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Re: st: Regressing ranked variables for causality testing


From   "JVerkuilen (Gmail)" <[email protected]>
To   [email protected]
Subject   Re: st: Regressing ranked variables for causality testing
Date   Tue, 23 Apr 2013 09:26:42 -0400

None of us know what that paper is. Please be sure to provide a
complete reference.


On Tue, Apr 23, 2013 at 8:48 AM, Happy Phiri <[email protected]> wrote:
> 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?
>> *
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>>
>
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-- 
JVVerkuilen, PhD
[email protected]

“He uses statistics as a drunken man uses lamp-posts – for support
rather than illumination.”--Andrew Lang

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