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st: RE: problems with conducting OLS-PCSE analysis
From
Gordon Hughes <[email protected]>
To
[email protected]
Subject
st: RE: problems with conducting OLS-PCSE analysis
Date
Tue, 17 Jan 2012 09:45:36 +0000
There are two separate problems with what you are trying to do:
A. There are no time periods (years) for which data is available for
all countries. Hence, using casewise inclusion/deletion means that
you cannot construct the cross-country error covariance
matrix. Specify the options "pairwise" or "hetonly" to address this
- see the manual for information on the different options.
B. As David Jacobs points out, autocorrelation routines don't like
gaps in data. His suggestion of imputing or interpolating missing
years will work if there are only a few gaps, especially if there are
strong time trends in the country time series. Alternatively,
suppress the calculation of the autocorrelation coefficient by
specifying the option "corr(independent)".
However, as always you should think carefully about the specification
of your model. It seems possible that you are trying to estimate a
model that is too complex given the nature of your data.
Gordon Hughes
[email protected]
=======================================
Date: Mon, 16 Jan 2012 20:54:01 +0000
From: "Jacobs, David" <[email protected]>
Subject: st: RE: problems with conducting OLS-PCSE analysis
As you probably already know, you have missing values or gaps within
various series included in your models.
Some obvious tricks to determine where these missing values are
located include running the command -xtdescribe if e(sample)-
immediately after an -xtpcse- run. That will show you what the exact
pattern of gaps is. Another possibility that will provide more detail
is to type ".browse if e(sample)" again immediately after a run. The
last command works best if you have only a few explanatory variables
in your model as it will show the entire data set the xtpcse routine
could access.
In general and as you probably already know AR(1) routines don't like
gaps within a series and you seem to have that problem. One
possibility is to employ Stata's commands that impute missing data to
overcome these difficulties.
D. Jacobs
- -----Original Message-----
From: [email protected]
[mailto:[email protected]] On Behalf Of Edward James
Sent: Monday, January 16, 2012 9:33 AM
To: [email protected]
Subject: st: problems with conducting OLS-PCSE analysis
Dear Statalist.
I am currently conducting ols-pcse(pannel corrected standard error) with stata.
Although the number of groups(countries) are 19, the result shows only
16 groups.
In addition, when I conduct different model, following error message comes up:
"Number of gaps in sample: 40
(note: computations for rho restarted at each gap)
(note: estimates of rho outside [-1,1] bounded to be in the range [-1,1])
no time periods are common to all panels, cannot estimate disturbance
covariance matrix using casewise inclusion"
Do you have any idea for including all countries?
Thanks.
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