominator degrees of freedom for the F-test: n(t-1)-(k-1); where n is
the number of regions, t the number of years, k the number of parameters, including the
constant. I thought that the use of the de-meaned data approach compared to LSDV approach
for the fixed effects model would lead to a higher number of denominator degrees of
freedom, as suggested in the Gretl Guide, with the following formula: nt-k.
I would greatly appreciate if someone could shed some light on the matter.
Thank you
Bruno Gobeil
Senior Consultant | Consultant principal
DUNSKY ENERGY CONSULTING | DUNSKY EXPERTISE EN ÉNERGIE
[t] 514.504.9030 *26 [f] 514.289.2665 [e]
bruno.gobeil@dunsky.com<mailto:bruno.gobeil@dunsky.com>
[cid:654DCECB-E50C-4670-80DE-CDA276C82480@home]<http://www.dunsky.com/>
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10:35 a.m.
Am 20.07.2016 um 15:28 schrieb Bruno Gobeil:
Hello!
I would like to better understand the rational for using the following
formula for determining the denominator degrees of freedom for the
F-test: n(t-1)-(k-1); where n is the number of regions, t the number of
years, k the number of parameters, including the constant. I thought
that the use of the de-meaned data approach compared to LSDV approach
for the fixed effects model would lead to a higher number of denominator
degrees of freedom, as suggested in the Gretl Guide, with the following
formula: nt-k.
If I understand your question correctly, then here is my answer: LSDV
and de-meaned data fixed effects ("within" estimation) are equivalent
for testing purposes. To put it differently, de-meaning is also a
statistical estimation procedure, because you do not know the expected
population values a priori and hence you have to estimate them via the
arithmetic means. Hence you cannot gain d.o.f. by the within/de-meaned
estimator.
This is not gretl-specific, of course.
hth,
sven
10:41 a.m.
Thanks very much for your quick response. It is much appreciated.
Regards,
Bruno Gobeil
Senior Consultant | Consultant principal
DUNSKY ENERGY CONSULTING | DUNSKY EXPERTISE EN ÉNERGIE
[t] 514.504.9030 *26 [f] 514.289.2665 [e] bruno.gobeil(a)dunsky.com
NOTICE: This message (including any attachments) is intended for the sole use of the
individual or entity to which it is addressed, and contains information that is
privileged, confidential and exempt from disclosure. Barring explicit indication to the
contrary in the text of the message, any copying, distribution or dissemination of any
part of this email (including any attachments), by the intended or accidental recipient,
is strictly prohibited. If you have received this communication in error, please notify us
immediately. Thank You.
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-----Original Message-----
From: gretl-users-bounces(a)lists.wfu.edu [mailto:gretl-users-bounces@lists.wfu.edu] On
Behalf Of Sven Schreiber
Sent: July 20, 2016 10:36 AM
To: gretl-users(a)lists.wfu.edu
Subject: Re: [Gretl-users] F-test: Fixed Effects vs Pooled OLS
Am 20.07.2016 um 15:28 schrieb Bruno Gobeil:
Hello!
I would like to better understand the rational for using the following
formula for determining the denominator degrees of freedom for the
F-test: n(t-1)-(k-1); where n is the number of regions, t the number
of years, k the number of parameters, including the constant. I
thought that the use of the de-meaned data approach compared to LSDV
approach for the fixed effects model would lead to a higher number of
denominator degrees of freedom, as suggested in the Gretl Guide, with
the following
formula: nt-k.
If I understand your question correctly, then here is my answer: LSDV and de-meaned data
fixed effects ("within" estimation) are equivalent for testing purposes. To put
it differently, de-meaning is also a statistical estimation procedure, because you do not
know the expected population values a priori and hence you have to estimate them via the
arithmetic means. Hence you cannot gain d.o.f. by the within/de-meaned estimator.
This is not gretl-specific, of course.
hth,
sven
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Sven Schreiber