<>
Hi Eva,
The way I understood Kit's response was that both suggested approaches (estat bgodfrey and wntestq) require the user to tsset the data, which I cannot do. I am looking to test the autocorrelation of residuals terms so that I can check the regression assumption of indepence of errors. Thank you.
Best,
Frank
On Thursday, May 07, 2009, at 09:31AM, "Eva Poen" <[email protected]> wrote:
>Frank,
>
>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.
>
>Eva
>
>
>2009/5/7 Frank Gallo <[email protected]>:
>> <>
>>
>> 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" <[email protected]> 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
>>>
>>>Kit Baum | Boston College Economics & DIW Berlin | http://ideas.repec.org/e/pba1.html
>>> An Introduction to Stata Programming
>>>| http://www.stata-press.com/books/isp.html
>>> An Introduction to Modern Econometrics Using Stata | http://www.stata-press.com/books/imeus.html
>>>
>
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