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RE: st: Statistically significant difference in R Squared


From   "Jacobs, David" <jacobs.184@sociology.osu.edu>
To   "'statalist@hsphsun2.harvard.edu'" <statalist@hsphsun2.harvard.edu>
Subject   RE: st: Statistically significant difference in R Squared
Date   Thu, 23 Aug 2012 18:36:44 +0000

Seems like you could use a version of the Chow test, which in time-series analyses is based on period interactions.  

For example, how about creating a dummy coded "1" for one period and "0" for the other and then creating interactions with your explanatory variables and this dummy?  Perhaps, I'm wrong about the relevance of this test to the question, but if these period interactions are statistically significant you then would have grounds for concluding that the relationships at issue differ by period.

Anyway if you can succeed in explaining coups with economic variables, that would be interesting.

Dave Jacobs

-----Original Message-----
From: owner-statalist@hsphsun2.harvard.edu [mailto:owner-statalist@hsphsun2.harvard.edu] On Behalf Of Aniruddha Rajan
Sent: Thursday, August 23, 2012 2:18 PM
To: statalist@hsphsun2.harvard.edu
Subject: Re: st: Statistically significant difference in R Squared

Thanks for your response Anees. In this case I don't think it is possible to look at information criteria or other forms of model comparison as the empirical representation of the underlying model does not change - it is fixed by theory. Hence the change I am attempting to find a way to examine is the model fit in this period versus last period.

Regards,
Ani 

On 23/08/2012 19:06, "Muhammad Anees" <anees@aneconomist.com> wrote:

>If you have to compare the two models, why not read on on the 
>comparison of nested and non-nested models on the list (by searching 
>the archives) and selecting the best or preferred model using the AIC, 
>BIC or HQIC.
>
>Comparisons based on R-squared ( or adjusted R-squared) does not need 
>be tested _Statistically. Simply you can chose a model with higher 
>R-squared ( or adjusted R-squared). Otherwise Nick's suggestion is what 
>seems to be the most appropriate one to me.
>
>Best
>Anees
>
>On Thu, Aug 23, 2012 at 11:07 PM, Aniruddha Rajan 
><aniruddha.rajan@googlemail.com> wrote:
>> Thanks very much for your helpful response Nick. The gist of what I'm  
>>trying to do is to see whether the data I have conforms to a specified  
>>theoretical model to a greater extent during the second period as 
>>compared  to the first. I guess the residual plot should be good 
>>enough. Do any  formal tests for something like this exist?
>>
>> On 23/08/2012 17:56, "Nick Cox" <njcoxstata@gmail.com> wrote:
>>
>>>I don't think the question makes much sense inferentially for several 
>>>quite different reasons. But looking at the residuals as a function 
>>>of time and seeing whether they vary systematically could be a very 
>>>sensible and helpful check.
>>>
>>>Nick
>>>
>>>On Thu, Aug 23, 2012 at 5:09 PM, Aniruddha Rajan 
>>><aniruddha.rajan@googlemail.com> wrote:
>>>
>>>> I am running a time-series regression model over a 10 year period. 
>>>>I would  be interested in splitting the sample into two five year 
>>>>periods and finding  out whether the model has a statistically 
>>>>significantly higher R^2 during  the second period as compared to 
>>>>the first. Is there a test for this, and if  so is it possible to 
>>>>implement in Stata?
>>>*
>>>*   For searches and help try:
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>>>*   http://www.ats.ucla.edu/stat/stata/
>>
>>
>> *
>> *   For searches and help try:
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>
>
>
>--
>
>Best
>---------------------------
>Muhammad Anees
>Assistant Professor/Programme Coordinator COMSATS Institute of 
>Information Technology Attock 43600, Pakistan 
>http://www.aneconomist.com
>*
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