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Re: st: Autocorrelation(testparm or wntstmvq?)


From   Katia Bobulova <katia.bobulova@googlemail.com>
To   statalist@hsphsun2.harvard.edu
Subject   Re: st: Autocorrelation(testparm or wntstmvq?)
Date   Sun, 12 Jun 2011 22:25:03 +0200

Dear Robson,

thank you very much for your reply.

So, this is the output that I have from Stata:

Source	SS	df       MS		Number of obs	=     694
F(  6,   687)	=   11.25
Model	60244.0295	6  10040.6716		        Prob > F	=  0.0000
Residual	613010.929	687  892.301206		R-squared	=  0.0895
				                                                Adj R-squared	=  0.0815
Total	673254.958	693  971.507876		        Root MSE	=  29.871

					
rt	Coef.	Std. Err.      t	P>t	[95% Conf.	Interval]
					
rt	
L1.	.2131653	.0380781     5.60	0.000	.1384018	.2879288
L2.	.0697527	.0384977     1.81	0.070	-.0058346	.14534
L3.	.0585814	.0386236     1.52	0.130	-.017253	.1344158
L4.	-.0130796	.0385477    -0.34	0.734	-.088765	.0626059
L5.	.1511356	.0385143     3.92	0.000	.0755158	.2267555
L6.	-.0665402	.0381089    -1.75	0.081	-.141364	.0082836
	
_cons	30.22744	3.645471     8.29	0.000	23.06984	37.38505
					
What are you saying is that I should look at the Prob>F?

Thanks a lot for your help.

Best,
Katia



2011/6/11, Robson Glasscock <glasscockrc@vcu.edu>:
> Hi Katia,
> The model you estimated attempts to explain current variation in your
> dependent variable (rt) using 4 lags of rt. The regression output
> tells you the impact/significance of each individual lag (l.rt- l4rt)
> on the current value of rt. The testparm command you wrote uses a Wald
> test to test the null hypothesis that beta l.rt= beta l2.rt= beta
> l3.rt= beta l4.rt= 0. Note that in your model you don't need to use
> the testparm command to test that all of your parameters are jointly
> equal to zero because the standard output already gives this to you in
> the form of the overall F/LR test in the upper right-hand corner of
> the output.
>
> Testing for autocorrelation in residuals of time-series models is
> different. The presence of autocorrelation in the residuals of our
> "best" model tells us that we haven't modeled the process perfectly.
> There is still some systematic variation in the error terms, but
> knowing that autocorrelation exists via the test still won't tell us
> what, exactly, the autocorrelation is caused by.
>
> best,
> Robson Glasscock
> On Fri, Jun 10, 2011 at 9:53 AM, Katia Bobulova
> <katia.bobulova@googlemail.com> wrote:
>> Dear All,
>>
>> I would like to test the autocorrelation between rt,rt-1 and so on.
>>
>> I typed this command:
>>
>> reg rt L(1/4).rt
>> testparm L.rt L2.rt L3.rt L4.rt
>>
>> However, I found in the book "Alaysis of Financial Time Series", pag.
>> 27 that I can test jointly that several autocorrelations of rt are
>> zero with the potmanteau test.
>>
>> The command in stata is:  wntstmvq.
>>
>> However, all the exmaples that I found related to this command refer
>> to autocorrelations in the residuals. Is it correct to do something
>> like this, to test instead the autocorrelation in the resturns?:
>>
>> wntstmvq bq
>>
>> Are testparm and wntstmvq two different ways to test the same thing?
>>
>> I am a little bit confused on which one should I use in my case. Any
>> help would be really appreciated.
>>
>> Katia
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