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Re: st: re: tsset with non-integers

From   Eva Poen <>
Subject   Re: st: re: tsset with non-integers
Date   Thu, 7 May 2009 17:31:47 +0100


please tell us what you don't understand about the replies you have
got so far. Kit gave recommendations for testing for autocorrelation
in residuals. If it is serial correlation that you are after, you have
time series (or panel) data, and should tell Stata about it, using the
-tsset- command. See -help tsset-.

If it is not serial correlation but some other kind of dependence, you
need to be more specific about the type of data you have.

Kit discouraged the use of -durbinh-, but if you insist on using it
anyway, you need to -tsset- your data first. In any case, residuals
are very unlikely to be integers. Your _time_ variable (e.g. years or
quarters or months)  could be integer. But that has nothing to do with
your residuals.


2009/5/7 Frank Gallo <>:
> <>
> Hi Nick & Kit,
> Thank you for your responses. My goal is only to check the independence of residual terms following a regression run. My reading of the durbinh command lead me to believe that it would help me achieve my goal. Can you suggest an alternative option to check the independence of residual terms that are non-integers? Thank you.
> Best,
> Frank
> On Thursday, May 07, 2009, at 06:32AM, "Kit Baum" <> wrote:
>>Frank said
>>What I would like to do, which I cannot find exactly in the archives,
>>is to check the independence of the residual terms (e) from a
>>regression. I would like to run the -durbinh- command...
>>Nick Cox answered the technical question re -tsset-. I do not
>>recommend you rely on the -durbinh- command. It is a special case of
>>the Breusch-Godfrey test in which you only consider AR(1) vs i.i.d.
>>The -estat bgodfrey- postestimation command allows you to test for
>>higher-order autocorrelation as well (which might well be present even
>>if an AR(1) coefficient is insignificant). Also consider using -
>>wntestq-, which is an unconditional test of the residuals'
>>autocorrelation function. (B-G is a conditional test in that it uses
>>the X matrix from the regression, whereas the Lung-Box-Pierce "Q" test
>>may be applied to any time series). All will require that the data are
>>properly -tsset-.
>>Kit Baum   |   Boston College Economics & DIW Berlin   |
>>                               An Introduction to Stata Programming
>>    An Introduction to Modern Econometrics Using Stata  |

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