11:13 p.m.
Hello gretl community. I'm running gretl on a Windows XP machine and am
contented. My computer guru suggests that I upgrade to Windows 7, and says
that all of my software will transfer seamlessly. Although I'm sure she's
right about a lot of my software (MS Office, for example), I'd like to be
assured that I'll have no trouble reinstalling gretl. What has been your
experience with an upgrade like this?
If you know, I'd like the same assurances regarding Exp, MatLab, R, and
Maple.
Thanks, Frank Benford
11:13 a.m.
Am 31.05.2012 01:13, schrieb Frank Benford:
Hello gretl community. I’m running gretl on a Windows XP machine and
am
contented. My computer guru suggests that I upgrade to Windows 7, and
says that all of my software will transfer seamlessly. Although I’m sure
she’s right about a lot of my software (MS Office, for example), I’d
like to be assured that I’ll have no trouble reinstalling gretl. What
has been your experience with an upgrade like this?
Slightly OT, but since you mentioned it: At my previous work we actually
had the most problems with the xp-to-7 migration concerning... [drum
roll] MS Office! (Admittedly, this is probably version-specific, but still.)
cheers,
sven
8:56 a.m.
New subject: 2SLS without HAC standard errors
Dear All,
My 2SLS results without HAC standard errors are promising whereas those with
HAC standard errors are not. Hitherto, I have been used to robust HAC standard errors in
my estimations. I'll like to enquire if a sound case could be made for presenting
results without HAC standard errors.
Cheers
________________________________
9:30 a.m.
New subject: 2SLS without HAC standard errors
On Fri, 1 Jun 2012, Anutechia Asongu wrote:
Dear All,
My 2SLS results without HAC standard errors are promising
whereas those with HAC standard errors are not. Hitherto, I have been
used to robust HAC standard errors in my estimations. I'll like to
enquire if a sound case could be made for presenting results without
HAC standard errors.
The prevailing attitude in the scientific community is to report those
which look better to you. Of course, the next step is to ignore what your
discussants say and accuse your referees of blatant bias and incompetence.
--------------------------------------------------
Riccardo (Jack) Lucchetti
Dipartimento di Economia
Università Politecnica delle Marche
(formerly known as Università di Ancona)
r.lucchetti(a)univpm.it
http://www2.econ.univpm.it/servizi/hpp/lucchetti
--------------------------------------------------
12:46 p.m.
New subject: 2SLS without HAC standard errors
On Fri, 1 Jun 2012, Anutechia Asongu wrote:
My 2SLS results without HAC standard errors are promising whereas
those with HAC standard errors are not. Hitherto, I have been used
to robust HAC standard errors in my estimations. I'll like to
enquire if a sound case could be made for presenting results
without HAC standard errors.
If in tests for heteroskedasticity and autocorrelation the null is
not rejected, one could argue that HAC estimation is just
introducing noise. On the other hand, if the HAC standard errors
differ substantially from the "classical" ones, that suggests that
the errors are not i.i.d.
Allin Cottrell
2 p.m.
New subject: 2SLS without HAC standard errors
Interesting result.
In the standard OLS framework moving from normal SE to robust ones usually
implies higher SE's and therefore reducing t-stats, which also
'reduces promising-results'. However, in 2SLS framework one of the main
problem is the bias of the estimator, which of course affects the estimate
of the robust SE's, leading to a dirty t-stat. So, let's move to the bias
issue.
I did explore it years ago (
http://www.bcentral.cl/eng/studies/working-papers/pdf/dtbc464.pdf). If you
check the Monte Carlo section in the paper, you will see in Tables 2 to 5
that 2SLS-bias increases with both endogeneity (rho) and the number of
instruments (K), this is of course a standard results. But moving to Tables
6 to 9, I did robust inference which is the main point of your question.
So, let's assume that your empirical problem implies a low 2SLS-bias as in
the case rho=0.3 and K=5, you could see that for all designs considered
there is not a significance distorsion in the rejection frequency meaning
that for 'almost-unbiased' estimators robust SE's shouldn't affect your
inference. It could be the case that your 2SLS estimator is biased, meaning
the 'promising-results' could be 'wrong-results'.
Maybe you could add to the discussion bootstrapping SE and reporting
coeff (non-robust SE) [robust SE or bootstrap SE], adding in text the
standard 'on the one hand... on the other hand ".
Best, Rodrigo.
2012/6/1 Allin Cottrell <cottrell(a)wfu.edu>
On Fri, 1 Jun 2012, Anutechia Asongu wrote:
My 2SLS results without HAC standard errors are promising whereas those
> with HAC standard errors are not. Hitherto, I have been used to robust HAC
> standard errors in my estimations. I'll like to enquire if a sound case
> could be made for presenting results without HAC standard errors.
>
If in tests for heteroskedasticity and autocorrelation the null is not
rejected, one could argue that HAC estimation is just introducing noise. On
the other hand, if the HAC standard errors differ substantially from the
"classical" ones, that suggests that the errors are not i.i.d.
Allin Cottrell
_______________________________________________
Gretl-users mailing list
Gretl-users(a)lists.wfu.edu
http://lists.wfu.edu/mailman/listinfo/gretl-users
4:15 p.m.
New subject: 2SLS without HAC standard errors
Humm, Rodrigo, let me digest "Inferences using Instrumental variable estimators"
first. I'll get back to you ASAP. Let me understand the stuff in the paper first.
Thanks for critical explanation.
________________________________
From: Rodrigo Alfaro Arancibia <ralfaro(a)fen.uchile.cl>
To: Gretl list <gretl-users(a)lists.wfu.edu>
Sent: Friday, June 1, 2012 4:00 PM
Subject: Re: [Gretl-users] 2SLS without HAC standard errors
Interesting result.
In the standard OLS framework moving from normal SE to robust ones usually implies higher
SE's and therefore reducing t-stats, which also 'reduces promising-results'.
However, in 2SLS framework one of the main problem is the bias of the estimator, which of
course affects the estimate of the robust SE's, leading to a dirty t-stat. So,
let's move to the bias issue.
I did explore it years
ago (http://www.bcentral.cl/eng/studies/working-papers/pdf/dtbc464.pdf). If you check the
Monte Carlo section in the paper, you will see in Tables 2 to 5 that 2SLS-bias increases
with both endogeneity (rho) and the number of instruments (K), this is of course a
standard results. But moving to Tables 6 to 9, I did robust inference which is the main
point of your question. So, let's assume that your empirical problem implies a low
2SLS-bias as in the case rho=0.3 and K=5, you could see that for all designs considered
there is not a significance distorsion in the rejection frequency meaning that for
'almost-unbiased' estimators robust SE's shouldn't affect your inference.
It could be the case that your 2SLS estimator is biased, meaning the
'promising-results' could be 'wrong-results'.
Maybe you could add to the discussion bootstrapping SE and reporting coeff (non-robust SE)
[robust SE or bootstrap SE], adding in text the standard 'on the one hand... on the
other hand ".
Best, Rodrigo.
2012/6/1 Allin Cottrell <cottrell(a)wfu.edu>
On Fri, 1 Jun 2012, Anutechia Asongu wrote:
My 2SLS results without HAC standard errors are promising whereas those with HAC standard
errors are not. Hitherto, I have been used to robust HAC standard errors in my
estimations. I'll like to enquire if a sound case could be made for presenting
results without HAC standard errors.
>
If in tests for heteroskedasticity and autocorrelation the null is not rejected, one could
argue that HAC estimation is just introducing noise. On the other hand, if the HAC
standard errors differ substantially from the "classical" ones, that suggests
that the errors are not i.i.d.
Allin Cottrell
_______________________________________________
Gretl-users mailing list
Gretl-users(a)lists.wfu.edu
http://lists.wfu.edu/mailman/listinfo/gretl-users
_______________________________________________
Gretl-users mailing list
Gretl-users(a)lists.wfu.edu
http://lists.wfu.edu/mailman/listinfo/gretl-users
5:03 p.m.
New subject: 2SLS without HAC standard errors
Hi Rodrigo,
I have touched the common denominator of your paper and with respect to
your last statement on the possibility of "wrong results", I need three
clarifications: (1) while your paper is premised on the hypothesis of many
instruments(significant overidentification), the instruments in my paper are very few(just
about six) in tandem with my research question which is based on 'assessing the
validity of certain channels to the endogenous variable, contingent on the instrumental
variables'; (2) the Hausman(prior to the 2SLS adoption) and Sargan-OIR(after the 2SLS)
tests have null hypotheses that are rejected and unrejected respectively(testament to good
model specification); (3)the example you ask me to follow( rho=0.3 and K=5) has fewer
instruments than the number employed in my paper, and this confuses me a bit. Did I get
something wrong?
Thanks
________________________________
From: Rodrigo Alfaro Arancibia <ralfaro(a)fen.uchile.cl>
To: Gretl list <gretl-users(a)lists.wfu.edu>
Sent: Friday, June 1, 2012 4:00 PM
Subject: Re: [Gretl-users] 2SLS without HAC standard errors
Interesting result.
In the standard OLS framework moving from normal SE to robust ones usually implies higher
SE's and therefore reducing t-stats, which also 'reduces promising-results'.
However, in 2SLS framework one of the main problem is the bias of the estimator, which of
course affects the estimate of the robust SE's, leading to a dirty t-stat. So,
let's move to the bias issue.
I did explore it years
ago (http://www.bcentral.cl/eng/studies/working-papers/pdf/dtbc464.pdf). If you check the
Monte Carlo section in the paper, you will see in Tables 2 to 5 that 2SLS-bias increases
with both endogeneity (rho) and the number of instruments (K), this is of course a
standard results. But moving to Tables 6 to 9, I did robust inference which is the main
point of your question. So, let's assume that your empirical problem implies a low
2SLS-bias as in the case rho=0.3 and K=5, you could see that for all designs considered
there is not a significance distorsion in the rejection frequency meaning that for
'almost-unbiased' estimators robust SE's shouldn't affect your inference.
It could be the case that your 2SLS estimator is biased, meaning the
'promising-results' could be 'wrong-results'.
Maybe you could add to the discussion bootstrapping SE and reporting coeff (non-robust SE)
[robust SE or bootstrap SE], adding in text the standard 'on the one hand... on the
other hand ".
Best, Rodrigo.
2012/6/1 Allin Cottrell <cottrell(a)wfu.edu>
On Fri, 1 Jun 2012, Anutechia Asongu wrote:
My 2SLS results without HAC standard errors are promising whereas those with HAC standard
errors are not. Hitherto, I have been used to robust HAC standard errors in my
estimations. I'll like to enquire if a sound case could be made for presenting
results without HAC standard errors.
>
If in tests for heteroskedasticity and autocorrelation the null is not rejected, one could
argue that HAC estimation is just introducing noise. On the other hand, if the HAC
standard errors differ substantially from the "classical" ones, that suggests
that the errors are not i.i.d.
Allin Cottrell
_______________________________________________
Gretl-users mailing list
Gretl-users(a)lists.wfu.edu
http://lists.wfu.edu/mailman/listinfo/gretl-users
_______________________________________________
Gretl-users mailing list
Gretl-users(a)lists.wfu.edu
http://lists.wfu.edu/mailman/listinfo/gretl-users
4586
days inactive
4588
days old
7 comments
6 participants
participants (6)
-
Allin Cottrell -
Anutechia Asongu -
Frank Benford -
Riccardo (Jack) Lucchetti -
Rodrigo Alfaro Arancibia -
Sven Schreiber