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Re: st: Regressing ranked variables for causality testing
From
Happy Phiri <[email protected]>
To
"[email protected]" <[email protected]>
Subject
Re: st: Regressing ranked variables for causality testing
Date
Tue, 23 Apr 2013 05:48:45 -0700 (PDT)
I want to use Multiple Rank F Test as developed by Holmes and Hutton (1990a, 1990b). To perform the multiple rank test, all the variables
including lagged variables should be transformed to the corresponding
rank representation. the ranked value of each observation is used to test for the causality relationship using the folowing
R(.)=α+∑δR(.)+∑λR(.)+∑θR(.)+ε
Thanks
Happy
----- Original Message -----
> From: Nick Cox <[email protected]>
> To: "[email protected]" <[email protected]>
> Cc:
> Sent: Tuesday, April 23, 2013 1:11 PM
> Subject: Re: st: Regressing ranked variables for causality testing
>
> Ranking is easy enough: see -help egen-.
>
> What that has to do with causality tests I do not know.
>
> Even more crucially, I think you need to spell out precisely which way
> of assessing causality you have in mind, with precise names and
> literature references.
>
> Nick
> [email protected]
>
>
> On 23 April 2013 07:50, Happy Phiri <[email protected]> wrote:
>> I have data for 3 variables (time series data) which I would like to rank
> using stata, and then run a regression on rank-transformed variables in order to
> test for causality. How is this done in stata?
> *
> * For searches and help try:
> * http://www.stata.com/help.cgi?search
> * http://www.stata.com/support/faqs/resources/statalist-faq/
> * http://www.ats.ucla.edu/stat/stata/
>
*
* For searches and help try:
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* http://www.stata.com/support/faqs/resources/statalist-faq/
* http://www.ats.ucla.edu/stat/stata/